how does collaborative learning enhances critical thinking

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Collaborative Learning Enhances Critical Thinking

The concept of collaborative learning, the grouping and pairing of students for the purpose of achieving an academic goal, has been widely researched and advocated throughout the professional literature. The term “collaborative learning” refers to an instruction method in which students at various performance levels work together in small groups toward a common goal. The students are responsible for one another’s learning as well as their own. Thus, the success of one student helps other students to be successful.

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• DOI: 10.21061/jte.v7i1.a.2
• Published on 22 Sep 1995
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• Published: 11 January 2023

The effectiveness of collaborative problem solving in promoting students’ critical thinking: A meta-analysis based on empirical literature

• Enwei Xu   ORCID: orcid.org/0000-0001-6424-8169 1 ,
• Wei Wang 1 &
• Qingxia Wang 1  

Humanities and Social Sciences Communications volume  10 , Article number:  16 ( 2023 ) Cite this article

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Collaborative problem-solving has been widely embraced in the classroom instruction of critical thinking, which is regarded as the core of curriculum reform based on key competencies in the field of education as well as a key competence for learners in the 21st century. However, the effectiveness of collaborative problem-solving in promoting students’ critical thinking remains uncertain. This current research presents the major findings of a meta-analysis of 36 pieces of the literature revealed in worldwide educational periodicals during the 21st century to identify the effectiveness of collaborative problem-solving in promoting students’ critical thinking and to determine, based on evidence, whether and to what extent collaborative problem solving can result in a rise or decrease in critical thinking. The findings show that (1) collaborative problem solving is an effective teaching approach to foster students’ critical thinking, with a significant overall effect size (ES = 0.82, z  = 12.78, P  < 0.01, 95% CI [0.69, 0.95]); (2) in respect to the dimensions of critical thinking, collaborative problem solving can significantly and successfully enhance students’ attitudinal tendencies (ES = 1.17, z  = 7.62, P  < 0.01, 95% CI[0.87, 1.47]); nevertheless, it falls short in terms of improving students’ cognitive skills, having only an upper-middle impact (ES = 0.70, z  = 11.55, P  < 0.01, 95% CI[0.58, 0.82]); and (3) the teaching type (chi 2  = 7.20, P  < 0.05), intervention duration (chi 2  = 12.18, P  < 0.01), subject area (chi 2  = 13.36, P  < 0.05), group size (chi 2  = 8.77, P  < 0.05), and learning scaffold (chi 2  = 9.03, P  < 0.01) all have an impact on critical thinking, and they can be viewed as important moderating factors that affect how critical thinking develops. On the basis of these results, recommendations are made for further study and instruction to better support students’ critical thinking in the context of collaborative problem-solving.

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Introduction.

Although critical thinking has a long history in research, the concept of critical thinking, which is regarded as an essential competence for learners in the 21st century, has recently attracted more attention from researchers and teaching practitioners (National Research Council, 2012 ). Critical thinking should be the core of curriculum reform based on key competencies in the field of education (Peng and Deng, 2017 ) because students with critical thinking can not only understand the meaning of knowledge but also effectively solve practical problems in real life even after knowledge is forgotten (Kek and Huijser, 2011 ). The definition of critical thinking is not universal (Ennis, 1989 ; Castle, 2009 ; Niu et al., 2013 ). In general, the definition of critical thinking is a self-aware and self-regulated thought process (Facione, 1990 ; Niu et al., 2013 ). It refers to the cognitive skills needed to interpret, analyze, synthesize, reason, and evaluate information as well as the attitudinal tendency to apply these abilities (Halpern, 2001 ). The view that critical thinking can be taught and learned through curriculum teaching has been widely supported by many researchers (e.g., Kuncel, 2011 ; Leng and Lu, 2020 ), leading to educators’ efforts to foster it among students. In the field of teaching practice, there are three types of courses for teaching critical thinking (Ennis, 1989 ). The first is an independent curriculum in which critical thinking is taught and cultivated without involving the knowledge of specific disciplines; the second is an integrated curriculum in which critical thinking is integrated into the teaching of other disciplines as a clear teaching goal; and the third is a mixed curriculum in which critical thinking is taught in parallel to the teaching of other disciplines for mixed teaching training. Furthermore, numerous measuring tools have been developed by researchers and educators to measure critical thinking in the context of teaching practice. These include standardized measurement tools, such as WGCTA, CCTST, CCTT, and CCTDI, which have been verified by repeated experiments and are considered effective and reliable by international scholars (Facione and Facione, 1992 ). In short, descriptions of critical thinking, including its two dimensions of attitudinal tendency and cognitive skills, different types of teaching courses, and standardized measurement tools provide a complex normative framework for understanding, teaching, and evaluating critical thinking.

Cultivating critical thinking in curriculum teaching can start with a problem, and one of the most popular critical thinking instructional approaches is problem-based learning (Liu et al., 2020 ). Duch et al. ( 2001 ) noted that problem-based learning in group collaboration is progressive active learning, which can improve students’ critical thinking and problem-solving skills. Collaborative problem-solving is the organic integration of collaborative learning and problem-based learning, which takes learners as the center of the learning process and uses problems with poor structure in real-world situations as the starting point for the learning process (Liang et al., 2017 ). Students learn the knowledge needed to solve problems in a collaborative group, reach a consensus on problems in the field, and form solutions through social cooperation methods, such as dialogue, interpretation, questioning, debate, negotiation, and reflection, thus promoting the development of learners’ domain knowledge and critical thinking (Cindy, 2004 ; Liang et al., 2017 ).

Collaborative problem-solving has been widely used in the teaching practice of critical thinking, and several studies have attempted to conduct a systematic review and meta-analysis of the empirical literature on critical thinking from various perspectives. However, little attention has been paid to the impact of collaborative problem-solving on critical thinking. Therefore, the best approach for developing and enhancing critical thinking throughout collaborative problem-solving is to examine how to implement critical thinking instruction; however, this issue is still unexplored, which means that many teachers are incapable of better instructing critical thinking (Leng and Lu, 2020 ; Niu et al., 2013 ). For example, Huber ( 2016 ) provided the meta-analysis findings of 71 publications on gaining critical thinking over various time frames in college with the aim of determining whether critical thinking was truly teachable. These authors found that learners significantly improve their critical thinking while in college and that critical thinking differs with factors such as teaching strategies, intervention duration, subject area, and teaching type. The usefulness of collaborative problem-solving in fostering students’ critical thinking, however, was not determined by this study, nor did it reveal whether there existed significant variations among the different elements. A meta-analysis of 31 pieces of educational literature was conducted by Liu et al. ( 2020 ) to assess the impact of problem-solving on college students’ critical thinking. These authors found that problem-solving could promote the development of critical thinking among college students and proposed establishing a reasonable group structure for problem-solving in a follow-up study to improve students’ critical thinking. Additionally, previous empirical studies have reached inconclusive and even contradictory conclusions about whether and to what extent collaborative problem-solving increases or decreases critical thinking levels. As an illustration, Yang et al. ( 2008 ) carried out an experiment on the integrated curriculum teaching of college students based on a web bulletin board with the goal of fostering participants’ critical thinking in the context of collaborative problem-solving. These authors’ research revealed that through sharing, debating, examining, and reflecting on various experiences and ideas, collaborative problem-solving can considerably enhance students’ critical thinking in real-life problem situations. In contrast, collaborative problem-solving had a positive impact on learners’ interaction and could improve learning interest and motivation but could not significantly improve students’ critical thinking when compared to traditional classroom teaching, according to research by Naber and Wyatt ( 2014 ) and Sendag and Odabasi ( 2009 ) on undergraduate and high school students, respectively.

The above studies show that there is inconsistency regarding the effectiveness of collaborative problem-solving in promoting students’ critical thinking. Therefore, it is essential to conduct a thorough and trustworthy review to detect and decide whether and to what degree collaborative problem-solving can result in a rise or decrease in critical thinking. Meta-analysis is a quantitative analysis approach that is utilized to examine quantitative data from various separate studies that are all focused on the same research topic. This approach characterizes the effectiveness of its impact by averaging the effect sizes of numerous qualitative studies in an effort to reduce the uncertainty brought on by independent research and produce more conclusive findings (Lipsey and Wilson, 2001 ).

This paper used a meta-analytic approach and carried out a meta-analysis to examine the effectiveness of collaborative problem-solving in promoting students’ critical thinking in order to make a contribution to both research and practice. The following research questions were addressed by this meta-analysis:

What is the overall effect size of collaborative problem-solving in promoting students’ critical thinking and its impact on the two dimensions of critical thinking (i.e., attitudinal tendency and cognitive skills)?

How are the disparities between the study conclusions impacted by various moderating variables if the impacts of various experimental designs in the included studies are heterogeneous?

This research followed the strict procedures (e.g., database searching, identification, screening, eligibility, merging, duplicate removal, and analysis of included studies) of Cooper’s ( 2010 ) proposed meta-analysis approach for examining quantitative data from various separate studies that are all focused on the same research topic. The relevant empirical research that appeared in worldwide educational periodicals within the 21st century was subjected to this meta-analysis using Rev-Man 5.4. The consistency of the data extracted separately by two researchers was tested using Cohen’s kappa coefficient, and a publication bias test and a heterogeneity test were run on the sample data to ascertain the quality of this meta-analysis.

Data sources and search strategies

There were three stages to the data collection process for this meta-analysis, as shown in Fig. 1 , which shows the number of articles included and eliminated during the selection process based on the statement and study eligibility criteria.

This flowchart shows the number of records identified, included and excluded in the article.

First, the databases used to systematically search for relevant articles were the journal papers of the Web of Science Core Collection and the Chinese Core source journal, as well as the Chinese Social Science Citation Index (CSSCI) source journal papers included in CNKI. These databases were selected because they are credible platforms that are sources of scholarly and peer-reviewed information with advanced search tools and contain literature relevant to the subject of our topic from reliable researchers and experts. The search string with the Boolean operator used in the Web of Science was “TS = (((“critical thinking” or “ct” and “pretest” or “posttest”) or (“critical thinking” or “ct” and “control group” or “quasi experiment” or “experiment”)) and (“collaboration” or “collaborative learning” or “CSCL”) and (“problem solving” or “problem-based learning” or “PBL”))”. The research area was “Education Educational Research”, and the search period was “January 1, 2000, to December 30, 2021”. A total of 412 papers were obtained. The search string with the Boolean operator used in the CNKI was “SU = (‘critical thinking’*‘collaboration’ + ‘critical thinking’*‘collaborative learning’ + ‘critical thinking’*‘CSCL’ + ‘critical thinking’*‘problem solving’ + ‘critical thinking’*‘problem-based learning’ + ‘critical thinking’*‘PBL’ + ‘critical thinking’*‘problem oriented’) AND FT = (‘experiment’ + ‘quasi experiment’ + ‘pretest’ + ‘posttest’ + ‘empirical study’)” (translated into Chinese when searching). A total of 56 studies were found throughout the search period of “January 2000 to December 2021”. From the databases, all duplicates and retractions were eliminated before exporting the references into Endnote, a program for managing bibliographic references. In all, 466 studies were found.

Second, the studies that matched the inclusion and exclusion criteria for the meta-analysis were chosen by two researchers after they had reviewed the abstracts and titles of the gathered articles, yielding a total of 126 studies.

Third, two researchers thoroughly reviewed each included article’s whole text in accordance with the inclusion and exclusion criteria. Meanwhile, a snowball search was performed using the references and citations of the included articles to ensure complete coverage of the articles. Ultimately, 36 articles were kept.

Two researchers worked together to carry out this entire process, and a consensus rate of almost 94.7% was reached after discussion and negotiation to clarify any emerging differences.

Eligibility criteria

Since not all the retrieved studies matched the criteria for this meta-analysis, eligibility criteria for both inclusion and exclusion were developed as follows:

The publication language of the included studies was limited to English and Chinese, and the full text could be obtained. Articles that did not meet the publication language and articles not published between 2000 and 2021 were excluded.

The research design of the included studies must be empirical and quantitative studies that can assess the effect of collaborative problem-solving on the development of critical thinking. Articles that could not identify the causal mechanisms by which collaborative problem-solving affects critical thinking, such as review articles and theoretical articles, were excluded.

The research method of the included studies must feature a randomized control experiment or a quasi-experiment, or a natural experiment, which have a higher degree of internal validity with strong experimental designs and can all plausibly provide evidence that critical thinking and collaborative problem-solving are causally related. Articles with non-experimental research methods, such as purely correlational or observational studies, were excluded.

The participants of the included studies were only students in school, including K-12 students and college students. Articles in which the participants were non-school students, such as social workers or adult learners, were excluded.

The research results of the included studies must mention definite signs that may be utilized to gauge critical thinking’s impact (e.g., sample size, mean value, or standard deviation). Articles that lacked specific measurement indicators for critical thinking and could not calculate the effect size were excluded.

Data coding design

In order to perform a meta-analysis, it is necessary to collect the most important information from the articles, codify that information’s properties, and convert descriptive data into quantitative data. Therefore, this study designed a data coding template (see Table 1 ). Ultimately, 16 coding fields were retained.

The designed data-coding template consisted of three pieces of information. Basic information about the papers was included in the descriptive information: the publishing year, author, serial number, and title of the paper.

The variable information for the experimental design had three variables: the independent variable (instruction method), the dependent variable (critical thinking), and the moderating variable (learning stage, teaching type, intervention duration, learning scaffold, group size, measuring tool, and subject area). Depending on the topic of this study, the intervention strategy, as the independent variable, was coded into collaborative and non-collaborative problem-solving. The dependent variable, critical thinking, was coded as a cognitive skill and an attitudinal tendency. And seven moderating variables were created by grouping and combining the experimental design variables discovered within the 36 studies (see Table 1 ), where learning stages were encoded as higher education, high school, middle school, and primary school or lower; teaching types were encoded as mixed courses, integrated courses, and independent courses; intervention durations were encoded as 0–1 weeks, 1–4 weeks, 4–12 weeks, and more than 12 weeks; group sizes were encoded as 2–3 persons, 4–6 persons, 7–10 persons, and more than 10 persons; learning scaffolds were encoded as teacher-supported learning scaffold, technique-supported learning scaffold, and resource-supported learning scaffold; measuring tools were encoded as standardized measurement tools (e.g., WGCTA, CCTT, CCTST, and CCTDI) and self-adapting measurement tools (e.g., modified or made by researchers); and subject areas were encoded according to the specific subjects used in the 36 included studies.

The data information contained three metrics for measuring critical thinking: sample size, average value, and standard deviation. It is vital to remember that studies with various experimental designs frequently adopt various formulas to determine the effect size. And this paper used Morris’ proposed standardized mean difference (SMD) calculation formula ( 2008 , p. 369; see Supplementary Table S3 ).

Procedure for extracting and coding data

According to the data coding template (see Table 1 ), the 36 papers’ information was retrieved by two researchers, who then entered them into Excel (see Supplementary Table S1 ). The results of each study were extracted separately in the data extraction procedure if an article contained numerous studies on critical thinking, or if a study assessed different critical thinking dimensions. For instance, Tiwari et al. ( 2010 ) used four time points, which were viewed as numerous different studies, to examine the outcomes of critical thinking, and Chen ( 2013 ) included the two outcome variables of attitudinal tendency and cognitive skills, which were regarded as two studies. After discussion and negotiation during data extraction, the two researchers’ consistency test coefficients were roughly 93.27%. Supplementary Table S2 details the key characteristics of the 36 included articles with 79 effect quantities, including descriptive information (e.g., the publishing year, author, serial number, and title of the paper), variable information (e.g., independent variables, dependent variables, and moderating variables), and data information (e.g., mean values, standard deviations, and sample size). Following that, testing for publication bias and heterogeneity was done on the sample data using the Rev-Man 5.4 software, and then the test results were used to conduct a meta-analysis.

Publication bias test

When the sample of studies included in a meta-analysis does not accurately reflect the general status of research on the relevant subject, publication bias is said to be exhibited in this research. The reliability and accuracy of the meta-analysis may be impacted by publication bias. Due to this, the meta-analysis needs to check the sample data for publication bias (Stewart et al., 2006 ). A popular method to check for publication bias is the funnel plot; and it is unlikely that there will be publishing bias when the data are equally dispersed on either side of the average effect size and targeted within the higher region. The data are equally dispersed within the higher portion of the efficient zone, consistent with the funnel plot connected with this analysis (see Fig. 2 ), indicating that publication bias is unlikely in this situation.

This funnel plot shows the result of publication bias of 79 effect quantities across 36 studies.

Heterogeneity test

To select the appropriate effect models for the meta-analysis, one might use the results of a heterogeneity test on the data effect sizes. In a meta-analysis, it is common practice to gauge the degree of data heterogeneity using the I 2 value, and I 2  ≥ 50% is typically understood to denote medium-high heterogeneity, which calls for the adoption of a random effect model; if not, a fixed effect model ought to be applied (Lipsey and Wilson, 2001 ). The findings of the heterogeneity test in this paper (see Table 2 ) revealed that I 2 was 86% and displayed significant heterogeneity ( P  < 0.01). To ensure accuracy and reliability, the overall effect size ought to be calculated utilizing the random effect model.

The analysis of the overall effect size

This meta-analysis utilized a random effect model to examine 79 effect quantities from 36 studies after eliminating heterogeneity. In accordance with Cohen’s criterion (Cohen, 1992 ), it is abundantly clear from the analysis results, which are shown in the forest plot of the overall effect (see Fig. 3 ), that the cumulative impact size of cooperative problem-solving is 0.82, which is statistically significant ( z  = 12.78, P  < 0.01, 95% CI [0.69, 0.95]), and can encourage learners to practice critical thinking.

This forest plot shows the analysis result of the overall effect size across 36 studies.

In addition, this study examined two distinct dimensions of critical thinking to better understand the precise contributions that collaborative problem-solving makes to the growth of critical thinking. The findings (see Table 3 ) indicate that collaborative problem-solving improves cognitive skills (ES = 0.70) and attitudinal tendency (ES = 1.17), with significant intergroup differences (chi 2  = 7.95, P  < 0.01). Although collaborative problem-solving improves both dimensions of critical thinking, it is essential to point out that the improvements in students’ attitudinal tendency are much more pronounced and have a significant comprehensive effect (ES = 1.17, z  = 7.62, P  < 0.01, 95% CI [0.87, 1.47]), whereas gains in learners’ cognitive skill are slightly improved and are just above average. (ES = 0.70, z  = 11.55, P  < 0.01, 95% CI [0.58, 0.82]).

The analysis of moderator effect size

The whole forest plot’s 79 effect quantities underwent a two-tailed test, which revealed significant heterogeneity ( I 2  = 86%, z  = 12.78, P  < 0.01), indicating differences between various effect sizes that may have been influenced by moderating factors other than sampling error. Therefore, exploring possible moderating factors that might produce considerable heterogeneity was done using subgroup analysis, such as the learning stage, learning scaffold, teaching type, group size, duration of the intervention, measuring tool, and the subject area included in the 36 experimental designs, in order to further explore the key factors that influence critical thinking. The findings (see Table 4 ) indicate that various moderating factors have advantageous effects on critical thinking. In this situation, the subject area (chi 2  = 13.36, P  < 0.05), group size (chi 2  = 8.77, P  < 0.05), intervention duration (chi 2  = 12.18, P  < 0.01), learning scaffold (chi 2  = 9.03, P  < 0.01), and teaching type (chi 2  = 7.20, P  < 0.05) are all significant moderators that can be applied to support the cultivation of critical thinking. However, since the learning stage and the measuring tools did not significantly differ among intergroup (chi 2  = 3.15, P  = 0.21 > 0.05, and chi 2  = 0.08, P  = 0.78 > 0.05), we are unable to explain why these two factors are crucial in supporting the cultivation of critical thinking in the context of collaborative problem-solving. These are the precise outcomes, as follows:

Various learning stages influenced critical thinking positively, without significant intergroup differences (chi 2  = 3.15, P  = 0.21 > 0.05). High school was first on the list of effect sizes (ES = 1.36, P  < 0.01), then higher education (ES = 0.78, P  < 0.01), and middle school (ES = 0.73, P  < 0.01). These results show that, despite the learning stage’s beneficial influence on cultivating learners’ critical thinking, we are unable to explain why it is essential for cultivating critical thinking in the context of collaborative problem-solving.

Different teaching types had varying degrees of positive impact on critical thinking, with significant intergroup differences (chi 2  = 7.20, P  < 0.05). The effect size was ranked as follows: mixed courses (ES = 1.34, P  < 0.01), integrated courses (ES = 0.81, P  < 0.01), and independent courses (ES = 0.27, P  < 0.01). These results indicate that the most effective approach to cultivate critical thinking utilizing collaborative problem solving is through the teaching type of mixed courses.

Various intervention durations significantly improved critical thinking, and there were significant intergroup differences (chi 2  = 12.18, P  < 0.01). The effect sizes related to this variable showed a tendency to increase with longer intervention durations. The improvement in critical thinking reached a significant level (ES = 0.85, P  < 0.01) after more than 12 weeks of training. These findings indicate that the intervention duration and critical thinking’s impact are positively correlated, with a longer intervention duration having a greater effect.

Different learning scaffolds influenced critical thinking positively, with significant intergroup differences (chi 2  = 9.03, P  < 0.01). The resource-supported learning scaffold (ES = 0.69, P  < 0.01) acquired a medium-to-higher level of impact, the technique-supported learning scaffold (ES = 0.63, P  < 0.01) also attained a medium-to-higher level of impact, and the teacher-supported learning scaffold (ES = 0.92, P  < 0.01) displayed a high level of significant impact. These results show that the learning scaffold with teacher support has the greatest impact on cultivating critical thinking.

Various group sizes influenced critical thinking positively, and the intergroup differences were statistically significant (chi 2  = 8.77, P  < 0.05). Critical thinking showed a general declining trend with increasing group size. The overall effect size of 2–3 people in this situation was the biggest (ES = 0.99, P  < 0.01), and when the group size was greater than 7 people, the improvement in critical thinking was at the lower-middle level (ES < 0.5, P  < 0.01). These results show that the impact on critical thinking is positively connected with group size, and as group size grows, so does the overall impact.

Various measuring tools influenced critical thinking positively, with significant intergroup differences (chi 2  = 0.08, P  = 0.78 > 0.05). In this situation, the self-adapting measurement tools obtained an upper-medium level of effect (ES = 0.78), whereas the complete effect size of the standardized measurement tools was the largest, achieving a significant level of effect (ES = 0.84, P  < 0.01). These results show that, despite the beneficial influence of the measuring tool on cultivating critical thinking, we are unable to explain why it is crucial in fostering the growth of critical thinking by utilizing the approach of collaborative problem-solving.

Different subject areas had a greater impact on critical thinking, and the intergroup differences were statistically significant (chi 2  = 13.36, P  < 0.05). Mathematics had the greatest overall impact, achieving a significant level of effect (ES = 1.68, P  < 0.01), followed by science (ES = 1.25, P  < 0.01) and medical science (ES = 0.87, P  < 0.01), both of which also achieved a significant level of effect. Programming technology was the least effective (ES = 0.39, P  < 0.01), only having a medium-low degree of effect compared to education (ES = 0.72, P  < 0.01) and other fields (such as language, art, and social sciences) (ES = 0.58, P  < 0.01). These results suggest that scientific fields (e.g., mathematics, science) may be the most effective subject areas for cultivating critical thinking utilizing the approach of collaborative problem-solving.

The effectiveness of collaborative problem solving with regard to teaching critical thinking

According to this meta-analysis, using collaborative problem-solving as an intervention strategy in critical thinking teaching has a considerable amount of impact on cultivating learners’ critical thinking as a whole and has a favorable promotional effect on the two dimensions of critical thinking. According to certain studies, collaborative problem solving, the most frequently used critical thinking teaching strategy in curriculum instruction can considerably enhance students’ critical thinking (e.g., Liang et al., 2017 ; Liu et al., 2020 ; Cindy, 2004 ). This meta-analysis provides convergent data support for the above research views. Thus, the findings of this meta-analysis not only effectively address the first research query regarding the overall effect of cultivating critical thinking and its impact on the two dimensions of critical thinking (i.e., attitudinal tendency and cognitive skills) utilizing the approach of collaborative problem-solving, but also enhance our confidence in cultivating critical thinking by using collaborative problem-solving intervention approach in the context of classroom teaching.

Furthermore, the associated improvements in attitudinal tendency are much stronger, but the corresponding improvements in cognitive skill are only marginally better. According to certain studies, cognitive skill differs from the attitudinal tendency in classroom instruction; the cultivation and development of the former as a key ability is a process of gradual accumulation, while the latter as an attitude is affected by the context of the teaching situation (e.g., a novel and exciting teaching approach, challenging and rewarding tasks) (Halpern, 2001 ; Wei and Hong, 2022 ). Collaborative problem-solving as a teaching approach is exciting and interesting, as well as rewarding and challenging; because it takes the learners as the focus and examines problems with poor structure in real situations, and it can inspire students to fully realize their potential for problem-solving, which will significantly improve their attitudinal tendency toward solving problems (Liu et al., 2020 ). Similar to how collaborative problem-solving influences attitudinal tendency, attitudinal tendency impacts cognitive skill when attempting to solve a problem (Liu et al., 2020 ; Zhang et al., 2022 ), and stronger attitudinal tendencies are associated with improved learning achievement and cognitive ability in students (Sison, 2008 ; Zhang et al., 2022 ). It can be seen that the two specific dimensions of critical thinking as well as critical thinking as a whole are affected by collaborative problem-solving, and this study illuminates the nuanced links between cognitive skills and attitudinal tendencies with regard to these two dimensions of critical thinking. To fully develop students’ capacity for critical thinking, future empirical research should pay closer attention to cognitive skills.

The moderating effects of collaborative problem solving with regard to teaching critical thinking

In order to further explore the key factors that influence critical thinking, exploring possible moderating effects that might produce considerable heterogeneity was done using subgroup analysis. The findings show that the moderating factors, such as the teaching type, learning stage, group size, learning scaffold, duration of the intervention, measuring tool, and the subject area included in the 36 experimental designs, could all support the cultivation of collaborative problem-solving in critical thinking. Among them, the effect size differences between the learning stage and measuring tool are not significant, which does not explain why these two factors are crucial in supporting the cultivation of critical thinking utilizing the approach of collaborative problem-solving.

In terms of the learning stage, various learning stages influenced critical thinking positively without significant intergroup differences, indicating that we are unable to explain why it is crucial in fostering the growth of critical thinking.

Although high education accounts for 70.89% of all empirical studies performed by researchers, high school may be the appropriate learning stage to foster students’ critical thinking by utilizing the approach of collaborative problem-solving since it has the largest overall effect size. This phenomenon may be related to student’s cognitive development, which needs to be further studied in follow-up research.

With regard to teaching type, mixed course teaching may be the best teaching method to cultivate students’ critical thinking. Relevant studies have shown that in the actual teaching process if students are trained in thinking methods alone, the methods they learn are isolated and divorced from subject knowledge, which is not conducive to their transfer of thinking methods; therefore, if students’ thinking is trained only in subject teaching without systematic method training, it is challenging to apply to real-world circumstances (Ruggiero, 2012 ; Hu and Liu, 2015 ). Teaching critical thinking as mixed course teaching in parallel to other subject teachings can achieve the best effect on learners’ critical thinking, and explicit critical thinking instruction is more effective than less explicit critical thinking instruction (Bensley and Spero, 2014 ).

In terms of the intervention duration, with longer intervention times, the overall effect size shows an upward tendency. Thus, the intervention duration and critical thinking’s impact are positively correlated. Critical thinking, as a key competency for students in the 21st century, is difficult to get a meaningful improvement in a brief intervention duration. Instead, it could be developed over a lengthy period of time through consistent teaching and the progressive accumulation of knowledge (Halpern, 2001 ; Hu and Liu, 2015 ). Therefore, future empirical studies ought to take these restrictions into account throughout a longer period of critical thinking instruction.

With regard to group size, a group size of 2–3 persons has the highest effect size, and the comprehensive effect size decreases with increasing group size in general. This outcome is in line with some research findings; as an example, a group composed of two to four members is most appropriate for collaborative learning (Schellens and Valcke, 2006 ). However, the meta-analysis results also indicate that once the group size exceeds 7 people, small groups cannot produce better interaction and performance than large groups. This may be because the learning scaffolds of technique support, resource support, and teacher support improve the frequency and effectiveness of interaction among group members, and a collaborative group with more members may increase the diversity of views, which is helpful to cultivate critical thinking utilizing the approach of collaborative problem-solving.

With regard to the learning scaffold, the three different kinds of learning scaffolds can all enhance critical thinking. Among them, the teacher-supported learning scaffold has the largest overall effect size, demonstrating the interdependence of effective learning scaffolds and collaborative problem-solving. This outcome is in line with some research findings; as an example, a successful strategy is to encourage learners to collaborate, come up with solutions, and develop critical thinking skills by using learning scaffolds (Reiser, 2004 ; Xu et al., 2022 ); learning scaffolds can lower task complexity and unpleasant feelings while also enticing students to engage in learning activities (Wood et al., 2006 ); learning scaffolds are designed to assist students in using learning approaches more successfully to adapt the collaborative problem-solving process, and the teacher-supported learning scaffolds have the greatest influence on critical thinking in this process because they are more targeted, informative, and timely (Xu et al., 2022 ).

With respect to the measuring tool, despite the fact that standardized measurement tools (such as the WGCTA, CCTT, and CCTST) have been acknowledged as trustworthy and effective by worldwide experts, only 54.43% of the research included in this meta-analysis adopted them for assessment, and the results indicated no intergroup differences. These results suggest that not all teaching circumstances are appropriate for measuring critical thinking using standardized measurement tools. “The measuring tools for measuring thinking ability have limits in assessing learners in educational situations and should be adapted appropriately to accurately assess the changes in learners’ critical thinking.”, according to Simpson and Courtney ( 2002 , p. 91). As a result, in order to more fully and precisely gauge how learners’ critical thinking has evolved, we must properly modify standardized measuring tools based on collaborative problem-solving learning contexts.

With regard to the subject area, the comprehensive effect size of science departments (e.g., mathematics, science, medical science) is larger than that of language arts and social sciences. Some recent international education reforms have noted that critical thinking is a basic part of scientific literacy. Students with scientific literacy can prove the rationality of their judgment according to accurate evidence and reasonable standards when they face challenges or poorly structured problems (Kyndt et al., 2013 ), which makes critical thinking crucial for developing scientific understanding and applying this understanding to practical problem solving for problems related to science, technology, and society (Yore et al., 2007 ).

Suggestions for critical thinking teaching

Other than those stated in the discussion above, the following suggestions are offered for critical thinking instruction utilizing the approach of collaborative problem-solving.

First, teachers should put a special emphasis on the two core elements, which are collaboration and problem-solving, to design real problems based on collaborative situations. This meta-analysis provides evidence to support the view that collaborative problem-solving has a strong synergistic effect on promoting students’ critical thinking. Asking questions about real situations and allowing learners to take part in critical discussions on real problems during class instruction are key ways to teach critical thinking rather than simply reading speculative articles without practice (Mulnix, 2012 ). Furthermore, the improvement of students’ critical thinking is realized through cognitive conflict with other learners in the problem situation (Yang et al., 2008 ). Consequently, it is essential for teachers to put a special emphasis on the two core elements, which are collaboration and problem-solving, and design real problems and encourage students to discuss, negotiate, and argue based on collaborative problem-solving situations.

Second, teachers should design and implement mixed courses to cultivate learners’ critical thinking, utilizing the approach of collaborative problem-solving. Critical thinking can be taught through curriculum instruction (Kuncel, 2011 ; Leng and Lu, 2020 ), with the goal of cultivating learners’ critical thinking for flexible transfer and application in real problem-solving situations. This meta-analysis shows that mixed course teaching has a highly substantial impact on the cultivation and promotion of learners’ critical thinking. Therefore, teachers should design and implement mixed course teaching with real collaborative problem-solving situations in combination with the knowledge content of specific disciplines in conventional teaching, teach methods and strategies of critical thinking based on poorly structured problems to help students master critical thinking, and provide practical activities in which students can interact with each other to develop knowledge construction and critical thinking utilizing the approach of collaborative problem-solving.

Third, teachers should be more trained in critical thinking, particularly preservice teachers, and they also should be conscious of the ways in which teachers’ support for learning scaffolds can promote critical thinking. The learning scaffold supported by teachers had the greatest impact on learners’ critical thinking, in addition to being more directive, targeted, and timely (Wood et al., 2006 ). Critical thinking can only be effectively taught when teachers recognize the significance of critical thinking for students’ growth and use the proper approaches while designing instructional activities (Forawi, 2016 ). Therefore, with the intention of enabling teachers to create learning scaffolds to cultivate learners’ critical thinking utilizing the approach of collaborative problem solving, it is essential to concentrate on the teacher-supported learning scaffolds and enhance the instruction for teaching critical thinking to teachers, especially preservice teachers.

Implications and limitations

There are certain limitations in this meta-analysis, but future research can correct them. First, the search languages were restricted to English and Chinese, so it is possible that pertinent studies that were written in other languages were overlooked, resulting in an inadequate number of articles for review. Second, these data provided by the included studies are partially missing, such as whether teachers were trained in the theory and practice of critical thinking, the average age and gender of learners, and the differences in critical thinking among learners of various ages and genders. Third, as is typical for review articles, more studies were released while this meta-analysis was being done; therefore, it had a time limit. With the development of relevant research, future studies focusing on these issues are highly relevant and needed.

Conclusions

The subject of the magnitude of collaborative problem-solving’s impact on fostering students’ critical thinking, which received scant attention from other studies, was successfully addressed by this study. The question of the effectiveness of collaborative problem-solving in promoting students’ critical thinking was addressed in this study, which addressed a topic that had gotten little attention in earlier research. The following conclusions can be made:

Regarding the results obtained, collaborative problem solving is an effective teaching approach to foster learners’ critical thinking, with a significant overall effect size (ES = 0.82, z  = 12.78, P  < 0.01, 95% CI [0.69, 0.95]). With respect to the dimensions of critical thinking, collaborative problem-solving can significantly and effectively improve students’ attitudinal tendency, and the comprehensive effect is significant (ES = 1.17, z  = 7.62, P  < 0.01, 95% CI [0.87, 1.47]); nevertheless, it falls short in terms of improving students’ cognitive skills, having only an upper-middle impact (ES = 0.70, z  = 11.55, P  < 0.01, 95% CI [0.58, 0.82]).

As demonstrated by both the results and the discussion, there are varying degrees of beneficial effects on students’ critical thinking from all seven moderating factors, which were found across 36 studies. In this context, the teaching type (chi 2  = 7.20, P  < 0.05), intervention duration (chi 2  = 12.18, P  < 0.01), subject area (chi 2  = 13.36, P  < 0.05), group size (chi 2  = 8.77, P  < 0.05), and learning scaffold (chi 2  = 9.03, P  < 0.01) all have a positive impact on critical thinking, and they can be viewed as important moderating factors that affect how critical thinking develops. Since the learning stage (chi 2  = 3.15, P  = 0.21 > 0.05) and measuring tools (chi 2  = 0.08, P  = 0.78 > 0.05) did not demonstrate any significant intergroup differences, we are unable to explain why these two factors are crucial in supporting the cultivation of critical thinking in the context of collaborative problem-solving.

Data availability

All data generated or analyzed during this study are included within the article and its supplementary information files, and the supplementary information files are available in the Dataverse repository: https://doi.org/10.7910/DVN/IPFJO6 .

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Acknowledgements

This research was supported by the graduate scientific research and innovation project of Xinjiang Uygur Autonomous Region named “Research on in-depth learning of high school information technology courses for the cultivation of computing thinking” (No. XJ2022G190) and the independent innovation fund project for doctoral students of the College of Educational Science of Xinjiang Normal University named “Research on project-based teaching of high school information technology courses from the perspective of discipline core literacy” (No. XJNUJKYA2003).

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Xu, E., Wang, W. & Wang, Q. The effectiveness of collaborative problem solving in promoting students’ critical thinking: A meta-analysis based on empirical literature. Humanit Soc Sci Commun 10 , 16 (2023). https://doi.org/10.1057/s41599-023-01508-1

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JTE v7n1 - Collaborative Learning Enhances Critical Thinking

Article Collaborative Learning Enhances Critical Thinking Anuradha A. Gokhale The concept of collaborative learning, the grouping and pairing of students for the purpose of achieving an academic goal, has been widely researched and advocated throughout the professional literature. The term "collaborative learning" refers to an instruction method in which students at various performance levels work together in small groups toward a common goal. The students are responsible for one another's learning as well as their own. Thus, the success of one student helps other students to be successful. Proponents of collaborative learning claim that the active exchange of ideas within small groups not only increases interest among the participants but also promotes critical thinking. According to Johnson and Johnson (1986) , there is persuasive evidence that cooperative teams achieve at higher levels of thought and retain information longer than students who work quietly as individuals. The shared learning gives students an opportunity to engage in discussion, take responsibility for their own learning, and thus become critical thinkers ( Totten, Sills, Digby, & Russ, 1991 ). In spite of these advantages, most of the research studies on collaborative learning have been done at the primary and secondary levels. As yet, there is little empirical evidence on its effectiveness at the college level. However, the need for noncompetitive, collaborative group work is emphasized in much of the higher education literature. Also, majority of the research in collaborative learning has been done in non-technical disciplines. The advances in technology and changes in the organizational infrastructure put an increased emphasis on teamwork within the workforce. Workers need to be able to think creatively, solve problems, and make decisions as a team. Therefore, the development and enhancement of critical-thinking skills through collaborative learning is one of the primary goals of technology education. The present research was designed to study the effectiveness of collaborative learning as it relates to learning outcomes at the college level, for students in technology. Purpose of Study This study examined the effectiveness of individual learning versus collaborative learning in enhancing drill-and-practice skills and critical-thinking skills. The subject matter was series and parallel dc circuits. Research Questions The research questions examined in this study were: Will there be a significant difference in achievement on a test comprised of "drill-and practice" items between students learning individually and students learning collaboratively? Will there be a significant difference in achievement on a test comprised of "critical-thinking" items between students learning individually and students learning collaboratively? Definition of Terms Collaborative Learning: An instruction method in which students work in groups toward a common academic goal. Individual Learning : An instruction method in which students work individually at their own level and rate toward an academic goal. Critical-thinking Items : Items that involve analysis, synthesis, and evaluation of the concepts. Drill-and-Practice Items : Items that pertain to factual knowledge and comprehension of the concepts. Methodology The independent variable in this study was method of instruction, a variable with two categories: individual learning and collaborative learning. The dependent variable was the posttest score. The posttest was made up of "drill-and- practice" items and "critical-thinking" items. Subjects The population for this study consisted of undergraduate students in industrial technology, enrolled at Western Illinois University, Macomb, Illinois. The sample was made up of students enrolled in the 271 Basic Electronics course during Spring 1993. There were two sections of the 271 class. Each section had 24 students in it. Thus, a total of forty-eight students participated in this study. Treatment The treatment comprised of two parts: lecture and worksheet. Initially, the author delivered a common lecture to both treatment groups. The lecture occurred simultaneously to both groups to prevent the effect of any extraneous variables such as time of day, day of week, lighting of room, and others. The lecture was 50 minutes in length. It was based on series dc circuits and parallel dc circuits. Next, one section was randomly assigned to the "individual learning group" while the other section was assigned to the "collaborative learning group". The two sections worked in separate classrooms. The same worksheet was given to both treatment groups. It was comprised of both drill- and- practice items and critical- thinking items. The full range of cognitive operations were called into play in that single worksheet. It began with factual questions asking for the units of electrical quantities. Next, the questions involved simple applications of Ohm's law and Watt's law or power formula. The factual questions and the simple application questions were analogous to the drill- and- practice items on the posttest. The questions that followed required analysis of the information, synthesis of concepts, and evaluation of the solution. These questions were analogous to the critical- thinking items on the posttest. When designing the critical- thinking items it was ensured that they would require extensive thinking. Both sections had the same treatment time. Individual Learning In individual learning, the academic task was first explained to the students. The students then worked on the worksheet by themselves at their own level and rate. They were given 30 minutes to work on it. At the end of 30 minutes, the students were given a sheet with answers to the questions on the worksheet. In case of problems, the solution sheet showed how the problem was solved. The students were given 15 minutes to compare their own answers with those on the solution sheet and understand how the problems were to be solved. The participants were then given a posttest that comprised of both drill- and- practice items and critical- thinking items. Collaborative Learning When implementing collaborative learning, the first step was to clearly specify the academic task. Next, the collaborative learning structure was explained to the students. An instruction sheet that pointed out the key elements of the collaborative process was distributed. As part of the instructions, students were encouraged to discuss "why" they thought as they did regarding solutions to the problems. They were also instructed to listen carefully to comments of each member of the group and be willing to reconsider their own judgments and opinions. As experience reveals, group decision- making can easily be dominated by the loudest voice or by the student who talks the longest. Hence, it was insisted that every group member must be given an opportunity to contribute his or her ideas. After that the group will arrive at a solution. Group Selection and Size Groups can be formed using self- selection, random assignment, or criterion- based selection. This study used self- selection, where students chose their own group members. The choice of group size involves difficult trade- offs. According to Rau and Heyl (1990) , smaller groups (of three) contain less diversity; and may lack divergent thinking styles and varied expertise that help to animate collective decision making. Conversely, in larger groups it is difficult to ensure that all members participate. This study used a group size of four. There were 24 students in the collaborative learning treatment group. Thus, there were six groups of four students each. Grading Procedure According to Slavin (1989) , for effective collaborative learning, there must be "group goals" and "individual accountability". When the group's task is to ensure that every group member has learned something, it is in the interest of every group member to spend time explaining concepts to groupmates. Research has consistently found that students who gain most from cooperative work are those who give and receive elaborated explanations ( Webb, 1985 ). Therefore, this study incorporated both "group goals" and "individual accountability". The posttest grade was made up of two parts. Fifty percent of the test grade was based on how that particular group performed on the test. The test points of all group members were pooled together and fifty percent of each student's individual grade was based on the average score. The remaining fifty percent of each student's grade was individual. This was explained to the students before they started working collaboratively. After the task was explained, group members pulled chairs into close circles and started working on the worksheet. They were given 30 minutes to discuss the solutions within the group and come to a consensus. At the end of 30 minutes, the solution sheet was distributed. The participants discussed their answers within the respective groups for 15 minutes. Finally, the students were tested over the material they had studied. Instruments The instruments used in this study were developed by the author. The pretest and posttest were designed to measure student understanding of series and parallel dc circuits and hence belonged to the cognitive domain. Bloom's taxonomy (1956) was used as a guide to develop a blueprint for the pretest and the posttest. On analyzing the pilot study data, the Cronbach Reliability Coefficients for the pretest and the posttest were found to be 0.91 and 0.87 respectively. The posttest was a paper- and- pencil test consisting of 15 "drill- and- practice" items and 15 "critical- thinking" items. The items that belonged to the "knowledge," "comprehension," and "application" classifications of Bloom's Taxonomy were categorized as "drill- and- practice" items. These items pertained to units and symbols of electrical quantities, total resistance in series and parallel, and simple applications of Ohm's Law. The items that belonged to "synthesis," "analysis," and "evaluation" classifications of Bloom's Taxonomy were categorized as "critical- thinking" items. These items required students to clarify information, combine the component parts into a coherent whole, and then judge the solution against the laws of electric circuits. The pretest consisted of 12 items, two items belonging to each classification of Bloom's Taxonomy. Research Design A nonequivalent control group design was used in this study. The level of significance (alpha) was set at 0.05. A pretest was administered to all subjects prior to the treatment. The pretest was helpful in assessing students' prior knowledge of dc circuits and also in testing initial equivalence among groups. A posttest was administered to measure treatment effects. The total treatment lasted for 95 minutes. In order to avoid the problem of the students becoming "test- wise", the pretest and posttest were not parallel forms of the same test. Findings A total of 48 subjects participated in this study. A nine item questionnaire was developed to collect descriptive data on the participants. Results of the questionnaire revealed that the average age of the participants was 22.55 years with a range of 19 to 35. The mean grade point average was 2.89 on a 4- point scale, with a range of 2.02 to 3.67. The questionnaire also revealed that eight participants were females and 40 were males. Nineteen students were currently classified as sophomores and 29 were juniors. Forty- five participants reported that they had no formal education or work experience in dc circuits either in high school or in college. Three students stated that they had some work experience in electronics but no formal education. The pretest and posttest were not parallel forms of the same test. Hence, the difference between the pretest and posttest score was not meaningful. The posttest score was used as the criterion variable. At first, a t- test was conducted on pretest scores for the two treatment groups. The mean of the pretest scores for the participants in the group that studied collaboratively (3.4) was not significantly different than the group that studied individually (3.1). The t- test yielded a value (t=1.62, p>0.05) which was not statistically significant. Hence, it was concluded that pretest differences among treatment groups were not significant. The posttest scores were then analyzed to determine the treatment effects using the t- test groups procedure which is appropriate for this research design. In addition, an analysis of covariance procedure was used to reduce the error variance by an amount proportional to the correlation between the pre and posttests. The correlation between the pretest and the posttest was significant (r=0.21, p<0.05). In this approach, the pretest was used as a single covariate in a simple ANCOVA analysis. Research Question I Will there be a significant difference in achievement on a test comprised of "drill- and- practice" items between students learning individually and students learning collaboratively? The mean of the posttest scores for the participants in the group that studied collaboratively (13.56) was slightly higher than the group that studied individually (11.89). A t- test on the data did not show a significant difference between the two groups. The result is given in Table 1. An analysis of covariance procedure yielded a F-value that was not statistically significant (F=1.91, p>0.05). Research Question II Will there be a significant difference in achievement on a test comprised of "critical- thinking" items between students learning individually and students learning collaboratively? The mean of the posttest scores for the participants in the group that studied collaboratively (12.21) was higher than the group that studied individually (8.63). A t- test on the data showed that this difference was significant at the 0.001 alpha level. This result is presented in Table 1. An analysis of covariance yielded a F-value that was significant at the same alpha level (F=3.69, p<0.001). Table 1 Results of t-Test Item Classification Method of Teaching N Mean SD t p Individual 24 11.89 2.62 Drill-and-Practice 1.73 .09 Collaborative 24 13.56 2.01 Individual 24 8.63 Critical-thinking 3.53 .001*** Collaborative 24 12.21 2.52 Discussion of the Findings After conducting a statistical analysis on the test scores, it was found that students who participated in collaborative learning had performed significantly better on the critical- thinking test than students who studied individually. It was also found that both groups did equally well on the drill- and- practice test. This result is in agreement with the learning theories proposed by proponents of collaborative learning. According to Vygotsky (1978) , students are capable of performing at higher intellectual levels when asked to work in collaborative situations than when asked to work individually. Group diversity in terms of knowledge and experience contributes positively to the learning process. Bruner (1985) contends that cooperative learning methods improve problem- solving strategies because the students are confronted with different interpretations of the given situation. The peer support system makes it possible for the learner to internalize both external knowledge and critical thinking skills and to convert them into tools for intellectual functioning. In the present study, the collaborative learning medium provided students with opportunities to analyze, synthesize, and evaluate ideas cooperatively. The informal setting facilitated discussion and interaction. This group interaction helped students to learn from each other's scholarship, skills, and experiences. The students had to go beyond mere statements of opinion by giving reasons for their judgments and reflecting upon the criteria employed in making these judgments. Thus, each opinion was subject to careful scrutiny. The ability to admit that one's initial opinion may have been incorrect or partially flawed was valued. The collaborative learning group participants were asked for written comments on their learning experience. In order to analyze the open- ended informal responses, they were divided into three categories: 1. Benefits focusing on the process of collaborative learning, 2. Benefits focusing on social and emotional aspects, and 3. Negative aspects of collaborative learning. Most of the participants felt that groupwork helped them to better understand the material and stimulated their thinking process. In addition, the shared responsibility reduced the anxiety associated with problem- solving. The participants commented that humor too played a vital role in reducing anxiety. A couple of participants mentioned that they wasted a lot of time explaining the material to other group members. The comments along with the number of participants who made those comments are described in Table 2. Table 2 Categorical Description of Students' Open-Ended Responses Regarding Collaborative Learning A. Benefits Focusing on the Process of Collaborative Learning Comments (# of responses): Helped understanding (21) Pooled knowledge and experience (17) Got helpful feedback (14) Stimulated thinking (12) Got new perspectives (9) B. Benefits Focusing on Social and Emotional Aspects Comments (# of responses) More relaxed atmosphere makes problem- solving easy (15) It was fun (12) Greater responsibility- for myself and the group (4) Made new friends (3) C. Negative Aspects of Collaborative Learning Comments (# of responses) Wasted time explaining the material to others (2) Implications for Instruction From this research study, it can be concluded that collaborative learning fosters the development of critical thinking through discussion, clarification of ideas, and evaluation of others' ideas. However, both methods of instruction were found to be equally effective in gaining factual knowledge. Therefore, if the purpose of instruction is to enhance critical- thinking and problem- solving skills, then collaborative learning is more beneficial. For collaborative learning to be effective, the instructor must view teaching as a process of developing and enhancing students' ability to learn. The instructor's role is not to transmit information, but to serve as a facilitator for learning. This involves creating and managing meaningful learning experiences and stimulating students' thinking through real world problems. Future research studies need to investigate the effect of different variables in the collaborative learning process. Group composition: Heterogeneous versus homogeneous, group selection and size, structure of collaborative learning, amount of teacher intervention in the group learning process, differences in preference for collaborative learning associated with gender and ethnicity, and differences in preference and possibly effectiveness due to different learning styles, all merit investigation. Also, a psycho- analysis of the group discussions will reveal useful information. References Bruner , J. (1985). Vygotsky: An historical and conceptual perspective. Culture, communication, and cognition: Vygotskian perspectives , 21-34. London: Cambridge University Press. Bloom , B. S. (1956). Taxonomy of educational objectives, handbook 1: Cognitive domain . New York: Longmans Green. Johnson , R. T., & Johnson, D. W. (1986). Action research: Cooperative learning in the science classroom. Science and Children , 24, 31-32. Rau , W. & Heyl, B. S. (1990). Humanizing the college classroom: Collaborative learning and social organization among students. Teaching Sociology , 18, 141-155. Slavin , R. E. (1989). Research on cooperative learning: An international perspective. Scandinavian Journal of Educational Research, 33(4), 231-243. Totten , S., Sills, T., Digby, A., & Russ, P. (1991). Cooperative learning: A guide to research . New York: Garland. Vygotsky , L. (1978). Mind in society: The development of higher psychological processes . Cambridge: Harvard University Press. Webb , N. (1985). Student interaction and learning in small groups: A research summary. Learning to Cooperate, Cooperating to Learn , 148-172. Anuradha A. Gokhale is an Associate Professor at Western Illinois University in the Department of Industrial Education and Technology, and is currently a Visiting Associate Professor at Illinois State University. Copyright, 1995, Journal of Technology Education ISSN 1045-1064 Permission is given to copy any article or graphic provided credit is given and the copies are not intended for sale. Journal of Technology Education Volume 7, Number 1 Fall 1995

Exploring Collaborative Learning: Theoretical and Conceptual Perspectives

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This chapter reviews the literature concerning the key aspects of CL. It opens with a review of the relevant learning theories and the conceptual framework on which this study is based so that the foundations of CL can be understood. More importantly, this chapter differentiates some of the confusing concepts such as collaboration , cooperation and group work and discusses how they have been researched in their own realm. A discussion of CL including its definition, rationale, characteristics, and structures serves as the closing part of this chapter.

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Lin, L. (2015). Exploring Collaborative Learning: Theoretical and Conceptual Perspectives. In: Investigating Chinese HE EFL Classrooms. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-44503-7_2

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Complementary strategies for teaching collaboration and critical thinking skills

Subscribe to the center for universal education bulletin, tara barnett , tb tara barnett 4th grade teacher - knollwood school, fair haven, new jersey ben lawless , bl ben lawless history teacher - aiken college, melbourne, australia helyn kim , and helyn kim former brookings expert @helyn_kim alvin vista alvin vista former brookings expert @alvin_vista.

December 12, 2017

This is the fifth piece in a six-part  blog series  on  teaching 21st century skills , including  problem solving ,  metacognition , critical thinking , and collaboration, in classrooms.

In today’s changing world, students need a broader range of skills beyond traditional academic subject areas that they can apply to a wide range of real-life situations. Students will encounter many future situations where they have to bring together multiple complex skills to complete tasks. Using examples from the U.S. and Australia, we will outline two complementary methods that teach these complex skillsets. In the U.S., a 4th grade reading class uses a method to develop collaboration skills, while simultaneously developing critical thinking skills. Similarly, an example from Australia will show how a secondary level history class also teaches these two skills simultaneously, but with a different method.

An American classroom

Being able to discuss our ideas and opinions thoughtfully with others is a crucial life skill. Collaborative discussion relies on peer interaction, communication, sharing, and at times expert guidance to extend student thinking. Students—not teachers—should drive conversations as they present, defend, elaborate upon, and respond to each other. As they make connections, they will clarify their understanding, refine their thinking, and synthesize information. To help illustrate this important skill, Tara Barnett, a 4th grade teacher in Fair Haven, New Jersey, supports and enhances collaborative talk through a number of strategies.

When Tara thinks back to her own schooling, she remembers the many times she was asked questions designed to check her knowledge; rarely was she asked to engage in discussion around a text or issue. Now, it is common practice to ask students to turn and talk to each other. However, it is not enough just to provide opportunities; teachers need to teach collaborative discussion skills explicitly and systematically. Tara uses accountable talk stems as a strategy to structure meaningful conversation. This gives students the language they need to engage in discussion with each other. All too often, however, students go through the motions of talking without full engagement. Kids will say, “I agree” or “I disagree” and even give reasons, but conversations often stay at a surface level. They seem to think that using these phrases are the end rather than a means to an end.

To address this issue in classrooms, use the following strategies—they are related to literacy lessons but can, of course, be applied more widely.

1) Launch entire-class conversations before moving students to less-supported conversations with partners. Beginning with the entire class helps to establish norms for conversation in the classroom and gives a model for what a conversation can and should look like.

2) Give students a question in which they have to take a stance . In order to have good discussions, ideas need to be worth discussing. If the idea is simply stating the obvious or agreeing with a previously mentioned idea, the conversation will stall.

3) If you use accountable talk stems, preface them as a “way to enter the conversation” and list 1-2 stems for each path. The stems support students in thinking about what they are trying to accomplish by making their talk more purposeful and thoughtful. It might look something like what is described in Figure 1.

Figure 1. Entering a conversation

4) Explicitly teach vocabulary that will support students to enter a discussion. For example, when we want to discuss the characters in Fox by Margaret Wild and Ron Brooks , we introduce words like cunning , optimistic, and pessimistic . After introducing students to these words, they begin to see the connections between the words and the characters, which prompts students to use them in a discussion. Vocabulary support is a game changer for students.

5) Once students are having discussions more independently, have them record their discussions for the purpose of self-assessment. After the discussion, they can watch their discussion and ask themselves questions such as:

• Is there one person who is overpowering the discussion or one person who isn’t getting a chance to say much?
• Are we sticking with a topic for at least one round, maybe more? (Teach the students that they should be “catching” ideas and not just bouncing from one idea to the next like popcorn.)

Students can use their self-assessment to set goals. Reflection and goal setting really helps focus and elevate conversations and makes students accountable to themselves—an essential learning to learn characteristic.

An Australian classroom

On the other side of the world, Ben teaches secondary students at Aitken College, a co-educational independent school in Melbourne, Australia. Although Ben’s class subject is History, when people ask him what he teaches, Ben points out that he teaches “conceptual analysis.” This is his approach to developing critical thinking skills in a collaborative setting as the students learn history. Irrespective of the content or skills learned the ability to analyze material and concepts is crucial.

Conceptual analysis can be applied to building structures based on hierarchies or progressions, such as when students are tasked to create their own developmental or progression-based rubrics . It is important to demonstrate to students how rubrics are created and why they are useful because understanding rubrics also helps them structure their task output to match the task requirements. To help them with this skill, have the students to generate a rubric together. Pick a common school assignment, such as a history essay. Ask students to list some of the skills they use when producing a history essay; support the students in doing this by querying statements of what they produce to help them distinguish the actual processes they use. Choose three or four of these processes. Now ask students to describe what different levels of quality of these processes would look like, i.e., a description of an advanced example, and a middle-level example, and a basic level example.

Figure 2. Analyzing the skills used in a history essay

Figure 2 shows how this class activity would look like when completed as a grid, where for each step in “researching,” the students provided what they think are different levels of quality. Students are demonstrating sub-skills that are important components of conceptual analysis: differentiating, organizing, and attributing. They are differentiating by recognizing that the words generated in a brainstorm can be classified. They are organizing by placing them in different categories. We could extend the task by asking students to come up with sub-categories and sub-sub-categories. This helps students deconstruct a concept. Students who can understand how to break a task down like this are much more likely to develop and demonstrate the skills and sub-skills involved. With this task, we could also show students a few examples of other student work and ask them to grade them according to the rubric they created.

Critical thinking is a systematic way of looking at the world for the purposes of reasoning and making decisions effectively. Although we may define critical thinking in a more complex manner, it is essentially a practical or applied activity because reasoning and decisionmaking are applied activities. Conceptual analysis is a useful tool to help students do critical thinking activities collaboratively, and it can be taught in a team-based or collaborative setting.

Both conceptual analysis and collaborative discussion strategies show that they can be applied practically in diverse classroom tasks for teaching multiple complex skills such as working collaboratively and thinking critically—two of the 21st century skills that will become increasingly important as the new generation of students move into the workforce of the future.

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Collaborative Learning in Higher Education: Evoking Positive Interdependence

Karin scager.

† Department of Social Sciences, Utrecht University, 3508 TC Utrecht, The Netherlands

Johannes Boonstra

‡ Department of Biology, Utrecht University, 3584 CH Utrecht, The Netherlands

Ton Peeters

Jonne vulperhorst, fred wiegant.

This study focuses on factors increasing the effectiveness of collaborative learning. Results show that challenging, open, and complex group tasks that required the students to create something new and original evoked effective collaboration.

Collaborative learning is a widely used instructional method, but the learning potential of this instructional method is often underused in practice. Therefore, the importance of various factors underlying effective collaborative learning should be determined. In the current study, five different life sciences undergraduate courses with successful collaborative-learning results were selected. This study focuses on factors that increased the effectiveness of collaboration in these courses, according to the students. Nine focus group interviews were conducted and analyzed. Results show that factors evoking effective collaboration were student autonomy and self-regulatory behavior, combined with a challenging, open, and complex group task that required the students to create something new and original. The design factors of these courses fostered a sense of responsibility and of shared ownership of both the collaborative process and the end product of the group assignment. In addition, students reported the absence of any free riders in these group assignments. Interestingly, it was observed that students seemed to value their sense of achievement, their learning processes, and the products they were working on more than their grades. It is concluded that collaborative learning in higher education should be designed using challenging and relevant tasks that build shared ownership with students.

INTRODUCTION

Students may learn a lot from working in groups, but the learning potential of collaboration is underused in practice ( Johnson et al ., 2007 ), particularly in science education ( Nokes-Malach and Richey, 2015 ). Collaborative, cooperative, and team-based learning are usually considered to represent the same concept, although they are sometimes defined differently ( Kirschner, 2001 ); we consider these concepts comparable and use the term “collaboration” throughout the paper. In collaborative learning, students participate in small-group activities in which they share their knowledge and expertise. In these student-driven activities, the teacher usually acts as a facilitator ( Kirschner, 2001 ).

Several decades of empirical research have demonstrated the positive relationship between collaborative learning and student achievement, effort, persistence, and motivation (for reviews, see Slavin, 1990 ; Webb and Palinscar, 1996 ; Barron, 2000 ; Johnson et al ., 2007 ). Collaborative learning potentially promotes deep learning, in which students engage in high-quality social interaction, such as discussing contradictory information ( Visschers-Pleijers et al ., 2006 ). In science education, a deep-learning approach is crucial for understanding concepts and complex processes ( Van Boxtel, 2000 ). Understanding of these concepts involves a process of conceptual change, a process particularly activated in collaborative learning, whereby students interact by explaining to and questioning one another critically ( Van Boxtel et al ., 2000 ; Linton et al ., 2014 ). In previous papers, we have explored and emphasized the relevance of collaborative learning in undergraduate biology courses ( Wiegant et al ., 2012 , 2014 ). By comparing university student achievement in a biology course in individual and group settings, Linton et al . (2014) found that students in group settings achieved significantly better with respect to conceptual understanding in comparison with students in courses with an individual setting. Besides these cognitive benefits, collaborative learning provides social skills needed for future professional work in the field of science.

Just forming groups, however, does not automatically result in better learning and motivation ( Salomon and Globerson, 1989 ; Gillies, 2004 ; Khosa and Volet, 2013 ). In their study of university students’ preferences for collaborative learning, Raidal and Volet (2009) found an overwhelming preference for individual forms of learning. Students are hesitant about group work because of the occurrence of “free riders,” logistical issues, or interpersonal conflicts ( Livingstone and Lynch, 2000 ; Aggarwal and O’Brien, 2008 ; Pauli et al ., 2008 ; Shimazou and Aldrich, 2010 ; Hall and Buzwell, 2012 ). As a result, students might opt for a strategic approach by dividing the work and merely using a stapler to “integrate” their work into a group paper. Johnson and Johnson (1999) refer to groups showing this kind of superficial behavior as “pseudo learning groups.” In turn, the resulting lack of synthesis can be disappointing for teachers. Dividing work also implies that students lose the potential learning effect of collaborating, since the extent to which students benefit from working with other students depends on the quality of their interactions ( Van Boxtel et al ., 2000 ; King, 2002 ; Palinscar and Herrenkohl, 2002 ; Volet et al ., 2009 ). Insight into factors that facilitate collaborative learning is critical for understanding how collaboration can be used effectively in higher education. Therefore, in the present study, we explore factors that optimize the quality of collaboration, using examples of effective group work in five different life sciences courses.

POTENTIAL FACTORS ENHANCING THE EFFECTIVENESS OF COLLABORATIVE LEARNING

Social interaction is crucial for effective collaboration ( Volet et al ., 2009 ). Learning outcomes of collaborative-learning groups have been found to depend on the quality of student discussions, including argumentation ( Teasley, 1995 ; Chinn et al ., 2000 ), explaining ideas to one another ( Veenman et al ., 2005 ), and incorporating and building on one another’s ideas ( Barron, 2003 ). These interactions with peers are assumed to promote students’ cognitive restructuring ( Webb, 2009 ). Explaining things to one another and discussing subject matter may lead to deeper understanding, to recognition of misconceptions, and to the strengthening of connections between new information and previously learned information ( Wittrock, 1990 ). The question of how to organize collaboration in a way that promotes these kinds of interactions is paramount.

Decades of research on group work have resulted in the identification of various factors that potentially enhance the effectiveness of collaboration. These factors can be differentiated as primary factors (design characteristics) and secondary or mediating factors (group-process characteristics). Regarding primary factors, groups need to be small (three to five students) to obtain meaningful interaction ( Lou et al ., 2001 ; Johnson et al ., 2007 ). With respect to group composition, mixed-ability groups have been found to increase performance for students of lower ability, but this composition does not necessarily benefit high-ability students ( Webb et al ., 2002 ). Equal participation, however, has been shown to be more important for students’ achievement than group composition, because students are more likely to use one another’s knowledge and skills fully when all students participate to the same extent ( Woolley et al ., 2015 ). Heterogeneity, with respect to diversity of perspectives and styles, has been found to increase learning, particularly in groups working on tasks that require creativity ( Kozhevnikov et al ., 2014 ). The nature of the task has been shown to be an important factor as well. Open and ill-structured tasks promote higher-level interaction and improve reasoning and applicative and evaluative thinking to a greater extent than closed tasks ( Gillies, 2014 ). In addition, complex tasks provoke deeper-level interactions than simple tasks ( Hertz-Lazarowitz, 1989 ).

Concerning secondary or intermediate factors affecting group work, positive interdependence theory is one of the best-founded theories explaining the quality of interaction in collaborative learning ( Slavin, 1990 ; Johnson and Johnson, 1999 , 2009 ; Gully et al ., 2002 ). According to this theory, collaboration is enhanced when positive interdependence exists among group members. This is achieved when students perceive the contribution of each individual to be essential for the group to succeed in completing the assigned activity ( Johnson and Johnson, 2009 ). Positive interdependence results in both individual accountability and promotive interaction. Individual accountability is defined as having feelings of responsibility for completing one’s own work and for facilitating the work of other group members. A sense of mutual accountability is necessary to avoid free riding ( Johnson and Johnson, 2009 ), which occurs when one or more group members are perceived by other members as failing to contribute their fair share to the group effort ( Aggarwal and O’Brien, 2008 ). Promotive interaction has been described as students encouraging and facilitating one another’s efforts to accomplish group goals, both with respect to group dynamics and the subject matter ( Johnson and Johnson, 2009 ).

Methods of inducing positive interdependence interaction are either reward or task based ( Johnson et al ., 2007 ). Reward-based interdependence structures the reward in such a way that students’ individual grades depend on the achievement of the whole team. According to Slavin (1991 , 1995 ), collaborative learning is rarely successful without group rewards. In higher education, however, findings on the effects of reward-based interdependence are inconclusive. The main concern is that rewards stimulate extrinsic motivation and may be detrimental to intrinsic motivation ( Parkinson and St. George, 2003 ). Intrinsically motivated students put effort into a task because they are interested in the task itself, while extrinsically motivated students are interested in the reward or grade ( Deci and Ryan, 2000 ). Strong incentives, such as grades, could steer student motivation toward the reward and subsequently reduce the task to being a means to an end. Serrano and Pons (2007) , however, found that using rewards (individual grades) created high positive interdependence in group work at a university level. They concluded that the reward structure did direct students’ motivation toward final grades, while the task still aroused the interest of the students. In contrast, Sears and Pai (2012) found that rewards were not crucial factors affecting group behavior. Their study showed that groups continued to work even after the reward was removed, whereas the efforts of students working individually decreased after the reward was removed.

In structured task-based interdependence, students are forced to exchange information; this can be achieved by assigning group members different roles, resources, or tasks (the “jigsaw” method) or by “scripting” the process, which involves giving students a set of instructions on how they should interact and collaborate ( Kagan, 1994 ; Dillenbourg, 2002 ). The effects of task structuring on collaborative learning are, however, not clear ( Fink, 2004 ; Hänze and Berger, 2007 ; Serrano and Pons, 2007 ). Hänze and Berger (2007) observed no differences in achievement between students who worked in jigsaw-structured groups and students who worked individually. In contrast, the observations of Brewer and Klein (2006) indicated that students in groups with given roles plus rewards interacted significantly more frequently than students in groups with given rewards only or in groups without structured interdependence factors. (Over)structuring interaction processes, on the other hand, could threaten intrinsic motivation and disturb natural interaction processes ( Dillenbourg, 2002 ). Although it is widely accepted that positive interdependence has been shown to be crucial in evoking social interaction, in practice, university students often tend to merely go through the motions and choose the solution requiring the least effort, which explains why positive interdependence often does not emerge ( Salomon and Globerson, 1989 ). Additional methods are necessary to encourage quality interactions that enhance learning. Moreover, the mixed results of university education studies concerning structuring interdependence—using either rewards or task structuring—do not solve the challenge of how to create interdependence without disturbing the intrinsic motivation of students. Forcing students to interact could endanger student autonomy and motivation, while merely putting students together has been shown to be ineffective.

THE CURRENT STUDY

Despite the considerable amount of research on collaborative learning, less is known about how to structure university-level group work in order to capitalize on the benefits of collaborative learning. The studies discussed earlier focused on primary and secondary education and are not fully applicable to higher education, because students in undergraduate classes may have different schedules and often have not met before. Moreover, group work of university students is mostly organized outside class hours in the absence of teachers. Furthermore, literature in this area may be limited in applicability, as many studies of factors affecting collaboration have used (quasi)experimental designs, in which outcomes of two or three designs were compared ( Johnson and Johnson, 2009 ). A restriction of this method is that only the hypothesized independent variables are studied, while other important factors contributing to effectiveness might be overlooked. In our study, we approached the theme retrospectively, investigating the learning of student groups known to have collaborated and achieved highly, according to their teachers. Rather than focusing on learning outcomes, we explored how group work in these courses was structured. Understanding the factors that facilitate students’ collaboration is critical to understanding how this approach to learning can be used more effectively in higher education. We explicitly focused on positive examples of effective collaborative learning, as best practices should be communicated to others ( Dewey, 1929 , p.11).

In the current study, we selected five different life sciences undergraduate courses that comprised successful group-work assignments. The specific question this study aimed to address was, according to the students, what factors increased collaboration in these courses? By uncovering the factors that make collaborative learning fruitful, we aim to provide useful guidelines for instructors implementing collaborative learning.

Participants

The present study involved focus group interviews with nine groups of second- and third-year students of five different undergraduate life sciences courses. We depended heavily on these focus group interviews to develop our understandings. They allowed us to gain insight into students’ perspectives, which is important because, to a large degree, students’ perspectives of instruction affect what they do and learn ( Shuell, 1996 ). Furthermore, the group exchanges of experiences and perspectives promoted breadth, as well as depth, in our understandings of the cognitive, behavioral, and situational factors contributing to the effectiveness of the collaboration. The particular courses were selected because they all implemented group work that, according to teacher assessments and student evaluations, was very effective. We approached the instructors of these courses with the request to ask their students to volunteer in focus group discussions. Students were willing to participate in these focus group discussions, although not all students were able to meet at the scheduled times. No specific reward was promised for participating in focus group discussions.

Between two and 10 students participated in each of the nine focus group interviews (see Table 1 ).

Course, number of focus group interviews, and students per interview

Course Descriptions

We focused on five courses that were all small-enrollment, upper-division courses in which 15–35 students participated per course. In all courses, collaborative activities occurred during class hours but also outside of class. In some courses, the out-of-class cooperative activities even exceeded the in-class activities.

Course A: The first course was part of a biology honors program. In this part of the program, groups of second-year bachelor’s students (12–19 students) were assigned the group task of writing a popular science book about a biology topic of their choice. Students had to perform all the activities necessary to produce the book. The project was strongly student-led, and students assigned themselves tasks necessary for finishing the project. The assignment comprised an entire academic year, starting in September and finishing in May/June as an extracurricular activity. More details of this course are described elsewhere ( Wiegant et al ., 2012 ).

Course B: Students in the immunology course, mostly third-year students, were assigned the task of writing, in groups of four, a short research project on an immunological topic. The assignment was structured in three parts: in part 1, groups designed a draft of their proposal; in part 2, the groups peer reviewed the draft of another group; and in part 3, the groups received the draft and comments of yet another group, which they had to finish and present. The assignment comprised approximately half of the course.

Course C: In the advanced cell biology course, three small teams of four or five students collaborated intensively during a semester of 15 weeks to formulate three PhD proposals within an overarching theme. Because the course was student-led, the teachers refrained from guiding the students in their decisions, instead taking a facilitating role by asking critical questions and providing feedback. As a result of the project, the teams presented and defended their research program and the three research proposals before a jury of experts. More details of this course are given elsewhere ( Wiegant et al ., 2011 , 2014 ; Scager et al ., 2014 ).

Course D: The objective of the molecular cell biology course was to learn to design a research project in groups of four. In this course, students were required to complete multiple assignments, such as reviewing a paper, developing a research proposal, designing experiments, and writing and defending their proposals. Groups met with their supervisor once a week and were supposed to keep the course coordinator informed on their progress. Final grades were based on individual (40%) and group (60%) components.

Course E: As a part of the pharmacy course, third-year students, in groups of four to six participants, were required to analyze the quality of a specific pharmacotherapy. The assignments were authentic and were provided by external commissioning companies. The group assignment counted for 70% of the final grade (50% group report and presentation; 20% individual reflection).

The interviews were semistructured and included two basic questions: 1) “What factors made group work effective in this course (as opposed to other experiences you have had)?” and 2) “What was the added value in this course of working in a group (as opposed to working individually)?” The addition of “as opposed to …” was aimed to encourage students’ thinking process; we did not ask students to elaborate on these opposing experiences. Interviewers stimulated and moderated discussions, ensuring depth as well as diversity. To focus and structure the interviews and to stimulate the sharing of discussion outcomes, we listed the answers to the two questions on a flip chart.

First, the intentions of the interview were clarified, followed by an explanation of the confidential nature of the interview. All students agreed and gave permission for the interviews to be audiotaped. All of the authors conducted one or more interviews, with the first author (K.S.) moderating them. The focus group interviews were held in or near the classroom associated with each of the specific courses. The interviews were ∼60 minutes each and were transcribed verbatim.

Detecting Factors That Facilitated Group Work.

Data were analyzed by the first and fourth authors (K.S. and J.V.) in three partially overlapping stages. Stage 1 comprised reading and rereading the transcripts to identify text units relevant to the subject of challenge. Given the aim of the focus group interviews, this meant ignoring small talk and sorting discussion units related to the two interview questions into focal issues. Stage 2 comprised identifying and coding themes related to the two main interview questions regarding 1) factors and 2) added value, using NVivo version 10 (a qualitative data-analysis computer software package). First, open coding was applied. The answers to both questions, however, evoked answers that pointed to intermediary variables affecting the outcomes of collaboration. For example, the question regarding factors brought forward the importance of the assignment being complex enough to make students feel mutually interdependent, while for the question regarding added value, students referred back to how the complexity of the assignment stimulated them to discuss, build on, and learn from one another’s ideas. The interactions provoked by the complexity of the task seemed to connect complexity with learning outcomes. Therefore, when axial coding was applied, we decided to develop three clusters of codes focused on the factors of effective collaboration, the mediating variables, and the added value of collaboration. Subsequently, selective coding was applied, wherein codes were clustered into larger sets informed by theory ( Braun and Clarke, 2006 ). Only factors that were mentioned in more than half of the focus groups were kept. This resulted in two sets of factors. The first set of factors related to the design of the group assignment (autonomy, group size, task design, and teacher expectations). The second set consisted of mediating variables related to the working processes of the groups (team and task regulation, promotive interaction, interdependence, responsibility, and mutual support and motivation).

Reliability and Validity.

Reliability is considered in terms of equivalence and internal consistency ( Sim and Wright, 2000 ). Reliability was ensured by intercoder consistency ( Burla et al ., 2008 ). Given the complexity and inhomogeneity of group discourse, agreement testing was constrained to core concepts or themes of substantive importance ( Kidd and Parshall, 2000 ). The equivalence of coding was addressed by selecting 20% of the data and comparing the coding of two secondary raters (10% each) for consistency, which yielded a kappa coefficient of 0.85. This strength of agreement is considered to be “nearly perfect” ( Everitt, 1996 ). Internal consistency was acquired by having one team member moderating all (but one) of the interviews ( Kidd and Parshall, 2000 ). The emergence of substantively similar viewpoints of the focus groups on the core issues across the five different courses supported content validity ( Kidd and Parshall, 2000 ). Furthermore, we assessed content validity by independent coding and by comparing this with theory in extant literature ( Morgan and Spanish, 1985 ; Torn and McNichol, 1998 ).

Factors That Contributed to the Effectiveness of the Collaboration

Eight factors were found to have a positive effect on the effectiveness of the collaboration. These factors are presented in Table 2 : 1) design factors: the design of the course and/or the assignment (the autonomy of the students, task characteristics, teacher expectations, and group size); and 2) process factors: the way students interacted and organized their work (team and task regulation, interdependence, promotive interaction, and mutual support and motivation).

Factors that contributed to the effectiveness of the collaboration

a “Source” refers to how many of the nine interviews the topic was discussed in; “reference” refers to the total number of times the topic was discussed.

Table 2 shows that autonomy and the density and complexity of the task were the factors most frequently mentioned by the students as contributing to the effectiveness of the collaboration. Team and task regulation, positive interdependence, and promotive interaction were perceived by students as the most important factors with respect to the way they processed the assignments. In the next section, we describe the results more elaborately, starting with the design features of these courses that are considered to enhance collaboration processes.

Design Factors

The autonomy the groups experienced was mentioned in all focus groups, indicating the importance of this factor to the effectiveness of collaboration. Autonomy was manifested in allowing student groups to choose their own topics (e.g., for their research plans) and giving them independence in organizing their processes. Statements such as “It was our own thing” occurred frequently in all nine focus group discussions. The references to “our thing” indicate that the students made choices as a group, which could have restricted individual feelings of autonomy. The students, however, did not seem to have experienced clear boundaries between individual and group autonomy. Even though their personal ideas may have been overruled by the team, they still felt autonomous, because they made decisions democratically. As one of the students said, “When you participate in the decision process it is easier to accept than when the decision is made by the teacher.”

Two features of the task were perceived as important contributors to the effectiveness of the group work. First, the density and complexity of the task was crucial. The group task needed to be extensive enough for the group members to really need one another’s contributions to finish in time and complex enough to require them to discuss their work and provide one another with feedback. Second, students perceived the relevance of the task at hand to be an important feature. The task relevance was found in different aspects, depending on the assignment. For the biology honors groups, for example, the process of writing a popular science book and getting it published increased their feelings of doing something significant. The cell biology and immunology groups emphasized the relevance of doing research, in terms of formulating a relevant proposal in the same way as it is done “in the real world.”

In terms of rewards , students emphasized that the inherent value of the end product, such as an article, a research proposal, or a book, stimulated them to achieve, which relates back to the perceived task relevance. As a student of the biology honors course said, “We have also had other group projects …, but that was taken less seriously, because you, well it was nice, but well, the result wouldn’t reach beyond the classroom, while in this project it will.” There were no grades involved in this particular course, which students appreciated, because they believed the end product to be more important than a grade. Also, in other groups, discussions about assessment were learning and/or reward oriented rather than grade oriented; for example, in one of the pharmacy groups it was said: “You are in a learning process, and I think sometimes that it is a shame that it should end in a grade—that creates a tension. And if things go wrong, that could be very beneficial for your learning, but it can also happen that you do not receive a high grade for it.”

In all of the interviews, students mentioned that it was crucial that the task was the core project in the course at that time, as students of the immunology course stated: “I think also because this is not something you do on the side, but this is the only thing we do at the moment, it is the main activity.” The fact that students’ final grades depended primarily on the group assignment was mentioned in some groups. Students emphasized that in previous experiences with group assignments they had not collaborated as intensively because their final grade did not depend largely on the team assignment.

Finally, group size was considered a factor stimulating collaboration in seven of the groups, specifically related to the level of responsibility students felt. Groups of three or four were believed to be optimal: “Otherwise, you get a sort of diffuse responsibility …, and with four you are clearly responsible for an important part of the process.”

Process Factors

The need for team and task regulation was mentioned most frequently in the focus group discussions as an important factor increasing the effectiveness of collaboration. Students divided tasks, appointed team leaders, and set their own deadlines. Organizing frequent face-to-face meetings was very helpful, according to students: “That we met each other physically, instead of doing everything by mail or chat, like in other projects. This works much better, if you can look each other in the eyes it is way faster and more efficient to manage and decide things …. It also increases the pressure, everybody prepares for a meeting.” The quote in Table 2 indicates the direct relation between the autonomy of the groups and their dedication to following their self-made group regulations.

As shown in Table 2 , students in all nine focus groups experienced a sense of positive interdependence in terms of needing one another in order to succeed and achieve their goal. The feeling of responsibility was discussed in six groups. The related issue of “uneven contribution” was discussed in all nine of the focus groups: students did experience differences in power and effort between team members. Interestingly, students did not perceive this as free riding. According to the students, some degree of uneven contribution is only natural; the students all did their best, but as the students said, “There weren’t students who contributed less; there were only students who contributed more.” According to the students, this uneven contribution was due to power differences, not to disinterest or laziness. Students showed empathy for their peers who contributed less: “The strong people might go too hard for the other people to be able to catch up.” This may have caused frustration in students who felt they were lagging behind, as one of them revealed: “You have that responsibility that drives you and then you feel the need to do more, but perhaps that is beyond your capabilities at that point.” Some of the groups discussed the issue of uneven contribution while working on their projects, but always, they stated, in an “understanding and respectful way.” Furthermore, students in all nine interviews mentioned the fact that the variety among students was useful and enhanced the discussions: “working in a group consisting of clones of yourself” would not be as interesting, one of the pharmacy groups stated.

All nine groups mentioned the need for promotive interaction several times, drawing attention to the need to discuss content to accomplish team goals. They mentioned several indicators of promotive interaction: discussions, exchange of information, and arguments, building on one another’s ideas, explaining to one another, providing and processing peer feedback, and asking one another critical questions. According to the students, these discussions enhanced their understanding, and they also learned how to discuss, voice their opinion, explain, listen to others, accept feedback, and reflect on their own work.

Last, but not least, students talked enthusiastically about the way they supported and motivated one another. There was explicit help and pep talks, and, perhaps even more importantly, implicit mutual inspiration effected by them perceiving the motivation of their peers.

Finally, we found one contextual factor (not included in Table 2 ) contributing to collaboration: the shared motivation of students to get the best out of the group assignment. Students mostly linked their having similar motivations to the fact that they were in their second or third year (four of the five courses were third-year courses). First, the students already knew one another: “When you are in your first year, you do not know each other, and some people are a bit insecure, so to say. But now we know each other, so we may scold each other all we can.” Furthermore, students suggested being equally motivated, because the unmotivated students had already left in previous years.

CONCLUSIONS AND DISCUSSION

The purpose of the current study was to find factors that enhance student collaboration. The collaboration processes (task and team regulation, mutual support and motivation, positive interaction) used by these students were distinctly effective. During these processes, positive interdependence was clearly present, supporting the notion that positive interdependence is a crucial factor affecting the effectiveness of collaboration ( Johnson and Johnson, 2009 ). Although the interview data do not allow causal relations between design factors and collaboration processes to be inferred, it seems reasonable to assume that positive interdependence was evoked by a combination of the nature of the task (autonomous, relevant, dense and complex, group rewards), the prominent placement of the group assignment within the course, and the group size.

The results indicate that positive interdependence was an important factor contributing to the effectiveness of collaboration. The positive effect of interdependence on student achievement has already been well documented (for reviews, see Slavin, 1990 ; Webb and Palinscar, 1996 ; Johnson et al ., 2007 ). Although we disassembled the factors contributing to collaboration in the analysis , we assume interdependence does not consist of a single factor but rather is constructed through the interaction between motivated students and design factors (the nature of the task and student autonomy). Furthermore, the fact that the final grade depended primarily on the group assignment can be expected to have contributed to students’ interdependence, which would concur with the findings of Slavin (1991) . Interestingly, however, these students seemed to value the learning process and the products they were working on more than their grades. Our finding, that a sense of achievement rather than a grade was of greater importance in motivating interdependence, contradicts findings of Slavin (1991) and Tsay and Brady (2010) . Tsay and Brady (2010) found that the degree of active participation of university students in collaborative groups was affected by the importance they attached to grades: students who perceived grades as highly important were more active collaborators.

The enthusiasm of the students when speaking of the way they supported and motivated one another and regulated the team and task processes indeed indicates the occurrence of strong self-regulatory processes. Although some structure was provided beforehand in all five courses (e.g., final deadlines), students were perceived to be autonomous in the planning and regulation of their work, which they said added to their motivation to follow their own rules and planning. This direct relationship between perceived autonomy and self-regulatory behavior is aligned with self-determination theory ( Deci and Ryan, 2000 ). According to Deci and Ryan (2000) , when teachers are supportive of student autonomy, students are motivated to internalize the regulation of their learning activities, whereas when teachers are controlling, self-regulated motivation is undermined. The self-regulatory social processes of these students, encouraged by the autonomy they were provided, were the most important factors increasing the effectiveness of their collaboration in these five cases.

Individual accountability is an important aspect within the theory of positive interdependence. Interestingly, instead of accountability, students used the word “responsibility.” The difference between responsibility and accountability is meaningful, because accountability is focused on the end result, or being answerable for your actions to relevant others, while responsibility is related to the task. Responsibility is viewed as having a higher level of autonomy and involves the ability to self-regulate actions free of external motivational pressure. In contrast, the accountable actor is subject to external oversight, regulation, and mechanisms of punishment ( Bivins, 2006 ). The term “responsibility” more appropriately fits the collaboration in these cases, as one of our participants illustrates: “You feel the responsibility to other people in your group, because as soon as soon as you drop the ball, the rest have to work harder.” This student does not refer to consequences externally imposed on him, but he feels responsibility toward others. The effect this has may be the same as when students are forced to be accountable because of reward- or task-based structures, as suggested by Johnson and Johnson (2009) ; however, the nature of the motivation is more intrinsically than extrinsically induced.

Related to the issue of accountability or responsibility is the problem of free riding, which is one of the main problems of group work in higher education ( Livingstone and Lynch, 2000 ; Aggarwal and O’Brien, 2008 ; Pauli et al ., 2008 ; Shimazou and Aldrich, 2010 ). In the interviews in which the issue of free riding came up, however, groups did not seem to have experienced the phenomenon. A putative explanation for the lack of free-riding behavior is the incidence of accountability ( Slavin, 1991 ; Johnson and Johnson, 2009 ; Onwegbuezie et al ., 2009 ), as students definitely felt responsible for the end result. The way students spoke about their group members, however, was in terms of mutual trust rather than accountability. Students recognized differences in contribution but did not perceive this as problematic. They were empathic toward differences between students. If there were negative feelings at all, the low contributors were more apt to feel frustrated, indicating that the differences in contribution were, as Hall and Buzwell (2012) have suggested, involuntary and due to inadequacy rather than apathy or laziness.

In the five courses of this study, the combination of design factors seems to have prevented free riding. Although the causal nature of the relationship between design features of the group work and effective group processing cannot be claimed in the current study, the results indicate that, in particular, perceived autonomy and the challenging nature of the task evoked students’ motivation to make an effort. The relevance of the tasks, which required students to produce something new (to them) and something original and tangible, motivated students. The tasks were also open and complex, which are features that have already been found to promote deeper-level interactions than simple tasks ( Hertz-Lazarowitz, 1989 ; Cohen, 1994 ). Autonomy was a factor frequently mentioned as contributing to the effectiveness of the group work. Contradictory to Johnson and Johnson’s (2009) recommendation for teachers to structure processes, students of these courses designated the autonomy they had in choosing their topic and in organizing the process, as one of the factors increasing their motivation. Results from organizational research show that autonomy can, in fact, increase teamwork achievement, but only when positive interdependence is high ( Langfred, 2000 ). Autonomy combined with low interdependence decreases achievement, indicating that autonomy should be combined with challenging tasks. Although autonomy and level of challenge in a group assignment appears to be vital, instructors in different settings may need to use greater scaffolding.

Future Research and Concluding Remarks

It is important to keep in mind the small sample and restricted context when interpreting these findings. Although the results have been obtained in small-enrollment, upper-division courses, we think that our findings might also be transferable to large-enrollment courses, provided students will be working in self-directed small groups on substantial and relevant projects. As generalizability requires data on large populations, the findings of our five cases within a restricted context are not necessarily representative of the larger population. We believe, however, that there are strong reasons for our findings to be deemed “transferable” ( Lincoln and Guba, 1985 ) to comparable situations. While generalization is applied by researchers, transferability is a process performed by the readers of research ( Metcalfe, 2005 ). Unlike generalizability, transferability does not involve broad claims but invites readers of research to make connections between elements of a study and their own experiences ( Barnes et al ., 2012 ). According to Berliner (2002 , p. 19), implementing scientific findings is always difficult in education, “because humans in schools are embedded in complex and changing networks of social interaction.” Therefore, we do not claim to have produced broadly generalizable findings but instead invite the reader to identify how the findings can be transferred to his or her situation. Similar studies with data from other university contexts, such as other countries or other class settings, would help in understanding how the conditions that facilitate collaborative learning relate to different settings.

We assume, however, that the concept of evoking, rather than enforcing, positive interdependence by increasing autonomy and the challenge level of the task provides relevant insights for discourse on effective design of group work within life sciences education. Students in life sciences education, in general, are quite experienced in working in groups and in regulating their own work. Autonomy, combined with a challenging task, evoked interdependence and generated interaction as well as student motivation in these five cases. Structuring the process, for example by scripting, seems unnecessary for promoting student interaction. It was, in Dillenbourg’s (2002) words, not necessary to “didactisise” collaborative interactions or to disturb the autonomy and natural interactions of students. Moreover, structuring the process could have impeded the feeling of autonomy, which is crucial for student motivation (Deci and Ryan, 2000). Brewer and Klein (2006) came to a similar conclusion in their investigation of the influence of types of interdependence (roles, rewards, roles plus rewards, no structure) on student interaction. The groups with no structured interdependence had significantly more cognitive interactions involving content discussion than the other groups, indicating that structuring interdependence is not always necessary with university students. We suggest that collaborative learning with university students should be designed using challenging and relevant tasks that build shared ownership with students.

Acknowledgments

Drs. Kristin Denzer, Mario Stassen, and Fons Cremers are gratefully acknowledged for encouraging their students to participate in the interviews.

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What Is Collaborative Learning? Strategies, Use Cases, & Techniques (2024)

What you'll learn in this article:

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What is collaborative learning? Collaborative learning is the practice of students working collectively to solve problems, creating a dynamic environment of shared knowledge and skills. In this article, we define what is collaborative learning, illustrate its role in effective education, and provide guidelines for its application in your classroom.

What we will discover together:

• Collaborative learning is a learner-driven approach that fosters a social, interactive classroom ecosystem aimed at enhancing communication, negotiation, feedback, and problem-solving skills among students.
• Collaborative environments encourage student engagement and active participation, which lead to deeper understanding, critical thinking, knowledge retention, and the development of important self-management and leadership skills.
• Effective collaborative learning involves the use of structured strategies, supportive environments, and technological platforms like Disco , which facilitate group interaction and personalized learning experiences through advanced features and tools.

What is the Importance of Collaborative Learning?

Collaborative learning is a learner-driven approach where the classroom transforms into a thriving ecosystem of shared goals and joint intellectual effort.

In a collaborative learning environment, students work together intertwining their unique strands of knowledge to create a robust tapestry of understanding. Building on the foundation of social constructivism, collaborative learning embodies the principle that learning is inherently a social act, shaped by the vibrant interactions among peers and the community at large.

It’s an environment where communication, negotiation, feedback, and problem-solving are not just taught but lived, preparing students for a world that values cooperation and adaptability.

The essence of collaborative learning is to:

• Nurture the ability to work effectively in groups, recognize differences, and construct universal agreements through effective communication
• Foster a collaborative learning community, where challenges are tackled collectively, and every student contributes to the collective knowledge of the entire class
• Enhance learning outcomes and ensure that students are career-ready, armed with essential skills honed through experience

Collaborative vs. Cooperative Learning: The Key Differences

Exploring the world of collaborative and cooperative learning is like looking at different paths for group work. Collaborative learning is all about diving in and finding things out together, with everyone pitching in. It's like being on an adventure where everyone has a say in which way to go. Cooperative learning, though, is more like following a map with someone leading the way and everyone having a specific job to do.

While cooperative learning leans on structured projects and assessments of individual and team efforts, collaborative learning thrives in more informal settings, with students working together towards shared objectives.

The choice between these educational approaches, such as collaborative or cooperative learning, is influenced by the desired learning goals, the subject matter at hand, and the level of student engagement.

Cooperative learning is particularly beneficial when clear roles and organization can enhance peer teaching and feedback, leading to individual learning performance that is lifted by group success. Yet, when the situation calls for an informal setting or students with more learning experience, collaborative learning’s flexibility and emphasis on group autonomy come to the fore.

Why You Should Build Collaborative Learning Environments

Embark on a deeper exploration of the myriad advantages that collaborative learning environments offer. In these vibrant learning spaces, students are not merely passive recipients of knowledge; rather, they are active participants, crafting and shaping their learning experiences.

These environments serve as incubators for deeper understanding, heightened motivation, and keen critical thinking, which are indispensable in today’s fast-paced and complex world. The psychological and social benefits of such an educational approach are particularly effective in secondary schools and in the teaching of science subjects, where the learning process is often most demanding.

A collaborative learning environment is a fertile ground for academic achievement. In this type of community, active participation and the continuous exchange of ideas through discussion boards are positively correlated with students’ performance. It’s a space where:

• Student-faculty and participant-trainer interaction blossoms
• Students work together, taking ownership of their learning and engaging with the learning material on a profound level
• Collaborative activities boost knowledge retention
• Students forge new relationships and express diverse ideas
• Students develop self-management and leadership skills, which are critical for future development

It Boosts Student Retention and Success

In the collaborative classroom, every student is given a lifeline to success. Lower-attaining students, in particular, find a nurturing haven where peer support illuminates the path to understanding.

Through collaborative learning methods such as active participation and the scaffolding of continuous peer feedback, students develop a robust sense of ownership over the course material, reinforcing their academic achievement and student retention.

The creation of tangible outcomes, such as group discussion summaries, ensures that each member is accountable, providing a clear measure of their grasp on the subject matter.

This collective educational approach is a cornerstone in higher education, where the stakes are high, and the need for persistent student engagement is critical. By encouraging active engagement, collaborative learning can:

• Maintain students’ interest
• Foster a positive impact that ripples through their academic journey
• Cement important factor for success in the educational experience

It Fosters Critical Thinking and Problem-Solving Skills

Dive into the heart of collaborative learning activities, where critical thinking and problem-solving skills are not just developed but put to the test. Exposed to a kaleidoscope of perspectives, students are challenged to synthesize new knowledge, evaluate information swiftly, and craft well-reasoned arguments.

The incorporation of social learning into collaborative activities sparks a surge of creativity and ushers in a more dynamic approach to problem-solving, where new ideas flourish and new concepts take root.

Through strategies like the jigsaw technique, students become masters of their content domains, nurturing tailored problem-solving strategies and contributing to the cognitive development of the whole group.

While competition has its place, it’s important to ensure it catalyzes learning rather than overshadowing the educational approach. Collaborative learning builds students’ self-esteem by fostering a sense of responsibility and offering opportunities for peer-to-peer instruction, thus paving the way for good development practice.

It Enhances Social and Communication Skills

Within the collaborative learning environment, students are encouraged to scale the heights of social and communication excellence. Team-building activities and exposure to a variety of viewpoints not only enrich learning but also prepare students for the diverse professional and social learning environments they will encounter after graduation.

Through active participation in communication exercises, students hone their public speaking and active listening skills, learning to express and challenge ideas with clarity and confidence.

Peer learning , a pillar of collaborative learning, involves students working together in a collaborative environment to discuss concepts, solve problems, and share knowledge.

It’s a process that enhances collective problem-solving skills and leads to a deeper understanding of collaborative experiences. Reflective activities following collaborative sessions offer students a mirror to their growth, helping them articulate the benefits gained and challenges faced, and fostering a sense of shared responsibility within the learning community.

5 Use Cases to Implement Effective Collaborative Learning Strategies

Transitioning from the ‘why’ to the ‘how, ’ successful implementation of collaborative learning strategies is key to unlocking the full potential of this educational approach.

Effective collaboration transcends the simple act of grouping students; it demands structured approaches that are tailored to the objectives at hand and the complexities of the project. A vibrant educational experience is cultivated not just through routine group work but also through implementing a variety of structures, from ad-hoc groups for short-term tasks to long-term project teams.

Creating an interactive and supportive learning environment is a multi-faceted endeavor. It requires:

• Students to form their accountability measures
• Instructors to regularly evaluate progress
• Facilitation of face-to-face collaboration that aligns with students’ schedules
• Use of collaborative learning platforms, which provide features such as sub-groups, targeted events, content sharing, discussions, and engagement tracking that are critical to the learning process.

Use Case #1: Utilizing Technology to Facilitate Collaboration

In the digital age, technology has become a cornerstone in facilitating collaboration and enhancing the learning experience. Advances in social media and mobile learning apps have revolutionized communication patterns, promoting collaboration through collective exploration and interaction.

Social learning platforms such as Disco provide spaces where students can engage in discourse, access materials, and connect with both peers and instructors, seamlessly blending learning with social interaction.

The convenience and cost-effectiveness of mobile devices and social media are especially valued by modern students, as these tools empower them to engage in academic partnerships and procure educational information.

With students’ familiarity with digital landscapes, the integration of technology in classrooms promotes greater engagement with non-AI & AI learning content and extends the reach of the classroom beyond its physical boundaries.

Interactive technologies like digital whiteboards and dedicated applications like the Disco app enhance learner engagement by fostering continuous communication and learning opportunities.

The Power of Groups and Sub-Groups in Collaborative Learning

"Disco has allowed us to build a scalable education offering at Dribbble. The subgroups function lets us break the hundreds of students who enroll in each cohort into mentorship groups, giving each student a personal, hands-on & intimate learning experience.” - Dribbble.com

Groups and sub-groups are the building blocks of a robust collaborative learning environment. They are the crucibles in which the alchemy of learning takes place, transforming individual knowledge into collective wisdom through assigning specific roles to group members.

How do you effectively organize students within your social learning LMS ? Begin by determining whether to group them by interests, geographic location, cohort, or skill level, and then devise creative social group names . If you're at a loss for names, you can default to simple labels such as Group A, Group B, or Group C.

Navigate the Admin Area -> Members -> Groups, and then click '+ Group' to add a custom group. Make sure you created a Disco account to complete this exercise.

In this example, I am creating a group for those new members who wish to become Ambassadors. I have entered the group name, selected a color, set the visibility, and added the existing members who have expressed an interest in joining this group.

Here's what it looks like after saving changes:

📺 Watch this short tutorial to learn more:

For larger learning organizations, the ability to create mini-communities within the collaborative learning framework is invaluable. These mini-communities, or cohorts, can be specifically tailored to focus on group activities that are ideal for project-based learning approaches and learning sprints.

By dividing the larger organization into more manageable sub-groups, each cohort can engage in targeted project work, fostering a more intimate and focused learning experience that aligns with the organization's broader educational goals.

With the Disco platform, you can create subgroups to ensure active participation and effective collaboration among your learners. With group sizes of 3-5 members showing the most positive impact on learning outcomes, the strength of collaborative learning is maximized.

📺 Learn to create subgroups in less than a minute:

Diversity within these groups is not just welcomed, but celebrated, enriching the collaborative learning experience as students prepare for the varied dynamics of the real-world workplace. By presenting a topical conflict or posing well-defined questions, facilitators can steer group discussions toward effectiveness and depth.

Furthermore, collaborative presentations across departmental teams foster knowledge sharing and collective problem-solving, weaving together the fabric of a truly collaborative learning community.

Use Case #2: Creating a Supportive Collaborative Environment

A supportive collaborative environment is the lifeblood of effective group learning. It is where students are assured of their place and voice, with teachers playing a pivotal role in assisting those who may struggle or not contribute.

Close monitoring of group dynamics is essential, ensuring that every student is heard and their contributions are valued. Facilitators must navigate group processes, intervene when necessary, and cultivate a positive learning environment that encourages students to take an active role in their education.

In such an environment, the facilitator’s role extends beyond mere oversight; it involves organizing communication, coordination, and providing support to all participants.

Creating clear collaborative rules and advocating for open discussion within the classroom enhances student engagement and contribution, making the collaborative environment a place where learning thrives. A well-defined process for collaborative work, which includes delivering detailed instructions and involving students in rule creation, is integral to the success of group work.

Furthermore, the use of surveys to consider students’ varied backgrounds and learning styles can stimulate diversity and equity in group selection.

An example of this is posting a poll in your feed to easily gather feedback from your learners and community members. All it takes is a simple click on 'add poll' to set up your questions and choices. In the example below, I utilized Disco AI , our multifunctional AI native tool that not only generates social posts but also creates curriculum and responds to member inquiries.

After you've set up your poll, this is how it will appear as a post within your feed. Learners can now cast or change their votes before the deadline. Additionally, they can react, write comments, and bookmark the post, making collaboration seamless and intuitive.

Use Case #3: Driving Collaborative Feedback Through Sub-Groups

Sub-groups within the collaborative framework are instrumental in driving feedback and enhancing the learning experience. They provide a platform for peer teaching, where students can hone their expertise in specific areas through methods like the Jigsaw technique before imparting that knowledge to their home group.

This not only ensures deeper engagement with the material but also fosters a collaborative approach where students can provide and receive feedback on their tasks, leveraging the collective intellect of the group.

Facilitate this peer learning while your students are engaged with your course materials. After you've created a course on the Disco platform, you can design various content types such as lessons, tasks, quizzes, and assignments. For the assignments, enable learners in the subgroups to review their peers' submissions and provide feedback directly within the lesson's comment section.

Simply click 'settings' and scroll down to adjust the 'submission visibility' to 'sub-group members'. Be aware that this setting is not available unless you have already established subgroups within the product. Ensure you've set them up beforehand.

Furthermore, by posting comments, you can foster a collaborative learning atmosphere by encouraging students to share their insights and knowledge as they progress through the lessons. Their classmates can then engage by reacting to and responding to these comments, ensuring the learning environment remains interactive and collaborative even during individual study times.

Structured within the classroom to maximize collaborative feedback among peers, sub-groups serve as a microcosm of the larger collaborative environment. They are particularly adept at:

• Engaging introverted students
• Ensuring that every voice is heard and every perspective is considered
• Ensuring balanced participation across different personality types.

Use Case #4: Designing Engaging Collaborative Activities Through Event-Driven Group Sessions

To captivate the minds of learners and maximize engagement, the design of collaborative learning activities should be both precise and imaginative. Group sessions created through events stand out as the best part of designing these activities, as they bring students together in a dynamic and interactive setting.

With well-defined objectives, these collaborative learning approaches aim to build knowledge, shift attitudes, and enhance skills while ensuring clarity in team roles and the availability of tools for managing time, resources, and conflicts. Innovative techniques such as ‘Fishbowl,’ ‘Pairs Check,’ ‘Think-Pair-Share,’ and ‘Think-Pair-Square’ breathe life into discussions, ensuring active participation from every student.

Start creating an event within your course. If this is your first time doing so, watch this 2-minute tutorial:

To ensure your event or group session is exclusively for a specific group or subgroup, navigate to 'settings', scroll down, and modify the event access to 'private'. Subsequently, you will be able to select the groups/subgroups that are intended to attend.

The setting for these event-driven group sessions is just as crucial as the activities themselves. By moving beyond the traditional classroom and into diverse environments, whether virtual or physical, students’ senses are engaged, the focus is sharpened, and a deeper level of collaboration is achieved.

Use Case #5: Measuring Engagement and Participation

Assessing the impact of collaborative learning activities requires a comprehensive look at how students engage with the material and participate in the learning process. Monitoring student engagement encompasses assessing cognitive, behavioral, and emotional experiences through various data and observations, such as:

• Classroom participation
• Presentation assignments
• Group discussions
• Peer evaluations

By utilizing journals as a reflective tool, teachers can encourage students’ engagement and understanding of the learning process over time, providing valuable insights into the effectiveness of collaborative activities.

An engagement scoring system and learner progress reports can provide a quantitative measure of learners’ participation levels within collaborative platforms, offering a clear picture of how actively students are involved in their learning.

Additionally, peer and self-assessment techniques are employed to evaluate individual contributions, influencing grading decisions and promoting active learning. By measuring these aspects of the learning experience, educators can ensure that collaborative activities are not only engaging but also lead to meaningful academic achievement.

A step-by-step guide to build and grow a thriving learning community.

Introducing DISCO : The #1 Social & Collaborative Learning Platform Powered by AI

Disco.co shines as the premier platform for social and collaborative learning, skillfully designed for up-skilling, customer and partner enablement, cohort training, and accelerator programs. Its AI-powered capabilities make learning a highly engaging and seamlessly operated experience.

With the backing of GSV, a leading edtech investor, Disco has been recognized as Fast Co’s most innovative edtech of the year and Edtech Breakthrough’s Startup of the Year. Its impressive client roster includes the Toronto Board of Trade, Kaplan, Coursehero, MonitorDeloitte, XPrize, and Baptist Health, showcasing its widespread impact and trust within the industry.

Key Features:

• Advanced course builder
• Quizzes, assignments, lessons, tasks, certificates
• Discussion boards, forums, and messaging
• Event management tool with video streaming and Zoom integration
• Full customization of the platform from branding, domain, and labels
• Groups and subgroups for peer learning
• Integration, automation, and course duplication
• Engagement scoring and learner progress reports
• Advanced analytics and insights
• Mobile app and custom branded app - coming soon!
• SSO, API, and other enterprise features
• Membership plans, public pages, and Stripe integration
• Disco Academy and many more!

Disco is not just a learning platform; it's a transformative social learning platform that's setting the standard for collaborative learning in the digital age.

Take the Next Step in Your Educational Journey with Disco's 14-day Free Trial!

By signing up with a 14-day free trial , users can enhance peer interaction and group learning, which are critical components of effective collaborative learning in the classroom. The platform’s suite of tools is designed to facilitate group discussion, idea sharing, and collective knowledge construction, making it an invaluable asset for educators and students alike.

Meanwhile, schedule a personalized demo to gain an in-depth understanding of Disco's extensive capabilities and have your questions expertly answered by our team.

Frequently Asked Questions (FAQs) About Collaborative Learning

What exactly is collaborative learning.

Collaborative learning is an educational approach where individuals work together to achieve shared learning goals. It emphasizes the collective effort of group members to solve problems, share knowledge, and learn from each other, thereby enriching the educational experience.

How Does Collaborative Learning Boost Student Retention and Success?

By fostering an environment of peer support and active engagement, collaborative learning significantly boosts student retention and success. It encourages continuous peer feedback and active participation, which deepens students' understanding and fosters a sense of ownership over the learning material, resulting in a more engaging and effective learning experience.

Can Collaborative Learning Enhance Critical Thinking and Problem-Solving Abilities?

Absolutely! Collaborative learning enhances critical thinking and problem-solving abilities by exposing learners to a variety of perspectives and challenges. This dynamic interaction stimulates engagement and promotes innovative, creative approaches to problem-solving.

How Are Groups and Sub-Groups Effectively Utilized in Collaborative Learning?

Groups and sub-groups are utilized effectively in collaborative learning by ensuring balanced participation and leveraging diversity. They facilitate peer teaching and foster a collaborative learning atmosphere through targeted events and structured activities, which significantly improves the learning experience for all participants.

What Features Position Disco as a Premier Collaborative Learning Platform?

Disco stands out as a premier collaborative learning platform thanks to its comprehensive suite of interactive features, which include engaging learning tools, multimedia content integration, real-time progress tracking, and seamless AI and productivity tool integration. Additionally, its extensive customization options cater to a wide range of learning styles and preferences, making it a top choice for collaborative learning endeavors.

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Supercharge your community.

The Learning Community Playbook delivers actionable insights, innovative frameworks, and valuable strategies to spark engagement, nurture growth, and foster deeper connections. Access this resource and start building a vibrant learning ecosystem today!

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How Collaborative Learning Enhances Critical Thinking and Problem-Solving Skills

Learning is a continuous process of acquiring knowledge, values, and skills. For learning to be meaningful, this process has to be in concurrence with the goals, requirements, and strengths of learners.

Yet, personal objectives should not exist in isolation within the broader educational context. Instead, they need to integrate seamlessly into it. This is where collaborative learning emerges as a catalyst for meaningful educational experiences. 

Collaboration not only enriches the learning process but also creates avenues for heightened engagement. In this regard, educators can leverage cloud-based digital textbook platforms like KITABOO to foster collaboration and drive home the desired outcomes. It not only facilitates seamless interaction but also provides a platform for students to collectively tackle challenges, cultivating a dynamic environment for skill development.

This blog offers insights into how collaborative learning can enhance critical thinking and problem-solving skills. Read on!

Table of Contents:

I. What is Collaborative Learning?

II. Understanding Critical Thinking and Problem-Solving Skills

III. How Does Collaborative Learning Help in Fostering Critical Thinking and Problem-Solving Skills?

Open-Ended Questions and Group Discussions

Real-world scenario challenges, cooperative learning strategies, modeling and scaffolding, peer evaluation activities.

IV. Wrapping Up

What is Collaborative Learning?

Collaborative learning refers to a learning style that fosters teamwork and social interaction. It engages students in working together in pairs or small groups, pooling their collective intellectual resources to complete various learning tasks.

This learning style follows a student-centric approach, which allows learners to understand, learn, seek solutions, or create something through discussions and sharing of ideas with their peers.

When used effectively, collaboration can increase engagement by providing cognitive challenges. Additionally, it can boost self-esteem and motivate students to attain learning milestones.

Today, technological innovations have made it easier for educators to implement collaborative learning strategies. With the help of a platform like KITABOO, they can easily create and deliver educational content that facilitates collaborative discussion and learning. This way, students can actively participate in the learning process, share insights, and benefit from diverse perspectives.

Understanding Critical Thinking and Problem-Solving Skills

Both critical thinking and problem-solving are crucial skills that are deeply intertwined.

The ability to interpret, analyze, and evaluate information logically to make informed decisions is referred to as critical thinking. This skill helps individuals approach challenges with an analytical and strategic mindset. It enables them to weigh all aspects of a problem and consider potential outcomes based on the available options.

Problem-solving refers to the ability to analyze a problem, identify the best course of action, and implement the solution. This skill helps individuals understand the root cause of a problem and consider the existing options before taking a call.

Together, these skills form a powerful toolset for navigating complex situations, fostering informed decision-making, and driving effective solutions in various contexts.

How Does Collaborative Learning Help in Fostering Critical Thinking and Problem-Solving Skills?

Critical thinking and problem-solving skills enable individuals to understand the implications of their decisions, leading to improved decision-making abilities.

Here’s how educators can leverage collaborative learning to help students develop critical thinking and problem-solving skills:

Open-ended questions and discussions count among the most effective ways of collaborative learning. They require students to share their reasoning, explain their perspectives, or justify their opinions. Such collaborative discussions boost critical thinking and problem-solving skills.

Educators can use open-ended questions to encourage students to think outside the box, explore different perspectives, and challenge their assumptions.

Challenging tasks and scenarios related to real-world problems and situations are a great way to foster critical thinking and problem-solving skills . Educators can ask students to solve the challenges as part of their group activities.

By creating tasks and scenarios that engage students and captivate their curiosity, educators can motivate them to find the right solutions. 

This approach serves as an ideal foundation for collaborative learning , where students are motivated to apply their knowledge and skills in significant, realistic contexts. In doing so, they benefit from a dynamic learning environment that fosters collective problem-solving and knowledge sharing.

Cooperative learning strategies boost collaboration and communication among students. They enable students to gain exposure to diverse perspectives, opinions, and ideas.

Collaboration and communication also help students to develop qualities like respect, empathy, communication skills, etc. Such diverse perceptions and qualities play an essential role in developing a mindset for critical thinking and problem-solving.

Modeling and scaffolding are pedagogical strategies where educators exemplify the step-by-step process of problem-solving.

This method typically encompasses stages such as identifying the problem, developing potential solutions, brainstorming alternatives, experimenting with theories or ideas, and analyzing the results.

For effective modeling and scaffolding, educators can employ a variety of innovative techniques. These might include integrating content with visual aids like graphic organizers, employing ‘think-aloud’ strategies to verbalize the thought process, and using rubrics for structured evaluation.

Peer evaluation is a purposeful activity designed to enhance critical thinking and problem-solving skills among students. In this activity, students exchange constructive feedback on tasks or projects with their peers.

Educators can facilitate this by organizing students into small groups, where each student’s work is reviewed and critiqued by the others in turn. Such peer-to-peer collaboration allows students to become actively involved in the learning process.

This activity is not just a learning exercise; it’s a social process that fosters a deeper understanding through dialogue.

Wrapping Up

Collaborative learning is an impactful educational approach that can help students enhance their critical thinking and problem-solving skills effectively.

By encouraging students to collaborate on tasks and activities, educators can enhance their educational experience. This way, they not only enable students to strengthen their understanding of concepts and ideas but also help them improve essential interpersonal skills. 

With the advantage of a well-recognized digital textbook platform like KITABOO , educators can easily engage students in collective learning activities. As an educator, you can leverage this platform to create interactive and engaging content that promotes group discussions and teamwork in the long run.

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Scott Hanson

Scott Hanson is the AVP of Business Development at Hurix. He is an experienced Business Development & Publishing Technology professional with expertise in dealing with Societies & Non-Profits.

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