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Systematic review article, educational technology and student performance: a systematic review.

• Grupo de Investigación ≪Nodo Educativo≫, Departamento de Ciencias de la Educación, Instituto Universitario de Investigación y Prospección Educativa (INPEX), Universidad de Extremadura, Cáceres, Spain

The digital transformation of educational systems requires an evaluation of the effects of the integration of technologies in teaching-learning processes. From a pedagogical approach, Information and Communication Technologies (ICT) are defined, on the one hand, as the set of technologies that contain, store and disseminate information (e.g., e-books, videos, or databases) and, on the other hand, those technologies designed for short-term communication (e.g., social networks and smartphones). Academic achievement is one of the most widely used variables to try to understand how information and communication technologies affect student learning outcomes. Several international studies have shown little improvement in performance attributed to the use of ICT, although other reviews have shown positive results in relation to certain curricular areas. However, in general, the research is inconclusive and more studies are needed on this complex relationship. A systematic review was carried out using the Education Resources Information Center (ERIC) educational database as a documentary source, and research articles on academic performance and ICT use were selected ( n = 100). As a result, there was evidence of improved performance in educational practices enriched with ICT. Mathematics and science are the areas of greatest interest to researchers, and it was observed that the educational systems most oriented toward competitiveness and educational selectivity are the most productive in this field. The discrepancies between the “macro-studies” of international organizations and the “micro-studies” analyzed in this review are discussed.

Introduction

There has been persistent controversy concerning the effectiveness of information and communication technologies (ICT) in improving student learning in recent decades. One of the most widely cited debates was the one between Clark (1983) and Kozma (1994) , in which Clark argued that educational technology had no impact on student learning under any circumstances and that the “media are mere vehicles that deliver instruction but do not influence student achievement any more than the truck that delivers our groceries causes changes in our nutrition” ( Clark, 1983 , p. 445). The impact of technologies on learning is mainly due to the effect of innovation or teaching strategies, but not to the technology itself. For Kozma (1994) , the analogy of the “truck” creates an unnecessary division between medium and method. This author considers that learning is not a receptive response to the distribution of educational content but an active, constructive, social, and cognitive process through which the student strategically manages physical, cognitive, and social resources to generate new knowledge, interacting with information available to them and integrating it with previous knowledge. Kozma (1994) argues that technological media have a physical or technical structure and mechanisms that can interact with the cognitive and social processes of students. These mechanisms are the symbol system (oral language, written text, numbers and formulas, images and sounds) and processing skills (reception, visualization, storage, retrieval, organization, translation, transformation, or evaluation, among others). Each medium has specific distinguishing characteristics depending on the mechanisms it incorporates (attributes) and the uses appropriate to these characteristics (variables), which is how ICT attributes should be used to have an effect on learning in a given context. Consequently, research on technological media must address their technical skills, the teaching methodologies in which they are integrated, and the complexity of the social situations in which they are used. Thus, we will aim to highlight the difficulties of the current educational research to demonstrate the effects of ICT on learning.

At the beginning of the twenty-first century, Cuban (2001) identified several unintended effects of the massive introduction of computers into education systems: more than half of teachers never used computers in their teaching practice and only 5% integrated the technology into their teaching routines; the use of digital technologies in classrooms was not linked to academic activities relevant to assessment, but to superficial and unconnected tasks. There was no clear evidence of an improvement in students' academic performance as a result of the use of ICT. Most teachers used technology to maintain existing teaching patterns.

In the last decade, the debate has been oriented toward analyzing the role of digital technologies in real classroom practices. As a result, it has become clear that the use of technologies does not promote a radical change in relation to pre-existing practices. The promised innovation is mainly of a symbolic and often ideological nature. It is therefore necessary to approach the phenomenon from the social, cultural, political, economic and historical aspects of education and technology. The effects of digital technologies on learning depend on the “goodness of fit” between the approach to learning, which involves values and ideology, and the educational technology. There is a gap between the rhetoric and the reality of technology-based learning. Many of the values currently espoused (interactive, learner-centered, social, communal, authentic, etc.) are often at odds with the nature of educational systems ( Selwyn, 2011 ).

International Reports

In recent years, several international reports have been published on the effects of ICT on teaching-learning processes (PIRLS, TIMSS, PISA). These studies offer a global and comparative vision that allows us to recognize certain variables and processes that either favor or hinder the full integration of ICT in educational systems.

Progress in International Reading Study (PIRLS) initially observed that there is no correlation between the frequency of ICT use in schools and reading test scores. In both the 2001 study ( Mullis et al., 2003 ) and the 2011 study ( Martin and Mullis, 2013 ), a positive correlation was found with computer use at home, and a negative correlation with its use in schools. In the 2016 study, the “ePIRLS” version was used for the first time to assess students' online information reading via computer and through a simulated internet environment. Students who scored as “good readers” showed little difficulty in online reading and, moreover, come from family environments with more digital devices at home. The results reveal that students in schools without ICT performed lower than students in schools with ICT, although this correlation is difficult to interpret, since socioeconomic levels and teaching methodologies are highly interrelated. The average computer use for reading activities is once per week, especially when used to search for information, research a problem, or read digital texts ( Mullis et al., 2017a ).

On the other hand, in 1995, Trends in International Mathematics and Science Study (TIMSS) showed a negative relationship between the frequency of ICT use and lower academic performance than that of students with less frequent use or non-use of ICT ( Martin et al., 2000 ). In the same vein, a negative relationship was found in the 1999 and 2004 studies, while the TIMSS 2011 report revealed the absence of a relationship between ICT use in the classroom and academic performance in mathematics ( Mullis et al., 2012 ). In the TIMSS 2015 and 2019 reports ( Mullis et al., 2017b , c , 2020 ), the academic performance in mathematics and science was observed to be higher among students who had access to ICT in the classroom. The most frequent use for mathematics was to conduct procedural exercises; and for science, it was the search for information. In both cases, computer use in the classroom varied considerably, as some countries exceeded 80% of usage and others barely reached 6%; with greater use in science (46–48%) than in mathematics (37–39%).

Very similar results were found in Program for International Student Assessment (PISA). In PISA 2000, no significant correlations were found between computer use at home or at school and academic performance. In PISA 2003, no significant correlations were found between computer use and test scores in mathematics, reading, and science. The findings showing positive effects of computer use at home and no effects or even negative effects of computer use at school have been replicated in different PISAs; in different countries, and by controlling different variables. PISA 2012 confirmed the previous results ( Petko et al., 2017 ).

Skryabin et al. (2015) analyzed data from PIRLS 2011, TIMSS 2011, and PISA 2012 in order to test the effects of the development of ICT integration, as well as the subject's frequency of ICT use at home and at school on mathematics, reading, and science scores. The results showed a positive correlation between test scores and the level of development of ICT integration and ICT use at home, while they found negative correlations between ICT use at school and academic performance.

The Organization for Economic Co-operation and Development ( OECD, 2015 ), in its report “Students, Computers, and Learning”, concluded that there is no evidence of the improvement of academic performance in schools that have invested in ICT, nor that this investment bridges the gap between higher- and lower-achieving students. The study considers that the potential of ICT has not been harnessed in schools and points out that the possible causes may lie in the poor quality of educational software, as well as in the ineffective methodologies used in teaching practices with ICT. Hu et al. (2018) found that students in countries with higher overall levels of digital competences were more likely to achieve better academic results. However, national ICT access and use did not correlate with students' mathematics, reading, and science literacy after mastering digital competences. Therefore, the integration of ICT into the curriculum and the reduction of the digital gap could be determined by the basic skills required for performance in a digital context, rather than by the availability of ICT. The findings show that the educational use of ICT in the classroom has an influence on the pedagogical adoption of the tools, as opposed to individual use without educational support. However, given that teachers tend to use ICT for a limited amount of pedagogical practices that do not substantially alter traditional ways of teaching, an increase in the frequency of ICT use does not seem to offer tangible benefits for learning and could even be considered a detrimental factor. The negative relationship between students' academic use of ICT, both in and out of school, and their learning outcomes could indicate that ICT are not being used appropriately to improve learning. On the other hand, students' interest, competence, and autonomy in the use of ICT revealed different degrees of positive correlation with their academic performance in mathematics, reading, and science, while the use of ICT for the purpose of social interaction showed negative correlations with academic performance in all three subjects. In conclusion, “the quantity of ICT use can advance student learning only when the quality of ICT use is ensured” ( Hu et al., 2018 , p. 11). Kunina-Habenicht and Goldhammer (2020) found negative correlations between ICT use at school and at home and performance in PISA tests. These results could be explained by the fact that more frequent use of ICT at school is likely to be associated with a purpose of retaking exams for students with lower academic performance.

Previous Reviews and Meta-Analyses on Academic Performance and ICT

It is very difficult to find conclusive and consistent evidence to support the hypothesis of a positive impact of ICT use on student performance, as measured by standardized tests ( Biagi and Loi, 2013 ). Some studies have found that the use of computers does not have a positive effect on academic results based on the assessment by standardized tests ( Angrist and Lavy, 2002 ), nor does increased internet connectivity in schools provide evidence of improved academic results ( Goolsbee and Guryan, 2006 ). However, other research studies have observed positive impacts of the use of ICT in specific disciplines, such as the improvement of reading and language competences ( Rouse and Krueger, 2004 ) and mathematic performance ( Banerjee et al., 2007 ; Barrow et al., 2009 ).

Three educational uses of ICT for learning mathematics were identified ( Drijvers et al., 2010 ): (a) “to do mathematics”, i.e., the use of devices or apps for performing mathematical calculations, which increase efficiency and accuracy, in addition to allowing teachers to perform more creative and applied learning activities; (b) instrumental understanding, referring to the ability to perform mathematical rules and procedures through repetition and immediate feedback, by means of exercises, tutorials or simulations that are used as a complement to the teaching provided by the teacher; and (c) conceptual understanding, which refers to “knowing what to do and why”, and involves the use of specific models in flexible environments that facilitate exploration and create multiple mathematical representations (e.g., the open source software GeoGebra).

Thousands of studies have been conducted over the past 30 years on the effects of mathematics teaching practices with ICT on academic performance. To gain insight into the extent of these results, Young (2017) conducted a “meta-analysis of meta-analyses” (or second-order meta-analysis) with studies published between 1986 and 2015. In relation to the use of ICT for the improvement of computational thinking skills, it is apparent that the results on the effects of calculator use on mathematic performance modified teachers' perceptions of its use in the classroom, although it is important to consider the assessment model and educational stage as moderating variables. Regarding the use of ICT in the improvement of mathematics teaching, through computer-based instruction (CBI) and computer-assisted instruction (CAI), and their relationship with academic performance, small to moderate effects were observed, considering the relevance of the time spent using ICT and the teaching methodology as influential factors. Lastly, concerning the use of ICT as a tool for exploration and modeling, meta-analyses are still limited because research on the use of mathematics-specific software is still in its early stages. Several effect size moderators were detected, such as age, duration of the educational intervention, or the mathematical content taught (e.g., algebra or geometry). The results suggest that the mean effect sizes were 0.47, 0.42, and 0.36 for computational enhancement technologies, instrumental understanding enhancement technologies, and conceptual understanding enhancement technologies. In conclusion, it can be stated that (a) the effect of ICT use in mathematics teaching on academic performance, regardless of the type of educational use, is moderate; and (b) it can be considered an effective means for the improvement of learning outcomes. It is estimated that students with ICT support would perform better than 62% of students who are not offered this resource.

Furthermore, the results of research on the impact of educational technology on reading coincide in showing positive but moderate effects compared to traditional methods ( Becker, 1992 ; Fletcher-Flinn and Gravatt, 1995 ; Soe et al., 2000 ). The use of reading instruction programs that use ICT resources as an educational supplement, which were the most frequently used programs in past decades, did not have a significant effect on reading performance ( Dynarski et al., 2007 ; Campuzano et al., 2009 ). Other more comprehensive models that use methodologies that combine practices with the presence/absence of ICT, together with specific teacher training, seem to reveal a greater impact on reading ( Cheung and Slavin, 2012 ). These findings show that integrating technological and non-technological components for the teaching of reading is the most relevant issue.

Technological development has contributed to a change in reading habits, and the reading of digital texts has become the predominant activity as an alternative and complement to reading printed material. Therefore, equity in education is important in both printed and digital reading. Rasmusson (2016) studied the influence of digital reading on reading performance. The results of the study show no influence of cultural capital and economic factors on students' digital reading performance. These results could indicate that digital reading is less valued than print reading in light of cultural capital standards. That is, digital reading does not yet belong to the activities and artifacts that represent desirable cultural capital in contemporary society.

Xiao and Hu (2019) found that ICT use improves the reading performance of students, especially those from a disadvantaged socioeconomic background. They observed that the impact of ICT use on students' reading performance gap caused by their socioeconomic status changed from negative to positive over a 3-year period (2012–2015). These researchers consider that a more interactive and attractive digital environment, as well as the use of creative activities in teaching practices with ICT, could explain this positive effect of ICT on reading performance among students from disadvantaged socioeconomic backgrounds.

Verhoeven et al. (2020) carried out a meta-analysis on the effects of computer use on early literacy in Early Childhood Education over the past 25 years. A small average effect size (0.28) was evident, with a very high variability, which was similar for each of the ICT-supported interventions: phonological awareness, alphabetic principle, a combination of both, and story reading. It can be affirmed that ICT can be beneficial in the field of early literacy, as long as they are integrated into the school curriculum and provide continuous instructional scaffolding. In any case, teachers outperform digital devices in facilitating phonological awareness and understanding of the alphabetic principle. Early Childhood Education teacher training should be promoted in order to increase the benefits of ICT.

Delgado et al. (2018) conducted a meta-analysis, with the aim of comparing the use of print and digital media on linear reading, with strong similarities between digital texts and printed texts. The results of the study clearly showed lower reading comprehension performances for digital texts compared to printed texts. These results were consistent across methodologies and for all theoretical frameworks. However, digital devices for reading must be considered, as the computer appears to have a greater negative impact on comprehension than other digital media. It was observed that the advantage of reading printed informational texts was significantly greater when a reading time limit was imposed, compared to self-paced reading, regardless of the length of the text. This evidence is important to consider when using digital texts in assessment tests. Current evidence supports the claim that experience with ICT alone does not improve students' comprehension skills, but may even have detrimental effects. Digital media behavior, based on quick interactions and motivated by immediate rewards, makes it difficult to perform more cognitively demanding tasks. This would explain the negative correlations between frequency of ICT use and reading comprehension among adolescents. Increased exposure to digital reading resources tends to enhance speed and multitasking, to the detriment of behaviors more conducive to deeper comprehension, which requires more time and concentration. As a result, digital environments may not always be the most appropriate choice to facilitate deeper learning. The competences linked to information search and selection or critical reading are essential for comprehension, but require a high level of executive processes, which are not yet sufficiently developed in students engaged in digital reading. The results indicate that the screen inferiority increased over the last 18 years and that there were no differences in the effects of the mediums between age groups. The preference for printed over digital reading has persisted despite technological advances. However, accepting the fact that the inclusion of digital devices in our educational systems is unavoidable, educational methods that encourage an effective digital reading competence must be developed.

In relation to the use of ICT at home and/or in the classroom for educational purposes, Bulut and Cutumisu (2018) examined the extent to which the use and availability of ICT at home and at school had a differential impact on academic performance in mathematics and science. It was observed that ICT use was found to be detrimental to mathematics and science performance, irrespective of learning outcomes in both subjects. ICT availability, especially at home, revealed a positive correlation with mathematics and science performance for students where ICT access was more scarce, but had no effect on students for whom ICT were widely available. On the other hand, the use of ICT at home for school work had no effect on academic performance in mathematics and science. Most recently, Gubbels et al. (2020) found that ICT access at home has a negative correlation with digitally assessed reading performance. Students with access to a variety of ICT resources at home scored lower on digitally assessed reading, compared to students with moderate levels of ICT resources at home. Moderate ICT use was associated with higher digitally assessed reading performance. Higher ICT use at home, explicitly in relation to school-related tasks, was negatively associated with students' test scores. It was also observed that high levels of perceived ICT autonomy is related to high performance in digitally assessed reading. Both a lack of interest in ICT and excessive interest in ICT are related to low digitally assessed reading performance. In conclusion, these results suggest that investing money and time to provide students with ICT resources at home or school and increasing the use of these resources does not necessarily improve digitally assessed reading performance.Similarly, Agasisti et al. (2020) observed the existence of a negative correlation between students' use of ICT at home for academic tasks and academic scores in mathematics, reading, and science assessment tests (PISA), regardless of students' level of academic performance. Researchers argue that “more frequent use of ICT at home, even when explicitly connected to school-related tasks, is detrimental to academic achievement” ( Agasisti et al., 2020 , p. 16–17). Promoting the widespread use of ICT for academic tasks at home, without precise guidance on how ICT should be used, can have detrimental effects on learning. Evaluating the quality of digital educational materials should be a central element of educational planning and part of the school culture. Among the reasons that could explain this result could be, to begin with, that the devices and software used are not suitable for the required academic functions because they are obsolete. Secondly, students have not been educated to develop the necessary skills that allow them to efficiently make use of ICT to improve their learning. This training should be modeled in the classroom through a variety of ICT-enriched teaching practices. The effective use of digital devices at home would depend on how students are previously trained in the classroom. Third, students could be underutilizing ICT for learning at home due to the lack of skills to avoid the distracting effects of ICT derived from their multiple functions and multitasking. Lastly, it could be that students who use ICT at home more frequently for school purposes do indeed improve in other variables relevant to learning that have not been measured in the assessment tests.

Park and Weng (2020) found (a) that students' use of ICT for entertainment purposes negatively affected their academic performance; (b) that students with a positive attitude toward ICT use have a high probability of attaining better learning outcomes; (c) that students' perceived ICT self-efficacy has a significant positive effect on their academic performance, and its effect size is larger than that of attitude or digital competence; (d) that a country's economic development levels are associated with student performance, as it affects ICT resources and competence in the schools, such as infrastructure, ICT support staff, and educational software. Therefore, it is essential to promote equitable access to ICT through related policies, including discounted internet access and the expansion of ICT infrastructure in public areas, such as schools or libraries, for low-income families; in order to resolve this educational inequality, based on addressing income inequality and the digital gap.

Finally, regarding the 1:1 Model (one computer per student), Zheng et al. (2016) , as a result of their meta-analysis, observe that its use modifies many aspects of education at the Primary and Secondary levels. The most common changes identified in the studies reviewed include significantly higher academic performance in science, writing, mathematics, and language subjects; increased use of technology for various learning purposes; more student-centered, individualized, and project-based learning; increased engagement and motivation among students; as well as improved relationships between teachers, students, and families. However, most published research consists of case studies with little representation of experimental and quasi-experimental research, which makes it difficult to conduct a meta-analysis.

The aim of this systematic review is to first discover the research results of the last decade concerning the relationship between ICT use and academic performance in mathematics, science, reading, and writing. This systematic review, unlike previous ones, integrates studies on academic performance and ICT in the most researched curricular skills. Second, this review aims to identify the teaching modalities supported by ICT that have been implemented and the educational contexts where these learning processes have taken place. In contrast to reviews based on “macro” studies (e.g., PISA), this study investigates “micro” research based on classroom practices. This systematic review aims to identify the teaching methodologies and learning contexts present in research on academic performance and ICT. It is very important to understand how technologies are used in the teaching process and what are the learning environments where these technologies are introduced. Third, this review aims to analyze the documentary characteristics of the articles that explain the results and to describe the methodological approaches used in the research.

Methodology

A systematic review consists of compiling a body of research according to previous inclusion criteria, with the objective of answering specific research questions. This systematic review applies the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 standards to identify inclusion criteria, information sources, search strategy, study selection process, data collection process, and presentation and synthesis of data. The systematic review process applied in this study consists of different phases ( Zawacki-Richter et al., 2020 ):

Phase 1: Research questions (RQ). The questions are organized into three areas, as shown in Table 1 : (1) documentation dimension (RQ1–RQ3), to identify the areas of knowledge on the topic, the geographical location of the researchers, and the impact of the journals where the results are published; (2) methodological dimension (RQ4–RQ5), to address the approaches and methods applied in the studies, as well as the sample sizes and time frame of the research studies; and (3) pedagogical dimension (RQ6–RQ10), to identify the different educational contexts involved in the educational use of ICT, the educational levels and curricular areas under study, the identification of teaching methods in the teaching practices analyzed, the effects observed on academic performance and, finally, to identify other variables of a pedagogical, psychological, sociological or technological nature that were used in the studies.

Phase 2: Inclusion criteria and information sources. The documentary sources are from articles published in scientific journals during the period 2013–2021, which include the following Education Resources Information Center (ERIC) Thesaurus terms as descriptors: “Technology uses in Education,” “Mathematics Achievement,” “Reading Achievement,” “Writing Achievement,” and “Science Achievement”. Empirical studies with quantitative, qualitative and mixed methods were also included. Exclusion criteria were applied to articles whose main subject of study was not academic performance in relation to ICT.

Phase 3: Search strategies. The ERIC database was used for the study selection process. ERIC is recognized as the largest database specialized in education, with references provided since 1966. In all search queries, the concept of the thesaurus “Technology uses in Education” was used together, alternatively, with the concepts “Mathematics Achievement,” “Reading Achievement,” “Writing Achievement,” and “Science Achievement”, also from the ERIC thesaurus.

Phase 4: Study selection process. The initial search resulted in 316 articles, of which 28 were duplicates. We analyzed the 288 articles on the basis of the title and abstract, according to the inclusion-exclusion criteria. Once we agreed on the results, 186 articles were excluded. We independently analyzed the remaining 102 articles in full, which resulted in the exclusion, upon agreement, of 2 articles. The final sample of documents for the systematic review consisted of 100 articles ( Data SRL ), as shown in Figure 1 .

Phase 5: Data coding and synthesis. The Zotero reference manager was used for data collection. Data synthesis was performed using a coding sheet with 29 fields (LibreOffice Calc). VOSViewer was used for the conceptual network analysis. The three researchers, first independently and then jointly, were involved in the different phases of selection according to prior inclusion criteria and definitive inclusion in the review.

Table 1 . Areas, research questions, and initial coding criteria.

Figure 1 . Flow chart of the study selection process.

RQ1. What Is the Conceptual Network Extracted From the Literature, and What Are the Topics of the Articles According to the Category of the Journal in the Databases?

A series of clusters generated by the co-occurrence of the keywords of the articles were obtained to analyze the conceptual network, as shown in Figure 2 . The first cluster (14 items), in green, shows a network formed by the educational uses of ICT that includes students' attitudes, gender, or the effectiveness of educational programs. The second cluster (14 items), in red, identifies a conceptual network on mathematics performance and the associated teaching methods to attain it. The third cluster (10 items) represents a conceptual network that includes the research methods and techniques used in the studies analyzed. As a result, the conceptual network of keywords in the articles included in this systematic review is composed of three main nodes that identify Pedagogy (Educational Technology), Curriculum (Mathematics as the most noteworthy area), and Educational Research (approaches, methods, and techniques) as pillars on which the interests of the researchers are structured.

Figure 2 . Map of co-occurrence by keywords of the articles reviewed. Source: prepared with VosViewer.

Of the articles analyzed, according to Scopus, 73% were published in journals with associated indexed categories; namely, in the category of “Education” (67%), “e-Learning” (4%), and “Communication Education” (2%). Eight percent belong to journals categorized in the “Mathematics (miscellaneous)” category. Seven percent belong to the “Multidisciplinary” category. The rest are comprised of various topics related to Natural Sciences (4%), Health (2%), Social Psychology (2%), Language and Linguistics (1%), and Computer Technology (3%).

RQ2. What Is the Geographical Distribution of the Publications?

The geographic location of the research in this review was established based on the country associated with the first author of the articles. As a result, a quarter of the studies were conducted in the United States. This was followed by Turkey (19%) and, in third place, Taiwan (8%). With a representation of 4%, studies from Malaysia and Indonesia were also identified. On the other hand, China, Finland, and Spain represented 3% of the studies analyzed.

RQ3 What Is the Distribution of Articles According to Their Position in the Databases?

The journals containing the articles selected for this review were classified according to the quartile they were assigned in Scopus, according to the year of publication of the study. Thus, it is evident that 28% of the articles were published in journals in quartile 1 (Q1), 22% of the articles belong to the second quartile (Q2), 13% of the studies are located in the third quartile (Q3), and lastly, 8% of the articles are located in the fourth quartile (Q4). The remaining 29% of the articles belong to journals not indexed in Scopus.

RQ4. What Methodological Approaches and Research Methods Are Used in the Selected Studies?

The studies were classified according to their approach as quantitative (58%), qualitative (4%), and mixed (38%). Regarding the methodologies used in the selected research studies, the quasi-experimental method is the most frequently used (54%), followed by experimental studies (26%). Exploratory studies represent 7% of the total, and case studies were used in 6% of the research studies. Studies based on questionnaires were used less frequently (2%), as well as those using instructional design, descriptive and observational studies (each representing 1%).

RQ5. What Are the Sample Sizes of the Studies, and What Is the Duration of Each One?

Half of the studies in this systematic review used samples ranging from 25 to 100 subjects. Eighteen percent were in the range above 100 and below 200. Approximately 22% used samples larger than 200 subjects. Three percent used samples smaller than 25, and the remaining 7% did not report sample size. The majority of the research studies reported a study duration of between 1 and 6 months (33%). Studies with a duration of <1 month represented 26%. Twelve percent reported a duration of between 6 months and 1 year, and 11% reported a duration of over 12 months. Four studies were carried out in a period of fewer than 7 days. Fourteen percent of the articles did not report the duration of their studies.

RQ6. In What Contexts Does the Teaching-Learning Process With ICT Take Place?

Almost three-quarters of the teaching practices with ICT in the studies analyzed were carried out in the classroom (73%). Blended learning accounted for 23% of the studies. Lastly, teaching practice outside the classroom with ICT accounted for 3% of the studies reviewed.

RQ7. Which Educational Levels Are Included in the Research Studies, and Which Components of the Core Curriculum Are Involved?

The highest percentage of the studies reviewed conducted their research in the educational field of secondary education (34%) and primary education (31%). In third place were studies on the academic performance of university students (27%) and, lastly, early childhood education represented 7% of the research. One of the studies analyzed was conducted at various educational levels. The curricular area with the most studies on the relationship between academic performance and ICT use was mathematics (48%), followed by science (35%). Research on reading and writing together accounted for 11%.

RQ8. What Are the ICT Teaching Modalities Applied in the Studies Analyzed?

As shown in Figure 3 , almost half of the studies (47%) identified expository methods (lecture). Secondly, the most frequent teaching methodology was Project-Based Learning (11%). Game-Based Learning and the 1:1 Model (one computer per student) each represented 10%. Flipped Classroom represented 8% of the studies, followed by Gamification (7%). The Bring Your Own Device (BYOD) model represented 4%. The Problem-Based Learning model was used in one study. Two studies did not report the teaching modality.

Figure 3 . Distribution of teaching modalities according to curricular area.

RQ9. What Are the Effects of ICT Use on Academic Performance?

In general, 83% of the research reviewed revealed positive results in the relationship between academic performance and the educational use of ICT. Nevertheless, 15% reported negative results in the relationship between the use of ICT in educational practice and students' academic results, and 2% did not provide any conclusive results in this regard.

RQ10. What Other Variables Have Been Studied in the Selected Research Studies?

In addition to academic performance, the research in this review has analyzed other variables, identified below, organized into different areas: (a) pedagogical variables (lecture length, collaboration, communication, comprehension, experience, gamification, inquiry skills, interactive, key competences, learning environments, mathematical skills, peer learning, student's point of view, student's background, teacher practice, teacher's point of view); (b) psychological variables (attitude, autonomy, cognitive skills, cognitive learning, perceptions, retention, self-efficacy, self-regulatory, spatial abilities); (c) sociological variables (gender); and (d) technological variables (augmented reality, virtual reality, use of e-books, use of smartphones, BYOD effects).

Conclusion and Discussion

The aim of this article was to discover the results of educational research on the relationships between academic performance and the educational use of ICT. To this end, a systematic review was carried out, which has allowed us to answer 10 research questions about the documentary characteristics of the articles analyzed: the thematic scope of the journals, the geographical location of the studies, and an estimate of the quality of the publications based on their positioning in Scopus; the methodological characteristics of the studies by identifying their approach and method applied, as well as the sample used and the time frame of the research; and, finally, in relation to the pedagogical dimension, we explored the educational contexts of use of these technologies (physical classroom, outside the physical classroom, and blended learning), the teaching modalities used, the educational levels and curricular areas involved.

The most relevant findings of this systematic review are, on the one hand, the identification of the curricular areas that focus the attention of educational research on the relationship between ICT use and academic performance. It was observed that interest in this subject of study has been expressed in educational journals, but it is no less relevant that they were also published in journals specialized in mathematics and science. In fact, more than 80% of the studies in this review address the effects of ICT use on mathematics and science learning, as these are the curricular areas in which researchers are most interested to discover how the educational use of ICT affects students' learning outcomes ( Liao and Chen, 2021 ; Çavuş and Deniz, 2022 ).

On the other hand, it was observed that educational research on the effects of ICT on academic performance seems to be conditioned by the characteristics of the educational systems where these studies are carried out. Considering that the use of ERIC implies a limitation of this review with respect to potential bias (language, sources) in the study selection process from which our sample was obtained, the geographical distribution of the research studies reveals that certain educational systems have a greater interest in ICT accountability. In addition to the expected prevalence of research conducted in the United States, other countries such as Turkey and Taiwan, both with highly competitive educational models focused on knowledge assessment, were also highlighted ( Chou, 2019 ; Gümüş et al., 2021 ).

With respect to the methodological approach, it has become evident that, as is usually the case, the study of academic performance uses quantitative approaches, although mixed approaches are beginning to play an important role. Quasi-experimental or experimental methods are clearly the dominant methods. Other methodological approaches were not used, characterized by the design of educational environments or resources as an integral part of the research, with the aim of contributing to the resolution of an educational problem or the improvement of the teaching-learning process, such as Design-Based Research ( Huang et al., 2019 ).

Half of the studies analyzed were conducted with small sample sizes of students, which should be considered a possible limitation in the generalization of the results. The same could be said in relation to the time frame of the studies to examine the results. Around 60% had a maximum time frame of 6 months, which could be considered a short time to be able to thoroughly observe the effects of ICT on academic performance. In this regard, we can describe these studies analyzed as “micro-studies” ( Moss, 2012 ). However, the fact that half of the studies analyzed were published in quartile 1 or 2 (Q1/Q2) journals attests to the quality of the research and its relevance for scientific progress.

It was observed that the research studies analyzed in this systematic review report that 3 out of 4 teaching practices with ICT have been carried out in the classroom and, on the other hand, the teaching methodology involved in half of these studies consisted of expository or traditional methods. Consequently, there is a need to increase the number of studies that analyze other blended or virtual educational contexts and their effects on academic performance. Although blended learning is present in almost a quarter of the studies analyzed, online teaching is underrepresented. There is also evidence of the need for further research using active methodologies supported by ICT for digital citizenship training ( Sancho-Gil et al., 2020 ).

The results of this systematic review allow us to conclude that there is a clear difference in the results obtained on academic performance and the use of ICT in the “macro-studies”, with large samples and over long periods of time, carried out by international organizations, especially the OECD, and in the “micro-studies” carried out within university research groups using small samples and over short periods of time, which we have analyzed in this research study.

International studies repeatedly show that frequent use of ICT in the classroom does not establish positive correlations with academic performance. Several explanations for these results can be considered. First, educational technology is a concept that includes the use of devices, applications, and methodological approaches that are applied in specific contexts. Therefore, educational technology can be effective to a certain degree, depending on how it is used. The questionnaires on ICT use in these studies are more concerned with quantity rather than the educational quality of the use of ICT in the classroom. Secondly, the concept of performance linked to ICT differs in the sense that the contributions of the use of ICT are mainly reflected in the development of new skills and not directly assessed, such as digital competence or self-regulated learning. Lastly, it is necessary to redefine the educational research methodologies that have been used in educational technology and to apply longitudinal and mixed studies that study the phenomenon in all its complexity ( Petko et al., 2017 ).

Evidence on the impact of educational ICT plans, programs and projects has been disappointing in most cases ( Luckin et al., 2012 ; Vrasidas, 2015 ). The great expectations of educational reform or “revolution” as predicted by the most influential technologists, multinational companies in the sector and political discourse have not been fulfilled. On the contrary, the radical changes produced in other social and human activity systems promoted by ICT, the transformation of everyday life due to the use of digital devices connected to the internet, and the increased use of ICT in any context outside the academic environment reveal that the barriers to the integration of ICT are not primarily rooted in the vision of ICT as potential tools for the transformation of the teaching-learning process, but in the obsolescence of organizational structures and dominant cultures in educational systems ( Somekh, 2007 ).

The closer approach to particular educational contexts enriched with ICT, offered by the “micro-studies” of this systematic review, reveals that academic performance improved with the use of technologies. Among the reasons behind this discrepancy with respect to the “macro-studies” is a potential publication bias that favors the dissemination of those studies showing “positive” results on academic performance. On the other hand, the specificity of the research objectives and greater precision in the selection and application of the methodology could lead to more in-depth and contextualized studies that better explain this phenomenon. Finally, consideration should be given to the conceptual and cultural differences that exist concerning the role of technologies in education, as well as the definition of academic performance. In subsequent reviews, it would be necessary to analyze how school culture and research perspectives in educational technology can influence the results of this complex relationship between academic performance and ICT ( Espíndola et al., 2020 ).

The main limitation of this review was the use of ERIC as the only database for the study selection process, which, although it is the most relevant database in the field of education, is limited to the English language. Subsequent reviews could consider the inclusion of other databases that increase the number of source documents (e.g., Scopus and WoS) or incorporate other languages such as Spanish (e.g., Dialnet). On the other hand, we chose to use terms strictly from the ERIC Thesaurus in the search queries for articles. The identification of other frequent keywords in the scientific community could have enriched the final selection of articles.

Data Availability Statement

Data is available in the Supplementary Material and https://doi.org/10.5281/zenodo.6426878 .

Author Contributions

JV-B: idea, methodology, and writing (original draft). JV-B and JA-B: literature review (state of the art). JV-B, JA-B, and MC-P: data analysis, result, discussion, conclusions, project design, and sponsorships. MC-P and JA-B: final revisions.

This publication has been made possible through funding granted by the Consejería de Economía, Ciencia y Agenda Digital from the Junta de Extremadura (Spain), and by the European Regional Development Fund of the European Union, through the Reference Grant IB18088. All authors contributed to the article and approved the submitted version.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary Material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/feduc.2022.916502/full#supplementary-material

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Keywords: educational technology, Technology uses in Education, Mathematics Achievement, Reading Achievement, Science Achievement, Writing Achievement

Citation: Valverde-Berrocoso J, Acevedo-Borrega J and Cerezo-Pizarro M (2022) Educational Technology and Student Performance: A Systematic Review. Front. Educ. 7:916502. doi: 10.3389/feduc.2022.916502

Received: 09 April 2022; Accepted: 31 May 2022; Published: 28 June 2022.

Reviewed by:

Copyright © 2022 Valverde-Berrocoso, Acevedo-Borrega and Cerezo-Pizarro. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Jesús Valverde-Berrocoso, jevabe@unex.es

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Educational Technology Adoption: A systematic review

Andrina granić.

Faculty of Science, Department of Computer Science, University of Split, Rudera Boskovica 33, 21000 Split, Croatia

During the past decades a respectable number and variety of theoretical perspectives and practical approaches have been advanced for studying determinants for prediction and explanation of user’s behavior towards acceptance and adoption of educational technology. Aiming to identify the most prominent factors affecting and reliably predicting successful educational technology adoption, this systematic review offers succinct account of technology adoption and acceptance theories and models related to and widely applied in educational research. Recognised journals of the Web of Science (WoS) database were searched with no time frame limit, and a total of 47 studies published between 2003 and 2021 were critically analysed. The key research findings revealed that in educational context a vast majority of selected studies explore the validity of Technology Acceptance Model (TAM) and its many different extensions (N=37), along with TAM’s integrations with other contributing theories and models (N=5). It was exposed that among numerous predictors, thematically grouped into user aspects, task & technology aspects, and social aspects, self-efficacy, subjective norm, (perceived) enjoyment, facilitating conditions, (computer) anxiety, system accessibility, and (technological) complexity were the most frequent predictive factors (i.e. antecedents) affecting educational technology adoption. Considering types of technologies, e-learning was found to be the most common validated mode of delivery, followed by m-learning, Learning Management Systems (LMSs), and social media services. The results also revealed that the majority of analysed studies were conducted in higher education environments. New directions of research along with potential challenges in educational technology acceptance, adoption, and actual use are discussed as well.

Introduction

Over the last half-century, a vast number of adoption theories and technology acceptance models, along with a plethora of their extensions and modifications has been advanced. Aiming to explore their applicability, as well as to enhance their predictive validity, proposed theories and models have been extensively used in assessment of various Information and Communication Technology (ICT) products and services. Commonly, technology adoption is a term that refers to the acceptance, integration, and embracement of any types of new technology. Technology acceptance, as the first step of technology adoption, is an attitude towards technology, and it is influenced by various factors. According to the Innovation Diffusion Theory (IDT) (Rogers, 1962 , 1995 ), adoption is a decision to make full use of technology innovation as the best course of action available. The key to adoption is that the adopter (individual or organization) must perceive the idea, behavior, or product as new or innovative. As for technology adoption research at the individual level, numerous theories and models have been used to predict and explain human behavior towards technology acceptance, adoption and usage.

Education presents an area of great interest in incorporating new technologies, thus technology acceptance and adoption theories and models are often used to inform research in educational context. Such setting is characterised by a great variety of potential users of various types of technology embraced in the process of learning, teaching, and assessment. Some of the most influential theoretical approaches involve (listed in chronological order with relevant illustrative example research):

• Technology Acceptance Model (TAM) (Davis, 1986 , 1989 ), the widely used reliable model, to explore new facilitating technologies in educational context, ranging from social media platforms (Yu, 2020 ) to the technology aimed at helping the learning process through teaching assistant robots (Park and Kwon, 2016 ), simulators (Lemay, Morin, Bazelais & Doleck, 2018 ), and virtual reality (Jang, Ko, Shin & Han, 2021 );
• Decomposed Theory of Planned Behavior (DTPB) (Taylor & Todd, 1995 ) to understand university students’ adoption of WhatsApp in learning (Nyasulu & Chawinga, 2019 ), to explore factors that influence teachers’ intentions to integrate digital literacy (Sadaf & Gezer, 2020 ), as well as to examine factors that impact the acceptance and usage of e-assessment by academics (Alruwais, Wills & Wald, 2017 );
• Unified Theory of Acceptance and Use of Technology (UTAUT) (Venkatesh, Morris, Davis & Davis, 2003 ) to study core factors affecting the university students’ attitude towards adoption of online classes during COVID-19 (Tiwari, 2020 ), to explore the factors that influence preservice teachers’ acceptance of ICT integration in the classroom (Birch & Irvine, 2009 ), and students’ usage of e-learning systems in developing countries (Abbad, 2021 );
• Extended UTAUT (UTAUT2) (Venkatesh, Thong & Xu, 2012 ) to evaluate acceptance of blended learning in executive education (Dakduk, Santalla-Banderali & van der Woude, 2018 ), and to examine preservice teachers’ acceptance of learning management software (Raman & Don, 2013 ).

Several reviews and meta-analysis that summarize empirical research have been focused on specific topics in the field of education, for example: (i) particular technology adoption model , like the meta-analysis dealing with TAM in prediction of teachers’ adoption of technology (Scherer, Siddiq & Tondeur, 2019 ), and the quantitative meta-analysis to identify the most commonly used external factors of TAM in the context of e-learning adoption (Abdullah & Ward, 2016 ); (ii) specific type of users , like reviews conducted to understand factors influencing academics’ adoption of learning technologies (Liu, Geertshuis & Grainger, 2020 ), to explore factors that affect teachers’ acceptance and use of ICT in the classroom (Gamage & Tanwar, 2018 ), as well as to study factors affecting students’ adoption and continuation of technology use in online learning (Panigrahi, Srivastava & Sharma, 2018 ); (iii) particular technology and mode of delivery , like reviews carried on to explore factors affecting blended learning adoption and implementation in higher education (Anthony, et al. 2020 ), to study technical factors affecting users’ intentions to use mobile phones as learning tools (Alghazi, Wong, Kamsin, Yadegaridehkordi & Shuib, 2020 ), as well as to examine the most prominent external factors affecting learning management systems (LMSs) adoption in higher educational institutions (Al-Nuaimi & Al-Emran, 2021 ). Besides, some theoretical work aimed to identify determinants of learning technology acceptance, but it was more focused on original constructs of reviewed technology adoption theories, like in the study conducted by Kaushik and Verma ( 2020 ).

However, to the best of authors’ knowledge, currently there is hardly a holistic view of factors that affect and reliably predict successful acceptance and adoption of technology engaged in educational process. Understanding these aspects can be beneficial and can help in an improvement of both, research and educational practices. Hence, this concept-centric review aims at addressing this concern with the following two main research questions (RQs):

• RQ1. Which technology acceptance and adoption theories and models are widely applied in educational research?
• RQ2. Which are the most prominent predictive factors (i.e. antecedents) affecting educational technology adoption?

Research Approach

The research scope of this systematic review is narrowed and piloted towards understanding the most recognized and applied theoretical models, as well as the most influential predictive factors affecting various technologies used to support the process of knowledge transfer and acquisition. Due to massive work worldwide, this study is used to offer succinct account of predominant predictors in educational technology adoption, and certainly cannot be all-encompassing. With the aim to filter and narrow the search, but at the same time to cover representative literature from recognised journals, the Web of Science (WoS) Current Contents Connect (CCC) database was searched. The search was not limited to a precise timespan. To denote different technology acceptance models and theories, the search was conducted using relevant terms connected with Boolean operators “OR” and “AND”, specifically (“theor*” OR “model”) AND (“technolog*”) AND (“adoption” OR “acceptance”) . To locate education related studies, (“education*” OR “learn*”) search terms were joined with the aforementioned ones by means of the operator “AND”. Truncation was used to cover all variations of some keywords, for example, the search term “ technolog* ” was used to search for literature that included the word “technology” as well as “technologies”.

It was searched for studies that have specified search terms in publication title (the filter “TITLE” was selected). For the purpose of this review, specified inclusion criteria enabled selection of studies that report on technology acceptance and adoption theories and models in which some type of ICT products and services to support the process of learning and teaching was used (in this context indicating all classes of technologies, interactive systems, environments, tools, applications, services, platforms, and devices). To be included, studies had to report on empirically evaluated research model and related research hypothesis. Besides, studies must be published as peer-reviewed journal articles written in English language. On the subject of exclusion criteria , studies that do not clearly and credibly describe model/theory constructs or variables, and the relationships among them, were not considered as valid to be selected and included in the analysis. In addition, theoretical studies published as peer-reviewed journal articles, specifically reviews and meta-analysis, were excluded as well.

The literature search was conducted in August 2021. No time frame period was specified; 1998-2021 is the full range of the CCC database search engine. In this inquiry, 71 publications that included specified search terms in the publication title were identified. Considering only peer-reviewed journal articles written in English, the number of 67 journal and review articles was reached. Title, abstract and full text of the filtered literature were screened to ensure publication suitability and relevance. Accordingly, the qualified publications were retained and eleven unrelated ones were excluded, thus narrowing the number and leaving for further detailed analysis 56 publications. Out of 56 identified journal articles, 47 publications were found to be compliant with the purpose of this study, while 9 publications offered theoretical work which summarized empirical research focused on specific topics in educational technology acceptance and adoption.

In view of the identified theoretical work, the majority of studies offered meta-analysis and reviews of Technology Acceptance Model (TAM) based studies in education (N=6), specifically (Dimitrijević & Devedžić, 2021 ; Granić & Marangunić, 2019 ; Kemp, Palmer & Strelan, 2019 ; Scherer et al., 2019 ; Al-Emran, Mezhuyev & Kamaludin, 2018 ; Abdullah & Ward,2016), while just few publications addressed other acceptance models and theories, in particular Unified Theory of Acceptance and Use of Technology (UTAUT) (Bervell & Umar, 2017 ), Senior Technology Exploration, Learning and Acceptance (STELA) model (Tsai, Rikard, Cotton & Shillair, 2019 ), along with Straub’s ( 2009 ) study in a context of informal learning which examined adoption processes through the lenses of Innovation Diffusion Theory (IDT), Concerns-Based Adoption Model (CBAM), TAM and UTAUT.

Results and Discussion

The analysis of 47 publications found to be compliant with the purpose of this study is presented and discussed in the following.

Publication History and Distribution by Countries

Considering the history of publishing, Fig.  1 shows the trend of publication frequency which started in 2003, and can be followed until 2021. The majority of studies has been published in the last decade thus reflecting an increased attention given to the researched domain. It can be noticed that there are only three identified studies in 2021, but this is connected with the fact that the search was undertaken in August 2021, and several potentially relevant articles/studies are not published yet.

Publication history

The interest of researchers worldwide in educational technology acceptance and adoption is evident (see Fig.  2 ). Most of the identified studies were conducted in Taiwan (N=7), followed by relevant research carried out in South Korea and USA (N=4), Spain (N=3), Canada, China, Hong Kong, Malaysia, Pakistan, Singapore and Turkey (N=2). In the rest of illustrated countries only single studies were piloted (alphabetical order): Azerbaijan, Cyprus, France, Hungary, Lebanon, Libya, Netherlands, Nigeria, Oman, Philippines, South Africa, UK, United Arab Emirates, as well as Qatar & USA.

Distribution of selected articles by countries

Type of Technologies and Modes of Delivery

This research revealed a diversity of ICT products and services employed in educational context, here referring to all classes of technologies, interactive systems, environments, tools, applications, services, platforms, and devices used in the selected research. Considering types of technologies and modes of delivery used to support the process of learning and teaching, it is noticeable that almost half of the analysed studies (N=20) validated e-learning technologies, in selected research referred to as e-learning systems (Hanif, Jamal & Imran 2018 ), e-learning platforms (Song & Kong, 2017 ), e-learning environments (Esteban-Millat, Martinez-Lopez, Pujol-Jover, Gazquez-Abad & Alegret 2018 ), e-learning tools (Tarhini, Hone, Liu & Tarhini 2016 ), web-based learning systems (Calisir, Gumussoy, Bayraktaroglu & Karaali 2014 ), Internet-based learning systems (Saade & Bahli, 2005 ), or just e-learning (Abdou & Jasimuddin, 2020 ). Many studies dealt with mobile learning (N=6) in which context mobile computing devices (Lai, 2020 ), mobile technology and apps (Briz-Ponce & Garcia-Penalvo, 2015 ), tablet personal computers (Moran, Hawkes & El Gayar, 2010 ), or just m-learning (Iqbal & Bhatti, 2015 ) was validated. Learning Management Systems (LMSs) in general, along with specific LMSs in particular, like Blackboard (Yi & Hwang, 2003 ), Moodle (Nagy, 2018 ), and Moodle gamification training platform (Vanduhe, Nat & Hasan, 2020 ), were also frequently researched (N=6).

Besides, some studies (N=5) counted on social media services/platforms at large (Al-Rahmi, Shamsuddin, Alturki, Aldraiweesh, Yusof, Al-Rahmi & Aljeraiwi, 2021), as well as on WeChat (Yu, 2020 ) and YouTube (Lee & Lehto, 2013 ) in particular. Since educational possibilities of virtual reality (VR) and augmented reality (AR) are getting more attention, few studies (N=3) were focused on VR technology (Lin and Yeh, 2019), VR and AR technology (Jang, Ko, Shin & Han, 2021 ), while one earlier study concerned virtual world Second Life (Chow, Herold, Choo & Chan, 2012 ). Use of computer technology in general was examined in a couple of studies (N=2) (e.g. Teo, 2010 ), while a number of single studies considered also assistive technology (Nam, Bahn & Lee, 2013 ), collaborative technology, specifically Google applications for collaborative learning (Cheung & Vogel, 2013 ), simulation-based learning environment (Lemay, Morin, Bazelais & Doleck, 2018 ), university communication model (UCOM) which works similar to Massive Open Online Course (MOOC) (Tawafak, Romli & Arshah, 2018 ), as well as Open Educational Resources (OER) (Kelly, 2014 ). Figure  3 provides insight into a variety of validated technologies and modes of delivery.

Validated technologies and modes of delivery

Type of Participants & Sample Size

Another aspect refers to different types of involved participants/users. In a great majority of analysed research (N=29) university students were the most commonly chosen sample group, since most data from web-based questionnaires and/or mailed surveys was collected from the universities (e.g. Salloum, Alhamad, Al-Emran, Monem & Shaalan, 2019 ; Park, 2009 ). Several studies involved employees (N=7) from a variety of organizations/companies, specifically faculty & educational stakeholders (Aburagaga, Agoyi & Elgedawy, 2020 ), bank officials (Abdou & Jasimuddin, 2020 ), business workforce (Lee, Hsieh & Hsu, 2011 ), blue-collar workers (Calisir et al., 2014 ), health nurses (Chen, Yang, Tang, Huang & Yu, 2008 ), along with employees from four international agencies of the United Nations (Roca, Chiu & Martinez, 2006 ), as well as from four industries, specifically manufacturing, information technology, marketing and government agencies (Lee, Hsieh & Chen, 2013 ). Quite a few studies engaged teachers (N=5), to be specific pre-service (Teo, 2010 ) and in-service teachers (Jang et al., 2021 ), special education teachers (Nam et al., 2013 ), as well as K-12 educators (Kelly, 2014 ). A small number of research also involved other participants, in particular university instructors (N=2) (Vanduhe et al., 2020 ), older adults (Lai, 2020 ), and senior high school students (Prasetyo, Ong, Concepcion, Navata, Robles, Tomagos, Young, Diaz, Nadlifatin & Redi, 2021). Finally, in one study information about the type of participants who took part in the conducted research was not provided (see Fig.  4 ).

Type of involved participants

It can be seen that sample size varied from the smallest sample of 72 students (Lin & Yeh, 2019) to the largest one of 2574 students involved in the study conducted by Esteban-Millat et al. ( 2018 ). However, the domination of smaller sample sizes up to 400 participants (N=30) compared to the number of larger sample sizes is notable.

Employed Technology Acceptance and Adoption Models

The conducted review clearly indicated that the vast majority of identified research used TAM model (N=42), in particular the core TAM (N=1), the extended TAM (N=36), along with some studies which integrated TAM with other individual models/theories aiming to advance TAM’s explanatory power (N=5), in particular with:

• Innovation Diffusion Theory (IDT) proposed by Rogers ( 1962 , 1995 ) as the most popular model in investigating innovation acceptance and adoption (N=2), specifically (Lee et al., 2011 ; Al-Rahmi, Yahaya, Aldraiweesh, Alamri, Aljarboa, Alturki & Aljeraiwi, 2019),
• Information Systems Success Model (ISSM) introduced by DeLone and McLean ( 1992 ) as a robust theoretical basis for the study of technology post-adoption (N=2), specifically (Prasetyo et al., 2021 ; Al-Rahmi et al., 2021 ),
• combination of ISSM and Expectation-Confirmation Theory (ECT), a post-adoption theory offered by Oliver ( 1980 ), in work conducted by Roca, Chiu, and Martinez ( 2006 ).

Besides TAM-based research, a few studies explored also the core (N=2) and the extended (N=2) UTAUT model, along with a single research which employed extended UTAUT2 model (refer to Fig.  5 ).

Used technology acceptance and adoption models

Factors Affecting Educational Technology Adoption

This study revealed that, aiming to increase the predictive validity of TAM and UTAUT, in most selected studies (N=44) the models have been extended with different predictive (antecedent) factors . In view of UTAUT model on the one hand, those factors are related to the behavioral intention (BI) variable/construct. On the other hand, when considering TAM, the majority of identified factors represent antecedents of the two core variables of TAM, perceived ease of use (PEU) and perceived usefulness (PU), while a minor number predicts behavioral intention (BI). Among selected research, only three studies have used original models without any modifications and enhancements, in particular the core TAM (Chipps, Kerr, Brysiewicz & Walters, 2015 ) and the core UTAUT (Lai, 2020 ; Yakubu & Dasuki, 2019 ).

In addition, besides a variety of introduced predictors for the core TAM constructs, as well as TAM’s and UTAUT’s behavioral intention variable, the results exposed also a number of incorporated supplementary factors which aimed to moderate relationships among TAM’s constructs. Consequently, categorization of identified factors from models’ modifications and enhancements included in this review is conducted, and three pools of factors affecting educational technology adoption are documented:

• antecedents of perceived ease of use (PEU) and perceived usefulness (PU),
• behavioral intention (BI) antecedents, and.
• moderating factors.

To shed-light-on, numerous identified predictive factors are thematically grouped into: (i) user aspects (individual attributes, and pleasure & usefulness), (ii) task & technology aspects , and (iii) social aspects . The categorised antecedents of TAM variables (PEU and PU), as well as TAM’s and UTAUT’s BI antecedents, along with related illustrative example research are presented in Tables  1 and ​ and2, 2 , respectively.

Predictors of the two core TAM variables (PEU and PU) along with relevant example research

Predictors of TAM’s and UTAUT’s behavioral intention (BI) variable along with example research

Antecedents of Perceived Ease of Use and Perceived Usefulness. By analysing the selected publications, self-efficacy was found as the most widely introduced predictive factor of TAM (N=16). In various empirical studies conducted in educational context it was revealed that self-efficacy, i.e. an individual judgement of one’s capability to use computer (e.g. Salloum et al., 2019 ; Teo, 2009 ), Internet (e.g. Nagy, 2018 ), m-learning (e.g. Park, Nam & Cha, 2012 ), e-learning (e.g. Chen et al., 2008 ) or specific application (e.g. Yi & Hwang, 2003 ), had a significant impact on the perceived usefulness and the perceived ease of use. Another widely researched predictive factors were subjective norm (N=9), defined as the degree to which an individual believes that people who are important to him/her think he/she should or should not perform the behavior in question, as well as perceived enjoyment (N=8) considered as the extent to which the activity of using the computer is perceived to be enjoyable in its own right, apart from any performance consequences that may be anticipated. It has been revealed that the subjective norm (Song & Kong, 2017 ), and enjoyment (Salloum et al., 2019 ), positively and significantly influence students’ perceived usefulness of e-learning, as well as perceived ease of use of e-learning systems (Hanif et al., 2018 ; Chang, Hajiyev & Su, 2017 )

The results indicated that system quality (e.g. Salloum et al., 2019 ) and system accessibility (e.g. Park et al., 2012 ; Hanif et al., 2018 ), along with technological complexity (e.g. Teo, 2009 ) have a significant influence on perceived ease of use. Besides, facilitating conditions , which originally provide resource factors (such as time and money needed) and technology factors regarding compatibility issues that may constrain usage, were indicated to be an essential factor that affect e-learning system (e.g. Song & Kong, 2017 ) or computer technology (e.g. Teo, 2009 ) acceptance. Finally, while the perceived playfulness, which operationalizes the question of how intrinsic motives affect the individual’s acceptance of technology, had a direct impact on the variables perceived usefulness and perceived ease of use (e.g. Padilla-Melendez, del Aguila-Obra & Garrido-Moreno, 2013 ), anxiety as a personal trait explained as evoking anxious or emotional reactions when it comes to performing a behavior, negatively affects the two core TAM variables (e.g. Chang et al., 2017 ; Calisir et al., 2014 )

Behavioral Intention Antecedents. Both self-efficacy and subjective norm were among frequently employed factors affecting attitude towards technology and behavioral intention. The results indicated that self-efficacy was found to have a direct effect and a positive influence on behavioral intention to use e-learning (e.g. Tarhini, Hone & Liu, 2014 ; Yi & Hwang, 2003 ), m-learning (e.g. Moran et al., 2010 ; Park et al., 2012 ), as well as collaborative technology (e.g. Cheung & Vogel, 2013 ), and computers (e.g. Nam et al., 2013 ; Teo, 2009 ). Subjective norm , as another important construct in providing an understanding of the determinants of usage in educational context, is shown to have strong influence on the behavioral intention to use e-learning systems/platforms (e.g. Song & Kong, 2017 ). It has been revealed that subjective norm represented by peers significantly moderate the relationship between attitude and intention toward the technology (Cheung & Vogel, 2013 )

Furthermore, perceived playfulness is found to be one of the key drivers for the adoption and use of blended learning system depending of user’s gender (Padilla-Melendez et al., 2013 ). Also, direct and indirect effect of perceived playfulness on the intention to use a computer-assisted training program has been confirmed (Lin & Yeh, 2019). Finally, the research has exposed that system accessibility was one of the dominant exogenous constructs affecting behavioral intention to use mobile learning (e.g. Park et al., 2012 )

Moderating Factors. Although the majority of selected research has been focused on finding PEU, PU and BI antecedents, there is also a growing need for understanding incorporated supplementary factors aiming to moderate the relationships among TAM variables, on the one hand, as well as those which have an impact on the model itself, on the other. In the investigation of the moderating effect of gender and age on e-learning acceptance Tarhini and colleagues ( 2014 ) have found that age moderates the effect of perceived ease of use, perceived usefulness and self-efficacy on behavioral intention, and that gender moderates the effect of perceived ease of use and social norms on behavioral intention. Yet, unexpectedly, no significant moderating effect of age on the relationship between social norms and behavioral intention was found; results also revealed no moderating of gender on perceived usefulness or self-efficacy and behavioral intention. Padilla-Melendez et al. ( 2013 ) argued that there exist gender differences in attitude and intentions to use. The main contribution of their study is provided evidence that there exist gender differences in the effect of playfulness in the student attitude toward technology and the intention to use it. In females, playfulness influences attitude toward using the system. In males, playfulness influences attitude moderated by perceived usefulness

When examining the moderating effect of individual-level cultural values on users’ acceptance of e-learning in developing countries, Tarhini et al. ( 2016 ) demonstrated that the relationship between social norms and behavioral intention was particularly sensitive to differences in individual cultural values, with significant moderating effects observed for all studied cultural dimensions, in particular masculinity/femininity , individualism/collectivism , power distance and uncertainty avoidance . As a final point, in an empirical study of the use of the General Extended Technology Acceptance Model for E-learning (GETAMEL) to determine the factors that affect students’ intention to use an e-learning system, Chang and colleagues ( 2017 ) found that technological innovation significantly moderates the relationship between subjective norm and perceived usefulness, as well as perceived usefulness and behavioral intention to use e-learning.

Integration with Other Models & Theories

Although TAM proved to be a powerful model applicable to various technologies and contexts at the individual level, research also revealed its successful integration with other contributing theories and models within a range of different application fields (Al-Emran & Granić, 2021 ). To evaluate students’ adoption of smartwatches for educational purposes, TAM has been successfully combined with Goodhue and Thompson’s ( 1995 ) Task-Technology Fit (TTF) (Al-Emran, 2021 ), and Rogers ( 1975 ) Protection Motivation Theory (PMT) (Al-Emran, Granić, Al-Sharafi, Nisreen & Sarrab, 2021 ). In addition, the Innovation Diffusion Theory (IDT) has been combined with TAM in an empirical investigation on university students’ intention to use e-learning systems (Al-Rahmi et al., 2019 ), to investigate factors affecting business employees’ behavioral intentions to use the e-learning system (Lee et al., 2011 ), as well as to explore diffusion and adoption of an open source learning platform (Huang, Wang, Yang & Shiau, 2020 ). The Information Systems Success Model (ISSM), as one of the post-adoption theories, has been integrated with TAM to help in determining factors which affected acceptance of e-learning platforms during the COVID-19 pandemic (Prasetyo et al., 2021 ), and in exploring students’ behavioral intention to use social media, specifically the perception of their academic performance and satisfaction (Al-Rahmi et al., 2021 ). Lastly, to understand e-learning continuance intention, TAM has been integrated with ISSM and Oliver’s ( 1980 ) Expectation-Confirmation Theory (ECT) (Roca et al., 2006 ).

Limitations of the Conducted Review

In the conducted review, specific criteria were used to search the WoS CCC database for relevant studies to be included and analysed. The applied research approach allowed to capture and cover only a representative selection of studies published in numerous recognized journals, and undoubtedly cannot be all-inclusive. Specification of other search criteria along with a selection of other databases might bring more and/or slightly different selection of relevant journal articles and proceeding papers. Hence, this review should be regarded as an attempt to explore relevant challenges and emerged topics in educational technology adoption field during the past. Finally, it should be noted that this study does not describe or pass any judgement on research methods and approaches employed in the analysed literature since this is out of the scope of this review.

Conclusion and Future Research

Over the past decades a variety of theoretical perspectives have been advanced to provide an understanding of the determinants of acceptance, adoption and usage of various technologies used to support the process of knowledge transfer and acquisition. However, it has been shown that over the years TAM has emerged as a leading scientific paradigm for studying the determinants affecting human behavior and usage of various technologies through beliefs about two factors: the perceived ease of use and the perceived usefulness (Al-Emran & Granić, 2021 ; Marangunić & Granić, 2015 ). Moreover, the conducted review once again exposed TAM predomination in educational context as well; refer also to (Granić & Marangunić, 2019 ). This study confirmed that TAM is the most widely used powerful and valid model for prediction and explanation of user’s behavior towards acceptance and adoption of various technologies used to support the process of learning and teaching.

Continuous development of new technologies, along with a growing number and diversity of users in educational context, opens new directions of research that could raise understanding of the technology acceptance, adoption, and actual use. Thus, despite the fact that extensive work has already been conducted, there is still a huge potential for further advancements, exploration and practice in this field of research. In light of current research findings, future work could follow new research directions:

• to explore predictive validity of technology acceptance models and theories when applied to various supporting ICT technologies employed in a number of emerging teaching strategies , like flipped learning, gamification-based learning, and visual scaffolding, favourable communication support , like chats, discussion forums, and discussion boards, as well as relevant facilitative tools , like blogs and wikis used in educational context;
• to further empirically validate predictive factors (antecedents) influencing the acceptance and adoption of technology in education which have not been so widely explored, for example perceived playfulness which has been associated with a high level of perceived usefulness (Lin & Yeh, 2019), social media usage which has indicated a positive and constructive influence on satisfaction and academic performance (Al-Rahmi et al., 2021 ), as well as psychological influence factors such as conformity behavior and self-esteem due to their positive and direct effect on perceived ease of use, perceived usefulness, perceived enjoyment and continuance intention (Yu, 2020 );
• to explore some possibly significant predictive factors that still have not been adequately examined, but could be important in understanding educational technology adoption as for example, the factor dealing with task & technology aspects, that can be described as cost-effective/pennyworth , here referring to employment of efficient solutions in educational context with relatively limited budget (e.g. simulation, VR, AR, visual scaffolding/visualization);
• to advance the explanatory power of individual technology acceptance and adoption models by reviewing and integrating them with already established theories and models from other fields, like social psychology – Bagozzi and Warshaw’s ( 1990 ) Theory of Trying (TofT), cognitive psychology – Bhattacherjee’s ( 2001 ) Expectation-Confirmation Model (ECM), along with information technology – Goodhue and Thompson’s (1995) Task-Technology Fit (TTF).

Declarations

The data of the systematic review consist of articles published in journals and conferences. Many of these are freely available online, others can be accessed for a fee or through subscription.

The authors declare no conflicts of interest.

No ethics review was required to undertake this literature review.

The original online version of this article was revised: Figures 2, 3 and 4 were incorrectly captured in the html version.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Change history

A Correction to this paper has been published: 10.1007/s10639-022-11053-0

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Assessing the state of technology education in primary schools: a systematic review of the last 2 decades

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• Published: 22 September 2023

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• Christina Ioanna Pappa   ORCID: orcid.org/0000-0001-5484-6528 1 ,
• Despoina Georgiou 2 &
• Daniel Pittich 1  

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This study reports on a systematic review of the current status of technology education in primary schools and the terminology used in the fields of technology and engineering education. Additionally, this review highlights crucial aspects of teaching and learning that must not be overlooked when outlining the current state of technology and engineering education, such as students’ and teachers’ personal factors, classroom communication, and teacher professional growth. Following PRISMA guidelines, two electronic databases were reviewed, Web of Science and Education Resources Information Center. The literature search identified a total of 1206 papers, 125 from Web of Science and 1081 from ERIC. After applying the inclusion and exclusion criteria, 33 papers were selected and evaluated in depth. The results show that research on technology education in primary schools is a growing field of interest but fragmented in focus. Our review is the first to indicate the wide range of technology and engineering education definitions. We also highlight the large heterogeneity of studies focusing on students’ and teachers’ personal factors and classroom interactions, a finding that may be explained by the unclear concepts and aims of technology and engineering curricula. This study contributes to and supports research and policymaking to better understand the current status, heterogeneities, and challenges in technology and engineering education in primary schools. In addition, we provide first insights to support professional development efforts targeting teachers’ technology acceptance and improvement of their technology-related teaching practices.

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Introduction

The significance of technology is constantly growing with the swift technical-productive advancements in all spheres of society (Mammes et al., 2019 ). Usually, technology (T) and engineering (E) are less emphasized in STEM (science, technology, engineering, and mathematics) education compared to science (S) and mathematics (M) (Bozick et al., 2017 ). Additionally, technology education in primary schools typically focuses on computer science and informatics, while the technical and practical aspects of technology education are often overlooked (Davies, 2011 ; Firat, 2017 ; Wender, 2004 ).

Differences in the description of technology education exist at various levels of education, including primary schools, both across countries and within a country's provinces and districts (Keskin, 2017 ; Mammes et al., 2016 ; Rasinen et al., 2009 ; Williams, 2006 ). The lack of unified standards regarding the definition, status, content, aims, and pedagogical approaches in technology education presents multiple challenges to its effective implementation (Rasinen et al., 2009 ; Williams, 2006 ). In Germany, for instance, where education governance is decentralized, significant variations in curriculum subjects, structures, and content exist among federal states (Mammes et al., 2012 , 2016 ).

Technology-related topics in the German curriculum fall under the category of “general science” based on the curriculum of each state (Mammes et al., 2016 ). Similarly, in the United States, the curriculum in primary schools can vary depending on the school district and state requirements (Sanders, 2009 ; Williams, 2006 ). Like Germany and US, a number of other European countries (such as Austria, Estonia, Finland, and France) were unable to successfully implement a standardized curriculum with common standards, objectives, and operational guidelines (Lavonen, 2021 ; Lee & Lee, 2022 ; Mammes et al., 2016 ; Rasinen et al., 2009 ). The subject of technology is often integrated into different subjects, such as "science and techniques" in France (Jones et al., 2013 ; Williams, 2006 ) and "craft and technology education" in Estonia (Rasinen et al., 2009 ). The blurred distinction between science, technology, and craft subjects may hinder students' technological competencies due to the lack of clear descriptions and operational instructions (Mammes et al., 2016 ; Rasinen et al., 2009 ; Williams, 2006 ). Additionally, distinguishing between technology and engineering poses challenges in terms of their aims and implementation process (Boeve-de Pauw et al., 2020 ; Rossouw et al., 2011 ).

Previous reviews have examined the status of STEM education, technology, and engineering education at higher educational levels. Reinholz et al. ( 2021 ) highlighted the lack of a clear and consistent theoretical framework for STEM subjects. Li et al. ( 2020 ) conducted a systematic analysis, finding that STEM education research is gaining global prominence, with distinct journals focusing on the field. Margot and Kettler ( 2019 ) identified perceived barriers among teachers and recommended collaboration opportunities and access to high-quality curriculum resources to enhance STEM implementation. Sherman et al. ( 2010 ) explored key issues related to technology education in middle schools.

Despite the inclusion of technology education in various countries’ educational curricula, there is a need to establish a clear and consistent understanding of the subject (Pappa et al., 2023 ). Additionally, it is crucial to establish unified standards, goals, and guidelines for effectively implementing technology education in schools (Rossouw et al., 2011 ). To successfully define and understand the role of technology education, we first investigated the current status of technology education research, summarized and identified the definitions used in empirical studies from the past 2 decades. Additionally, the review includes studies that address key stakeholders in primary education, including teachers, students, and the classroom environment. Technology education holds the potential to enhance the development of personal factors for both students and teachers (e.g., Douglas et al., 2016 ; Post & van der Molen, 2014 ; Rohaan et al., 2010 ). Teaching and learning are intricate processes, and to comprehend and enhance technology education practices, it is crucial to examine all the essential teaching and learning parameters (Kilpatrick et al., 2001 ).

Teachers’ and students’ personal factors and technology education

Irregular educational standards in technology education might influence both students’ and teachers’ technical personal factors (i.e., beliefs, perceptions, competences, etc.) (Georgiou, et al., 2023b ; Mammes et al., 2012 ; Möller et al., 1996 ) and teachers’ lesson planning decisions (Georgiou, et al., 2023b ; Mammes et al., 2016 ; Pappa et al., 2023 ). Competence and confidence are required for teachers in technical education (Davies, 2000 ; Möller et al., 1996 ; Pappa et al., 2023 ). It is essential for teachers to acquire a cohesive and clear understanding of the concept of technology so that they can foster positive student attitudes toward the subject (De Vries, 2000 ). Moreover, teachers’ lack of training and technical expertise may affect their lesson planning and implementation and increase their resistance toward technical education (Mammes et al., 2016 ; Pappa et al., 2023 ; Rohaan, 2009 ).

Similar to teachers, students’ technological skills and engagement with technology and engineering subjects may help them to connect their daily experiences with these subjects and enhance their critical thinking and problem-solving skills (Sneider & Ravel, 2021 ; Wright et al., 2018 ). Students’ positive attitudes toward technology are often linked to an accurate and broader understanding of technology (Rohaan et al., 2010 ). Students who do not feel confident and competent in their technological abilities might neglect these subjects in their learning processes (Rasinen et al., 2009 ). More specifically, a lack of technological abilities can restrict students’ opportunities and decisions regarding their educational options, such as university courses and vocational training (Mammes et al., 2012 ; Rohaan et al., 2010 ). Additionally, in early childhood, inadequate technical socialization may often lead to negative self-cognitions regarding technology and negative judgments about one’s technical capabilities (Jakobs & Ziefle, 2010 ; Mammes et al., 2016 ). Thus, the development of technological education in primary school curriculum may foster teachers’ personal factors related to technology implementation, increase students’ interest in technology and science, and reduce the existing gender interest (i.e., gender stereotypes about male and female interest in STEM subjects) and motivational differences in STEM subjects (Mammes et al., 2016 ; Wright et al., 2018 ).

Aim of the study

Defining technology education is a critical issue in the teacher education literature, and it is not without controversy (Boeve-de Pauw et al., 2020 ; Rossouw et al., 2011 ). Technology education curricula and course descriptions are relatively diverse, and there is no common understanding and agreement about the aims and learning purposes of technology education (Sherman et al., 2010 ). The disciplines, definition, and understanding of technology education, in general, have often been interpreted similarly to engineering education (Rossouw et al., 2011 ). However, they have also been viewed as distinct subjects with different goals and aims (Koul et al., 2018 ).

This study adopts the terminology of technology education of Fox-Turnbull ( 2016 ) and Ropohl ( 1991 ) as the examination of the function of artifacts, design processes, and the evaluation of technological solutions within social and cultural contexts. The first aim of this literature review study is to examine how technology education in primary schools has been defined based on empirical studies from the past 2 decades. In addition to clarifying terminology, the study also seeks to investigate the extent to which empirical studies have focused on the personal factors of teachers and students, as well as the classroom environments that support effective technology education. To achieve this, a diverse array of topics, methodologies, and research designs are incorporated to examine the current research evidence. Specifically, the current literature review addresses the following research questions:

How is technology education in primary schools defined based on empirical studies from the last 2 decades?

To what extent do empirically based studies focus on students’ and teachers’ personal factors as well as classroom environments in primary school technology education?

The focus of this review is on primary school teachers, students, and classroom environments for several reasons. Firstly, technology and engineering education in primary education is often under-emphasized or only briefly addressed within other subjects, such as science (Mammes et al., 2016 ; Wright et al., 2018 ). Secondly, technology education has the potential to enhance the development of personal factors among both students and teachers (e.g., Douglas et al., 2016 ; Post & van der Molen, 2014 ; Rohaan et al., 2010 ). Thirdly, a lack of technology socialization in early school years may negatively impact students’ competencies, future career choices, and gender stereotypes (Jakobs & Ziefle, 2010 ; Mammes et al., 2016 ).

Through the two aforementioned research questions, we seek to set the ground frameworks for the concepts and goals of technology and engineering curriculum, with implications for enhancing and developing teacher professional development (TPD) initiatives pertaining to technology education. These efforts are intended to positively impact students' perceptions, attitudes, and comprehension of the technology and engineering curriculum.

Information sources and search strategy

A systematic literature review was conducted by searching for published articles between 2000 and 2020 in two widely recognized databases: Web of Science (WoS) Core Collection and Education Resources Information Center (ERIC). The selection of these databases was based on their reputation for containing peer-reviewed scientific and scholarly literature from various disciplines and regions worldwide. The search strategy was developed in consultation with a librarian and included the following terms: “technolog* educat*”, “primary educat*”, “primary school*”, “elementary educat*”, “elementary school*”. After reviewing the syntax of each database with the support of the librarian a search string was generated (Table 1 ). Each term was searched individually in the databases and then in the advanced search in WoS Core Collection and the Search History in ERIC the terms “primary educat*”, “primary school*”, “elementary educat*”, “elementary school*” were selected and combined with the demand OR. This search string was then selected and combined with the term “technolog* educat*” and the demand AND. The search string was refined by using additional parameters, such as a defined time frame, document type (articles, review articles), and language (English), and was limited to peer-reviewed articles to increase the credibility of the study. The final search in all databases was performed in January 2023.

Inclusion and exclusion criteria

In order to select and include the relevant articles for our research questions from the selected datasets specific inclusion (IC) and exclusion (EC) criteria were defined. The inclusion criteria were the followings: IC1: journal articles, IC2: the study is written in English, IC3: the study is peer-reviewed, and IC4: the study is not listed in another database. The exclusion criteria of the study were: EC1: the study is not conducted at primary school educational level, EC2: the study is not about technology/engineering/technical education, EC3: the study does not refer to primary school students or primary school in-service teachers.

Data collection and analysis

The current systematic literature review was conducted in five phases according to the PRISMA 2020 guidelines (Page et al., 2021 ). In the first phase, the initial literature was conducted in both electronic databases WoS ( n  = 125) and ERIC ( n  = 1081). Based on the inclusion (IC1, IC2, IC3) criteria, a total of 282 papers (52 papers from WoS and 230 from ERIC) were excluded because of the type of paper, language, and peer-review criteria. To check the duplicates (IC4) Microsoft Excel software was used and 72 papers were excluded. Additionally, regarding the exclusion (EC1, EC2, EC3) criteria, 623 papers were excluded as illegible by the database search engine categories, such as “High school education”, “Computer Science”, “Pre-service teachers” etc. To validate the accurate exclusion of papers based on the refinement categories of the database search engine, a researcher from our team conducted a rigorous review of the excluded papers. This comprehensive assessment was undertaken to ensure that no valuable paper was inadvertently omitted.

In the second phase, the title and the abstract of the remaining 230 papers were reviewed and the exclusion criteria (EC1, EC2, EC3) were applied. In case of insufficient information in the abstracts, the entire paper was browsed. This step resulted in 74 relevant articles for the review.

In the third step, the search results from this query were then used to retrieve the full-text articles. The resulting articles were reviewed independently by the first and the second author of this paper using the same inclusion and exclusion criteria and descriptors. The authors compared and verified their findings, and the degree of agreement was 95%. Disagreements were discussed until a consensus was reached. The first set of studies (n = 33) were excluded as they focused on topics outside the scope of the current review, such as computer science, mathematics, digital media, or science (EC2). The second set of studies (n = 10) were excluded as they were focused on higher education (EC1). Similarly, the third set of studies (n = 7) was excluded as they focused on pre-service teacher education (EC3). Finally, the fourth set of 3 studies was excluded as they did not involve primary school students or teachers (EC3). This method resulted in the exclusion of 21 articles due to the lack of fit to the predetermined criteria (Fig.  1 ).

PRISMA 2020 flow diagram

In the fourth phase, to identify additional relevant publications, a manual search of reference lists of included studies and all their authors was conducted. This search resulted in 23 papers, which were thoroughly reviewed for relevance to the inclusion and exclusion criteria. In the fifth phase, the full text of the 33 papers was examined for relevance to the criteria and research questions of the current review. The described process is depicted in a PRISMA flow diagram (Page et al., 2021 ) (Fig.  1 ).

Additionally, to ensure the quality of the papers included in the review, two research experts from our team reviewed the selected articles regarding the Objectives and Purposes, Review of the Literature, Theoretical Frameworks, Participants, Methods, Results and Conclusions, and Significance. Because of the variety of studies, methods, and research designs, each of the seven components was evaluated to determine if they met the standards for quality reporting, as outlined in Mullet’s ( 2016 ) guidelines (Margot & Kettler, 2019 ; Mullet et al., 2017 ) (See Table 2 ). Each criterion was assessed using a 4-point scale, with a score of 1 indicating that the criterion did not meet the standard and a score of 4 indicating that it exceeded the standard. The total score for each article was between 7 and 28. Articles that scored 14 or less were considered to be of low quality and were excluded from the analysis. Articles with a score of 15 or above were included in this review. The assessment score of 15 out of 28 in our review was based on methodologies used in different peer-reviewed articles (e.g., Alangari, 2022 ; Davis, 2021 ; Margot & Kettler, 2019 ). Among the included articles, 10% scored between 15 and 19, 60% scored between 20 and 24, and the remaining 30% achieved scores ranging from 25 to 28.To ensure objectivity, in addition to the two research experts, the second author reviewed all 33 selected articles and confirmed that all retained articles met the quality criteria.

The final 33 articles were categorized into three groups based on the above-mentioned aspects for further analysis: definitions of technology education stemming from engineering and technology education (Group 1), technology education in primary schools for teachers and students (Group 2), and classroom practices (Group 3). A total of 22 articles were identified in Group 1, 24 in Group 2, and 9 in Group 3.

Analysis of articles

We designed a table (Table 3 ) to collect and organize the selected articles representing relevant aspects of each study. The table included information about the focus of each article regarding the study field (i.e., technology and engineering), study population (i.e., students, teachers, classroom environment), sample characteristics, the content of the study (i.e., which was the focus of the articles), research methodology, and the primary outcome. The first author read the full text of every article, identified the relevant aspects of each study, and completed the table. After completing the table, the second author randomly analyzed 30% of the selected articles (O’Connor & Joffe, 2020 ). Both authors independently compared their results.

The next step included the categorization of the content of each study into subcategories: (a) students’ personal factors: beliefs/perceptions, knowledge/skills, attitudes, and students’ group differences; (b) teachers’ personal factors: beliefs/perceptions, knowledge/skills, attitudes, and teachers’ TPDs; (c) both student and teacher data and classroom learning environment. The subcategories of students’ personal factors and teachers’ personal factors were selected based on previous studies indicating that knowledge and beliefs are strongly related and both contribute to teaching and learning procedures (Charalambous, 2015 ; Georgiou, Diery, et al., 2023a ; Georgiou et al., 2020 ; Kilpatrick et al., 2001 ; Vermunt, 2005 ). Additionally, previous studies have demonstrated the strong interplay between personal factors, such as age, beliefs, knowledge, and attitudes, and contextual factors, such as the classroom environment, student–teacher interactions, and teacher instructions, in determining the learning experiences in a classroom setting (Vermunt, 2005 ).

As in the previous step of the analysis, the first author constructed a table for each group including the content and subcategories of each study: (Group 1), technology education in primary schools for teachers and students (Group 2), and classroom practices (Group 3) the table of the content and subcategories. Next, the second author analyzed randomly 30% of the chosen articles. Cohen’s K was used to determine if there was agreement between two raters (Brennan & Silman, 1992 ; McHugh, 2012 ). The results revealed that there was excellent agreement between the two raters (K = 0.862 (95% CI 0.300 to 0.886), p  < 0.0005).

Description of technology education in primary schools

The first group of selected articles was used to answer the first research question and identify a definition of technology education. A total of 33 articles were selected, with 22 of them including definitions related to technology or engineering education. Among these articles, 12 focused on technology education, nine on engineering education, and one discussed both. As Table 4 illustrates, there is a degree of heterogeneity in how studies refer to technology and engineering education. In several articles, technology education was seen as part of the STEM courses or engineering or science. The study of Boeve-de Pauw et al. ( 2020 ) argues that technology education is not distinct from engineering education and can be interpreted as "Design and Technology" or "learning toward design technology". Hong et al. ( 2011 ) define technology education as the comprehension, construction, and development of artifacts and their functions. Milne ( 2013 ) emphasizes the importance of design and design processes in technology education, based on New Zealand's curriculum which includes the aspects of "Nature of Technology," "Technological Knowledge," and "Technological Practice". Another study that was located in New Zealand by Jones and Moreland ( 2004 ) defines technology education as the development of students’ technological literacy by exploring and solving complex and related technological problems.

In Sweden, technology education is a mandatory subject aimed at developing students' technological competence and awareness (Sultan et al., 2020 ). The Swedish curriculum includes three aspects: a specific component, practical processes, and the relation to humans.

Studies based on the Australian national curriculum describe technology education as the purposeful application of knowledge, experience, and resources to create products and processes that meet human needs (Stein et al., 2002 , 2007 ).

Firat ( 2017 ) differentiates technology from computer equipment and defines technology as the competence to understand and reason about technological artifacts and phenomena. Fox-Turnbull ( 2016 ) emphasizes the importance of conversation in learning and understanding technology.

Rohaan et al. ( 2010 ) emphasized that technology education should enable students to think critically about design, development, and implementation processes to solve practical problems. Solomonidou and Tassios ( 2007 ) defined technology as the process of dealing with crafts and human innovations to develop systems that solve problems and enhance human capacities. They highlighted the role of technology education and technological literacy in promoting technological knowledge and reasoning.

The connection between technology and engineering is highlighted in the study by Koul et al. ( 2018 ), which defined technology literacy as the understanding of designed procedures and tools, while engineering literacy involves understanding the improvement of technologies through design procedures. Both literacies are strongly connected and contribute to STEM literacy.

Various articles focused on engineering education, defining engineering and its aims based on the National Research Council ( 2012 ) and the Council ( 2013 ) (Cunningham & Kelly, 2017 ; Deniz et al., 2020 ; Douglas et al., 2016 ; Mangiante & Gabriele-Black, 2020 ; McFadden & Roehrig, 2019 ; Wendell & Rogers, 2013 ). Cunningham and Kelly ( 2017 ) described engineering as a collective enterprise that considers the affordances and constraints of the problem space, materials, and clients. Deniz et al. ( 2020 ) defined engineering as systematically engaging in the practice of design to achieve solutions for specific problems. Douglas et al. ( 2016 ) related engineering to design processes connected to scientific processes. Mangiante and Gabriele-Black ( 2020 ) concluded that engineering education involves defining engineering problems, finding solutions, and engaging in design processes. McFadden and Roehrig ( 2019 ) and Capobianco et al. ( 2011 ) described engineering as engagement with practices that reflect the work of engineers. Wendell and Rogers ( 2013 ) investigated an engineering design-based curriculum, emphasizing engagement in design procedures to address constraints and find solutions.

The studies of English and King ( 2017 ) and English et al. ( 2017 ) highlighted the development of design procedures in early school years within engineering education. Their model of engineering design processes included problem scoping, idea creation, designing and constructing, design assessment, and redesign and reconstruction. These studies provide insights into the importance of design, problem-solving, and the connection between technology and engineering in technology education and STEM literacy.

Students’ personal factors and group differences in technology education

The second group included articles on student and teacher technology education in primary schools. In this chapter, articles about students’ personal factors and group differences in technology education were selected to address the first part of the second research question (Table 5 ).

Students’ attitudes towards technology and engineering design-based science were examined in the studies of Boeve-de Pauw et al. ( 2020 ), Wendell and Rogers ( 2013 ), and Koul et al. ( 2018 ). Boeve-de Pauw et al. ( 2020 ) onducted a study on the impact of a short-term educational intervention on students' attitudes toward technology. The intervention positively influenced students' attitudes, particularly among female students who held stereotypical views about technology being for boys. Wendell and Rogers ( 2013 ) conducted a study on the impact of a short-term educational intervention on students' attitudes toward technology. The intervention positively influenced students' attitudes, particularly among female students who held stereotypical views about technology being for boys. Koul et al. ( 2018 ) developed an instrument to evaluate student attitudes in STEM classrooms, revealing some misconceptions among students about engineers. Male students showed an advantage in engineering and technology materials, while female students displayed better understanding of engineering concepts.

Capobianco et al. ( 2011 ), Davis et al. ( 2002 ), Slangen et al. ( 2011 ), and Solomonidou and Tassios ( 2007 ) discussed students’ perceptions of technology and engineering. Capobianco et al. ( 2011 ) investigated students' perceptions of engineers, finding that students conceptualized engineers as mechanics, laborers, and technicians, often associated with male figures. Solomonidou and Tassios ( 2007 ) explored students' conceptions of technology, with some perceiving technology as modern tools and appliances while others emphasized its negative impact on the environment. The study conducted by Davis and colleagues ( 2002 ) examined students' understanding of technology concepts across different age groups, revealing both similarities and differences in their level of understanding. Slangen and colleagues ( 2011 ) studied students' understanding of robotics and found that problem-solving activities and teacher-led dialogue improved students' technological understanding and knowledge of robot functions.

The topic of students’ knowledge and skills appeared to be most frequently discussed in the literature in terms of primary school students’ personal competences (e.g., English & King, 2017 ; English et al., 2017 ; Firat, 2017 ; Hong et al., 2011 ; Koul et al., 2018 ; Milne, 2013 ). Milne ( 2013 ) found that project-based learning helped students develop technological knowledge and skills, as evidenced by their understanding of the purpose of a photo frame, creation of design plans, and reflection on emotions. English et al. ( 2017 ) examined students' STEM knowledge and design problem-solving skills, finding variations in engineering techniques and problem components between different schools In another study, English and King ( 2017 ) investigated students' skills and design processes in a civil engineering task, identifying the importance of content knowledge and gestures in problem-solving.

The aspect of communication and collaborative learning in technological project design was explored by Hong et al. ( 2011 ), who found that collaborative learning enhanced students' participation, reflection, and problem-solving during the design process. Looijenga et al. ( 2020 ) found that well-structured tasks and dialogue improved student engagement and relationships.

Firat ( 2017 ) examined students' recognition and reasoning skills regarding technological artifacts, highlighting moderate levels of recognition and associations of electricity with technology. Socioeconomic factors influenced students' technology recognition. Students’ differences and more specifically gender differences were addressed in the studies of Mammes ( 2004 ), Sultan et al. ( 2020 ), and Virtanen et al. ( 2015 ). Mammes ( 2004 ) observed increased technological interest and reduced differences in dealing with technological objects among male and female students. The study of Sultan et al. ( 2020 ) found that despite gender-neutral activities, female students adhered to existing gender stereotypes and expressed dissatisfaction when males dominated activities. The research conducted by Virtanen and colleagues in ( 2015 ) discovered gender differences in preferences for environmentally-focused topics and decorative items among female students, while male students showed a preference for building electronic devices and reported higher self-assurance in their abilities.

Teachers’ personal factors in technology education

This chapter discussed teachers’ personal factors based on eight selected articles, addressing the second part of the second research question (Table 6 ). Four articles included a TPD on technology education and reported the results on teachers’ factors (Deniz et al., 2020 ; Stein et al., 2000 , 2007 ; Watkins et al., 2021 ). Deniz et al. ( 2020 ) examined the changes in teachers’ engineering views after a 3-day TPD. Their study found that precise and reflective strategies should be included in engineering design experiences. Teachers’ nature of engineering views (NOE) was improved after the TPD, and above all NOE aspects, their views regarding engineering design processes were more informed.

Watkins et al. ( 2021 ) studied the reasoning of two teachers about teaching engineering design processes following a teacher education program. Changes in the teachers' reasoning reflected both context sensitivity and growing stability.

Stein et al. conducted several studies on teachers' beliefs and understandings of technology education. In their first study (2000), they found that teachers related the meaning of technology to other learning areas already included in their teaching programs. In a later study (Stein et al., 2002 ), they investigated teachers' beliefs on implementing design and technology education practices, highlighting the impact of prior beliefs, experiences, and limited knowledge on teaching the subject. Finally, in a third study (Stein et al., 2007 ), they explored teachers' experiences in a TPD program, noting that it helped them express ideas, ask better questions, and increase confidence in teaching technology.

Rohaan et al. ( 2012 ) examined teachers' knowledge domains in technology education and their relationship. The study found that subject matter knowledge (SMK) was essential for pedagogical content knowledge (PCK) and self-efficacy, with self-efficacy influencing teachers' attitudes toward technology. However, teachers had a relatively low level of PCK despite acquiring a basic level of SMK.

Moreland and Jones in ( 2000 ) explored the impact of teachers' technology classroom assessment practices, noting that these practices were influenced by school culture, policies, and subject expertise. Lack of technology-related knowledge hindered assessment practices, with a focus on general skills rather than students' technological understanding. In a subsequent study, Jones and Moreland in ( 2004 ) examined the use of frameworks and tools to enhance teachers' pedagogical content knowledge (PCK), identifying strategies such as reflecting on practices, utilizing frameworks, participating in workshops, providing support, and using student portfolios.

Teacher–student interactions and the classroom environment in technology education

The third group included articles regarding teacher–student interactions and the classroom environment in technology education (Table 7 ). In this chapter, nine articles were selected to address the third part of the second research question. Four studies focused on the classroom environment in engineering and technology education (Björkholm, 2014 ; Cunningham & Kelly, 2017 ; Fox-Turnbull, 2016 ; McFadden & Roehrig, 2019 ). Björkholm ( 2014 ) evaluated technical solutions in technology classrooms, finding that group discussions improved students' ability to assess suitability for purpose. Cunningham and Kelly ( 2017 ) examined classroom discourse in an engineering class, highlighting the development of communal knowledge and students' agency. McFadden and Roehrig ( 2019 ) analyzed instructional discourse strategies in engineering design activities, emphasizing the importance of pedagogical support processes. Fox-Turnbull ( 2016 ) identified stages of conversation in technology education and found that prior learning aided current learning processes.

Several studies reported data on teacher and student personal competencies, their influences, and interactions. Douglas et al. ( 2016 ) studied the implementation of engineering through a TPD program, noting variations in school support and time constraints. Mangiante and Gabriele-Black ( 2020 ) discussed the outcomes of TPD on teachers' implementation of engineering design curriculum practices and students' misunderstandings. Lottero-Perdue and Lachapelle ( 2020 ) examined students' general and engineering mindsets, observing differences based on socioeconomic status and the predictive power of general mindset.

Post and van der Molen ( 2014 ) investigated the effect technology-oriented company visits on students' attitudes and competencies, with limited changes observed and teacher involvement affecting the outcomes. In a review, Rohaan et al. ( 2010 ) the connection between teachers' technology knowledge and students' attitudes, highlighting the importance of teachers' PCK in fostering positive attitudes and influencing students' learning and interest in technology.

The results of our literature review spanning from 2000 to 2020 indicate that technology and engineering education is a growing area of interest as evidenced by the increasing number of publications in recent years. Our study provides a thorough overview of how technology education in primary schools has been defined based on empirical studies from the past 2 decades. Alongside clarifying terminology, the review examines the extent to which empirical studies have emphasized the personal factors of teachers and students, as well as the classroom environments that promote effective technology education. These findings offer valuable insights into the current state of technology education in primary schools and the implications of the research for future practice and policy.

Our study reveals that little research has addressed the topic of technology education in primary schools without focusing on the aspects of computer science and informatics. As the article analysis pointed out the majority of the excluded studies were related to computer science, mathematics, digital media, or science (EC2). In addition, some studies were excluded because they were focused on higher education (EC1), and pre-service teacher education (EC3) or they did not refer to primary school students or teachers (EC3).

Technology and engineering are often mentioned in studies regarding science and STEM but not as distinct subjects with concrete aims and learning contexts (Keskin, 2017 ; Mammes et al., 2016 ; Rasinen et al., 2009 ). Various studies have highlighted significant differences in the technology education curriculum at different levels of education, including primary schools (Jones et al., 2013 ; Rasinen et al., 2009 ; Williams, 2006 ). These differences are not only apparent among different countries but also within the same country, making it challenging to implement technology education successfully (Mammes et al., 2016 ; Rasinen et al., 2009 ; Williams, 2006 ). The lack of unified standards, including the definition, status, content, aims, and pedagogical structures, further complicates the situation (Williams, 2006 ). Additionally, since there are no clear concepts and aims of technology and engineering curriculum, primary school teachers may not have the appropriate preparation or confidence to teach technological subjects (Georgiou et al., 2023b ; Mammes et al., 2016 ; Pappa et al., 2023 ).

An analysis and synthesis of studies on engineering and technology education revealed that the terms "technology" and "engineering" sometimes overlap but have distinct emphases. As Table 4 illustrates, there is a degree of heterogeneity in how studies refer to technology and engineering education. Koul et al. ( 2018 ) defined technology literacy as the capacity to comprehend the design process, its tools, and frameworks. In contrast, engineering literacy is defined as an understanding of how technology is enhanced through the design process. However, other studies have argued that technology and engineering are interconnected and cannot be easily distinguished from each other (Boeve-de Pauw et al., 2020 ; Rossouw et al., 2011 ).

Based on previous research and the findings of this review, it is evident that technology and engineering education are interconnected. Both fields focus on understanding the design and operational processes, as well as the tools and methodologies used to develop and assess problem-solving solutions (Boeve-de Pauw et al., 2020 ; Fox-Turnbull, 2016 ; Rossouw et al., 2011 ). Therefore, it is recommended to create a unified list of concepts and contexts, such as product design, functionality, and structure, to establish standardized frameworks for technology and engineering education curricula (Rossouw et al., 2011 ).

The findings regarding the second research question revealed the plethora of studies on students’ and teachers’ personal factors as well as on their interactions and classroom discourse. This review synthesizes studies on both students and teachers to give a comprehensive understanding of the intricate aspects of education and the acquisition of knowledge (Charalambous, 2015 ; Kilpatrick et al., 2001 ; Vermunt, 2005 ). Sixteen articles examined students’ personal factors (Table 5 ), eight articles focused on teachers’ personal factors (Table 6 ) (i.e., personal factors), and nine articles on student–teacher personal and contextual factors (Table 7 ). In alignment with previous research, several studies argued that teachers’ personal and contextual factors are strongly connected to students’ personal factors (i.e., knowledge, perceptions, and attitudes) about technology and engineering education (Douglas et al., 2016 ; Post & van der Molen, 2014 ; Rohaan et al., 2010 ; Vermunt, 2005 ). This leads us to further recognize the importance of TPDs for fostering teachers’ technology acceptance and information technology skills (Deniz et al., 2020 ; Douglas et al., 2016 ; Koul et al., 2018 ). TPDs should support teachers to understand, experiment, and reflect on the contexts, procedures, and approaches of technology and engineering education, leading to increased confidence and successful implementation of technology in the classroom (Mangiante & Gabriele-Black, 2020 ; Stein et al., 2000 ; Watkins et al., 2021 ).

This review study seeks to analyze and synthesize relevant research articles about the current status of technology and engineering education, taking into account all key stakeholders in primary education, including teachers, students, and the classroom environment. Therefore, our findings have implications for both research and practice, providing a framework for discussing advancements in technology and engineering education research. Specifically, our findings provide the necessary common ground for understanding the concepts and aims of technology and engineering curriculum. This study also emphasizes the important role technology plays in primary schools and urges future studies to focus on the development and implementation of technology-oriented professional development programs for pre-service and in-service primary school teachers.

In sum, this study serves as a valuable knowledge base and enhances the understanding of technology and engineering education from the perspectives of both teachers and students. Building upon the current findings, our future research endeavors will involve the development of a Teacher Development Program (TDP) focused on technology education in primary schools in Germany. This program aims to bridge the gap between theory and practice in the field by providing professional development opportunities to motivate, prepare, and support teachers in the design and implementation of technology-focused lessons in primary school classrooms. By incorporating practical training and ongoing support, we aim to facilitate the effective integration of technology education into primary school curricula.

Limitations

Our review study has several limitations that need to be acknowledged. Firstly, we focused solely on research articles published in journals, neglecting potentially valuable information from sources such as conference proceedings, which may not be widely accessible or published at an international level due to language barriers. Secondly, our investigation specifically targeted in-service teachers to examine their implementation processes in technology and engineering subjects and their impact on students' personal skills and classroom interactions. However, it would be beneficial to have an overview of pre-service educational programs related to technology and engineering subjects. Understanding teachers' backgrounds in these subjects is crucial for establishing and enhancing the foundational frameworks for the development of effective TPD programs. Recognizing these limitations is important as they provide insights into areas for future research and potential avenues for improving the comprehensiveness and depth of our study.

In conclusion, the growing interest and research in technology and engineering education highlight the need for a shared understanding of its objectives, concepts, and contexts to establish cohesive curricular frameworks and implementation practices. Our study contributes to the field by shedding light on the current state, diversities, and challenges within technology and engineering education in primary schools. This insight can inform further research endeavors and policymaking, ultimately facilitating the development of effective TPD programs in this domain. By addressing the existing gaps and challenges, we can advance the quality and impact of technology and engineering education in primary schools.

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The use of technology in higher education teaching by academics during the COVID-19 emergency remote teaching period: a systematic review

• McQueen Sum   ORCID: orcid.org/0000-0002-7763-1105 1 &
• Alis Oancea 1  

International Journal of Educational Technology in Higher Education volume  19 , Article number:  59 ( 2022 ) Cite this article

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This paper presents a systematic review of scholarly efforts that uniquely emerged at the onset of the COVID-19 pandemic and focused primarily on higher education teachers’ perspectives on technology use and on associated changes in the relationship between teachers and students amidst the transition to emergency remote teaching worldwide. Our narrative synthesis of 32 studies, the majority of which come from lower-and middle-income countries/regions, suggests that numerous factors interact to shape academics’ technology use in emergency remote teaching across higher education contexts. We report strong findings of teachers’ resilience and resourcefulness in their self-exploration of various technologies and teaching strategies in response to the continued severity of the pandemic. Ultimately, this review suggests directions for further research on engaging educational leaders and faculty in reimagining teaching as not only a core academic function of higher education, but also, and importantly, a humanising experience shaped by an ethics of care.

Review of literature and research questions

Since the continued devastating spread of COVID-19 across continents from early 2020, the coronavirus pandemic has led to massive numbers of hospitalisations and deaths around the world, abruptly upending public health and many other domains of life. As the disaster has unfolded, a multitude of sweeping challenges have continued to reshape the global higher education (‘HE’) landscape. With HE institutions (‘HEIs’) worldwide closing their campuses in Spring 2020, teachers were forced to make a hasty transition from typically in-person teaching configured in physically proximate space to alternative teaching approaches in response to the COVID-19 emergency (Crawford et al., 2020 ).

The term ‘emergency remote teaching’ (‘ERT’) is used by Hodges et al. ( 2020 ) and subsequent literature to denote the rapid and putatively ephemeral shift to remote teaching to continue teaching and learning during emergencies. Although ‘ERT’ and ‘online teaching’ may be two domains with considerable overlaps, ‘online teaching’ is importantly distinguished from ‘ERT’ as it includes teaching and learning arising from a prolonged collective effort in curriculum planning and instructional design from a wide range of stakeholders pre-launching (Hodges et al., 2020 ).

Despite the growing literature on ERT, few efforts had been made to review this body of research systematically at the time of conducting this review (see Table 1 for a few exceptions). Since there have been abundant discussions on the perspectives of students at the HE level during COVID-19 [see, for example, Chakraborty et al. ( 2021 ) on Indian students’ opinions on various aspects of ERT; Mok et al. ( 2021 ) on Hong Kong students’ evaluation of their learning experiences during ERT; Resch et al. ( 2022 ) on social and academic integration of Austrian students; and Salas-Pilco et al. ( 2022 ) for a systematic review focusing on student engagement in Latin American HE], our review focuses systematically on synthesising the body of worldwide literature on teachers’ perspectives on technology use during the period of ERT. Moreover, much attention has been devoted to medical education (Rajab et al., 2020 ; see also Table 1 ) and STEM education since the coronavirus outbreak (Amunga, 2021 ; Bond et al., 2021 ; Gaur et al., 2020 ; Singh-Pillay & Naidoo, 2020 ). Our review focuses on the less explored perspectives of humanities, arts, and social sciences (HASS) teachers—whose perceived difficulties of using digital technologies in teaching were reportedly distinct from those of their counterparts in other disciplines, both before (Mercader & Gairín, 2020 ) and during the COVID-19 outbreak (Wu et al., 2020 ).

Prior to COVID-19, a respectable amount of scholarly work was devoted to the development and adaptation of theoretical models to identify, explain, and even predict factors that influenced technology use in educational contexts (Granić & Marangunić, 2019 ). But Lee and Jung ( 2021 ) argue that ‘in higher education contexts, crisis-driven changes may happen differently from pre-planned, voluntary change, and that factors influencing crisis-driven changes are different from those influencing voluntary changes; as reported in previous studies based on technology acceptance theories and models’ (p. 16). Given the novelty of COVID-19, few studies have been conducted to explicate the factors shaping HE teachers’ decisions about, and experiences of, technology use in the unique context of the global pandemic [see Mittal et al. ( 2021 ) for an exception that studies faculty members in Northern India and Lee and Jung ( 2021 ) for another study on South Korean university educators]. Therefore, the first question that this review aims to answer is: How have different potential factors, as identified by teachers in the included studies, shaped teachers’ technology use across various higher education contexts during the COVID-19 emergency remote teaching period?

Existing scholarly efforts that aim to provide an overview of the literature focus predominantly on a bifurcated discussion of the opportunities and challenges, or advantages and disadvantages pertinent to using technologies in teaching during the COVID-19 crisis (Adedoyin & Soykan, 2020 ; Dhawan, 2020 ; Pokhrel & Chhetri, 2021 ; Stewart, 2021 ). We therefore frame the second research question in a way that circumvents a binary pros-and-cons discussion of the implications of technology use in times of the COVID pandemic, as already well-documented in the literature. Hence, our second question is: What are the implications of technology use in COVID-19 emergency remote teaching from the perspectives of higher education teachers?

The broader term ‘technology’ (in the singular form) used in the review questions includes the socio-cultural contexts of the educational settings in which technology use is situated. The discussion of ‘context’ is of particular importance (Selwyn, 2022 ). Although pre-COVID studies (such as Broadbent & Poon, 2015 ; Liu et al., 2020 ) offered valuable insights into technology use in HE teaching, the pandemic brought about starkly and often perilously different contexts for research as well as for teaching and learning (Stewart, 2021 ; Williamson et al., 2020 ).

We use the term ‘technologies’ in its plural form throughout this review, in a narrower sense, meaning specifically the wide range of digital tools and systems and other technical resources that are used for pedagogical purposes. These can include but are not limited to electronic hardware devices, software systems, online services, and social media. We note, however, that the meanings attached to the term ‘technologies’ may be substantively different across contexts. Some of the studies included in this review, as we will show below, extend it to other-than-digital forms of technologies, leading to results beyond our initial scope of research. As a result, the use of (digital) technologies is understood in this review as an often necessary but not sufficient condition for ERT—a novel concept to many teachers who had been using various ‘technologies’ in other ways in facilitating their teaching for years before the COVID-19 outbreak.

Methodology

Characterised by the principles of replicability and transparency, a systematic review aims to ‘review ... existing research using explicit, accountable rigorous research methods’ (Gough et al., 2017 , p. 4). This methodology is used because it helps elucidate the current understanding and available evidence of the above research questions, clarify any replication of existing research findings, and inform future research and policy directions in HE teaching in a systematic and trustworthy manner. Below is a detailed, transparent report of the processes involved in conducting this systematic review.

Inclusion/exclusion criteria

Our review is restricted to peer-reviewed journal articles that report original empirical studies written in English and/or simplified Chinese. Papers written in these two languages account for a high volume of worldwide literature published at the onset of the COVID-19 outbreak. Also, Chinese studies are particularly valuable for this review, for mainland China was the first region affected by COVID-19 and its HE system was amongst the first to respond to the challenges ensuing from the spread of coronavirus.

Since the review seeks to capture a ‘snapshot’ of perspectives on technology use by teachers during the immediate COVID-19 outbreak, only articles published in 2020 (including those published online ahead of print that year) were eligible for review. Included publications may cover any country/region worldwide but should systematically gather data from teachers other than the authors themselves and focus primarily on the perspectives of HASS teachers on matters pertaining to technology use in ERT in HE settings. Opinion pieces, editorials, reflection articles on one’s own practice, conference papers, and books are not within the purview of this review (see Appendix 1  for detailed inclusion/exclusion criteria).

Search strategy

Prior to conducting the database search, we piloted and modified the search strings several times. Our final search strategy is a combination of Boolean operators and variations of four key terms: ‘higher education’, ‘technology’, ‘teaching’, and ‘COVID-19’ (see Appendix 2  for detailed search terms).

Screening and selection

On 13 January 2021, a targeted search returned 4204 records indexed in fourteen databases including Scopus, Web of Science, and three Chinese databases (see Appendix 3  for PRISMA flow diagram and the complete list of databases). From these, we extracted 20 different papers at random to screen by title and abstract independently by applying the inclusion/exclusion criteria, and with the intention to repeat the process until unanimous agreement was reached. Having achieved full inter-reviewer agreement in our first attempt and after a further calibration session, we then proceeded to de-duplication and title-and-abstract screening, after which only 129 papers remained for full-text retrieval and further screening. Meanwhile, 16 relevant publications from various other sources were also identified and passed the initial screening. We then examined the full text of the resulting total of 145 articles and excluded any that did not fulfil the inclusion criteria, leading to a set of 40 studies to be considered for review.

Quality and relevance assessment and content extraction

To assess the 40 papers’ quality and relevance to this review, we adapted the assessment rubric from Oancea et al. ( 2021 ) (see Appendix 4 ). In parallel with the quality assessment, we developed a grid for content extraction by piloting on three papers, after which multiple revisions of the extraction grid were made. Then both authors used the updated extraction grid (see Appendix 5 ) and extracted content from two full papers independently to check for inter-reviewer agreement. In subsequent communications, discrepancies of our extraction were reconciled and the final quality thresholds for inclusion were agreed upon. As of May 2021, after excluding 8 papers of low quality, the final corpus for review comprised 32 articles.

Analysis and synthesis

We developed an initial coding scheme with broad theme boundaries based on the research questions, and resolved any conflicting views. We coded line-by-line the extracted data both deductively and inductively: we first applied the pre-configured coding scheme to the full set of data, and then updated and re-applied the coding scheme to include further themes identified through inductive coding. For example, we realised that the category of ‘ethical use of technology’ spanned the themes of ‘pedagogical implications’ and ‘work-related implications’. As a result we categorised it under a separate theme titled ‘cross-cutting implications’. After multiple rounds of scheme refinement and iterative coding which started in June 2021, the process of synthesis concluded in late December 2021.

The research synthesis is presented narratively; note that we integrated quantitative findings (for example, from surveys) descriptively into the narrative analysis, as in most cases the samples were not representative, the analysis was largely descriptive and findings from qualitative answers to open questions were presented in detail.

Limitations

Our review did not include insights from reflection pieces (such as Czerniewicz et al., 2020 ; Jandrić et al., 2020 ; Joseph & Trinick, 2021 ) and reports not published in peer-reviewed journals (such as Ferdig et al., 2020 ); these exclusions are not a judgment on either the quality or the level of insight of such pieces, nor on the modes of research and scholarship that they embody. This decision, as well as the focus on studies published in English and Chinese, limit the extent to which this review covers the experiences of ERT technology use by teacher populations across the world.

Due to our international remit, another limitation is the integration of findings grounded in different local contexts and HE environments. We overcome this partially by extracting from each paper the context in which teachers’ technology use is situated and taking such information into account when narratively integrating data across studies and presenting our review findings (see Appendix 5 ). However, the inconsistent terminology used to allude to the notions of ‘technology’ and ‘emergency remote teaching’ in the reviewed articles poses a major challenge to our cross-context comparison [see discussion on the jingle-jangle fallacy in Sum and Oancea ( 2021 )]. Another review conducted by Bond et al. ( 2021 ) also found at least ten different terms used for ‘online teaching’ (including ‘emergency remote teaching’) in their selected papers.

Although uniformly agreed-upon definitions of these terms are absent (Singh & Thurman, 2019 ), the nuances of concepts underlying them have not been given due consideration in the majority of the studies reviewed (see “ Description of included articles ” section). Further terminological complexity arises from the imperfect overlap between Chinese and English vocabularies. Whilst we tried to overcome this by extracting information on each study’s conceptualisation of ‘technology’ and ‘ERT’ (see Appendix 5 ) and accompanying translations with original Chinese terms (for example, the phrase ‘线上教学’ in Chinese can be sometimes translated into ‘online teaching and learning’), we acknowledge that terminological and translation gaps remain in our cross-context synthesis of the selected literature.

Description of included articles

Included in our final synthesis are 32 empirical research studies covering 71 countries and reporting perspectives from 4725 HE teachers altogether. Of these, the largest proportion focuses on the HE context in Asia (n = 15), followed by Europe (n = 7) and Africa (n = 6) (see Table 2 ). Given our inclusion of articles indexed in Chinese databases, Mainland China alone is the focal context of n = 5 studies. A wide range of subject areas in HASS disciplines are covered (see Table 3 ). Studies using qualitative data are most common (n = 14) (see Table 4 ), and a sample size of fewer than 50 teachers is often reported (n = 21) (see Table 5 ). Appendix 6 presents a summary of the characteristics of included studies.

Exactly half of the studies (n = 16) have a local remit (see Table 6 ), amongst which many recruited fellow academics from the authors’ institutions (n = 14). As noted by several researchers in their papers, the public health emergency and its concomitant restrictions had in various ways altered the methods for research and data collection, including shifting to a local focus whilst access to other settings was limited.

Authors of three quarters of the reviewed studies (n = 24) obtained data from participants remotely, either by phone or online. Much empirical data were collected in a space that was relatively new and unfamiliar to the researcher and the researched during a time when both individuals were coping with not only the expected expeditious embrace of various technologies for ERT but also, amongst other things, the physical and psychological burden posed by the coronavirus pandemic. Hence, this review integrates, in a systematic and holistic fashion, data from the discrete, often inevitably limited, yet valiant research initiatives undertaken in different countries during the periods of drastic increases in infections and deaths at the incipient phase of the COVID-19 outbreak.

In terms of substantive focus, whilst most of the included studies describe ‘what’ and/or ‘how’ technologies were being used by teachers during ERT (n = 14) and offer a dichotomous pros-or-cons narrative of technology use for ERT (n = 21), often vis-à-vis in-person teaching prior to COVID-19, some (n = 7) also examine the wider implications for teachers and HE at large.

Due partly to the novelty of COVID-19 and the haste with which research was conducted, the conceptualisation of technology and its relation with remote teaching in times of COVID-19 is either weak or largely absent in the majority of the reviewed studies. Technologically deterministic views seem prevalent in the literature reviewed. Many studies place ‘technology’ as the centre of inquiry and underscore the palpable ‘impact’ that various technical objects impose on teaching. For example, the attribution of recent pedagogical innovations and educational developments to technological advancements features prominently in the introductory paragraphs of numerous papers. Some assert that the emergence of social networking sites has begun to direct all walks of life including the ways in which teaching has been carried out since before the pandemic. Additionally, the discussion of ‘technology-enabled’ and ‘technology-enhanced’ teaching used in some articles implies that ‘technology’ plays an almost indispensable role in teaching and that teaching would be seriously disrupted without it. In contrast, there was little awareness in many of these papers of the extent to which technologies may carry political or commercial agendas or may be underpinned by complex ideologies and social structures (Selwyn et al., 2020 ). This echoes the conclusions of pre-COVID research by An and Oliver ( 2021 ) and Costa et al. ( 2019 ) that theoretical understanding of ‘technology’ in educational research is under-developed.

A brief narrative of ERT experiences from teachers’ perspectives

An eclectic range of technological artefacts and their uses during ERT across HE settings is reported in the studies. Cases of initial technology use range widely from straightforward approaches such as uploading teaching materials online to (mis)uses such as creating excessive recorded lectures and assignments. What is common, however, across reports in most studies is the acutely negative sentiments of intimidation, angst, confusion, and even despair of ERT amongst teachers at the outset of the transitioning period. It gave teachers great shock and pain to make a forced, often slapdash migration to ERT—a terrain that many of them were unfamiliar with and uncertain of—whilst juggling with their home and other work responsibilities during the distressing period. In addition to the psychological burden, teachers were worried about the well-being of their students, particularly those from underprivileged backgrounds and in vulnerable environments. Across HE settings worldwide, teachers had on average less than a week’s preparation time, leaving them feeling woefully unprepared. Hence, it is unsurprising that the majority of teachers in the studies reviewed found the immediate phase of migration to ERT burdensome and emotionally exhausting. Yet, some sought a silver lining and considered ERT as a creative challenge and an opportunity for a long-needed meaningful reflection and overhaul of HE teaching practices.

We mapped each included article’s findings about teachers’ overall attitudes towards ERT using the World Bank’s classification of country development (2020) (see Table 7 ). For studies not examining teachers’ attitudes directly, we inferred negative attitudes from teachers’ reports of dissatisfaction and frustrations over the challenges in ERT, and any indication of concern and anxiety; positive attitudes were inferred from teachers’ expressions of satisfaction and awareness of benefits brought by ERT, and any indication of optimism and hope.

Reports by teachers from higher-income countries/regions were more positive whilst those from lower-and middle-income countries/regions tended to be more negative, though with a few exceptions (for example, teachers in mainland China had relatively positive emotional responses and teachers of hearing-impaired students in high-income Saudi Arabia reported overwhelmingly negative emotional responses during the ERT period). In propitious circumstances, teachers’ emotional responses could change substantially over time from apprehension, frustration, and pessimism to relief, affirmation, and an eventual sense of achievement. Sometimes, as teachers gradually became conversant with various technological artefacts and encountered a suitable way of teaching, either serendipitously or after multiple experimentation, they eventually saw ERT as a humbling and rewarding experience. Some teachers evaluated the pedagogical revisions they made during ERT positively and even expressed the intention to keep part of their teaching online or expected to continue to use the technologies employed for ERT in the future.

Factors shaping technology use by teachers in ERT across HE contexts

The 32 papers reviewed include results on qualitative and quantitative factors identified by teacher participants that potentially shape teachers’ technology use in ERT. Note that these are not always empirically validated, nor explicitly identified as ‘factors’ in the included articles (particularly in qualitative accounts they may be described as reasons, drivers, challenges, barriers, and conditions). Thus, we adopted an open and inclusive definition of factors based on the implied or explicit direction of influence on ERT, and we grouped them thematically. Summary accounts of these thematic groupings based on the data presented in the review corpus are discussed below in descending order of the respective strength of evidence in the reviewed studies (see full references in Table 8 ).

Social-technological factors

Whilst Tartavulea et al. ( 2020 ) note that the transition to ERT can be facilitated by having online platforms and facilities, they also found that access to electronic devices and internet connection can be a luxury. Frequently reported technical concerns by teachers include the unreliability of network conditions, lack of devices and equipment, and limitations of digital infrastructure. These issues are not only powerful barriers to technology use in emergency teaching but they also disproportionately affect teachers and students in lower-income countries/regions. Note, however, that even in the context of an affluent country like the United States, teachers and students may report inequitable access to the necessities of ERT from home (Cutri et al., 2020 ; Sales et al., 2020 ).

Beneath the surface of these technical difficulties are the imbalanced allocation of resources and entrenched socio-economic problems which most commonly beset lower-and middle-income countries and regions (Tanga et al., 2020 ). Whilst the issues teachers face are highly contextualised, a considerable number of students come from underprivileged backgrounds. Even before the pandemic hit, these students had been confronting different challenges such as, particularly in lower-income countries, frequent commute of several miles from rural areas to the city for internet connection. Even if internet access were provided at home, these students would still need to overcome problems of intermittent or no power supply in their localities. In addition, during lockdowns they may shoulder more home-care responsibilities, sometimes in overcrowded or even abusive home environments.

Some teachers were also amongst vulnerable groups and had limited access to the internet at home, for example due to the sharing of cellular data with household members, and therefore exposed themselves to greater health risks by visiting commercial establishments such as cafés with free internet provision in order to teach remotely. Compounding this predicament is that HE teachers reported that they often had little information about students’ backgrounds, which hindered their efforts to address students’ educational and psychological needs and any equity issues pertinent to their studies (Cutri et al., 2020 ). These technical complications are situated in specific social contexts and have been a major hindrance to technology use in ERT.

Institutional factors

In most of the studies reviewed, the migration to ERT was described as mandatory, and teachers’ use of certain applications was often resultant from policies imposed by their institutions—whose regulations on teaching could be heavily influenced by government decisions, for example in universities in Mainland China (Tang et al., 2020 ). To ensure continuity and safety of teaching and learning in times of upheaval and uncertainty, some HEIs exercised greater control over the ways in which technologies were used in teaching, such as mandating the use of certain Learning Management Systems (LMS) in teaching (Khoza & Mpungose, 2020 ) or prohibiting asynchronous methods of teaching (Cutri et al., 2020 ). Whilst some teachers felt that their creative freedoms to use different technologies in their teaching were constrained by institutional policies , others sought detailed guidance and perceived the lack of clear institutional protocols as a significant barrier to technology use in this emergency (Sobaih et al., 2020 ).

Aside from policy, different forms of institutional support (such as the provision of digital infrastructure and training for both teachers and students) could also be of value to teachers in ERT, although the level of support felt by teachers could vary by discipline (Watermeyer et al., 2021 ). However, the value of technical assistance might be undermined when technology specialists were just as confused as teachers about teaching remotely in emergency times (Gyampoh et al., 2020 ; Tanga et al., 2020 ). Another gap in institutional support pointed out by some studies is the lack of recognising teachers’ hardship and efforts in teaching in the form of pecuniary (such as support for procurement of equipment) and non-pecuniary rewards (such as teaching awards) (Joshi et al., 2020 ).

Individual factors

Sometimes teachers resisted institutional policies and employed instead other technologies of their own preference. Individual factors therefore play an important role in shaping teachers’ technology use. Despite the challenges posed by the pandemic, some teachers were tolerant of uncertainties, valiantly departing from their previous pedagogical praxis and forging ahead with ‘pedagogical agility’ (Kidd & Murray, 2020 )—the flexibility of adapting to the new teaching conditions in rapid yet meaningful ways. Resilient and adaptive, these teachers ‘rolled up their sleeves’ and worked around the clock to seek teaching solutions and countermeasures through constant, active self-exploration (Sales et al., 2020 ). Some music teachers, for instance, would make immediate remedies for the connection disruptions to synchronous lessons by providing students with recordings of their playing as examples (Akyürek, 2020 ). In an Israeli college, teacher educators incorporated topics like ‘distance learning’ into the teacher training curriculum to reflect the new circumstances of teaching (Hadar et al., 2021 ). One teacher educator even painted a wall at home with special paint to make it into a ‘blackboard’ where his writings were presented and screened to students (Hadar et al., 2021 ). These are just a few of the many manifestations of teachers’ agentic creativity and ongoing inventiveness in innovating their own use of technologies and resources despite the presence of severe constraints in ERT times.

In terms of readiness, despite receiving considerable institutional support in some cases, teachers often felt ill-prepared for ERT and doubtful of their abilities in using various technologies to teach (Scherer et al., 2021 ), and only a minority felt rather ready for ERT (Alqabbani et al., 2020 ). The studies reviewed discussed the variation in teachers’ readiness for ERT in relation to gender, academic discipline, and country context (Scherer et al., 2021 ). For example, in predominantly high-income economies teachers moved from a customary integration of technologies in pre-COVID teaching to fully-online ERT (Mideros, 2020 ; Sales et al., 2020 ). But not all teachers and students had had the opportunities to familiarise themselves with various technologies (including otherwise widely used applications like Word processing) prior to COVID-19 (Gyampoh et al., 2020 ). Whilst experienced online teachers felt more prepared and expected themselves to employ more frequently a wide array of technologies in teaching, across HE contexts many teachers had seriously limited prior experience in ‘online teaching’ and were apprehensive about using technologies for teaching purposes (Bailey & Lee, 2020 ). Besides, being experienced in ‘online teaching’ does not necessarily translate to successful handling of ERT, given the limited time frame and the stressful and even traumatising circumstances at the outset of the crisis.

Pedagogical factors

Across HE settings, teachers considered how to connect and engage dislocated groups of students through technologies, how to empower students to explore beyond the curriculum as students gained more control over what and how they study in the shifting context of teaching and learning (Mideros, 2020 ), and how to reconfigure spaces in ways that provide students with a nourishing, inter-connected intellectual environment despite being physically apart during the ERT period (Kidd & Murray, 2020 ). In Australia, teachers were especially concerned about first-year students, as the southern hemisphere’s Autumn 2020 was their very first term at the university. In addition to providing students with considered feedback, these teachers employed strategies such as the online polls and hand-raising functions on various EdTech platforms (Zeng, 2020 ), or made students the host of Blackboard Collaborate in order for teaching to be more engaging (Marshalsey & Sclater, 2020 ).

As coronavirus infections spread, teachers also attended to students’ emotional and educational well-being. Some teacher educators in the United Kingdom offered one-on-one tutorials online to establish personal connections with student teachers and monitor their progress (Kidd & Murray, 2020 ). A teacher in Pakistan went the extra mile to care for the students living in far-flung areas without internet access by sending them CD recordings of their lectures (Said et al., 2021 ). In Saudi Arabia, teachers of hard-of-hearing students used a special configuration of multiple spaces to enable the inclusion of synchronous sign-language translation in their online lectures (Alsadoon & Turkestani, 2020 ). In cases where the discrepancy between technology use by teachers and students was significant, teachers would often bridge the gap by adapting and adopting technologies (such as social media) that they were not always conversant with, but which were most used and preferred by students. As a teacher participant put it, teachers have ‘to go where [students] are, and not wait for [students] to come to where [they] are’ (Sales et al., 2020 , p. 13).

Often teachers would consider the compatibility of certain technologies with their teaching philosophies and practices within their disciplines. Teacher educators in Israel, for example, might feel additional pressure from the expectation that their pedagogical use of technologies has to set examples for their student teachers (Hadar et al., 2021 ). As another example, teaching translation/interpretation in Mainland China was especially challenging during the ERT period since teachers have to demonstrate to students the operation of simultaneous interpretation equipment and the use of dual-track recording function—which is not commonly found in existing online applications (Ren, 2020 ).

Peer factors

Teachers reported that they saw their colleagues as not only sources of inspiration for technology use, but also remedies for stress and uncertainty during the ERT period (Ren, 2020 ). Unlike in prior ‘online teaching’ where they could still meet in person to discuss technology use, many teachers struggled with technological learning-by-doing in relative isolation during the COVID-19 lockdown period (Cutri et al., 2020 ). In view of the absence of physical spaces for colleagues to informally exchange professional practices and channel their emotionality and empathy for one another (Cutri et al., 2020 ; Scherer et al., 2021 ), some teachers put in deliberate effort into organising new networking spaces to bring the academic community together online. In an attempt to alleviate the uncertainties brought by ERT and their adverse impact on psychological well-being, teachers worked together remotely as a team to explore solutions and share useful insights about technology use in teaching. They felt empowered by the constant encouragement and motivational texts from their peers (Ren, 2020 ). Teachers thrived on establishing connections with technology-proficient colleagues whose technical expertise and guidance were relied upon (Bailey & Lee, 2020 ; Mouchantaf, 2020 ) and whose ingenious engagement with technologies inspired and were even assimilated into their own teaching practices. As a mitigation strategy to ease teachers’ hasty migration into ERT, mutual empowerment through facilitated discussions amongst colleagues meaningfully shaped the ways technologies were used by teachers in ERT.

Interplay of factors

Whilst we have delineated potential factors shaping technology use in ERT in a linear, point-by-point fashion, this list of non-exhaustive items should not be conceived as separate, stand-alone factors since they interact in a complex and nuanced way across various contexts. For instance, having little institutional support and no access to LMS or students’ information, some teachers in public HEIs in Egypt resorted to reaching students through popular social media. Teachers then explored on their own the ways in which they could continue teaching activities via these platforms which were new to them (Sobaih et al., 2020 ). As for teachers in an Israeli college, upon realising some Arabic female students refused to appear online due to their cultural values, they made allowance for students’ decisions to keep their cameras off (Hadar et al., 2021 ). But the inability to read students’ expressions during class added to the teaching challenges during ERT and demanded additional flexibility and pedagogical adjustments from teachers. Therefore, technology use is influenced by the combined factors of students’ socio-cultural backgrounds and teachers’ resources and adaptability to changes. In addition to the complex interplay of these factors, these examples demonstrate that teachers’ technology use in ERT is heavily contextualised across HE settings and should therefore be understood in its wider cultural embedding and socio-economic contexts.

Implications of technology use in ERT for teachers

As for our second research question, the studies reviewed indicate that the implications of technology use in ERT for teachers are manifold. These findings are categorised into pedagogical, work-related, and cross-cutting implications, discussed below (see Table 9 for a summary table).

Pedagogical implications

With the paradoxical amalgam of being ‘together but (physically) apart’ (Marshalsey & Sclater, 2020 ) in the new COVID-19 context of teaching, the notions of space and time, as well as the dynamics of the classroom and teacher-student relationship, have undergone less palpable yet important changes.

Spatiality-wise, teachers realised the loss of important physical spaces and the erosion of values traditionally attached to these spaces during the transition to ERT. Marshalsey and Sclater ( 2020 ), for example, reason how a physical art and design studio embodies a distinctive set of values, resources, and the signature experiential hands-on pedagogical practice of their discipline. But when artworks are presented online, their materiality, colours, and texture may be diminished.

Temporality-wise, some teachers felt a strongly contorted notion of time which rendered futile any discussion on the ordinary longitudinal perception of ‘being ready for teaching’ (Cutri et al., 2020 ). Not only was the migration to ERT perceived as rushed and disorganised but teachers also felt time as short, discrete intervals when many changes could occur. Some even found it difficult to find ‘a point of reference for their sense of self as experienced professionals’ (Cutri et al., 2020 , p. 533). This new sense of temporality is perhaps most concisely summarised by a comment made by a teacher during ERT: ‘I always plan a month ahead. Now I live from one day to the next’ (Hadar et al., 2021 , p. 454).

Within this new spatial–temporal context, teachers often felt that student engagement in remote teaching and learning activities was superficial and unequally distributed (Joshi et al., 2020 ; Kidd & Murray, 2020 ). Deprived of in-person interaction, teachers can neither hear the voices nor see the expressions of all students, and find the classroom discourse to be dominated by students who are generally more confident in sharing their ideas in front of the whole class (Hadar et al., 2021 ; Marshalsey & Sclater, 2020 ). With the loss of informal physical spaces where students used to ask questions and interact further with teachers before and after class (Cutri et al., 2020 ), some teachers commented that both teachers and students were more likely to stay in their ‘echo chambers’ during the pandemic (Eringfeld, 2021 ).

Teachers adopted different strategies to navigate being outside the comfort zone of the physical classroom. Some attempted to retain or increase control over interactions in the remote ‘classroom’ (Mideros, 2020 ) such as by only letting students speak when allowed (Gyampoh et al., 2020 ) and shifting to a predominantly teacher-centric, didactic approach of lecturing because of the perceived difficulty of implementing hands-on training in an exclusively remote teaching environment (Cutri et al., 2020 ). The students, too, adopted their own strategies, often distinct from their teachers’ (Callo & Yazon, 2020 ; Sobaih et al., 2020 ). As some students generally adapted to ERT with relative ease (Mideros, 2020 ; Ren, 2020 ), sometimes they even used technology as a defensive wall to exclude teachers (who were in some cases less tech-savvy than their students) from being involved in their studies during the pandemic (Sales et al., 2020 ). Many teachers in the studies reviewed reported that the mandated use of various technologies in ERT puts a strain on pedagogy, the major implications of which may include an elevated feeling of detachment from the class, a heightened distance from students (Kidd & Murray, 2020 ), and a more pronounced gap in teacher-student interactions (Callo & Yazon, 2020 ; Sales et al., 2020 ).

Moreover, ERT is thought to have precipitated the collapse of ‘yishigan’ (仪式感)—a Chinese expression which, when applied to this context, refers to the sense that teaching is a special, ritualised occasion (Lu, 2020 ; Ren, 2020 ). As ‘yishigan’ abates in the context of ERT, so does the sense of formality and immediacy felt by teachers and students, both of whom may no longer view teaching and learning as a serious, formalised routine of life in the same way as before; some of the studies reviewed note that motivation and classroom engagement are lowered as a result of this change in perception (see examples in Joshi et al., 2020 ; Lu, 2020 ; Marshalsey & Sclater, 2020 ).

In contrast with the sense of limitation, hierarchy, and loss illustrated by the accounts summarised above, other teachers reported a sense of the ‘intimacy of distance’ and a less visible teacher-student hierarchy as a combined result of emergency technology use during the pandemic. Such teachers valued the creation of spaces for more student-oriented and student-empowering pedagogy. In Mainland China, for example, the classroom atmosphere was livened up as students were encouraged by teachers to engage in class via alternative forms of interaction online such as sending emojis, raising ‘hands’, and taking polls (Gao & Zhang, 2020 ; Zeng, 2020 ). In other contexts, teachers felt an idiosyncratic sense of closeness as they shared a screen and read the same text with students on their devices (Eringfeld, 2021 ). They also reported a better understanding of students’ personal circumstances, home environment, and even household responsibilities as students turned on their cameras in class (Hadar et al., 2021 ; Kidd & Murray, 2020 ). In many ways, teachers observed their students being more relaxed in class, which enabled teachers to build personal relationships with their students in ways that they had never envisioned before (Marshalsey & Sclater, 2020 ).

Because of the collapse of ‘yishigan’ and the resultant casual and more relaxed classroom dynamics in the new spatiality, some teachers adapt to the ‘online etiquette’ by using emojis and GIFs when communicating with students (Marshalsey & Sclater, 2020 ). Also, the fact that students may be more technology-competent than teachers meaningfully shifts the dynamic of the teacher-student relationship in the ERT classroom (Kidd & Murray, 2020 ), for teachers often solicited help from students on questions regarding technology use, and during this process teachers increasingly saw students as their partners in teaching rather than subordinates to themselves (Cutri et al., 2020 ). As Cutri et al. ( 2020 ) remark, ‘the negative connotations of risk-taking and making mistakes while learning to teach online seem to have been mitigated by a combination of affective factors such as humility, empathy, and even optimism’ (p. 523). As an experience of vulnerability, ERT has grounded and humbled teachers, allowing them to develop both more appreciation for self-care (Eringfeld, 2021 ), and more empathy for students (Khoza & Mpungose, 2020 ; Kidd & Murray, 2020 ).

Teachers realised the salience of exercising care for students and themselves and considering the emotionality of students, especially those in vulnerable states (Alqabbani et al., 2020 ; Sales et al., 2020 ). Pastoral care took priority during particularly distressing periods when students were most in need of emotional support (Sobaih et al., 2020 ; Tejedor et al., 2020 ). All these examples suggest that under the new spatial–temporal reorientation an intricate web of human relations has evolved and, to varying degrees, been revitalised.

Work-related implications

The task of transitioning teaching to an alternative mode is only one of the many challenges teachers face in the larger contexts of academia during the pandemic period (Cutri et al., 2020 ). Although the extra time seemingly freed up by, say, the lack of commutes is highly valued for student support, self-care or family care (Eringfeld, 2021 ; Kidd & Murray, 2020 ; Tejedor et al., 2020 ), there has also been an excessive intensification of workload in preparation for ERT (Khan et al., 2020 ; Lu, 2020 ; Mouchantaf, 2020 ; Said et al., 2021 ), and this is expected to last for a few years into the post-ERT era (Watermeyer et al., 2021 ). When working from home, teachers received as many as hundreds of students’ inquiries throughout the day via various applications (Alsadoon & Turkestani, 2020 ; Sobaih et al., 2020 ). Coupled with the pressure to prove that work has been conducted remotely (Kidd & Murray, 2020 ; Marshalsey & Sclater, 2020 ), some teachers report feeling compelled to be present online around the clock. The ‘timelessness’ of working remotely in a home setting has been succinctly summarised by a teacher: ‘it is too easy to “just send one more email”’ (Watermeyer et al., 2021 ). The praxis and boundaries of academic work were shifted and reconstructed in ways many perceived as intrusive into the personal life sphere and deteriorative to work-life balance and also teachers’ well-being and occupational welfare (Watermeyer et al., 2021 ).

In addition, with looming financial challenges to the HE sector, casualised and untenured staff reported an elevated feeling of job precarity because their extra commitment to teaching cuts into time for other academic work, such as publishing research—which they perceived as often prioritised over teaching efforts in HE career progression (Cutri et al., 2020 ). Some reported that these teachers’ vulnerability was compounded by the management’s misperception that teaching remotely during emergency lightens teachers’ workload, and by their misinterpretation that low scores given by students on evaluations of ERT are a marker of ‘teacher quality’ rather than a way for students to express disinclination towards ERT in general (Watermeyer et al., 2021 ).

Technology use in ERT was further complicated by the need for swift re-coordination of private routines and domestic spaces to make room for professional work. A teacher, for example, asked all household members to disconnect from the Wi-Fi when teaching (Kidd & Murray, 2020 ). Having a separate, free-of-disturbance workspace at home is a luxury that not many teachers could afford (Gyampoh et al., 2020 ; Joshi et al., 2020 ) especially in contexts like Pakistan where joint families may live together in a crowded household (Said et al., 2021 ). Due to the non-separation of home/workspaces, customary parameters between the private and public domains were being reconstituted, and the boundaries between teachers’ personal and professional identities became blurry (Khoza & Mpungose, 2020 ). Consequently, female academics with caring responsibilities were disproportionately affected, and increasingly teachers found themselves struggling to perform either role well (Watermeyer et al., 2021 ).

In the larger context of HE, teachers were also worried about the ‘placelessness’ of HE during lockdowns and that the role of HE as an embodied, communal space for teaching and learning, self-formation, and socialisation was being undermined (Eringfeld, 2021 ). In two studies based in the UK (Eringfeld, 2021 ; Watermeyer et al., 2021 ), the accounts of their teacher participants add up to a strong ‘dystopian’ rhetoric, reflecting their fears that the ERT migration epitomises the beginning of a prolonged contraction of HE as an on-campus experience and monetisation of part of the HE experience driven largely by massification but not quality, thereby undermining the core academic values and humanising aims of HE.

Not all studies reviewed painted a consistently gloomy picture of the work-related implications of ERT and technology use. Some studies note that the compulsory, emergency move to remote teaching may have offered multiple opportunities. For example, in some propitious circumstances, teachers were able to constitute their networking spaces online to channel mutual support and facilitate exchanges on technology use. There are also reports that more trust was placed on technology specialists, technicians, and younger faculty who were often seen as more technologically adept and relied upon during ERT (Watermeyer et al., 2021 ). Moreover, the infrastructural divisions that used to separate departments on a physical campus are largely dismantled with the migration to ERT, enabling possibilities of various forms of inter-departmental communication and cross-disciplinary collaboration (Tejedor et al., 2020 ) and thereby making HE a flatter-structured and less hierarchically-organised workplace for teachers (Eringfeld, 2021 ).

Cross-cutting implications

Some of the teachers in the studies reviewed commented on the potential of ERT to undermine the ethos of the academic profession and imperil the work of academics. They noted that ERT could be pedagogically regressive, as teachers’ role may be reduced to merely technical functions, such as uploading materials online. This challenged their beliefs about what good teaching entails and compromised their often long-established pedagogical practices (Watermeyer et al., 2021 ). Other teachers struggled with balancing depth in their teaching with what they saw as their students’ preference for over-simplified yet visually appealing inputs such as bite-sized explanations shared on TikTok and other social media (Sales et al., 2020 ). Some anticipate worrying trends of ‘dumbing down’ of HE if teaching continues to be impersonal, disembodied and mediated predominantly by digital technologies in the post-ERT era (Watermeyer et al., 2021 ).

We have discussed so far the changes to HE teaching due to the relocation to newly formed spaces, as reported in the studies reviewed. Yet, some principles and values that teachers apply to guide their teaching practices remained unchanged amidst the ongoing crisis. These include the upholding of integrity, academic transparency, privacy, and other ethical principles in teaching (Mouchantaf, 2020 ). For example, teachers were concerned about the potential collection of students’ data for third-party use without prior informed consent (Diningrat et al., 2020 ; Joshi et al., 2020 ). Others also recognise the importance for students of using technology responsibly (Gyampoh et al., 2020 ) and being equipped with critical and reflective thinking capacity to evaluate the accuracy and relevance of information online (Sales et al., 2020 ; Tejedor et al., 2020 ), including resisting the temptation to reuse others’ ideas as their own work (Dampson et al., 2020 ) and refraining from using improper language on social media (Ghounane, 2020 ; Sobaih et al., 2020 ). This was especially relevant during the absence of teacher’s in-person monitoring, when the responsibility to access and study educational materials was partially shifted to students (Gyampoh et al., 2020 ), many of whom were inclined to explore topics of interest on their own (Marshalsey & Sclater, 2020 ; Mideros, 2020 ; Sales et al., 2020 ).

For teachers themselves, their practical wisdom and professional deliberation to ‘consider when, why, and how to use technology properly’ (Diningrat et al., 2020 , p. 706) were put to the test during the emergency contexts of teaching. A teacher participant in the study by Cutri et al. ( 2020 ) shared his belated reflection on an inadvertent, frivolous ridicule he had made about a student’s slow internet speed in front of the entire class online. This anecdote alludes to two problems looming in the wider context of HE teaching: (1) the largely absent code of conduct that delineates appropriate practices and roles of teachers and students in the new spatiality (and this can be due partly to the short time horizon in ERT); and (2) the difficulty for teachers to create supportive yet private spaces to address equity issues and attend to students’ emotionality in strict confidence when being online (Cutri et al., 2020 ).

Teachers participating in the studies reviewed in this paper indicated a multiplicity of factors that interacted to shape their technology use during the ERT period. In line with Liu et al. ( 2020 )’s pre-pandemic work, we find strong evidence that technology use in teaching is a context-sensitive, socially-embedded topic of study and hence should be understood in the socio-political, cultural and material context in which academics and students are situated (Selwyn et al., 2020 ). For example, the label ‘technical issues’ could encompass a wide range of contextualised problems, from power outages to long commutes for Internet access, from material shortages to widespread hunger, from trenchant poverty to deep-seated structured inequalities, which afflict disproportionately relatively poor, underserved communities and the most disadvantaged segments of populations (Chan et al., 2022 ) but are also palpable within higher-income countries/regions [see, for example, Cullinan et al. ( 2021 ) for a study on broadband access disparities in Ireland].

The narrative account we constructed is indicative of the resourcefulness and resilience of teachers to continue teaching during the crisis, even those in marginalised communities where resources are limited. This view is also shared by Padilla Rodríguez et al. ( 2021 ) who study the changes teachers in rural Mexico have made to their teaching practice in response to the suspension of in-person classes without receiving much external support during the pandemic. Around the world, teachers forayed into ERT during times of uncertainty by seeking to empower themselves and exploring various technological artefacts in teaching on their own, on the one hand; and by endorsing mutual empowerment and drawing inspiration from amongst their peers, on the other. Their collective efforts in supporting one another in the wake of crisis created what Matthewman and Uekusa ( 2021 ) call ‘disaster communitas’, which temporarily served to support teachers when adapting to the hasty conversion to ERT. We concur with Hickling et al. ( 2021 ) that the creation of a supportive space and environment for HE teachers to commiserate, discuss experiences, and share insights and resources with colleagues helps advance teaching practices with technology.

In answering the second research question, we have discussed at length the implications of a more encompassing use of technology in ERT and how evolving notions of space and time combined to reconstitute teacher-student relationships and the nature of academics’ work (Williamson et al., 2020 ). The studies reviewed indicate that the rushed transition to ERT has affected the sense of professional identity of academics as HE teachers (Littlejohn et al., 2021 ) in ways that are as yet only partly explored. Echoing the findings of Ramlo ( 2021 ), we believe that teachers’ negotiation of the blurring home-workspace boundaries (Blumsztajn et al., 2022 ; Littlejohn et al., 2021 ) and attempts to rebalance their professional work and personal life have important implications for future HE teaching and merit further investigation (Gourlay et al., 2021 ).

As COVID-19 continues to take a toll on people’s lives, we draw on the studies reviewed to emphasise the importance of re-prioritising the value of social and emotional connections in HE teaching, as well as the overall well-being of both teachers and students (Baker et al., 2022 ; Yeung & Yau, 2021 ). ‘Networks of care’ between teachers and students as well as amongst teachers themselves may be constructed to ameliorate uncertainties brought by the pandemic (Czerniewicz et al., 2020 ; Joseph & Trinick, 2021 ). Elements of care can be developed by simple acts of kindness (Murray et al., 2020 ) and gestures to communicate approachability (Glantz et al., 2021 ), all of which contribute to constructing more supportive and less hierarchical teacher-student relationships in the digital context. We note, however, that evidence scattered across the studies reviewed indicates that academic recognition and reward systems have not accounted well for the creative efforts that academics (including casualised and untenured staff) have put into teaching and maintaining relationships with their colleagues and students in response to the ongoing challenges ensuing from the coronavirus crisis. This is another priority for HEIs and leadership teams. On a final note, future research may explore further, innovative ways in which HE teaching can be reconstituted in the presence and context of technology without undermining teachers’ professional identity or compromising the revitalisation of teaching as an embodied, communal, and humanising experience as campuses around the world re-open, in full or in part, for in-person activities in post-pandemic times.

Appendix 1. A detailed version of inclusion/exclusion criteria

Appendix 2. search terms in english and chinese (note that the search strategy varied slightly across databases due to the different limits they set on the length of search input), appendix 3. prisma 2020 flow diagram for systematic review (page et al., 2021 ).

Appendix 4. Quality and relevance assessment rubric and the average scores of the 32 included studies (adapted from Oancea et al., 2021 )

• a Score description: 4—criterion fully met; 3—criterion mostly met, though with some weaknesses; 2—criterion only partly met, with several or serious weaknesses; 1—criterion largely not met

Appendix 5. Data extraction grid

Appendix 6. summary of characteristics of 32 reviewed studies.

• a The references of four articles show the publication year of 2021. These four articles were published online ahead of print in 2020 and hence are included in this study

Availability of data and materials

All data generated or analysed during this study are included in this published article.

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Acknowledgements

The corresponding author gave a presentation on the preliminary findings of this systematic review at the 1st International Yidan Prize Doctoral Conference (online) organized by the University of Oxford on 27 May 2021. The insightful questions raised by the audience are gratefully acknowledged. We would like to thank Dr. Victoria Elliott, Ms. Renyu Jiang, Ms. Abbey Palmer, and Ms. Catherine Scutt who have directly and indirectly provided their support for this research project.

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The corresponding author is a doctoral candidate reading Education. This paper is an original work, conducted by the corresponding author in parallel to the preparation for submission of a thesis for a Doctor of Philosophy (DPhil) degree under the supervision of the second author. Preliminary findings of this systematic review have been published in the Proceedings of the Yidan Prize Doctoral Conference under the terms of a Creative Commons Attribution License (CC-BY) (see Sum & Oancea, 2021 ).

This work was generously supported by a scholarship jointly awarded by the Clarendon Fund and New College of the University of Oxford (2020–2023).

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Under the guidance and supervision of AO, MS performed all stages of the systematic review, from conceptualising the review project to writing the manuscript. Both authors worked collaboratively from late 2020 to mid 2022 on this project. MS and AO independently coded and analysed a selection of data excerpts at various stages to check for inter-rater reliability as mentioned in ‘ Methodology ’ section. The rubric for quality assessment was based on past work by AO. Communications between the authors were maintained throughout the research process. MS worked on drafting this paper, which was subsequently revised by the AO. Both authors read and approved the final manuscript.

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Sum, M., Oancea, A. The use of technology in higher education teaching by academics during the COVID-19 emergency remote teaching period: a systematic review. Int J Educ Technol High Educ 19 , 59 (2022). https://doi.org/10.1186/s41239-022-00364-4

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Education reform and change driven by digital technology: a bibliometric study from a global perspective

• Chengliang Wang 1 ,
• Xiaojiao Chen 1 ,
• Teng Yu   ORCID: orcid.org/0000-0001-5198-7261 2 , 3 ,
• Yidan Liu 1 , 4 &
• Yuhui Jing 1  

Humanities and Social Sciences Communications volume  11 , Article number:  256 ( 2024 ) Cite this article

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• Development studies
• Science, technology and society

Amidst the global digital transformation of educational institutions, digital technology has emerged as a significant area of interest among scholars. Such technologies have played an instrumental role in enhancing learner performance and improving the effectiveness of teaching and learning. These digital technologies also ensure the sustainability and stability of education during the epidemic. Despite this, a dearth of systematic reviews exists regarding the current state of digital technology application in education. To address this gap, this study utilized the Web of Science Core Collection as a data source (specifically selecting the high-quality SSCI and SCIE) and implemented a topic search by setting keywords, yielding 1849 initial publications. Furthermore, following the PRISMA guidelines, we refined the selection to 588 high-quality articles. Using software tools such as CiteSpace, VOSviewer, and Charticulator, we reviewed these 588 publications to identify core authors (such as Selwyn, Henderson, Edwards), highly productive countries/regions (England, Australia, USA), key institutions (Monash University, Australian Catholic University), and crucial journals in the field ( Education and Information Technologies , Computers & Education , British Journal of Educational Technology ). Evolutionary analysis reveals four developmental periods in the research field of digital technology education application: the embryonic period, the preliminary development period, the key exploration, and the acceleration period of change. The study highlights the dual influence of technological factors and historical context on the research topic. Technology is a key factor in enabling education to transform and upgrade, and the context of the times is an important driving force in promoting the adoption of new technologies in the education system and the transformation and upgrading of education. Additionally, the study identifies three frontier hotspots in the field: physical education, digital transformation, and professional development under the promotion of digital technology. This study presents a clear framework for digital technology application in education, which can serve as a valuable reference for researchers and educational practitioners concerned with digital technology education application in theory and practice.

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Introduction.

Digital technology has become an essential component of modern education, facilitating the extension of temporal and spatial boundaries and enriching the pedagogical contexts (Selwyn and Facer, 2014 ). The advent of mobile communication technology has enabled learning through social media platforms (Szeto et al. 2015 ; Pires et al. 2022 ), while the advancement of augmented reality technology has disrupted traditional conceptions of learning environments and spaces (Perez-Sanagustin et al., 2014 ; Kyza and Georgiou, 2018 ). A wide range of digital technologies has enabled learning to become a norm in various settings, including the workplace (Sjöberg and Holmgren, 2021 ), home (Nazare et al. 2022 ), and online communities (Tang and Lam, 2014 ). Education is no longer limited to fixed locations and schedules, but has permeated all aspects of life, allowing learning to continue at any time and any place (Camilleri and Camilleri, 2016 ; Selwyn and Facer, 2014 ).

The advent of digital technology has led to the creation of several informal learning environments (Greenhow and Lewin, 2015 ) that exhibit divergent form, function, features, and patterns in comparison to conventional learning environments (Nygren et al. 2019 ). Consequently, the associated teaching and learning processes, as well as the strategies for the creation, dissemination, and acquisition of learning resources, have undergone a complete overhaul. The ensuing transformations have posed a myriad of novel issues, such as the optimal structuring of teaching methods by instructors and the adoption of appropriate learning strategies by students in the new digital technology environment. Consequently, an examination of the principles that underpin effective teaching and learning in this environment is a topic of significant interest to numerous scholars engaged in digital technology education research.

Over the course of the last two decades, digital technology has made significant strides in the field of education, notably in extending education time and space and creating novel educational contexts with sustainability. Despite research attempts to consolidate the application of digital technology in education, previous studies have only focused on specific aspects of digital technology, such as Pinto and Leite’s ( 2020 ) investigation into digital technology in higher education and Mustapha et al.’s ( 2021 ) examination of the role and value of digital technology in education during the pandemic. While these studies have provided valuable insights into the practical applications of digital technology in particular educational domains, they have not comprehensively explored the macro-mechanisms and internal logic of digital technology implementation in education. Additionally, these studies were conducted over a relatively brief period, making it challenging to gain a comprehensive understanding of the macro-dynamics and evolutionary process of digital technology in education. Some studies have provided an overview of digital education from an educational perspective but lack a precise understanding of technological advancement and change (Yang et al. 2022 ). Therefore, this study seeks to employ a systematic scientific approach to collate relevant research from 2000 to 2022, comprehend the internal logic and development trends of digital technology in education, and grasp the outstanding contribution of digital technology in promoting the sustainability of education in time and space. In summary, this study aims to address the following questions:

RQ1: Since the turn of the century, what is the productivity distribution of the field of digital technology education application research in terms of authorship, country/region, institutional and journal level?

RQ2: What is the development trend of research on the application of digital technology in education in the past two decades?

RQ3: What are the current frontiers of research on the application of digital technology in education?

Literature review

Although the term “digital technology” has become ubiquitous, a unified definition has yet to be agreed upon by scholars. Because the meaning of the word digital technology is closely related to the specific context. Within the educational research domain, Selwyn’s ( 2016 ) definition is widely favored by scholars (Pinto and Leite, 2020 ). Selwyn ( 2016 ) provides a comprehensive view of various concrete digital technologies and their applications in education through ten specific cases, such as immediate feedback in classes, orchestrating teaching, and community learning. Through these specific application scenarios, Selwyn ( 2016 ) argues that digital technology encompasses technologies associated with digital devices, including but not limited to tablets, smartphones, computers, and social media platforms (such as Facebook and YouTube). Furthermore, Further, the behavior of accessing the internet at any location through portable devices can be taken as an extension of the behavior of applying digital technology.

The evolving nature of digital technology has significant implications in the field of education. In the 1890s, the focus of digital technology in education was on comprehending the nuances of digital space, digital culture, and educational methodologies, with its connotations aligned more towards the idea of e-learning. The advent and subsequent widespread usage of mobile devices since the dawn of the new millennium have been instrumental in the rapid expansion of the concept of digital technology. Notably, mobile learning devices such as smartphones and tablets, along with social media platforms, have become integral components of digital technology (Conole and Alevizou, 2010 ; Batista et al. 2016 ). In recent times, the burgeoning application of AI technology in the education sector has played a vital role in enriching the digital technology lexicon (Banerjee et al. 2021 ). ChatGPT, for instance, is identified as a novel educational technology that has immense potential to revolutionize future education (Rospigliosi, 2023 ; Arif, Munaf and Ul-Haque, 2023 ).

Pinto and Leite ( 2020 ) conducted a comprehensive macroscopic survey of the use of digital technologies in the education sector and identified three distinct categories, namely technologies for assessment and feedback, mobile technologies, and Information Communication Technologies (ICT). This classification criterion is both macroscopic and highly condensed. In light of the established concept definitions of digital technology in the educational research literature, this study has adopted the characterizations of digital technology proposed by Selwyn ( 2016 ) and Pinto and Leite ( 2020 ) as crucial criteria for analysis and research inclusion. Specifically, this criterion encompasses several distinct types of digital technologies, including Information and Communication Technologies (ICT), Mobile tools, eXtended Reality (XR) Technologies, Assessment and Feedback systems, Learning Management Systems (LMS), Publish and Share tools, Collaborative systems, Social media, Interpersonal Communication tools, and Content Aggregation tools.

Methodology and materials

Research method: bibliometric.

The research on econometric properties has been present in various aspects of human production and life, yet systematic scientific theoretical guidance has been lacking, resulting in disorganization. In 1969, British scholar Pritchard ( 1969 ) proposed “bibliometrics,” which subsequently emerged as an independent discipline in scientific quantification research. Initially, Pritchard defined bibliometrics as “the application of mathematical and statistical methods to books and other media of communication,” however, the definition was not entirely rigorous. To remedy this, Hawkins ( 2001 ) expanded Pritchard’s definition to “the quantitative analysis of the bibliographic features of a body of literature.” De Bellis further clarified the objectives of bibliometrics, stating that it aims to analyze and identify patterns in literature, such as the most productive authors, institutions, countries, and journals in scientific disciplines, trends in literary production over time, and collaboration networks (De Bellis, 2009 ). According to Garfield ( 2006 ), bibliometric research enables the examination of the history and structure of a field, the flow of information within the field, the impact of journals, and the citation status of publications over a longer time scale. All of these definitions illustrate the unique role of bibliometrics as a research method for evaluating specific research fields.

This study uses CiteSpace, VOSviewer, and Charticulator to analyze data and create visualizations. Each of these three tools has its own strengths and can complement each other. CiteSpace and VOSviewer use set theory and probability theory to provide various visualization views in fields such as keywords, co-occurrence, and co-authors. They are easy to use and produce visually appealing graphics (Chen, 2006 ; van Eck and Waltman, 2009 ) and are currently the two most widely used bibliometric tools in the field of visualization (Pan et al. 2018 ). In this study, VOSviewer provided the data necessary for the Performance Analysis; Charticulator was then used to redraw using the tabular data exported from VOSviewer (for creating the chord diagram of country collaboration); this was to complement the mapping process, while CiteSpace was primarily utilized to generate keyword maps and conduct burst word analysis.

Data retrieval

This study selected documents from the Science Citation Index Expanded (SCIE) and Social Science Citation Index (SSCI) in the Web of Science Core Collection as the data source, for the following reasons:

(1) The Web of Science Core Collection, as a high-quality digital literature resource database, has been widely accepted by many researchers and is currently considered the most suitable database for bibliometric analysis (Jing et al. 2023a ). Compared to other databases, Web of Science provides more comprehensive data information (Chen et al. 2022a ), and also provides data formats suitable for analysis using VOSviewer and CiteSpace (Gaviria-Marin et al. 2019 ).

(2) The application of digital technology in the field of education is an interdisciplinary research topic, involving technical knowledge literature belonging to the natural sciences and education-related literature belonging to the social sciences. Therefore, it is necessary to select Science Citation Index Expanded (SCIE) and Social Science Citation Index (SSCI) as the sources of research data, ensuring the comprehensiveness of data while ensuring the reliability and persuasiveness of bibliometric research (Hwang and Tsai, 2011 ; Wang et al. 2022 ).

After establishing the source of research data, it is necessary to determine a retrieval strategy (Jing et al. 2023b ). The choice of a retrieval strategy should consider a balance between the breadth and precision of the search formula. That is to say, it should encompass all the literature pertaining to the research topic while excluding irrelevant documents as much as possible. In light of this, this study has set a retrieval strategy informed by multiple related papers (Mustapha et al. 2021 ; Luo et al. 2021 ). The research by Mustapha et al. ( 2021 ) guided us in selecting keywords (“digital” AND “technolog*”) to target digital technology, while Luo et al. ( 2021 ) informed the selection of terms (such as “instruct*,” “teach*,” and “education”) to establish links with the field of education. Then, based on the current application of digital technology in the educational domain and the scope of selection criteria, we constructed the final retrieval strategy. Following the general patterns of past research (Jing et al. 2023a , 2023b ), we conducted a specific screening using the topic search (Topics, TS) function in Web of Science. For the specific criteria used in the screening for this study, please refer to Table 1 .

Literature screening

Literature acquired through keyword searches may contain ostensibly related yet actually unrelated works. Therefore, to ensure the close relevance of literature included in the analysis to the research topic, it is often necessary to perform a manual screening process to identify the final literature to be analyzed, subsequent to completing the initial literature search.

The manual screening process consists of two steps. Initially, irrelevant literature is weeded out based on the title and abstract, with two members of the research team involved in this phase. This stage lasted about one week, resulting in 1106 articles being retained. Subsequently, a comprehensive review of the full text is conducted to accurately identify the literature required for the study. To carry out the second phase of manual screening effectively and scientifically, and to minimize the potential for researcher bias, the research team established the inclusion criteria presented in Table 2 . Three members were engaged in this phase, which took approximately 2 weeks, culminating in the retention of 588 articles after meticulous screening. The entire screening process is depicted in Fig. 1 , adhering to the PRISMA guidelines (Page et al. 2021 ).

The process of obtaining and filtering the necessary literature data for research.

Data standardization

Nguyen and Hallinger ( 2020 ) pointed out that raw data extracted from scientific databases often contains multiple expressions of the same term, and not addressing these synonymous expressions could affect research results in bibliometric analysis. For instance, in the original data, the author list may include “Tsai, C. C.” and “Tsai, C.-C.”, while the keyword list may include “professional-development” and “professional development,” which often require merging. Therefore, before analyzing the selected literature, a data disambiguation process is necessary to standardize the data (Strotmann and Zhao, 2012 ; Van Eck and Waltman, 2019 ). This study adopted the data standardization process proposed by Taskin and Al ( 2019 ), mainly including the following standardization operations:

Firstly, the author and source fields in the data are corrected and standardized to differentiate authors with similar names.

Secondly, the study checks whether the journals to which the literature belongs have been renamed in the past over 20 years, so as to avoid the influence of periodical name change on the analysis results.

Finally, the keyword field is standardized by unifying parts of speech and singular/plural forms of keywords, which can help eliminate redundant entries in the knowledge graph.

Performance analysis (RQ1)

This section offers a thorough and detailed analysis of the state of research in the field of digital technology education. By utilizing descriptive statistics and visual maps, it provides a comprehensive overview of the development trends, authors, countries, institutions, and journal distribution within the field. The insights presented in this section are of great significance in advancing our understanding of the current state of research in this field and identifying areas for further investigation. The use of visual aids to display inter-country cooperation and the evolution of the field adds to the clarity and coherence of the analysis.

Time trend of the publications

To understand a research field, it is first necessary to understand the most basic quantitative information, among which the change in the number of publications per year best reflects the development trend of a research field. Figure 2 shows the distribution of publication dates.

Time trend of the publications on application of digital technology in education.

From the Fig. 2 , it can be seen that the development of this field over the past over 20 years can be roughly divided into three stages. The first stage was from 2000 to 2007, during which the number of publications was relatively low. Due to various factors such as technological maturity, the academic community did not pay widespread attention to the role of digital technology in expanding the scope of teaching and learning. The second stage was from 2008 to 2019, during which the overall number of publications showed an upward trend, and the development of the field entered an accelerated period, attracting more and more scholars’ attention. The third stage was from 2020 to 2022, during which the number of publications stabilized at around 100. During this period, the impact of the pandemic led to a large number of scholars focusing on the role of digital technology in education during the pandemic, and research on the application of digital technology in education became a core topic in social science research.

Analysis of authors

An analysis of the author’s publication volume provides information about the representative scholars and core research strengths of a research area. Table 3 presents information on the core authors in adaptive learning research, including name, publication number, and average number of citations per article (based on the analysis and statistics from VOSviewer).

Variations in research foci among scholars abound. Within the field of digital technology education application research over the past two decades, Neil Selwyn stands as the most productive author, having published 15 papers garnering a total of 1027 citations, resulting in an average of 68.47 citations per paper. As a Professor at the Faculty of Education at Monash University, Selwyn concentrates on exploring the application of digital technology in higher education contexts (Selwyn et al. 2021 ), as well as related products in higher education such as Coursera, edX, and Udacity MOOC platforms (Bulfin et al. 2014 ). Selwyn’s contributions to the educational sociology perspective include extensive research on the impact of digital technology on education, highlighting the spatiotemporal extension of educational processes and practices through technological means as the greatest value of educational technology (Selwyn, 2012 ; Selwyn and Facer, 2014 ). In addition, he provides a blueprint for the development of future schools in 2030 based on the present impact of digital technology on education (Selwyn et al. 2019 ). The second most productive author in this field, Henderson, also offers significant contributions to the understanding of the important value of digital technology in education, specifically in the higher education setting, with a focus on the impact of the pandemic (Henderson et al. 2015 ; Cohen et al. 2022 ). In contrast, Edwards’ research interests focus on early childhood education, particularly the application of digital technology in this context (Edwards, 2013 ; Bird and Edwards, 2015 ). Additionally, on the technical level, Edwards also mainly prefers digital game technology, because it is a digital technology that children are relatively easy to accept (Edwards, 2015 ).

Analysis of countries/regions and organization

The present study aimed to ascertain the leading countries in digital technology education application research by analyzing 75 countries related to 558 works of literature. Table 4 depicts the top ten countries that have contributed significantly to this field in terms of publication count (based on the analysis and statistics from VOSviewer). Our analysis of Table 4 data shows that England emerged as the most influential country/region, with 92 published papers and 2401 citations. Australia and the United States secured the second and third ranks, respectively, with 90 papers (2187 citations) and 70 papers (1331 citations) published. Geographically, most of the countries featured in the top ten publication volumes are situated in Australia, North America, and Europe, with China being the only exception. Notably, all these countries, except China, belong to the group of developed nations, suggesting that economic strength is a prerequisite for fostering research in the digital technology education application field.

This study presents a visual representation of the publication output and cooperation relationships among different countries in the field of digital technology education application research. Specifically, a chord diagram is employed to display the top 30 countries in terms of publication output, as depicted in Fig. 3 . The chord diagram is composed of nodes and chords, where the nodes are positioned as scattered points along the circumference, and the length of each node corresponds to the publication output, with longer lengths indicating higher publication output. The chords, on the other hand, represent the cooperation relationships between any two countries, and are weighted based on the degree of closeness of the cooperation, with wider chords indicating closer cooperation. Through the analysis of the cooperation relationships, the findings suggest that the main publishing countries in this field are engaged in cooperative relationships with each other, indicating a relatively high level of international academic exchange and research internationalization.

In the diagram, nodes are scattered along the circumference of a circle, with the length of each node representing the volume of publications. The weighted arcs connecting any two points on the circle are known as chords, representing the collaborative relationship between the two, with the width of the arc indicating the closeness of the collaboration.

Further analyzing Fig. 3 , we can extract more valuable information, enabling a deeper understanding of the connections between countries in the research field of digital technology in educational applications. It is evident that certain countries, such as the United States, China, and England, display thicker connections, indicating robust collaborative relationships in terms of productivity. These thicker lines signify substantial mutual contributions and shared objectives in certain sectors or fields, highlighting the interconnectedness and global integration in these areas. By delving deeper, we can also explore potential future collaboration opportunities through the chord diagram, identifying possible partners to propel research and development in this field. In essence, the chord diagram successfully encapsulates and conveys the multi-dimensionality of global productivity and cooperation, allowing for a comprehensive understanding of the intricate inter-country relationships and networks in a global context, providing valuable guidance and insights for future research and collaborations.

An in-depth examination of the publishing institutions is provided in Table 5 , showcasing the foremost 10 institutions ranked by their publication volume. Notably, Monash University and Australian Catholic University, situated in Australia, have recorded the most prolific publications within the digital technology education application realm, with 22 and 10 publications respectively. Moreover, the University of Oslo from Norway is featured among the top 10 publishing institutions, with an impressive average citation count of 64 per publication. It is worth highlighting that six institutions based in the United Kingdom were also ranked within the top 10 publishing institutions, signifying their leading position in this area of research.

Analysis of journals

Journals are the main carriers for publishing high-quality papers. Some scholars point out that the two key factors to measure the influence of journals in the specified field are the number of articles published and the number of citations. The more papers published in a magazine and the more citations, the greater its influence (Dzikowski, 2018 ). Therefore, this study utilized VOSviewer to statistically analyze the top 10 journals with the most publications in the field of digital technology in education and calculated the average citations per article (see Table 6 ).

Based on Table 6 , it is apparent that the highest number of articles in the domain of digital technology in education research were published in Education and Information Technologies (47 articles), Computers & Education (34 articles), and British Journal of Educational Technology (32 articles), indicating a higher article output compared to other journals. This underscores the fact that these three journals concentrate more on the application of digital technology in education. Furthermore, several other journals, such as Technology Pedagogy and Education and Sustainability, have published more than 15 articles in this domain. Sustainability represents the open access movement, which has notably facilitated research progress in this field, indicating that the development of open access journals in recent years has had a significant impact. Although there is still considerable disagreement among scholars on the optimal approach to achieve open access, the notion that research outcomes should be accessible to all is widely recognized (Huang et al. 2020 ). On further analysis of the research fields to which these journals belong, except for Sustainability, it is evident that they all pertain to educational technology, thus providing a qualitative definition of the research area of digital technology education from the perspective of journals.

Temporal keyword analysis: thematic evolution (RQ2)

The evolution of research themes is a dynamic process, and previous studies have attempted to present the developmental trajectory of fields by drawing keyword networks in phases (Kumar et al. 2021 ; Chen et al. 2022b ). To understand the shifts in research topics across different periods, this study follows past research and, based on the significant changes in the research field and corresponding technological advancements during the outlined periods, divides the timeline into four stages (the first stage from January 2000 to December 2005, the second stage from January 2006 to December 2011, the third stage from January 2012 to December 2017; and the fourth stage from January 2018 to December 2022). The division into these four stages was determined through a combination of bibliometric analysis and literature review, which presented a clear trajectory of the field’s development. The research analyzes the keyword networks for each time period (as there are only three articles in the first stage, it was not possible to generate an appropriate keyword co-occurrence map, hence only the keyword co-occurrence maps from the second to the fourth stages are provided), to understand the evolutionary track of the digital technology education application research field over time.

2000.1–2005.12: germination period

From January 2000 to December 2005, digital technology education application research was in its infancy. Only three studies focused on digital technology, all of which were related to computers. Due to the popularity of computers, the home became a new learning environment, highlighting the important role of digital technology in expanding the scope of learning spaces (Sutherland et al. 2000 ). In specific disciplines and contexts, digital technology was first favored in medical clinical practice, becoming an important tool for supporting the learning of clinical knowledge and practice (Tegtmeyer et al. 2001 ; Durfee et al. 2003 ).

2006.1–2011.12: initial development period

Between January 2006 and December 2011, it was the initial development period of digital technology education research. Significant growth was observed in research related to digital technology, and discussions and theoretical analyses about “digital natives” emerged. During this phase, scholars focused on the debate about “how to use digital technology reasonably” and “whether current educational models and school curriculum design need to be adjusted on a large scale” (Bennett and Maton, 2010 ; Selwyn, 2009 ; Margaryan et al. 2011 ). These theoretical and speculative arguments provided a unique perspective on the impact of cognitive digital technology on education and teaching. As can be seen from the vocabulary such as “rethinking”, “disruptive pedagogy”, and “attitude” in Fig. 4 , many scholars joined the calm reflection and analysis under the trend of digital technology (Laurillard, 2008 ; Vratulis et al. 2011 ). During this phase, technology was still undergoing dramatic changes. The development of mobile technology had already caught the attention of many scholars (Wong et al. 2011 ), but digital technology represented by computers was still very active (Selwyn et al. 2011 ). The change in technological form would inevitably lead to educational transformation. Collins and Halverson ( 2010 ) summarized the prospects and challenges of using digital technology for learning and educational practices, believing that digital technology would bring a disruptive revolution to the education field and bring about a new educational system. In addition, the term “teacher education” in Fig. 4 reflects the impact of digital technology development on teachers. The rapid development of technology has widened the generation gap between teachers and students. To ensure smooth communication between teachers and students, teachers must keep up with the trend of technological development and establish a lifelong learning concept (Donnison, 2009 ).

In the diagram, each node represents a keyword, with the size of the node indicating the frequency of occurrence of the keyword. The connections represent the co-occurrence relationships between keywords, with a higher frequency of co-occurrence resulting in tighter connections.

2012.1–2017.12: critical exploration period

During the period spanning January 2012 to December 2017, the application of digital technology in education research underwent a significant exploration phase. As can be seen from Fig. 5 , different from the previous stage, the specific elements of specific digital technology have started to increase significantly, including the enrichment of technological contexts, the greater variety of research methods, and the diversification of learning modes. Moreover, the temporal and spatial dimensions of the learning environment were further de-emphasized, as noted in previous literature (Za et al. 2014 ). Given the rapidly accelerating pace of technological development, the education system in the digital era is in urgent need of collaborative evolution and reconstruction, as argued by Davis, Eickelmann, and Zaka ( 2013 ).

In the domain of digital technology, social media has garnered substantial scholarly attention as a promising avenue for learning, as noted by Pasquini and Evangelopoulos ( 2016 ). The implementation of social media in education presents several benefits, including the liberation of education from the restrictions of physical distance and time, as well as the erasure of conventional educational boundaries. The user-generated content (UGC) model in social media has emerged as a crucial source for knowledge creation and distribution, with the widespread adoption of mobile devices. Moreover, social networks have become an integral component of ubiquitous learning environments (Hwang et al. 2013 ). The utilization of social media allows individuals to function as both knowledge producers and recipients, which leads to a blurring of the conventional roles of learners and teachers. On mobile platforms, the roles of learners and teachers are not fixed, but instead interchangeable.

In terms of research methodology, the prevalence of empirical studies with survey designs in the field of educational technology during this period is evident from the vocabulary used, such as “achievement,” “acceptance,” “attitude,” and “ict.” in Fig. 5 . These studies aim to understand learners’ willingness to adopt and attitudes towards new technologies, and some seek to investigate the impact of digital technologies on learning outcomes through quasi-experimental designs (Domínguez et al. 2013 ). Among these empirical studies, mobile learning emerged as a hot topic, and this is not surprising. First, the advantages of mobile learning environments over traditional ones have been empirically demonstrated (Hwang et al. 2013 ). Second, learners born around the turn of the century have been heavily influenced by digital technologies and have developed their own learning styles that are more open to mobile devices as a means of learning. Consequently, analyzing mobile learning as a relatively novel mode of learning has become an important issue for scholars in the field of educational technology.

The intervention of technology has led to the emergence of several novel learning modes, with the blended learning model being the most representative one in the current phase. Blended learning, a novel concept introduced in the information age, emphasizes the integration of the benefits of traditional learning methods and online learning. This learning mode not only highlights the prominent role of teachers in guiding, inspiring, and monitoring the learning process but also underlines the importance of learners’ initiative, enthusiasm, and creativity in the learning process. Despite being an early conceptualization, blended learning’s meaning has been expanded by the widespread use of mobile technology and social media in education. The implementation of new technologies, particularly mobile devices, has resulted in the transformation of curriculum design and increased flexibility and autonomy in students’ learning processes (Trujillo Maza et al. 2016 ), rekindling scholarly attention to this learning mode. However, some scholars have raised concerns about the potential drawbacks of the blended learning model, such as its significant impact on the traditional teaching system, the lack of systematic coping strategies and relevant policies in several schools and regions (Moskal et al. 2013 ).

2018.1–2022.12: accelerated transformation period

The period spanning from January 2018 to December 2022 witnessed a rapid transformation in the application of digital technology in education research. The field of digital technology education research reached a peak period of publication, largely influenced by factors such as the COVID-19 pandemic (Yu et al. 2023 ). Research during this period was built upon the achievements, attitudes, and social media of the previous phase, and included more elements that reflect the characteristics of this research field, such as digital literacy, digital competence, and professional development, as depicted in Fig. 6 . Alongside this, scholars’ expectations for the value of digital technology have expanded, and the pursuit of improving learning efficiency and performance is no longer the sole focus. Some research now aims to cultivate learners’ motivation and enhance their self-efficacy by applying digital technology in a reasonable manner, as demonstrated by recent studies (Beardsley et al. 2021 ; Creely et al. 2021 ).

The COVID-19 pandemic has emerged as a crucial backdrop for the digital technology’s role in sustaining global education, as highlighted by recent scholarly research (Zhou et al. 2022 ; Pan and Zhang, 2020 ; Mo et al. 2022 ). The online learning environment, which is supported by digital technology, has become the primary battleground for global education (Yu, 2022 ). This social context has led to various studies being conducted, with some scholars positing that the pandemic has impacted the traditional teaching order while also expanding learning possibilities in terms of patterns and forms (Alabdulaziz, 2021 ). Furthermore, the pandemic has acted as a catalyst for teacher teaching and technological innovation, and this viewpoint has been empirically substantiated (Moorhouse and Wong, 2021 ). Additionally, some scholars believe that the pandemic’s push is a crucial driving force for the digital transformation of the education system, serving as an essential mechanism for overcoming the system’s inertia (Romero et al. 2021 ).

The rapid outbreak of the pandemic posed a challenge to the large-scale implementation of digital technologies, which was influenced by a complex interplay of subjective and objective factors. Objective constraints included the lack of infrastructure in some regions to support digital technologies, while subjective obstacles included psychological resistance among certain students and teachers (Moorhouse, 2021 ). These factors greatly impacted the progress of online learning during the pandemic. Additionally, Timotheou et al. ( 2023 ) conducted a comprehensive systematic review of existing research on digital technology use during the pandemic, highlighting the critical role played by various factors such as learners’ and teachers’ digital skills, teachers’ personal attributes and professional development, school leadership and management, and administration in facilitating the digitalization and transformation of schools.

The current stage of research is characterized by the pivotal term “digital literacy,” denoting a growing interest in learners’ attitudes and adoption of emerging technologies. Initially, the term “literacy” was restricted to fundamental abilities and knowledge associated with books and print materials (McMillan, 1996 ). However, with the swift advancement of computers and digital technology, there have been various attempts to broaden the scope of literacy beyond its traditional meaning, including game literacy (Buckingham and Burn, 2007 ), information literacy (Eisenberg, 2008 ), and media literacy (Turin and Friesem, 2020 ). Similarly, digital literacy has emerged as a crucial concept, and Gilster and Glister ( 1997 ) were the first to introduce this concept, referring to the proficiency in utilizing technology and processing digital information in academic, professional, and daily life settings. In practical educational settings, learners who possess higher digital literacy often exhibit an aptitude for quickly mastering digital devices and applying them intelligently to education and teaching (Yu, 2022 ).

The utilization of digital technology in education has undergone significant changes over the past two decades, and has been a crucial driver of educational reform with each new technological revolution. The impact of these changes on the underlying logic of digital technology education applications has been noticeable. From computer technology to more recent developments such as virtual reality (VR), augmented reality (AR), and artificial intelligence (AI), the acceleration in digital technology development has been ongoing. Educational reforms spurred by digital technology development continue to be dynamic, as each new digital innovation presents new possibilities and models for teaching practice. This is especially relevant in the post-pandemic era, where the importance of technological progress in supporting teaching cannot be overstated (Mughal et al. 2022 ). Existing digital technologies have already greatly expanded the dimensions of education in both time and space, while future digital technologies aim to expand learners’ perceptions. Researchers have highlighted the potential of integrated technology and immersive technology in the development of the educational metaverse, which is highly anticipated to create a new dimension for the teaching and learning environment, foster a new value system for the discipline of educational technology, and more effectively and efficiently achieve the grand educational blueprint of the United Nations’ Sustainable Development Goals (Zhang et al. 2022 ; Li and Yu, 2023 ).

Hotspot evolution analysis (RQ3)

The examination of keyword evolution reveals a consistent trend in the advancement of digital technology education application research. The emergence and transformation of keywords serve as indicators of the varying research interests in this field. Thus, the utilization of the burst detection function available in CiteSpace allowed for the identification of the top 10 burst words that exhibited a high level of burst strength. This outcome is illustrated in Table 7 .

According to the results presented in Table 7 , the explosive terminology within the realm of digital technology education research has exhibited a concentration mainly between the years 2018 and 2022. Prior to this time frame, the emerging keywords were limited to “information technology” and “computer”. Notably, among them, computer, as an emergent keyword, has always had a high explosive intensity from 2008 to 2018, which reflects the important position of computer in digital technology and is the main carrier of many digital technologies such as Learning Management Systems (LMS) and Assessment and Feedback systems (Barlovits et al. 2022 ).

Since 2018, an increasing number of research studies have focused on evaluating the capabilities of learners to accept, apply, and comprehend digital technologies. As indicated by the use of terms such as “digital literacy” and “digital skill,” the assessment of learners’ digital literacy has become a critical task. Scholarly efforts have been directed towards the development of literacy assessment tools and the implementation of empirical assessments. Furthermore, enhancing the digital literacy of both learners and educators has garnered significant attention. (Nagle, 2018 ; Yu, 2022 ). Simultaneously, given the widespread use of various digital technologies in different formal and informal learning settings, promoting learners’ digital skills has become a crucial objective for contemporary schools (Nygren et al. 2019 ; Forde and OBrien, 2022 ).

Since 2020, the field of applied research on digital technology education has witnessed the emergence of three new hotspots, all of which have been affected to some extent by the pandemic. Firstly, digital technology has been widely applied in physical education, which is one of the subjects that has been severely affected by the pandemic (Parris et al. 2022 ; Jiang and Ning, 2022 ). Secondly, digital transformation has become an important measure for most schools, especially higher education institutions, to cope with the impact of the pandemic globally (García-Morales et al. 2021 ). Although the concept of digital transformation was proposed earlier, the COVID-19 pandemic has greatly accelerated this transformation process. Educational institutions must carefully redesign their educational products to face this new situation, providing timely digital learning methods, environments, tools, and support systems that have far-reaching impacts on modern society (Krishnamurthy, 2020 ; Salas-Pilco et al. 2022 ). Moreover, the professional development of teachers has become a key mission of educational institutions in the post-pandemic era. Teachers need to have a certain level of digital literacy and be familiar with the tools and online teaching resources used in online teaching, which has become a research hotspot today. Organizing digital skills training for teachers to cope with the application of emerging technologies in education is an important issue for teacher professional development and lifelong learning (Garzón-Artacho et al. 2021 ). As the main organizers and practitioners of emergency remote teaching (ERT) during the pandemic, teachers must put cognitive effort into their professional development to ensure effective implementation of ERT (Romero-Hall and Jaramillo Cherrez, 2022 ).

The burst word “digital transformation” reveals that we are in the midst of an ongoing digital technology revolution. With the emergence of innovative digital technologies such as ChatGPT and Microsoft 365 Copilot, technology trends will continue to evolve, albeit unpredictably. While the impact of these advancements on school education remains uncertain, it is anticipated that the widespread integration of technology will significantly affect the current education system. Rejecting emerging technologies without careful consideration is unwise. Like any revolution, the technological revolution in the education field has both positive and negative aspects. Detractors argue that digital technology disrupts learning and memory (Baron, 2021 ) or causes learners to become addicted and distracted from learning (Selwyn and Aagaard, 2020 ). On the other hand, the prudent use of digital technology in education offers a glimpse of a golden age of open learning. Educational leaders and practitioners have the opportunity to leverage cutting-edge digital technologies to address current educational challenges and develop a rational path for the sustainable and healthy growth of education.

Discussion on performance analysis (RQ1)

The field of digital technology education application research has experienced substantial growth since the turn of the century, a phenomenon that is quantifiably apparent through an analysis of authorship, country/region contributions, and institutional engagement. This expansion reflects the increased integration of digital technologies in educational settings and the heightened scholarly interest in understanding and optimizing their use.

Discussion on authorship productivity in digital technology education research

The authorship distribution within digital technology education research is indicative of the field’s intellectual structure and depth. A primary figure in this domain is Neil Selwyn, whose substantial citation rate underscores the profound impact of his work. His focus on the implications of digital technology in higher education and educational sociology has proven to be seminal. Selwyn’s research trajectory, especially the exploration of spatiotemporal extensions of education through technology, provides valuable insights into the multifaceted role of digital tools in learning processes (Selwyn et al. 2019 ).

Other notable contributors, like Henderson and Edwards, present diversified research interests, such as the impact of digital technologies during the pandemic and their application in early childhood education, respectively. Their varied focuses highlight the breadth of digital technology education research, encompassing pedagogical innovation, technological adaptation, and policy development.

Discussion on country/region-level productivity and collaboration

At the country/region level, the United Kingdom, specifically England, emerges as a leading contributor with 92 published papers and a significant citation count. This is closely followed by Australia and the United States, indicating a strong English-speaking research axis. Such geographical concentration of scholarly output often correlates with investment in research and development, technological infrastructure, and the prevalence of higher education institutions engaging in cutting-edge research.

China’s notable inclusion as the only non-Western country among the top contributors to the field suggests a growing research capacity and interest in digital technology in education. However, the lower average citation per paper for China could reflect emerging engagement or different research focuses that may not yet have achieved the same international recognition as Western counterparts.

The chord diagram analysis furthers this understanding, revealing dense interconnections between countries like the United States, China, and England, which indicates robust collaborations. Such collaborations are fundamental in addressing global educational challenges and shaping international research agendas.

Discussion on institutional-level contributions to digital technology education

Institutional productivity in digital technology education research reveals a constellation of universities driving the field forward. Monash University and the Australian Catholic University have the highest publication output, signaling Australia’s significant role in advancing digital education research. The University of Oslo’s remarkable average citation count per publication indicates influential research contributions, potentially reflecting high-quality studies that resonate with the broader academic community.

The strong showing of UK institutions, including the University of London, The Open University, and the University of Cambridge, reinforces the UK’s prominence in this research field. Such institutions are often at the forefront of pedagogical innovation, benefiting from established research cultures and funding mechanisms that support sustained inquiry into digital education.

Discussion on journal publication analysis

An examination of journal outputs offers a lens into the communicative channels of the field’s knowledge base. Journals such as Education and Information Technologies , Computers & Education , and the British Journal of Educational Technology not only serve as the primary disseminators of research findings but also as indicators of research quality and relevance. The impact factor (IF) serves as a proxy for the quality and influence of these journals within the academic community.

The high citation counts for articles published in Computers & Education suggest that research disseminated through this medium has a wide-reaching impact and is of particular interest to the field. This is further evidenced by its significant IF of 11.182, indicating that the journal is a pivotal platform for seminal work in the application of digital technology in education.

The authorship, regional, and institutional productivity in the field of digital technology education application research collectively narrate the evolution of this domain since the turn of the century. The prominence of certain authors and countries underscores the importance of socioeconomic factors and existing academic infrastructure in fostering research productivity. Meanwhile, the centrality of specific journals as outlets for high-impact research emphasizes the role of academic publishing in shaping the research landscape.

As the field continues to grow, future research may benefit from leveraging the collaborative networks that have been elucidated through this analysis, perhaps focusing on underrepresented regions to broaden the scope and diversity of research. Furthermore, the stabilization of publication numbers in recent years invites a deeper exploration into potential plateaus in research trends or saturation in certain sub-fields, signaling an opportunity for novel inquiries and methodological innovations.

Discussion on the evolutionary trends (RQ2)

The evolution of the research field concerning the application of digital technology in education over the past two decades is a story of convergence, diversification, and transformation, shaped by rapid technological advancements and shifting educational paradigms.

At the turn of the century, the inception of digital technology in education was largely exploratory, with a focus on how emerging computer technologies could be harnessed to enhance traditional learning environments. Research from this early period was primarily descriptive, reflecting on the potential and challenges of incorporating digital tools into the educational setting. This phase was critical in establishing the fundamental discourse that would guide subsequent research, as it set the stage for understanding the scope and impact of digital technology in learning spaces (Wang et al. 2023 ).

As the first decade progressed, the narrative expanded to encompass the pedagogical implications of digital technologies. This was a period of conceptual debates, where terms like “digital natives” and “disruptive pedagogy” entered the academic lexicon, underscoring the growing acknowledgment of digital technology as a transformative force within education (Bennett and Maton, 2010 ). During this time, the research began to reflect a more nuanced understanding of the integration of technology, considering not only its potential to change where and how learning occurred but also its implications for educational equity and access.

In the second decade, with the maturation of internet connectivity and mobile technology, the focus of research shifted from theoretical speculations to empirical investigations. The proliferation of digital devices and the ubiquity of social media influenced how learners interacted with information and each other, prompting a surge in studies that sought to measure the impact of these tools on learning outcomes. The digital divide and issues related to digital literacy became central concerns, as scholars explored the varying capacities of students and educators to engage with technology effectively.

Throughout this period, there was an increasing emphasis on the individualization of learning experiences, facilitated by adaptive technologies that could cater to the unique needs and pacing of learners (Jing et al. 2023a ). This individualization was coupled with a growing recognition of the importance of collaborative learning, both online and offline, and the role of digital tools in supporting these processes. Blended learning models, which combined face-to-face instruction with online resources, emerged as a significant trend, advocating for a balance between traditional pedagogies and innovative digital strategies.

The later years, particularly marked by the COVID-19 pandemic, accelerated the necessity for digital technology in education, transforming it from a supplementary tool to an essential platform for delivering education globally (Mo et al. 2022 ; Mustapha et al. 2021 ). This era brought about an unprecedented focus on online learning environments, distance education, and virtual classrooms. Research became more granular, examining not just the pedagogical effectiveness of digital tools, but also their role in maintaining continuity of education during crises, their impact on teacher and student well-being, and their implications for the future of educational policy and infrastructure.

Across these two decades, the research field has seen a shift from examining digital technology as an external addition to the educational process, to viewing it as an integral component of curriculum design, instructional strategies, and even assessment methods. The emergent themes have broadened from a narrow focus on specific tools or platforms to include wider considerations such as data privacy, ethical use of technology, and the environmental impact of digital tools.

Moreover, the field has moved from considering the application of digital technology in education as a primarily cognitive endeavor to recognizing its role in facilitating socio-emotional learning, digital citizenship, and global competencies. Researchers have increasingly turned their attention to the ways in which technology can support collaborative skills, cultural understanding, and ethical reasoning within diverse student populations.

In summary, the past over twenty years in the research field of digital technology applications in education have been characterized by a progression from foundational inquiries to complex analyses of digital integration. This evolution has mirrored the trajectory of technology itself, from a facilitative tool to a pervasive ecosystem defining contemporary educational experiences. As we look to the future, the field is poised to delve into the implications of emerging technologies like AI, AR, and VR, and their potential to redefine the educational landscape even further. This ongoing metamorphosis suggests that the application of digital technology in education will continue to be a rich area of inquiry, demanding continual adaptation and forward-thinking from educators and researchers alike.

Discussion on the study of research hotspots (RQ3)

The analysis of keyword evolution in digital technology education application research elucidates the current frontiers in the field, reflecting a trajectory that is in tandem with the rapidly advancing digital age. This landscape is sculpted by emergent technological innovations and shaped by the demands of an increasingly digital society.

Interdisciplinary integration and pedagogical transformation

One of the frontiers identified from recent keyword bursts includes the integration of digital technology into diverse educational contexts, particularly noted with the keyword “physical education.” The digitalization of disciplines traditionally characterized by physical presence illustrates the pervasive reach of technology and signifies a push towards interdisciplinary integration where technology is not only a facilitator but also a transformative agent. This integration challenges educators to reconceptualize curriculum delivery to accommodate digital tools that can enhance or simulate the physical aspects of learning.

Digital literacy and skills acquisition

Another pivotal frontier is the focus on “digital literacy” and “digital skill”, which has intensified in recent years. This suggests a shift from mere access to technology towards a comprehensive understanding and utilization of digital tools. In this realm, the emphasis is not only on the ability to use technology but also on critical thinking, problem-solving, and the ethical use of digital resources (Yu, 2022 ). The acquisition of digital literacy is no longer an additive skill but a fundamental aspect of modern education, essential for navigating and contributing to the digital world.

Educational digital transformation

The keyword “digital transformation” marks a significant research frontier, emphasizing the systemic changes that education institutions must undergo to align with the digital era (Romero et al. 2021 ). This transformation includes the redesigning of learning environments, pedagogical strategies, and assessment methods to harness digital technology’s full potential. Research in this area explores the complexity of institutional change, addressing the infrastructural, cultural, and policy adjustments needed for a seamless digital transition.

Engagement and participation

Further exploration into “engagement” and “participation” underscores the importance of student-centered learning environments that are mediated by technology. The current frontiers examine how digital platforms can foster collaboration, inclusivity, and active learning, potentially leading to more meaningful and personalized educational experiences. Here, the use of technology seeks to support the emotional and cognitive aspects of learning, moving beyond the transactional view of education to one that is relational and interactive.

Professional development and teacher readiness

As the field evolves, “professional development” emerges as a crucial area, particularly in light of the pandemic which necessitated emergency remote teaching. The need for teacher readiness in a digital age is a pressing frontier, with research focusing on the competencies required for educators to effectively integrate technology into their teaching practices. This includes familiarity with digital tools, pedagogical innovation, and an ongoing commitment to personal and professional growth in the digital domain.

Pandemic as a catalyst

The recent pandemic has acted as a catalyst for accelerated research and application in this field, particularly in the domains of “digital transformation,” “professional development,” and “physical education.” This period has been a litmus test for the resilience and adaptability of educational systems to continue their operations in an emergency. Research has thus been directed at understanding how digital technologies can support not only continuity but also enhance the quality and reach of education in such contexts.

Ethical and societal considerations

The frontier of digital technology in education is also expanding to consider broader ethical and societal implications. This includes issues of digital equity, data privacy, and the sociocultural impact of technology on learning communities. The research explores how educational technology can be leveraged to address inequities and create more equitable learning opportunities for all students, regardless of their socioeconomic background.

Innovation and emerging technologies

Looking forward, the frontiers are set to be influenced by ongoing and future technological innovations, such as artificial intelligence (AI) (Wu and Yu, 2023 ; Chen et al. 2022a ). The exploration into how these technologies can be integrated into educational practices to create immersive and adaptive learning experiences represents a bold new chapter for the field.

In conclusion, the current frontiers of research on the application of digital technology in education are multifaceted and dynamic. They reflect an overarching movement towards deeper integration of technology in educational systems and pedagogical practices, where the goals are not only to facilitate learning but to redefine it. As these frontiers continue to expand and evolve, they will shape the educational landscape, requiring a concerted effort from researchers, educators, policymakers, and technologists to navigate the challenges and harness the opportunities presented by the digital revolution in education.

Conclusions and future research

Conclusions.

The utilization of digital technology in education is a research area that cuts across multiple technical and educational domains and continues to experience dynamic growth due to the continuous progress of technology. In this study, a systematic review of this field was conducted through bibliometric techniques to examine its development trajectory. The primary focus of the review was to investigate the leading contributors, productive national institutions, significant publications, and evolving development patterns. The study’s quantitative analysis resulted in several key conclusions that shed light on this research field’s current state and future prospects.

(1) The research field of digital technology education applications has entered a stage of rapid development, particularly in recent years due to the impact of the pandemic, resulting in a peak of publications. Within this field, several key authors (Selwyn, Henderson, Edwards, etc.) and countries/regions (England, Australia, USA, etc.) have emerged, who have made significant contributions. International exchanges in this field have become frequent, with a high degree of internationalization in academic research. Higher education institutions in the UK and Australia are the core productive forces in this field at the institutional level.

(2) Education and Information Technologies , Computers & Education , and the British Journal of Educational Technology are notable journals that publish research related to digital technology education applications. These journals are affiliated with the research field of educational technology and provide effective communication platforms for sharing digital technology education applications.

(3) Over the past two decades, research on digital technology education applications has progressed from its early stages of budding, initial development, and critical exploration to accelerated transformation, and it is currently approaching maturity. Technological progress and changes in the times have been key driving forces for educational transformation and innovation, and both have played important roles in promoting the continuous development of education.

(4) Influenced by the pandemic, three emerging frontiers have emerged in current research on digital technology education applications, which are physical education, digital transformation, and professional development under the promotion of digital technology. These frontier research hotspots reflect the core issues that the education system faces when encountering new technologies. The evolution of research hotspots shows that technology breakthroughs in education’s original boundaries of time and space create new challenges. The continuous self-renewal of education is achieved by solving one hotspot problem after another.

The present study offers significant practical implications for scholars and practitioners in the field of digital technology education applications. Firstly, it presents a well-defined framework of the existing research in this area, serving as a comprehensive guide for new entrants to the field and shedding light on the developmental trajectory of this research domain. Secondly, the study identifies several contemporary research hotspots, thus offering a valuable decision-making resource for scholars aiming to explore potential research directions. Thirdly, the study undertakes an exhaustive analysis of published literature to identify core journals in the field of digital technology education applications, with Sustainability being identified as a promising open access journal that publishes extensively on this topic. This finding can potentially facilitate scholars in selecting appropriate journals for their research outputs.

Limitation and future research

Influenced by some objective factors, this study also has some limitations. First of all, the bibliometrics analysis software has high standards for data. In order to ensure the quality and integrity of the collected data, the research only selects the periodical papers in SCIE and SSCI indexes, which are the core collection of Web of Science database, and excludes other databases, conference papers, editorials and other publications, which may ignore some scientific research and original opinions in the field of digital technology education and application research. In addition, although this study used professional software to carry out bibliometric analysis and obtained more objective quantitative data, the analysis and interpretation of data will inevitably have a certain subjective color, and the influence of subjectivity on data analysis cannot be completely avoided. As such, future research endeavors will broaden the scope of literature screening and proactively engage scholars in the field to gain objective and state-of-the-art insights, while minimizing the adverse impact of personal subjectivity on research analysis.

Data availability

The datasets analyzed during the current study are available in the Dataverse repository: https://doi.org/10.7910/DVN/F9QMHY

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Acknowledgements

This research was supported by the Zhejiang Provincial Social Science Planning Project, “Mechanisms and Pathways for Empowering Classroom Teaching through Learning Spaces under the Strategy of High-Quality Education Development”, the 2022 National Social Science Foundation Education Youth Project “Research on the Strategy of Creating Learning Space Value and Empowering Classroom Teaching under the background of ‘Double Reduction’” (Grant No. CCA220319) and the National College Student Innovation and Entrepreneurship Training Program of China (Grant No. 202310337023).

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Wang, C., Chen, X., Yu, T. et al. Education reform and change driven by digital technology: a bibliometric study from a global perspective. Humanit Soc Sci Commun 11 , 256 (2024). https://doi.org/10.1057/s41599-024-02717-y

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Literature Review on the Impact of Digital Technology on Learning and Teaching

This literature review was commissioned by the Scottish Government to explore how the use of digital technology for learning and teaching can support teachers, parents, children and young people in improving outcomes and achieving our ambitions for education in Scotland

Digital learning and raising attainment

Key findings

There is conclusive evidence that digital equipment, tools and resources can, where effectively used, raise the speed and depth of learning in science and mathematics for primary and secondary age learners. There is indicative evidence that the same can be said for some aspects of literacy, especially writing and comprehension. Digital technologies appear to be appropriate means to improve basic literacy and numeracy skills, especially in primary settings.

The effect sizes are generally similar to other educational interventions that are effective in raising attainment, though the use of digital learning has other benefits. Also, the extent of the effect may be dampened by the level of capability of teachers to use digital learning tools and resources effectively to achieve learning outcomes. More effective use of digital teaching to raise attainment includes the ability of teachers to identify how digital tools and resources can be used to achieve learning outcomes and adapting their approach, as well as having knowledge and understanding of the technology. This applies in all schools.

Where learners use digital learning at home as well as school for formal and non-formal learning activities these have positive effects on their attainment, because they have extended their learning time. This is particularly important for secondary age learners.

The assessment framework, set out in Annex 2 , identifies a number of educational benefits that digital learning and teaching has the potential to help learners aged 5 to 18 to realise, through the opportunity to learn in different ways, access more sources of information, and be tested and get feedback differently. In terms of raising attainment, these benefits include short term outcomes, such as having a greater feeling of control over learning and more confidence to practise a skill, through to medium term outcomes such as faster acquisition of knowledge and skills, and improved impacts in terms of learners achieving higher exam or test results where digital technology has been used.

In this section, the impact of digital technology on children's attainment in a range of areas is discussed, followed by the impact on aspects of numeracy, literacy and science learning.

Raising children's attainment

There is a substantial body of research that has examined the impact of digital tools and resources on children's attainment in a range of areas.

Higgins et al (2012) provide a summary of research findings from studies with experimental and quasi-experimental designs, which have been combined in meta-analyses to assess the impact of digital learning in schools. Their search identified 48 studies which synthesised empirical research of the impact of digital tools and resources on the attainment of school age learners (5-18 year olds).

They found consistent but small positive associations between digital learning and educational outcomes. For example, Harrison et al (2004) identified statistically significant findings, positively associating higher levels of ICT use with school achievement at each Key Stage in England, and in English, maths, science, modern foreign languages and design technology. Somekh et al (2007) identified a link between high levels of ICT use and improved school performance. They found that the rate of improvement in tests in English at the end of primary education was faster in ICT Test Bed education authorities in England than in equivalent comparator areas. However, Higgins et al note that while these associations show, on average, schools with higher than average levels of ICT provision also have learners who perform slightly higher than average, it may be the case that high performing schools are more likely to be better equipped or more prepared to invest in technology or more motivated to bring about improvement.

Higgins et al report that in general analyses of the impact of digital technology on learning, the typical overall effect size is between 0.3 and 0.4 - just slightly below the overall average for researched interventions in education (Sipe & Curlette, 1997; Hattie, 2008) and no greater than other researched changes to teaching to raise attainment, such as peer tutoring or more focused feedback to learners. The range of effect sizes is also very wide (-0.03 to 1.05),which suggests that it is essential to take into account the differences between technologies and how they are used.

Table 4: Summary of meta-analyses published between 2000 and 2012 (in Higgins et al 2012)

In an earlier meta-analysis, Liao et al (2007), considered the effects of digital tools and resources on elementary school learners' achievement in Taiwan. Synthesizing research comparing the effects of digital learning (equipment, tools and resources) with traditional instruction on elementary school learners' achievement, they considered quantitative and qualitative information from 48 studies including over 5,000 learners. Of the 48 studies, 44 (92%) showed positive effects in favour of a computer assisted intervention, while four (8%) were negative and favoured a traditional instruction method. Nearly 60% of the studies examined the effects of computer aided instruction for teaching mathematics or science. Another 11% of the studies concentrated on the teaching of reading and language. They found an overall positive effect size across all the studies of 0.45 (study-weighted grand mean), which is considered to be a moderate effect, with a wide range of effect sizes (from 0.25 to 2.67).

No significant differences were found between subject areas, and the authors suggest that digital learning has the potential to be implemented in many different subject areas. They found that the two subjects that showed the highest effects were reading and languages, which had a high positive effect size of 0.7. Studies using computer simulations also had higher effects. The authors suggest this may be because simulations can provide learners with the opportunity to engage in a learning activity which could not be replicated in a classroom.

More qualitative studies have identified how improvements in attainment are achieved. From a wide study of primary and secondary schools in England that were early adopters in using digital learning and teaching, Jewitt et al (2011) concluded that:

• Using digital resources provided learners with more time for active learning in the classroom;
• Digital tools and resources provided more opportunity for active learning outside the classroom, as well as providing self-directed spaces, such as blogs and forums, and access to games with a learning benefit;
• Digital resources provided learners with opportunities to choose the learning resources;
• The resources provided safer spaces for formative assessment and feedback.

The sections below focus on specific key areas of attainment: literacy, numeracy, and science learning.

There is a large body of research that has examined the impact of digital equipment, tools and resources on children's literacy. The effects are generally positive, though not as large as the effects found where digital learning is used to improve numeracy, and consistent in finding that ICT helps improve reading and writing skills, as well as developing speaking and listening skills.

Effect of context

Archer and Savage (2014) undertook a meta-analysis to reassess the outcomes presented in three previous meta-analyses considering the impact of digital learning on language and literacy learning: Slavin et al (2008 and 2009) and Torgenson and Zhu (2003). Overall they found a relatively small average positive effect size of 0.18, with a few of the studies having a negative effect and three studies showing moderate to large effect sizes. The authors found that programmes with a small number of participants tended to show larger effect sizes than larger programmes but that not all were statistically significant.

Archer and Savage sought to understand whether the context within which the digital tool or resource was used has an impact on outcomes. In particular, they examined whether training and support given to the teachers or other staff delivering the programme had an impact. The authors found that training and support could be identified in around half of the studies and that it did appear to have a positive impact on the effectiveness of the literacy intervention, with the average effect size rising to 0.57. The authors conclude that this indicates the importance of including implementation factors, such as training and support, when considering the relative effectiveness of digital learning and teaching.

Effect on specific literacy skills

In their meta-analysis, Higgins et al (2012) found that digital learning has a greater impact on writing than on reading or spelling. For example, Torgenson and Zhu (2003) reviewed the impact of using digital technology on the literacy competences of 5-16 year-olds in English and found effect sizes on spelling (0.2) and reading (0.28) much lower than the high effect size for writing (0.89).

In their meta-analysis of studies investigating the effects of digital technology on primary schools in Taiwan, Laio et al (2007) considered studies over a range of curriculum areas; 11 of which addressed the effects of using digital learning in one or more literacy competence. They found no significant differences in effect size between the different subject areas, suggesting the potential for digital technology to raise outcomes is equal across different subjects. However, they did note that the two areas that showed the highest effect sizes (over 0.7) were reading and comprehension.

Effect of specific digital tools and resources

Somekh et al (2007) evaluated the Primary School Whiteboard Expansion ( PSWB ) project in England. They found that the length of time learners were taught with interactive whiteboards ( IWB s) was a major factor in learner attainment at the end of primary schooling, and that there were positive impacts on literacy (and numeracy) once teachers had experienced sustained use and the technology had become embedded in pedagogical practice. This equated to improvements at Key Stage 2 writing (age 11), where boys with low prior attainment made 2.5 months of additional progress.

Hess (2014) investigated the impact of using e-readers and e-books in the classroom, among 9-10 year olds in the USA . The e-books were used in daily teacher-led guided reading groups, replacing traditional print books in these sessions. Teachers also regularly used the e-readers in sessions where the class read aloud, and e-readers were available to learners during the school day for silent reading. The study found a significant difference in reading assessment scores for the group using the e-readers. Scores improved for both male and female learners and the gap between males and females decreased.

The use of digital tools and resources also appears to affect levels of literacy. Lysenko and Abrami (2014) investigated the use of two digital tools on reading comprehension for elementary school children (aged 6-8) in Quebec, Canada. The first was a multimedia tool which linked learning activities to interactive digital stories. The tool included games to engage learners in reading and writing activities, and instructions were provided orally to promote listening comprehension. The second tool was a web-based electronic portfolio in which learners could create a personalised portfolio of their reading and share work with peers, teachers and parents to get feedback. The authors found that in classes where both tools were used together during the whole school year learners performed significantly better both in vocabulary and reading comprehension (with medium-level effect sizes) than learners in classes where the tools were not part of English language instruction.

Rosen and Beck-Hill (2012) reported on a study programme that incorporated an interactive core curriculum and a digital teaching platform. At the time of their report it was available for 9-11 year old learners in English language, arts and mathematics classes in Dallas, Texas. The online platform contained teaching and learning tools. Learners were assessed using standardised tests administered before the programme and after a year's participation. The results of increased achievement scores demonstrated that in each of the two school year groups covered, the experimental learners significantly outperformed the control learners in reading and maths scores. In observations in classrooms that used the programme, the researchers observed higher teacher-learner interaction, a greater number and type of teaching methods per class, more frequent and complex examples of differentiation processes and skills, more frequent opportunities for learner collaboration, and significantly higher learner engagement. The authors report that the teaching pedagogy observed in the classrooms differed significantly from that observed in more traditional classrooms. The teachers following the programme commented that the digital resources made planning and implementing 'differentiation' more feasible. This is differentiation of teaching in terms of content, process, and product, to reflect learners' readiness, interests, and learning profile, through varied instructional and management strategies.

Effect of the amount and quality of digital technology use

The uses of digital technology and access to it appear to be critical factors. Lee et al (2009) analysed how in the US 15-16 year-old learners' school behaviour and standardised test scores in literacy are related to computer use. Learners were asked how many hours a day they typically used a computer for school work and for other activities. The results indicated that the learners who used the computer for one hour a day for both school work and other activities had significantly better reading test scores and more positive teacher evaluations for their classroom behaviours than any other groups [5] . This was found while controlling for socio-economic status, which has been shown to be a predictor of test scores in other research. The analysis used data from a national 2002 longitudinal study, and it is likely that learners' usage of computers has increased and changed since that time.

Biagi and Loi (2013), using data from the 2009 Programme for International Student Assessment ( PISA ) and information on how learners used digital technology at school and at home (both for school work and for entertainment), assessed the relationship between the intensity with which learners used digital tools and resources and literacy scores. They examined uses for: gaming activities (playing individual or collective online games), collaboration and communication activities (such as linking with others in on-line chat or discussion forums), information management and technical operations (such as searching for and downloading information) and creating content, knowledge and problem solving activities (such as using computers to do homework or running simulations at school). These were then compared to country specific test scores in reading. The authors found a positive and significant relationship between gaming activity and language attainment in 11 of the 23 countries studied. For the other measures, where relationships existed and were significant, they tended to be negative.

The more recent PISA data study ( OECD , 2015, using 2012 results) also found a positive relationship between the use of computers and better results in literacy where it is evident that digital technology is being used by learners to increase study time and practice [6] . In addition, it found that the effective use of digital tools is related to proficiency in reading.

There is a large body of research which has examined the impact of digital equipment, tools and resources on children's numeracy skills and mathematical competences throughout schooling. Higgins et al (2012) found from their meta-analysis that effect sizes of tested gains in knowledge and understanding tend to be greater in mathematics and science than in literacy. The key benefits found relate to problem solving skills, practising number skills and exploring patterns and relationships (Condie and Monroe, 2007), in addition to increased learner motivation and interest in mathematics.

Effect on specific numeracy skills

Li and Ma's (2010) meta-analysis of the impact of digital learning on school learners' mathematics learning found a generally positive effect. The authors considered 46 primary studies involving a total of over 36,000 learners in primary and secondary schools. About half of the mathematics achievement outcomes were measured by locally-developed or teacher-made instruments, and the other half by standardized tests. Almost all studies were well controlled, employing random assignment of learners to experimental or control conditions.

Overall, the authors found that, on average, there was a high, significantly positive effect of digital technology on mathematics achievement (mean effect size of 0.71), indicating that, in general, learners learning mathematics with the use of digital technology had higher mathematics achievement than those learning without digital technology. The authors found that:

• Although the difference was small, younger school learners (under 13 years old) had higher attainment gains than older secondary school learners;
• Gains were more positive where teaching was more learner-centred than teacher-centred. In this regard, the authors differentiate between traditional models, where the teacher tends to teach to the whole class, and a learner-centred teaching model which is discovery-based (inquiry-oriented) or problem-based (application-oriented) learning;
• Shorter interventions (six months or less) were found to be more effective in promoting mathematics achievement than longer interventions (between six and 12 months). It is suggested that such gains in mathematics achievement are a result of the novelty effects of technology, as suggested in other research, and as learners get familiar with the technology the novelty effects tend to decrease;
• The authors found no significant effects from different types of computer technology on mathematics achievement. Whether it was used as communication media, a tutorial device, or exploratory environment, learners displayed similar results in their mathematics achievement;
• Equally, the authors found no significant relationship between the effect of using digital technology and the characteristics of learners included in the samples for studies, such as gender, ethnicity, or socio-economic characteristics.

The studies by Lee et al (2009) and Biagi and Loi (2013) found similar results for mathematics as they did for reading and literacy in relation to the use of digital equipment. Learners who used a computer at least one hour a day for both school work and other activities had significantly better mathematics test scores and more positive teacher evaluations for their classroom behaviour in mathematics classes than those who did not use the computer. Biagi and Loi (2013) found a significant positive relationship between intensity of gaming activity and maths test scores in 15 countries out of the 23 studied. As with language, the authors found that learners' total use of digital technologies was positively and significantly associated with PISA test scores for maths in 18 of the 23 countries studied.

Studies have found that using digital equipment for formal learning is also associated with increases in learners' motivation for learning mathematics. House and Telese (2011 and 2012) found that:

• For learners aged 13 and 14 in South Korea, for example, those who expressed high levels of enjoyment at learning mathematics, more frequently used computers in their mathematics homework. However, learners who more frequently played computer games and used the internet outside of school tended to report that they did not enjoy learning mathematics;
• Learners in the USA and Japan aged 13 and 14 who showed higher levels of algebra achievement also used computers more at home and at school for school work. Those who used computers most for other activities had lower test scores. In each of the USA and Japan they found that overall computer usage which included use for school work was significantly related to improvements in test scores.

Somekh et al (2007) found that, once the use of IWB s was embedded, in Key Stage 1 mathematics (age 7) in England, high attaining girls made gains of 4.75 months, enabling them to catch up with high attaining boys. In Key Stage 2 mathematics (age 11), average and high attaining boys and girls who had been taught extensively with the IWB made the equivalent of an extra 2.5 to 5 months' progress over the course of two years.

Digital tools and resources can also increase some learners' confidence in mathematics as well as their engagement in new approaches to learning and their mathematical competences. Overcoming learners' anxieties about mathematics and their competence in specific aspects of the subject are common concerns in teaching mathematics which hampers their ability to learn (reported in Huang et al 2014).

Huang et al (2014) researched the outcomes, in Taiwan, from a computer game simulating the purchase of commodities, from which 7 and 8 year-old primary school learners can learn addition and subtraction, and apply mathematical concepts. The model combined games-based learning with a diagnosis system. When the learner made a mistake, the system could detect the type of mistake and present corresponding instructions to help the learner improve their mathematical comprehension and application. The authors compared two learning groups: both used the game-based model but one without the diagnostic, feedback element. They found that the learning achievement post-test showed a significant difference and also that the mathematics anxiety level of the two learner groups was decreased by about 3.5%.

Passey (2011) found that among over 300 schools in England using Espresso digital resources, those that had been using them over a longer period made significantly greater increases in end of primary school numeracy test results than schools which were recent users.

Science learning

Effects on science knowledge and skills

In their meta-analysis, Laio et al (2007) considered 11 studies looking at the impact of digital technology on science learning. These had a moderate average effect size of 0.38 and generally had positive effects. Condie and Monroe (2007) identified that digital learning made science more interesting, authentic and relevant for learners and provided more time for post-experiment analysis and discussion.

In their study of the PISA data, Biagi and Loi (2013) found a significant positive relationship between learners' total use of digital equipment and science test scores in 21 of the 23 countries they studied. They also found evidence of a significant positive relationship between the intensity of using gaming activity and science scores in 13 of the 23 countries they studied. Somekh et al (2007) found that in primary school science all learners, except high attaining girls, made greater progress when given more exposure to IWB s, with low attaining boys making as much as 7.5 months' additional progress.

Effects of specific digital tools and resources

Digital tools and resources generally have a positive effect on learners' science learning. This can be seen from a number of studies assessing outcomes for learners in different stages of education.

Hung et al (2012) explored the effect of using multi-media tools in science learning in an elementary school's science course in Taiwan. Learners were asked to complete a digital storytelling project by taking pictures with digital cameras, developing the story based on the pictures taken, producing a film based on the pictures by adding subtitles and a background, and presenting the story. From the experimental results, the authors found that this approach improved the learners' motivation to learn science, their attitude, problem-solving capability and learning achievements. In addition, interviews found that the learners in the experimental group enjoyed the project-based learning activity and thought it helpful because of the digital storytelling aspect.

Hsu et al (2012) investigated the effects of incorporating self-explanation principles into a digital tool facilitating learners' conceptual learning about light and shadow with 8-9 year old learners in Taiwan. While they found no difference in the overall test scores of the experimental and control groups, they found a statistically significant difference in retention test scores. Those learners who had paid more attention to the self-explanation prompts tended to outperform those in the control group.

Anderson and Barnett's (2013) study, in the US , examined how a digital game used by learners aged 12-13 increased their understanding of electromagnetic concepts, compared to learners who conducted a more traditional inquiry-based investigation of the same concepts. There was a significant difference between the control and experimental groups in gains in knowledge and understanding of physics concepts. Additionally, learners in the experimental group were able to give more nuanced responses about the descriptions of electric fields and the influence of distance on the forces that change experience because of what they learnt during the game.

Güven and Sülün (2012) considered the effects of computer-enhanced teaching in science and technology courses on the structure and properties of matter, such as the periodical table, chemical bonding, and chemical reactions, for 13-14 year olds in Turkey. Their proposition was that computer-enhanced teaching can instil a greater sense of interest in scientific and technological developments, make abstract concepts concrete through simulation and modelling, and help to carry out some dangerous experiments in the classroom setting. They found a significant difference in achievement tests between the mean scores of the group of learners who were taught with the computer-enhanced teaching method and the control group who were taught with traditional teaching methods.

Belland (2009) investigated the extent to which a digital tool improved US middle school children's ability to form scientific arguments. Taking the premise that being able to construct and test an evidence-based argument is critical to learning science, he studied the impact of using a digital problem based learning tool on 12-14 year olds. Learners worked in small groups and were asked to develop and present proposals for spending a grant to investigate an issue relating to the human genome project. Those in the experimental group used an online system which structured the project into stages of scientific enquiry. The system prompted the learners to structure and organise their thinking in particular ways: by prompting the learners individually, sharing group members' ideas, tasking the group to form a consensus view, and prompting the group to assign specific tasks among themselves.

Using pre- and post- test scores to assess the impact on learners' abilities to evaluate arguments, Belland found a high positive effect size of 0.62 for average-achieving learners compared to their peers in the control group. No significant impacts were found for higher or lower-achieving learners. Belland suggests that for high-achieving learners, this may be because they already have good argument making skills and are already able to successfully structure how they approach an issue and gather evidence. The study also used qualitative information to consider how the learners used the digital tool and compared this to how learners in the control group worked. The author found that in the experimental group they made more progress and were more able to divide tasks up between them, which saved time. They also used the tool more and the teacher less to provide support.

Kucukozer et al (2009) examined the impact of digital tools on teaching basic concepts of astronomy to 11-13 year old school children in Turkey. Learners were asked to make predictions about an astronomical phenomenon such as what causes the seasons or the phases of the moon. A digital tool was used to model the predictions and display their results. The learners were then asked to explain the differences and the similarities between their predictions and their observations. In the prediction and explanation phase the learners worked in groups to discuss their ideas and come to a conclusion. In the observation phase they watched the 3D models presented by their teacher. Thereafter, they were asked to discuss and make conclusions about what they had watched. The authors found that instruction supported by observations and the computer modelling was significantly effective in bringing about better conceptual understanding and learning on the subject.

Ingredients of success

Where studies examine the process that brings about positive results from digital learning and teaching compared to traditional approaches, it is evident that these are more likely to be achieved where digital equipment, tools and resources are used for specific learning outcomes and built into a teaching model from the outset. This broadly supports Higgins et al's (2012) conclusions that:

• Digital technology is best used as a supplement to normal teaching rather than as a replacement for it;
• It is not whether technology is used (or not) which makes the difference, but how well the technology is applied to support teaching and learning by teachers;
• More effective schools and teachers are more likely to use digital technologies effectively than other schools.

Differences in effect sizes and the extent that learners achieve positive gains in attainment are ascribed by most authors of the studies above to:

• The quality of teaching and the ability of teachers to use the digital equipment and tools effectively for lessons;
• The preparation and training teachers are given to use equipment and tools;
• The opportunities teachers have to see how digital resources can be used and pedagogies adapted (Rosen and Beck-Hill, 2012; Belland, 2009).

Teachers have to adapt to learner-centred approaches to learning if they are to use digital tools and resources (Li and Ma, 2010).

As well as ensuring digital tools and resources are supporting learning goals, success appears to also be linked to some other factors:

• The availability of equipment and tools within schools (and at home);
• How learners use digital equipment. Higgins et al (2012) found that collaborative use of technology (in pairs or small groups) is usually more effective than individual use, though some learners - especially younger children - may need guidance in how to collaborate effectively and responsibly;
• The extent that teaching continues to innovate using digital tools and resources (Higgins et al, 2012).

Fullan (2013) suggested four criteria that schools should meet if their use of digital technology to support increased attainment is to be successful. These were that systems should be engaging for learners and teachers; easy to adapt and use; ubiquitous - with access to the technology 24/7; and steeped in real life problem solving.

Fullan and Donnelly (2013) developed these themes further, proposing an evaluation tool to enable educators to systematically evaluate new companies, products and school models, using the context of what they have seen as necessary for success. Questions focus on the three key criteria of pedagogy (clarity and quality of intended outcome, quality of pedagogy and the relationship between teacher and learner, and quality of assessment platform and functioning); system change (implementation support, value for money, and whole system change potential) and technology (quality of user experience/model design, ease of adaptation, and comprehensiveness and integration).

Email: Catriona Rooke

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