case studies in education industry

12 Digital Transformation Trends & Use Cases in Education in '24

The COVID-19 pandemic has accelerated digital transformation in education as nearly 1.5 billion students across the world became distanced from their classrooms. However, online education is not the only way digital technologies transform the teaching and learning experience. We explore how digital transformation affects the education sector with key technologies and trends.

What does digital transformation mean for education?

Digital transformation in education means digitalizing processes and products to improve the teaching and learning experience for everyone involved.

Digital transformation in education focuses on:

• Accessibility: Digital technologies enable learners (e.g. students, employees) to access learning resources more easily and less expensively than traditional education. People across the world, from all ages, with different socioeconomic statuses have access to classes and resources through the internet. Technologies such as text-to-speech remove the barriers for students with disabilities.
• Interactive learning: Micro lessons, videos, interactive tests, gamification, etc. are all different learning formats that are transforming education with a more interactive learning environment. For example, interactive language teaching apps like Duolingo claim to reach more US learners interested in foreign languages than the school system.
• Customized learning: Computer technology and AI enable educational methods such as adaptive learning where each learner is allowed to learn in a way appropriate to them.

Why is digital transformation in education important now?

School shutdowns and distance education are some of the most profound effects of COVID-19 which has demonstrated the importance and urgency of incorporating digital technologies into education. Even before the pandemic, the education industry was in the process of digital transformation. The image below from research by HolonIQ shows that global EdTech (education technology) venture capital funding had increased from $500 million to $7 billion between 2010 and 2019. The effect of the pandemic is also staggering as the investments almost tripled in 2021.

What are the key technologies and trends enabling digital transformation in education?

1- artificial intelligence.

Artificial intelligence applications can undertake simple but time-consuming tasks in education to ease the workload of educators or school staff. They can also be used to deliver an improved and custom learning experience to students. The applications include:

Improving student performance

• Voice-to-text  technologies transforming classes to notes are helpful to students with hearing impairment
• Text-to-voice technologies help dyslexic students learn more effectively by listening instead of reading.
• Personalized learning  can involve a diverse set of technologies including AI to elicit how a student learns best and tailor the education accordingly. Blended and adaptive learning are examples of methods that combine face-to-face instruction with digital learning tools that encourage students to learn by discovery.

Increasing the effectiveness of staff

• Intelligent FAQ chatbots  to answer questions about class, homework, campus, etc. Chatbots can act as virtual advisors for college students which can free up professors’ time.
• Domain specific chatbots: College admission is a complex and stressful process for high school students. College counsellors have limited time to support hundreds of students. Chatbots focused on the admission process can support students in this challenging and important process
• Educational businesses also have back office functions like finance. Process mining can help identify inefficiencies in the back office functions. Read our article on educational process mining to learn more about the applications of process mining in education.
• Individual automation technologies like RPA or combining multiple automation technologies (also called hyperautomation) can help save the time of support staff.

Explore the top 20 use cases of RPA in education in more detail.

2- Analytics

Digital technologies enable schools to collect and analyze a wealth of data about their students to monitor and enhance their performance. Using traditional and advanced analytics, they can determine where students struggle and succeed, develop new methods, and test whether these methods yield expected results.

3- Augmented reality/Virtual reality

Augmented reality and virtual reality (AR/VR) technologies can create interactive and virtual environments for students and help them better engage with the subject. These technologies can enable virtual field trips to historical locations or facilitate learning-by-doing for applied sciences and medicine. The distance learning experience can also be improved with AR/VR technologies.

4- Internet of Things (IoT)

The increasing use of smartphones and other edge devices improves the connectivity between students and their educational institutions by enabling real-time communication and data transfer. IoT devices can also be used to track young children’s absence or presence in class and alert teachers and parents for their security.

5- Online learning

Distance learning (or remote learning) through Zoom or Skype was an emergency response from schools and colleges to the pandemic. Educational institutions can also build their own online class systems, commonly called learning management systems (LMS), and integrate them into their websites or platforms. This will allow them to customize the online learning experience according to the needs of learners or the subject of the course.

6- Smart classes

Digital technologies have also improved face-to-face learning. Smart classes equipped with smart boards, computers, internet connections, projectors, etc. unlock the ways of delivering learning resources to students that were impossible with a blackboard and chalks.

What are some case studies?

• Google Expedition is an education app that contains 1000 VR and 100 AR tours. It helps teachers and students to explore art galleries, museums, underwater, or outer space. Google is now sunsetting the Expedition app and migrating the tours to Google Arts & Culture and making it available to everyone.

• Arizona State University has leveraged Amazon Echo Dot devices in their campus and student resident halls as voice assistants that provide information about the university for students, faculty, staff, and alumni.
• EdTech company Carnegie Learning provides technology solutions to K-12 schools. Their math learning platform MATHia uses artificial intelligence to act as a personal tutor that adjusts itself continually to each student and delivers a personalized learning experience.

How can educational institutions transform digitally?

We outlined the steps to achieve digital transformation and AI transformation . These steps are similar across industries. These involve understanding the challenges of your business and buying or building solutions to resolve these challenges. When it comes to building custom solutions, working with agencies that have done it before can help.

For more on digital transformation:

• Digital Transformation
• Digital Transformation Statistics
• Digital Transformation Consulting

You can also check our data-driven, sortable/filterable list of digital transformation consultant companies .

If you have more questions about digital transformation or digital education, let us know:

Cem has been the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per similarWeb) including 60% of Fortune 500 every month. Cem's work has been cited by leading global publications including Business Insider , Forbes, Washington Post , global firms like Deloitte , HPE, NGOs like World Economic Forum and supranational organizations like European Commission . You can see more reputable companies and media that referenced AIMultiple. Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised businesses on their enterprise software, automation, cloud, AI / ML and other technology related decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization. He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider . Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.

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Top 40 Most Popular Case Studies of 2021

Two cases about Hertz claimed top spots in 2021's Top 40 Most Popular Case Studies

Two cases on the uses of debt and equity at Hertz claimed top spots in the CRDT’s (Case Research and Development Team) 2021 top 40 review of cases.

Hertz (A) took the top spot. The case details the financial structure of the rental car company through the end of 2019. Hertz (B), which ranked third in CRDT’s list, describes the company’s struggles during the early part of the COVID pandemic and its eventual need to enter Chapter 11 bankruptcy. 

The success of the Hertz cases was unprecedented for the top 40 list. Usually, cases take a number of years to gain popularity, but the Hertz cases claimed top spots in their first year of release. Hertz (A) also became the first ‘cooked’ case to top the annual review, as all of the other winners had been web-based ‘raw’ cases.

Besides introducing students to the complicated financing required to maintain an enormous fleet of cars, the Hertz cases also expanded the diversity of case protagonists. Kathyrn Marinello was the CEO of Hertz during this period and the CFO, Jamere Jackson is black.

Sandwiched between the two Hertz cases, Coffee 2016, a perennial best seller, finished second. “Glory, Glory, Man United!” a case about an English football team’s IPO made a surprise move to number four.  Cases on search fund boards, the future of malls,  Norway’s Sovereign Wealth fund, Prodigy Finance, the Mayo Clinic, and Cadbury rounded out the top ten.

Other year-end data for 2021 showed:

• Online “raw” case usage remained steady as compared to 2020 with over 35K users from 170 countries and all 50 U.S. states interacting with 196 cases.
• Fifty four percent of raw case users came from outside the U.S..
• The Yale School of Management (SOM) case study directory pages received over 160K page views from 177 countries with approximately a third originating in India followed by the U.S. and the Philippines.
• Twenty-six of the cases in the list are raw cases.
• A third of the cases feature a woman protagonist.
• Orders for Yale SOM case studies increased by almost 50% compared to 2020.
• The top 40 cases were supervised by 19 different Yale SOM faculty members, several supervising multiple cases.

CRDT compiled the Top 40 list by combining data from its case store, Google Analytics, and other measures of interest and adoption.

All of this year’s Top 40 cases are available for purchase from the Yale Management Media store .

And the Top 40 cases studies of 2021 are:

1.   Hertz Global Holdings (A): Uses of Debt and Equity

2.   Coffee 2016

3.   Hertz Global Holdings (B): Uses of Debt and Equity 2020

4.   Glory, Glory Man United!

5.   Search Fund Company Boards: How CEOs Can Build Boards to Help Them Thrive

6.   The Future of Malls: Was Decline Inevitable?

7.   Strategy for Norway's Pension Fund Global

8.   Prodigy Finance

9.   Design at Mayo

10. Cadbury

11. City Hospital Emergency Room

13. Volkswagen

14. Marina Bay Sands

15. Shake Shack IPO

16. Mastercard

17. Netflix

18. Ant Financial

19. AXA: Creating the New CR Metrics

20. IBM Corporate Service Corps

21. Business Leadership in South Africa's 1994 Reforms

22. Alternative Meat Industry

23. Children's Premier

24. Khalil Tawil and Umi (A)

25. Palm Oil 2016

26. Teach For All: Designing a Global Network

27. What's Next? Search Fund Entrepreneurs Reflect on Life After Exit

28. Searching for a Search Fund Structure: A Student Takes a Tour of Various Options

30. Project Sammaan

31. Commonfund ESG

32. Polaroid

33. Connecticut Green Bank 2018: After the Raid

34. FieldFresh Foods

35. The Alibaba Group

36. 360 State Street: Real Options

37. Herman Miller

38. AgBiome

39. Nathan Cummings Foundation

40. Toyota 2010

• Our Mission

Making Learning Relevant With Case Studies

The open-ended problems presented in case studies give students work that feels connected to their lives.

To prepare students for jobs that haven’t been created yet, we need to teach them how to be great problem solvers so that they’ll be ready for anything. One way to do this is by teaching content and skills using real-world case studies, a learning model that’s focused on reflection during the problem-solving process. It’s similar to project-based learning, but PBL is more focused on students creating a product.

Case studies have been used for years by businesses, law and medical schools, physicians on rounds, and artists critiquing work. Like other forms of problem-based learning, case studies can be accessible for every age group, both in one subject and in interdisciplinary work.

You can get started with case studies by tackling relatable questions like these with your students:

• How can we limit food waste in the cafeteria?
• How can we get our school to recycle and compost waste? (Or, if you want to be more complex, how can our school reduce its carbon footprint?)
• How can we improve school attendance?
• How can we reduce the number of people who get sick at school during cold and flu season?

Addressing questions like these leads students to identify topics they need to learn more about. In researching the first question, for example, students may see that they need to research food chains and nutrition. Students often ask, reasonably, why they need to learn something, or when they’ll use their knowledge in the future. Learning is most successful for students when the content and skills they’re studying are relevant, and case studies offer one way to create that sense of relevance.

Teaching With Case Studies

Ultimately, a case study is simply an interesting problem with many correct answers. What does case study work look like in classrooms? Teachers generally start by having students read the case or watch a video that summarizes the case. Students then work in small groups or individually to solve the case study. Teachers set milestones defining what students should accomplish to help them manage their time.

During the case study learning process, student assessment of learning should be focused on reflection. Arthur L. Costa and Bena Kallick’s Learning and Leading With Habits of Mind gives several examples of what this reflection can look like in a classroom: 

Journaling: At the end of each work period, have students write an entry summarizing what they worked on, what worked well, what didn’t, and why. Sentence starters and clear rubrics or guidelines will help students be successful. At the end of a case study project, as Costa and Kallick write, it’s helpful to have students “select significant learnings, envision how they could apply these learnings to future situations, and commit to an action plan to consciously modify their behaviors.”

Interviews: While working on a case study, students can interview each other about their progress and learning. Teachers can interview students individually or in small groups to assess their learning process and their progress.

Student discussion: Discussions can be unstructured—students can talk about what they worked on that day in a think-pair-share or as a full class—or structured, using Socratic seminars or fishbowl discussions. If your class is tackling a case study in small groups, create a second set of small groups with a representative from each of the case study groups so that the groups can share their learning.

4 Tips for Setting Up a Case Study

1. Identify a problem to investigate: This should be something accessible and relevant to students’ lives. The problem should also be challenging and complex enough to yield multiple solutions with many layers.

2. Give context: Think of this step as a movie preview or book summary. Hook the learners to help them understand just enough about the problem to want to learn more.

3. Have a clear rubric: Giving structure to your definition of quality group work and products will lead to stronger end products. You may be able to have your learners help build these definitions.

4. Provide structures for presenting solutions: The amount of scaffolding you build in depends on your students’ skill level and development. A case study product can be something like several pieces of evidence of students collaborating to solve the case study, and ultimately presenting their solution with a detailed slide deck or an essay—you can scaffold this by providing specified headings for the sections of the essay.

Problem-Based Teaching Resources

There are many high-quality, peer-reviewed resources that are open source and easily accessible online.

• The National Center for Case Study Teaching in Science at the University at Buffalo built an online collection of more than 800 cases that cover topics ranging from biochemistry to economics. There are resources for middle and high school students.
• Models of Excellence , a project maintained by EL Education and the Harvard Graduate School of Education, has examples of great problem- and project-based tasks—and corresponding exemplary student work—for grades pre-K to 12.
• The Interdisciplinary Journal of Problem-Based Learning at Purdue University is an open-source journal that publishes examples of problem-based learning in K–12 and post-secondary classrooms.
• The Tech Edvocate has a list of websites and tools related to problem-based learning.

In their book Problems as Possibilities , Linda Torp and Sara Sage write that at the elementary school level, students particularly appreciate how they feel that they are taken seriously when solving case studies. At the middle school level, “researchers stress the importance of relating middle school curriculum to issues of student concern and interest.” And high schoolers, they write, find the case study method “beneficial in preparing them for their future.”

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Center for Teaching

Case studies.

Print Version

Case studies are stories that are used as a teaching tool to show the application of a theory or concept to real situations. Dependent on the goal they are meant to fulfill, cases can be fact-driven and deductive where there is a correct answer, or they can be context driven where multiple solutions are possible. Various disciplines have employed case studies, including humanities, social sciences, sciences, engineering, law, business, and medicine. Good cases generally have the following features: they tell a good story, are recent, include dialogue, create empathy with the main characters, are relevant to the reader, serve a teaching function, require a dilemma to be solved, and have generality.

Instructors can create their own cases or can find cases that already exist. The following are some things to keep in mind when creating a case:

• What do you want students to learn from the discussion of the case?
• What do they already know that applies to the case?
• What are the issues that may be raised in discussion?
• How will the case and discussion be introduced?
• What preparation is expected of students? (Do they need to read the case ahead of time? Do research? Write anything?)
• What directions do you need to provide students regarding what they are supposed to do and accomplish?
• Do you need to divide students into groups or will they discuss as the whole class?
• Are you going to use role-playing or facilitators or record keepers? If so, how?
• What are the opening questions?
• How much time is needed for students to discuss the case?
• What concepts are to be applied/extracted during the discussion?
• How will you evaluate students?

To find other cases that already exist, try the following websites:

• The National Center for Case Study Teaching in Science , University of Buffalo. SUNY-Buffalo maintains this set of links to other case studies on the web in disciplines ranging from engineering and ethics to sociology and business
• A Journal of Teaching Cases in Public Administration and Public Policy , University of Washington

For more information:

• World Association for Case Method Research and Application

Book Review :  Teaching and the Case Method , 3rd ed., vols. 1 and 2, by Louis Barnes, C. Roland (Chris) Christensen, and Abby Hansen. Harvard Business School Press, 1994; 333 pp. (vol 1), 412 pp. (vol 2).

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In This Article Expand or collapse the "in this article" section Case Study in Education Research

Introduction, general overview and foundational texts of the late 20th century.

• Conceptualisations and Definitions of Case Study
• Case Study and Theoretical Grounding
• Choosing Cases
• Methodology, Method, Genre, or Approach
• Case Study: Quality and Generalizability
• Multiple Case Studies
• Exemplary Case Studies and Example Case Studies
• Criticism, Defense, and Debate around Case Study

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Case Study in Education Research by Lorna Hamilton LAST REVIEWED: 27 June 2018 LAST MODIFIED: 27 June 2018 DOI: 10.1093/obo/9780199756810-0201

It is important to distinguish between case study as a teaching methodology and case study as an approach, genre, or method in educational research. The use of case study as teaching method highlights the ways in which the essential qualities of the case—richness of real-world data and lived experiences—can help learners gain insights into a different world and can bring learning to life. The use of case study in this way has been around for about a hundred years or more. Case study use in educational research, meanwhile, emerged particularly strongly in the 1970s and 1980s in the United Kingdom and the United States as a means of harnessing the richness and depth of understanding of individuals, groups, and institutions; their beliefs and perceptions; their interactions; and their challenges and issues. Writers, such as Lawrence Stenhouse, advocated the use of case study as a form that teacher-researchers could use as they focused on the richness and intensity of their own practices. In addition, academic writers and postgraduate students embraced case study as a means of providing structure and depth to educational projects. However, as educational research has developed, so has debate on the quality and usefulness of case study as well as the problems surrounding the lack of generalizability when dealing with single or even multiple cases. The question of how to define and support case study work has formed the basis for innumerable books and discursive articles, starting with Robert Yin’s original book on case study ( Yin 1984 , cited under General Overview and Foundational Texts of the Late 20th Century ) to the myriad authors who attempt to bring something new to the realm of case study in educational research in the 21st century.

This section briefly considers the ways in which case study research has developed over the last forty to fifty years in educational research usage and reflects on whether the field has finally come of age, respected by creators and consumers of research. Case study has its roots in anthropological studies in which a strong ethnographic approach to the study of peoples and culture encouraged researchers to identify and investigate key individuals and groups by trying to understand the lived world of such people from their points of view. Although ethnography has emphasized the role of researcher as immersive and engaged with the lived world of participants via participant observation, evolving approaches to case study in education has been about the richness and depth of understanding that can be gained through involvement in the case by drawing on diverse perspectives and diverse forms of data collection. Embracing case study as a means of entering these lived worlds in educational research projects, was encouraged in the 1970s and 1980s by researchers, such as Lawrence Stenhouse, who provided a helpful impetus for case study work in education ( Stenhouse 1980 ). Stenhouse wrestled with the use of case study as ethnography because ethnographers traditionally had been unfamiliar with the peoples they were investigating, whereas educational researchers often worked in situations that were inherently familiar. Stenhouse also emphasized the need for evidence of rigorous processes and decisions in order to encourage robust practice and accountability to the wider field by allowing others to judge the quality of work through transparency of processes. Yin 1984 , the first book focused wholly on case study in research, gave a brief and basic outline of case study and associated practices. Various authors followed this approach, striving to engage more deeply in the significance of case study in the social sciences. Key among these are Merriam 1988 and Stake 1995 , along with Yin 1984 , who established powerful groundings for case study work. Additionally, evidence of the increasing popularity of case study can be found in a broad range of generic research methods texts, but these often do not have much scope for the extensive discussion of case study found in case study–specific books. Yin’s books and numerous editions provide a developing or evolving notion of case study with more detailed accounts of the possible purposes of case study, followed by Merriam 1988 and Stake 1995 who wrestled with alternative ways of looking at purposes and the positioning of case study within potential disciplinary modes. The authors referenced in this section are often characterized as the foundational authors on this subject and may have published various editions of their work, cited elsewhere in this article, based on their shifting ideas or emphases.

Merriam, S. B. 1988. Case study research in education: A qualitative approach . San Francisco: Jossey-Bass.

This is Merriam’s initial text on case study and is eminently accessible. The author establishes and reinforces various key features of case study; demonstrates support for positioning the case within a subject domain, e.g., psychology, sociology, etc.; and further shapes the case according to its purpose or intent.

Stake, R. E. 1995. The art of case study research . Thousand Oaks, CA: SAGE.

Stake is a very readable author, accessible and yet engaging with complex topics. The author establishes his key forms of case study: intrinsic, instrumental, and collective. Stake brings the reader through the process of conceptualizing the case, carrying it out, and analyzing the data. The author uses authentic examples to help readers understand and appreciate the nuances of an interpretive approach to case study.

Stenhouse, L. 1980. The study of samples and the study of cases. British Educational Research Journal 6:1–6.

DOI: 10.1080/0141192800060101

A key article in which Stenhouse sets out his stand on case study work. Those interested in the evolution of case study use in educational research should consider this article and the insights given.

Yin, R. K. 1984. Case Study Research: Design and Methods . Beverley Hills, CA: SAGE.

This preliminary text from Yin was very basic. However, it may be of interest in comparison with later books because Yin shows the ways in which case study as an approach or method in research has evolved in relation to detailed discussions of purpose, as well as the practicalities of working through the research process.

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• About Education »
• Meet the Editorial Board »
• Academic Achievement
• Academic Audit for Universities
• Academic Freedom and Tenure in the United States
• Action Research in Education
• Adjuncts in Higher Education in the United States
• Administrator Preparation
• Adolescence
• Advanced Placement and International Baccalaureate Courses
• Advocacy and Activism in Early Childhood
• African American Racial Identity and Learning
• Alaska Native Education
• Alternative Certification Programs for Educators
• Alternative Schools
• American Indian Education
• Animals in Environmental Education
• Art Education
• Artificial Intelligence and Learning
• Assessing School Leader Effectiveness
• Assessment, Behavioral
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• Assistive Technology
• Augmented Reality in Education
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• Character Education
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• College Admissions in the United States
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• Community Relations
• Comparative Education
• Computer-Assisted Language Learning
• Computer-Based Testing
• Conceptualizing, Measuring, and Evaluating Improvement Net...
• Continuous Improvement and "High Leverage" Educational Pro...
• Counseling in Schools
• Critical Approaches to Gender in Higher Education
• Critical Perspectives on Educational Innovation and Improv...
• Critical Race Theory
• Crossborder and Transnational Higher Education
• Cross-National Research on Continuous Improvement
• Cross-Sector Research on Continuous Learning and Improveme...
• Cultural Diversity in Early Childhood Education
• Culturally Responsive Leadership
• Culturally Responsive Pedagogies
• Culturally Responsive Teacher Education in the United Stat...
• Curriculum Design
• Data-driven Decision Making in the United States
• Deaf Education
• Desegregation and Integration
• Design Thinking and the Learning Sciences: Theoretical, Pr...
• Development, Moral
• Dialogic Pedagogy
• Digital Age Teacher, The
• Digital Citizenship
• Digital Divides
• Disabilities
• Distance Learning
• Distributed Leadership
• Doctoral Education and Training
• Early Childhood Education and Care (ECEC) in Denmark
• Early Childhood Education and Development in Mexico
• Early Childhood Education in Aotearoa New Zealand
• Early Childhood Education in Australia
• Early Childhood Education in China
• Early Childhood Education in Europe
• Early Childhood Education in Sub-Saharan Africa
• Early Childhood Education in Sweden
• Early Childhood Education Pedagogy
• Early Childhood Education Policy
• Early Childhood Education, The Arts in
• Early Childhood Mathematics
• Early Childhood Science
• Early Childhood Teacher Education
• Early Childhood Teachers in Aotearoa New Zealand
• Early Years Professionalism and Professionalization Polici...
• Economics of Education
• Education For Children with Autism
• Education for Sustainable Development
• Education Leadership, Empirical Perspectives in
• Education of Native Hawaiian Students
• Education Reform and School Change
• Educational Statistics for Longitudinal Research
• Educator Partnerships with Parents and Families with a Foc...
• Emotional and Affective Issues in Environmental and Sustai...
• Emotional and Behavioral Disorders
• Environmental and Science Education: Overlaps and Issues
• Environmental Education
• Environmental Education in Brazil
• Epistemic Beliefs
• Equity and Improvement: Engaging Communities in Educationa...
• Equity, Ethnicity, Diversity, and Excellence in Education
• Ethical Research with Young Children
• Ethics and Education
• Ethics of Teaching
• Ethnic Studies
• Evidence-Based Communication Assessment and Intervention
• Family and Community Partnerships in Education
• Family Day Care
• Federal Government Programs and Issues
• Feminization of Labor in Academia
• Finance, Education
• Financial Aid
• Formative Assessment
• Future-Focused Education
• Gender and Achievement
• Gender and Alternative Education
• Gender, Power and Politics in the Academy
• Gender-Based Violence on University Campuses
• Gifted Education
• Global Mindedness and Global Citizenship Education
• Global University Rankings
• Governance, Education
• Grounded Theory
• Growth of Effective Mental Health Services in Schools in t...
• Higher Education and Globalization
• Higher Education and the Developing World
• Higher Education Faculty Characteristics and Trends in the...
• Higher Education Finance
• Higher Education Governance
• Higher Education Graduate Outcomes and Destinations
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• Higher Education in China
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• Higher Education in the United States, Historical Evolutio...
• Higher Education, International Issues in
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• Higher Education Policy
• Higher Education Research
• Higher Education Student Assessment
• High-stakes Testing
• History of Early Childhood Education in the United States
• History of Education in the United States
• History of Technology Integration in Education
• Homeschooling
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• Inclusive Education
• Indigenous Education in a Global Context
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• Indigenous Students in Higher Education in the United Stat...
• Infant and Toddler Pedagogy
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• Intelligence
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• Leadership Training with an Emphasis on the United States
• Learning Analytics in Higher Education
• Learning Difficulties
• Learning, Lifelong
• Learning, Multimedia
• Learning Strategies
• Legal Matters and Education Law
• LGBT Youth in Schools
• Linguistic Diversity
• Linguistically Inclusive Pedagogy
• Literacy Development and Language Acquisition
• Literature Reviews
• Mathematics Identity
• Mathematics Instruction and Interventions for Students wit...
• Mathematics Teacher Education
• Measurement for Improvement in Education
• Measurement in Education in the United States
• Meta-Analysis and Research Synthesis in Education
• Methodological Approaches for Impact Evaluation in Educati...
• Methodologies for Conducting Education Research
• Mindfulness, Learning, and Education
• Motherscholars
• Multiliteracies in Early Childhood Education
• Multiple Documents Literacy: Theory, Research, and Applica...
• Multivariate Research Methodology
• Museums, Education, and Curriculum
• Music Education
• Narrative Research in Education
• Native American Studies
• Nonformal and Informal Environmental Education
• Note-Taking
• Numeracy Education
• One-to-One Technology in the K-12 Classroom
• Online Education
• Open Education
• Organizing for Continuous Improvement in Education
• Organizing Schools for the Inclusion of Students with Disa...
• Outdoor Play and Learning
• Outdoor Play and Learning in Early Childhood Education
• Pedagogical Leadership
• Pedagogy of Teacher Education, A
• Performance Objectives and Measurement
• Performance-based Research Assessment in Higher Education
• Performance-based Research Funding
• Phenomenology in Educational Research
• Philosophy of Education
• Physical Education
• Podcasts in Education
• Policy Context of United States Educational Innovation and...
• Politics of Education
• Portable Technology Use in Special Education Programs and ...
• Post-humanism and Environmental Education
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• Qualitative Data Analysis Techniques
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• Quantitative Research Designs in Educational Research
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Industry and Higher Education

Case Studies for Sustainable Futures

• © 2020
• Leigh Wood 0 ,
• Lay Peng Tan 1 ,
• Yvonne A. Breyer 2 ,
• Sally Hawse 3

Macquarie Business School, Macquarie University, Sydney, Australia

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UTS Business School, University of Technology Sydney, Sydney, Australia

• Provides an overview of sustainability in higher-education business education
• Features a range of detailed international business case studies designed together with industry experts
• Includes teaching notes, discussion points, and marking guides

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Table of contents (13 chapters)

Front matter, towards sustainable futures.

• Leigh N. Wood, Lay Peng Tan, Yvonne A. Breyer, Sally Hawse

Industry Case Studies

Health system sustainability: the pharmaceutical benefits scheme in australia.

• Joanne Epp, Bonny Parkinson, Sally Hawse

Ensuring Healthy Lives: Saving Lives at Birth in Indonesia

• Salut Muhidin, Rachmalina Prasodjo, Maria Silalahi, Jerico Pardosi

Sustainability for Organisational Success: How Is Optus Joining the Dots?

• Zak Baillie, Lay Peng Tan, Yvonne A. Breyer, Andrew Buay

Climate Change and Extreme Events: Risk Assessment of Adaptation in Sydney

• Stefan Trück, Chi Truong, Tim Keighley, Feng Liu, Supriya Mathew

Institutionalising Sustainable Production Practices: Malaysia’s Solar Photovoltaic Industry

• Brian Low, Stephanie Kay Ann Cheah

Sustainable Tourism Development and Stakeholder Analysis: The Freycinet Lodge Case in Tasmania

• Peter Dixon, Leigh N. Wood

Supply Chain Management and Social Enterprise Towards Zero Hunger: The Akshaya Patra Foundation in India

• Meena Chavan, Yvonne A. Breyer

Industry-Academia Partnerships for Sustainability: Project Genesis in India

Migrant workers and corporate social responsibility: workplace practices in mauritius.

• Sevika Varaden, Manjit Singh Sandhu, Fandy Tjiptono

Mainstreaming Neurodiversity for an Inclusive and Sustainable Future Workforce: Autism-Spectrum Employees

• Anna Krzeminska, Sally Hawse

Towards Sustainable Futures in Higher Education

F.i.r.s.t: principles of discipline for 21st century skills.

• Hana Krskova, Leigh N. Wood, Yvonne A. Breyer, Chris Baumann

Developing Sustainability Discourse Skills for Business

• Susan Hoadley, Chris Baumann
• sustainability
• business education
• employability
• sustainable practice
• product stewardship
• higher education
• sustainable growth
• climate change
• higher education institutions
• corporate social responsibility
• corporate sustainability
• job readiness
• graduate skills

About this book

Editors and affiliations.

Leigh Wood, Lay Peng Tan, Yvonne A. Breyer

Sally Hawse

About the editors

Bibliographic information.

Book Title : Industry and Higher Education

Book Subtitle : Case Studies for Sustainable Futures

Editors : Leigh Wood, Lay Peng Tan, Yvonne A. Breyer, Sally Hawse

DOI : https://doi.org/10.1007/978-981-15-0874-5

Publisher : Springer Singapore

eBook Packages : Education , Education (R0)

Copyright Information : Springer Nature Singapore Pte Ltd. 2020

Hardcover ISBN : 978-981-15-0873-8 Published: 16 January 2020

Softcover ISBN : 978-981-15-0876-9 Published: 17 January 2021

eBook ISBN : 978-981-15-0874-5 Published: 15 January 2020

Edition Number : 1

Number of Pages : X, 314

Number of Illustrations : 31 b/w illustrations, 36 illustrations in colour

Topics : Environmental and Sustainability Education , Sustainability Management , Management Education , Careers in Business and Management , Higher Education

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AI in Education: Case Studies from Around the World Showcase Innovative Solutions

AI moves into the spotlight of a new World Economic Forum report, which predicts how this technology might transform education systems, making the work of teachers and students more efficient and effective. The new study deals with many areas where AI is in use – from individualized learning to optimizing organizational procedures, bringing AI into school curriculums, and seeing a responsible application of emerging technologies among several global effects in the educational field.

AI’s educational transformation

The new report, Shaping the Future of Learning: AI Education 4.0, predicts the role of new technology to lead the education systems to encounter an overwhelming increase in demand for digital literacy and the creation of personalized learning environments. It does that by providing a bunch of case studies that demonstrate how AI innovations are already changing education: They help to enhance academic outcomes, engage teachers, and build the abilities and skills of future students.

“AI, the fast-revolutionizing element of education settings worldwide, can be harnessed in a considered way to enhance education when it’s used strategically to assess the needs of each learner, permitting a safe and adaptive experience that is important not just for student assessment but also for the effectiveness of the educators,” said Saadia Zahidi, Managing Director, World Economic Forum.

The report aims to examine AI’s myriad possibilities for education, suggesting modifying how student assessments are carried out with more timely and rich evaluations and metrics on student performance. It includes the outline of how AI can improve the function of educators by taking over and incorporating clerk tasks that are up to 20% percent of all functional duties of educators, thus increasing the benefits of teachers and allowing them to spend more time doing their tasks on a personal level which include improving pedagogy and supporting the emotional needs of students. AI will help transform the education system by working it into various subject areas that develop students’ advanced learning skills and knowledge. Using personalized content and approaches for individual learners will give different students specific pathways to suit their individual needs.

Responsible AI implementation

Several innovative examples of how AI is already revolutionizing education systems are outlined in the report: Several innovative examples of how AI is already revolutionizing education systems are outlined in the report:

The Accessible Digital Textbooks by UNICEF is embracing AI to invent digital tools that students with different learning needs can use. This project is good for students with disabilities, as they can have customized, inclusive, and educational materials.

In Brazil, the Letters initiative implemented a system with artificial intelligence feedback to raise reading skills among the highest number of schools in each status.

In West Africa, using AI to assist virtual mentors in providing tailored lessons and mentorship with Kabakoo Business Academies encourages young people to explore self-employment in informal economies.

The Ministry of Education of the Republic of Korea is dedicated to designing AI-powered digital textbooks appropriate for students at different proficiency levels. This is part of efforts to promote personalized learning and reduce reliance on private education.

The UAE Ministry of Education, in cooperation with other educational institutions, elaborates on an AI virtual tutor aimed at bettering individual learning and reducing the gaps related to learning from one student to the other.

Unlike in the past, when humans could not improve the quality of the outcomes in the educational sector, AI can kindly change the outcomes but view the challenges they have raised. The availability of such technologies should be equal for all, and communicating these issues, such as personal data privacy, bias, and replacing traditional roles, should be, as well, a community of concern.

The report requests the implementation of appropriate privacy and security rules and regulations for data that will go through these protocols before it is shared with students or other stakeholders (such as teachers). Also, the article requests deep collaboration between AI developers and educators to guarantee that new AI tools are responsible for better student outcomes. The World Economic Forum’s Special Meeting, held in Riyadh, Saudi Arabia, with the theme of Global Collaboration, Sustainable Growth, and a Global Energy Transition for Sustainable Development, aims to facilitate a more comprehensive discussion between the major global players.

This article originally appeared in the World Economic Forum .

Case studies

.css-7qmtvr{overflow:hidden;max-height:108px;text-indent:0px;} How to train world-champion cardiologists

Gellér László, Zoltán Salló, Nándor Szegedi

Semmelweis University

A framework to teach library research skills

Anna Hvass, Karen Rolfe, Siân Furmage , Michael Latham

University of Southampton

Going for gold: how to craft a winning TEF submission

Emily Pollinger , Julian Chaudhuri

University of Bath

Creating an impactful social group for neurodivergent students

Brooke Szücs, Ben Roden-Cohen

The University of Queensland

Sharing qualitative research through open access

Nathaniel D. Porter

Virginia Tech

Using storybooks to share research with a wider audience

Dominic Petronzi , Dean Fido, Rebecca Petronzi

University of Derby

Making higher education accessible for students with unmet financial need

A food pantry can help support your campus through the cost-of-living crisis

Lauren Dinour, Fatima deCarvalho, Karina Escobar

Montclair State University

Nourishing bodies and minds: the vital role of a student food pantry

Isabelle Largen

Support for faculty on long-term leave is a career lifeline

Theresa Mercer , Jim Harris, Ron Corstanje, Chhaya Kerai-Jones

Cranfield University

Use design thinking principles to create a human-centred digital strategy

Joe Holland

University of Exeter

Film storytelling can enhance learning in STEM subjects

Arijit Mukhopadhyay

University of Salford

Creating safe spaces for students to talk about financial difficulties

Caroline Deylaud Koukabi, Joanna West

University of Luxembourg

How our Study Together programme promotes belonging and improves well-being

Gemma Standen

University of East Anglia

Use Etherpad to improve engagement in large transnational classes

Xi’an Jiaotong-Liverpool University 

How to harness community knowledge to tackle complex policy challenges

Saffron Woodcraft, Joseph Cook

University College London

What we learned from a pilot study aimed at getting first-generation students into pharmacy

Carl Harrington, Rosemary Norton

Fostering student co-creation to give back to the community

Martha Sullivan

How to keep first-generation students engaged throughout the academic year

Araceli Martinez , Athina Cuevas

Chapman University

We used a hybrid escape room to dramatically boost student attendance

Erick Purwanto, Na Li, Ting Ting Tay

A road map for advancing digital inclusion for your students, staff and community

Raheel Nawaz

Staffordshire University

Building trust in research: how effective patient and public involvement can help

Gary Hickey

Community organising: a case study in parent engagement

Michael Bennett

King’s College London

Designing 24/7 hubs for students

Kieron Broadhead

Using partnerships to establish and build on project success

Dominic Wood

Royal Northern College of Music (RNCM)

Case study: how to do an independent evaluation on homelessness on six continents

Suzanne Fitzpatrick

Heriot-Watt University

Embrace the chaos of real-world learning experiences

Jim Entwistle

Teesside University

Teaching business students how to prepare sustainability reports for SMEs

Ven Tauringana

How storytelling boosts environmental impact and engagement

Denise Baden

Bring the SDGs into the classroom through role play and gamification

Shelini Surendran, Kat Mack, Anand Mistry

University of Surrey

How to support international students’ smooth transition to a new country

Mengping Cheng

Te Whare Wānanga o Waitaha | University of Canterbury

Dealing with abuse after public commentary

Michael Head, Larisa Yarovaya , Ashton Kingdon , Millie Downer

Messy decisions and creative science in the classroom

Charlotte Dodson, Steve Flower

Transforming the classroom through experiential learning

Kate Williams

Georgia Tech’s Center for 21st Century Universities

How to combat the mental health crisis on campus

Jonathan Koppell

Using the power of debate to enhance critical thinking

M. C. Zhang

Macau University of Science and Technology

A case study in developing the next STEM generation

Michael Head, Jessica Boxall, Winfred Dotse-Gborgbortsi, Kathryn Woods-Townsend

Why we need a new model for professional development credentials

Mick Grimley

Lessons learned from a fellowship year as a dentist and early career researcher

Dániel Végh

Learning to learn: developing students into effective lifelong learners

Kevinia Cheung

The Hong Kong Polytechnic University

Using co-creation to make young people equal research partners

Kathryn Woods-Townsend

Six lessons from facilitating a formalised mentoring programme

Karen Mather

Perfect doesn’t exist and other lessons from developing a whole-university well-being strategy

Ben Goose, Cassie Wilson

Using film to prompt discussion in legal studies

Michael Randall

University of Strathclyde

How supported social groups create safe spaces

Hannah Moore

A practical approach to tackling eco-anxiety

Helen Hicks, Dawn Lees

Nudge technology can help students re-engage

A whole-campus approach to boost belonging for student success

Lorett Swank, Catherine Thomas

Using VR to change medical students’ attitudes towards older patients

János Kollár

Recognising First Nations through place: creating an inclusive university environment

Angela Leitch

Queensland University of Technology

Undergraduate research to enrich teacher education

Molly Riddle, Jacquelyn J. Singleton, Cathy Johnson

Indiana University Southeast

How to make dual-enrolment programmes work

Laura Brown Simmons

A case for bringing ethics of friendship and care to academic research

Noam Schimmel

University of California, Berkeley

Co-creation as a liberating activity

Terry Greene

Trent University

Steps to address the operational challenges of widening participation

Angus Howat

From cohort to community: how to support student-led initiatives

Ranita Thompson, Joanne Walmsley, Ben Graham

How to sustain a journal and beat the academic publishing racket

James Williams, Asma Mohseni

Grow your own accessibility allies

Luke Searle

A colour matrix to make visual content more accessible

Matthew Deeprose

What is authentic enquiry learning?

Kate Black, Jonny Hall

Northumbria University

You wake up in a locked room… Using digital escape rooms to promote student engagement

Steven Montagu-Cairns

University of Leeds

Charting a shared path to net zero universities

Shreejan Pandey, Rebecca Powell

Monash University

Creating a reusable takeout dish programme on campus

Rojine McVea

University of Alberta

Power to the people through automation of peer support programmes

Amanda Pocklington

How can universities get more school pupils enthusiastic about science?

Carl Harrington

Unifying theoretical and clinical education in a medical curriculum

László Köles

A campaign to communicate the impact of university research

Paul M. Rand

The University of Chicago

‘I just wish all lecturers would use the VLE in the same way’

Alison Torn

Leeds Trinity University

A ‘grocery store’ model can help your campus food bank reduce waste

Erin O’Neil

Advice for lecturers on how to keep students’ attention

Kinga Györffy, András Matolcsy

Individual consultations can help PhD students to complete their studies

Szabolcs Várbíró , Judit Réka Hetthéssy, Marianna Török

How to support students considering self-employment

Victoria Prince

Nottingham Trent University

Silence is golden when you ‘shut up and write’ together

Kelly Louise Preece, Jo Sutherst

Why we start undergraduate transdisciplinary research from day one

Gray Kochhar-Lindgren, Julian Tanner

The University of Hong Kong

Raising aspirations: lessons in running a young scholars programme

Valsa Koshy

Brunel University London

Restructuring a university, part one

Bill Flanagan

Restructuring a university, part two

How to write better awards entries

Sam Russell

Arden University

Using gamification as an incentive for revision

Teegan Green, Iliria Stenning, Rasheda Keane

Phenomenon-based learning: what, why and how

Sue Lee, Kate Cuthbert

Student support takes a village – but you need to create one first

Melissa Leaupepe

University of Auckland

AI or VR? Matching emerging tech to real-world learning

Martin Brown , Philip Poronnik, Claudio Corvalan-Diaz, William Havellas

University of Sydney

Virtually writing together: creating community while supporting individual endeavour

Karen Kenny

Supporting LGBTQ+ aspiring leaders in universities

Catherine Lee, Daniel Burman

Anglia Ruskin University

Making space for innovation: a higher education challenge

Michelle Prawer

Victoria University

Can online oral exams prevent cheating?

Temesgen Kifle, Anthony Jacobs

A help desk to protect intellectual property

Frank Soodeen

The University of the West Indies

Autonomy, fun and other benefits of student-centred learning design

A tool to navigate information overload

Shonagh Douglas

Robert Gordon University

How university leaders can use an ‘innovation for’ mindset to drive enrolment

Nivine Megahed

National Louis University

To improve the admission process, get faculty involved

The power of events to build belonging among students

Xiaotong Lu

Full circle: using the cycle of teaching, module design and research

Glenn Fosbraey

University of Winchester

Matching technology training to industry needs: a case study

Daniel Garrote

Nuclio Digital School

My experience of speaking in front of a select committee

Nicola Searle

Goldsmiths, University of London, Universities Policy Engagement Network (UPEN)

A holistic approach to student support

Fran Hornsby, Rebecca Clark

University of York

Peer mentoring to support staff well-being: lessons from a pilot

Fiona Cust, Jessica Runacres

Decolonising learning through access to primary sources

June Barrow-Green , Brigitte Stenhouse

The Open University

Mini virtual writing retreats to support and connect tutees

Aspasia Eleni Paltoglou

Manchester Metropolitan University

A model for deploying AI across a university and region

Cheryl Martin

A collective action framework to help Ukraine’s universities survive and rebuild

Charles Cormack, Blanca Torres-Olave

Cormack Consultancy Group

How to train university staff to become anti-racist agents of change

Adam Danquah

University of Manchester

A guide to promoting equity in HE for refugees and asylum seekers

Yeşim Deveci, Claire Mock-Muñoz de Luna , Jess Oddy

University of East London

Mix technology and personal contact to support students

Jonathan Powles

University of the West of Scotland

Virtual mobility: a first step to creating global graduates

Coventry University

Home labs and simulations to spark curiosity and exploration

Francesco Fornetti

University of Bristol

Food for thought: advice for building a university-community collaboration

]oshua Gruver

Ball State University

Flip the script: why listening is the best form of outreach

Lynne Bianchi

How a sustainable internship programme can support social mobility

Fiona Hudson, Inís Fitzpatrick , Cathy Mcloughlin

Dublin City University

Collective voices, zero tolerance

Louise Crowley

University College Cork

So, you want to reach out? Lessons from a ‘science for all’ programme

Mary Gagen , Will Bryan, Rachel Bryan

Swansea University

Counter-mapping as a pedagogical tool

Daniel Gutiérrez-Ujaque , Dharman Jeyasingham

Brunel University London , University of Manchester

The practicalities of delivering a multi-institutional online workshop

Kelly Edmunds , Richard Bowater

Experiential education through a simulated summit to combat human trafficking

Clara Chapdelaine-Feliciati

How professional practitioners help connect crime theory with real-world investigations

Paul McFarlane

Lessons from completing an award-winning knowledge transfer project

Rachel McCrindle, Richard Mitchell, Yota Dimitriadi

University of Reading

In the loop: how formative feedback supports remote teaching

Jonna Lee , Meryem Yilmaz Soylu

Tutor training for architect-educators: twinning, observation, reflection and testing

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Education for humanity: designing learner-centric solutions for refugee students

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There are a number of open access journals featuring case studies across many disciplines. This list is not exhaustive. You may be able to locate additional case studies within OA journals by searching the Directory of Open Access Journals . 

• Case Studies in Engineering Failure Analysis While this title was discontinued in 2018, the archive contains five years of case studies on engineering failures.
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• Mathematics-in-Industry Case Studies This journal provides access to case studies written by mathematicians working on industry problems.
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How Effective is AI in Education? 10 Case Studies and Examples

99.4% of 509 higher education institutions in the US say that artificial intelligence (AI) in education and learning will be instrumental to their institution’s competitiveness in the next three years.

In a world where technology is advancing at an unprecedented pace, it’s no surprise that AI is making its way into the classroom. As educators and researchers continue to explore the possibilities of AI in education, they are discovering its potential to revolutionize the way we learn. The AI education market is predicted to cross 20 billion USD by 2027.

In this article, we will explore some real-life examples of how AI is being used to improve education and how it can help students succeed.

1.  80% accurate recommendations to help students, when compared to expert human advice

A Stanford researcher developed an AI program to provide students with assistance when they get stuck in self-paced digital learning . The study tested a machine-learning program that would predict when a student was likely to get stuck and start “wheel-spinning”, at which point it would recommend a relevant solution. The program was trained by analyzing performance data from 1,170 Ugandan school children who had used tablets to learn English reading skills through videos and mini-games. The program was able to predict whether a child would fall into “wheel-spinning”, even before they had begun a new lesson.

In four out of the six cases, the model and the human expert came up with the same recommendations. The study concludes that AI can be used to identify student problems and make it easier for a limited number of human teachers to help a large number of students.

2. With 91% accuracy, AI-enhanced Chatbots provided personalized help and guidance to students

The University of Murcia in Spain recently implemented an AI-powered chatbot to assist students with inquiries about the campus and academic programs. To the surprise of administrators, the chatbot demonstrated a high level of proficiency, answering over 38,708 questions correctly more than 91% of the time. Keep in mind, this was before ChatGPT, and we can only expect these metrics to improve even further.

This implementation not only provided students with prompt responses outside of standard office hours but also resulted in an increase in student motivation. Additionally, the implementation of the chatbot did not require any changes to the existing staff structure.

3 . 62% Increase in Test Scores Through Adaptive Learning

A study by Knewton , an adaptive learning company, found that students using their AI-powered adaptive learning program improved their test scores by 62% compared to students who did not use the program. The program provided personalized feedback and instruction to students, tailoring the learning experience to their individual needs and abilities.

4. AI Improved Students’ Grades by 30% While Reducing Their Anxiety by 20%

Pai et al. (2020) proposed an intelligent tutoring system to help fifth-grade students learn the mathematical unit of multiplication and division. They found that the intelligent tutoring system (ITS) improved students’ mathematics learning performance and increased their learning motivation.

5. Over 47% of Learning Management Tools Will Be Powered by AI in the Following Three Years

It is projected that nearly 47% of learning management tools will incorporate AI by 2024 . This will enable teachers to personalize education for each student by utilizing the core curriculum and supplementing it with various materials, facilitated by the assistance of AI.

The market for these AI-enhanced e-Learning tools is anticipated to reach over $6 billion by 2024. Again this survey was conducted prior to the proliferation of AI tools like ChatGPT over the last few months, therefore we think it’s likely that this statistic could be even larger than originally predicted.

6. With a 97% Success Rate, AI Teaching Assistant Answers 10,000 Messages a Semester

At the Georgia Institute of Technology, an AI-powered chatbot named Jill Watson , developed by IBM’s Watson , was employed as a teaching assistant for a course with 300 students.

With a 97% accuracy rate, Jill Watson was able to respond to around 10,000 student inquiries each semester with remarkable human-like efficiency.

7. AI Predicts a Student’s Final Grade with 80% Accuracy, to Save 34,712 Students From Failing

Ivy Tech Community College in Indiana conducted a pilot study using data from 10,000 course sections. By identifying 16,000 students at risk of failing within the first two weeks of the semester, the college was able to address non-academic obstacles that contributed to their struggles.

By the end of the semester, 3,000 students were saved from failing – 98% of the contacted students obtained a C grade or better. Through Project Student Success, the college has been able to assist 34,712 students and counting.

8. 95% of graduates with hearing impairments are successfully employed, thanks to AI-assisted education

Text-to-speech and speech-to-text technology are being used to make learning materials more accessible to students with visual and hearing impairments. National Technical Institute for the Deaf (NTID) at RIT serves more than 1,100 deaf and hard-of-hearing students from around the United States and the world, allowing students to access and engage with learning materials in a way that is comfortable and convenient for them.

9. Over 800,000 students across Latin America, Korea, and Japan have improved their English by practicing with AI voice technology

Edwin is an AI-powered service for learning English as a foreign language. To provide affordable, personalized, 1:1 learning, it combines adaptive learning and Natural Language Understanding technologies with pedagogical content.

Using adaptive learning technology, Edwin’s team built English test preparation courses that were taught by a Facebook chatbot and a human teacher in tandem. Over 800,000 students have improved their English with Edwin.

10. Educators Spend 70% Less Time Grading Assignments By Using an AI-Powered Grading Tool

Gradescope is a platform designed to streamline the grading process, delivering benefits to both educators and students.

The AI tech was shown to reduce the amount of time teachers spent on grading by 70% . The platform operates by allowing students to upload their assignments, which are then sorted and grouped by Gradescope. Educators have access to per-question and per-rubric statistics, providing valuable insights into student performance.

AI in Education: A Gateway to a Better Future of Learning

The above are just a small handful of examples to demonstrate the power of AI for education. Given the recent explosion of AI tools into the market, this is just the beginning of what is certain to be a transformative time for education and learning. At Axon Park, we’ve been exploring the use of AI in education since 2019, and look forward to sharing our latest work with you all over the coming days.

If you come across any great statistics that have recently been released, and you think they should be added to this list, please don’t hesitate to reach out.

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Learning social and emotional skills in pre-school creates brighter futures for children (North Macedonia)

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Supporting Teachers to Improve Foundational Learning for Syrian Refugee Students in Jordan

Empowering teachers in Guinea: Transformative solutions for foundational learning

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Supporting the socio-emotional learning and psychological wellbeing of children through a whole-school approach (China)

Engaging parents to overcome reading poverty (India)

Integrated school health and wellness ensure better learning for students (India)

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Multi-sectoral programme to improve the nutrition of school-aged adolescents (Malawi)

Parents on the frontlines of early grade reading and math (Nigeria)

Training, inspiring and motivating early grade teachers to strengthen children’s skills in literacy and numeracy (Sierra Leone) Life skills and citizenship education through Experiential Learning Objects Bank (State of Palestine)

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Improving early grade reading and numeracy through ‘Catch-Up,’ a remedial learning programme (Zambia)

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Education 2.0: skills-based education and digital learning (Egypt)

Empowering adolescents through co-creation of innovative digital solutions (Indonesia)

Virtual instructional leadership course (Jamaica)

Learning Bridges accelerates learning for over 600,000 students (Jordan)

Unleashing the potential of youth through the Youth Learning Passport (Jordan)

Lessons learned from the launch of the Learning Passport Shkollat.org (Kosovo)

Opening up the frontiers of digital learning with the Learning Passport (Lao PDR)

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Energizing collaborative industry-academia learning: a present case and future visions

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In Industry-Academia Collaborations (IAC) both academic, scientific research results and industrial practitioner findings and experiences are produced. Both types of knowledge should be gathered, codified, and disseminated efficiently and effectively. This paper investigates a recent (2014–2017) large-scale IAC R&D&I program case (Need for Speed, N4S) from a learning perspective. It was one of the programs in the Finnish SHOK (Strategic Centres of Science, Technology, and Innovation) system. The theoretical bases are in innovation management, knowledge management, and higher education (university) pedagogy. In the future, IAC projects should be more and more commonplace since major innovations are hardly ever done in isolation, not even by the largest companies. Both intra-organizational and inter-organizational learning networks are increasingly critical success factors. Collaborative learning capabilities will thus be required more often from all the participating parties. Efficient and effective knowledge creation and sharing are underpinning future core competencies. In this paper, we present and evaluate a collaboratively created and publicly shared digital knowledge repository called “Treasure Chest” produced during our case program. The starting point was a jointly created Strategic Research and Innovation Agenda (SRIA), which defined the main research themes and listed motivating research questions to begin with—i.e., intended learning outcomes (ILO). During the 4-year program, our collaborative industry-academia (I-A) learning process produced a range of theoretical and empirical results, which were iteratively collected and packaged into the Treasure Chest repository. Outstandingly, it contained, in addition to traditional research documents, narratives of the industrial learning experiences and more than 100 actionable knowledge items. In conclusion, our vision of the future is that such transparently shared, ambitious, and versatile outcome goals with a continuous integrative collection of the results are keys to effective networked I-A collaboration and learning. In that way, the N4S largely avoided the general problem of often conflicting motives between industrial firms seeking answers and applied solutions to their immediate practical problems and academic researchers aiming at more generalizable knowledge creation and high-quality scientific publications.

Introduction

In Industry-Academia Collaborations (IAC), both academic, scientific research results and industrial practitioner findings and experiences are produced. Both types of knowledge should be gathered, codified, and disseminated efficiently and effectively.

This paper investigates a recent large-scale IAC R&D&I program case called Need for Speed (N4S) [ 1 ]. The industry-driven research program was executed in 2014–2017. It was at that time the biggest Finnish national investment in software-related research with a budget of over 50 M€ involving 40 leading Finnish software-intensive companies and research organizations. In total, roughly 500 people participated in the program over the years.

We investigate the N4S IAC from knowledge creation and learning perspectives. The theoretical bases are in innovation management, knowledge management, and higher education (university) pedagogy.

During the 4-year program, our energized, collaborative I-A learning process produced a wide range of theoretical and empirical N4S consortia results, which were iteratively collected and jointly packaged into the shared repository called Treasure Chest available in the public domain. It helps companies to make use of the possibilities of digitalization and provides also advices for post-digitalization activities. The authors participated in the program. The second and third authors led the program representing the industrial and academic perspectives, respectively.

The rest of this paper is organized as follows. The following section frames the empirical landscape of industry-academia collaboration with recognized success factors and challenges. The next section describes our N4S case, and the succeeding section presents the empirical results. We then discuss the findings, experiences, and lessons learned with managerial and theoretical implications. Finally, we conclude with practical suggestions and pointers to further research work.

Challenges and success factors of effective industry-academia collaboration

In the future, IAC projects will probably be more and more commonplace since major innovations are hardly ever done in isolation, not even by the largest companies. Especially the current and future grand challenges of for example energy systems transformations coupled with digitalization require multidisciplinary research and new knowledge creation and acquisition in many different domains. Often, no single company possesses all. There are increasing needs for bi-directional knowledge co-creation and technology transfers between industry and academia.

Software is increasingly a key enabling technology (KET) for industrial innovations also in non-ICT companies. Since the pace of product development is accelerating in almost all industry sectors, companies need speed for their software creation and production processes.

In academic context, empirical software engineering research has been advancing for decades. However, in order to produce practical value and utility, the research knowledge and technological development must be transferred to industrial companies in actionable forms.

There are also increasing demands for transferring knowledge and new technology the other way around from software-related industries to academia in order to inform researchers about relevant research questions, industrial opportunities, and practitioners’ challenges. To be effective, such knowledge and technology transfer requires often industrial domain knowledge and practical experience not necessarily possessed by academic software researchers.

Overall, it follows that there are increasing needs and demands for effective IAC research endeavors. However, like highlighted above, there are many challenges to overcome. On the other hand, a lot is known about the key success factors of IAC programs.

IAC has been investigated quite extensively over the years in many different disciplines and from multiple viewpoints (e.g., [ 2 – 4 ]). It has also been examined in the context of software research (e.g., [ 5 – 9 ]).

Table 1 presents an aggregated summary of the literature review on typical challenges and success factors of effective IAC in the software research domain. Notably, there are already prior publications describing and evaluating the N4S program’s overall research and development approach [ 10 , 11 ]. Those are included in Table 1 .

In general, both intra-organizational and inter-organizational learning networks are increasingly considered critical success factors. Collaborative learning capabilities will thus be required more often from all the participating parties. Efficient and effective knowledge creation and sharing are then underpinning future core competencies.

Case Need for Speed (N4S)

The Need for Speed (N4S) research program was funded by Tekes (nowadays Business Finland) as the Finnish SHOK (Strategic Centres of Science, Technology, and Innovation) program in 2014–2017 [ 17 ]. The consortia consisted initially of 11 large industrial organizations, 14 SMEs, and 10 research institutes and universities.

All the authors of the present paper participated in the program. The second author acted as the program leader (Focus Area Director, FAD) and the third author as the academic coordinator (ACO). The second actor was at the time employed by the so-called driver company of the program. Moreover, the first author contributed especially to the Treasure Chest development and dissemination.

The overarching ambition of the N4S program was stated as follows: “N4S will create the foundation for the Finnish software intensive businesses in the new digital economy”. Consequently, the long-term plan of N4S was to serve other companies where software plays a dominant role—by making the program’s results, tools, and processes widely available.

The starting point of the N4S program was a jointly created Strategic Research and Innovation Agenda (SRIA) [ 18 ]. It defined the strategic main research themes and listed motivating research questions to begin with as follows:

“N4S adopts a real-time experimental business model and provides capability for instant value delivery based upon deep customer insight”:

Delivering value in real time

Deep customer insight—better business hit-rate

Mercury business—find the new money

In the SRIA document, each of the three above research themes (breakthrough targets) was further elaborated with specific focus areas, goals, and envisioned results. There were motivating and engaging metaphors like “Goal-Driven Hunting Culture” for the Mercury Business and instant value delivery by just “pushing one button”.

In addition to the strategic research goals stated in the SRIA, each industrial partner company defined at least one business case [ 19 ]. There were 49 cases defined in the beginning of the program. Each case had an industrial business owner and an academic research coordinator. Typically multiple research partners worked on each business case.

In this paper, we contribute by exhibiting and analyzing the collaboratively created and publicly shared digital knowledge repository called Treasure Chest produced during the N4S program. Conceptually, the Treasure Chest comprises the following main elements:

Knowledge items

Viewing, filtering, and searching mechanisms for accessing them.

The Treasure Chest was implemented as a publicly available web service. Figure 1 illustrates the web main page.

N4S Treasure Chest home page (excerpt)

In the following, we first describe the organization, structure, and the information item categories of the Treasure Chest repository with illustrations of the actual web site. We then exhibit certain representative examples of each item type. Outstandingly, it contains, in addition to traditional research documents, narratives of the industrial learning experiences and more than 100 actionable knowledge items (called Gold Nuggets).

The Treasure Chest consists of the following main parts and sections (see Fig. 2 ):

Main strategic themes

Guiding and triggering questions to explore each theme from typical angles

Solutions for the different research focus areas in each theme

Narratives from industrial and academic partners

Book publications

Keyword selectors (links) to explore the research publications

N4S Treasure Chest main organization and sectioning

The six parts (1)–(6) marked in Fig. 2 work in practice for the user as follows:

By selecting (“clicking”) the icons of the three main themes, a list of all the related Gold Nugget knowledge items is displayed. The textual listing shows the titles of the items (in alphabetical order).

By selecting the different statements, designated subsets of the Gold Nuggets under the main theme are listed (in alphabetical order).

This section tabulates the research focus areas as stated in the N4S SRIA [ 18 ]. By selecting them, the corresponding subsets of the Gold Nuggets are listed (in alphabetical order).

Narratives are free-form reports of the N4S program achievements, works, results, and experiences written by each industrial and academic partner. Typically, they embed links to the related Gold Nuggets and research publications.

In addition to research publications, a collection of practitioner-oriented books were co-authored. This section provides links to access them.

During the program, more than 200 hundred publications (mostly research papers) were produced. Much emphasis, however, was also put in elaborating publications intended for practitioners by a professional journalist who was on program staff. This section of the Treasure Chest provides a tabularized set of keywords to browse them.

In the Treasure Chest, all the Gold Nuggets have the same defined format as presented in Table 2 . The “Context” field intends to suggest where the particular Gold Nugget is most suitable to be applied. This is just an indicative suggestion as the real situations may vary. The two possible values are defined as follows:

EXPLORATION: Discovering new product and service ideas and/or markets, inventing new business models; Feeding the realization for EXPLOITATION.

EXPLOITATION: Implementing new products and services following the opportunities, developing new features for the products based on the feedback; Detecting potential new opportunities for further EXPLORATION.

In the “Maturity of the organization” field, the Novice-Practitioner-Elite ranking suggests the familiarity and experience of organization with respect to the Gold Nugget topic getting most benefits out of the nugget. The Novice-Practitioner-Elite ranking is, however, just an indicative suggestion as the real situations may vary.

Altogether, the Treasure Chest repository includes 171 Gold Nuggets. Table 3 illustrates one example. It was created collaboratively with research partners and an industrial company partner including a co-authored scientific conference paper.

The narratives (part 4 in Fig. 2 ) varied a lot for different industrial and academic partners reflecting the diversity and richness of the research, development, and innovation done during the N4S program. The following are some examples of the titles:

3 Years of continuous everything

Amplifying the cycle between data and impact

Continuous value definition (CE), actualization (CD), and determination (CX) practices and enabling capabilities development for real-time business

Finally, the Treasure Chest launching was publicly promoted at the end of the N4S program in 2017 as shown in Fig. 3 . In addition, the individual Gold Nuggets were advertised with a long series of Twitter messages by the end of 2017 (see @N4S_fi). The Treasure Chest was also one of the key outcomes highlighted in the N4S program final reporting as depicted in Fig. 4 .

N4S Treasure Chest launching (excerpt)

Treasure Chest in the N4S final outcomes reportage

Industry-academia cooperation in praxis

As the N4S program consortium comprised many industrial and academic partners (initially 25 and 10, respectively), there were many collaboration relationships and consequently various specific ways of working in cooperation. However, certain common patterns and features can be inferred. Table 4 decribes such. Here, we utilize a recent framework of evaluating IAC in Finland [ 20 ].

In hindsight, the SRIA envisaged a shared, energizing picture of the future. The three research themes depicted scenario paths to reach such futures. From the learning perspective, we can discern that the SRIA research goals and expected results actually defined intended learning outcomes (ILO) for everyone both in the industry and in the academia.

An important aspect of setting such an engaging vision was that the SRIA document was created with a joint effort by a large group (altogether 31 people, including the authors of the present paper) representing both the industrial partners and the research organizations (18 academic authors of which 9 professors). Interestingly, the actual writing was essentially accomplished in a couple of days during an intensive writing session at offsite premises. Before that, industrial needs and expectations were collected and captured as business case proposals and there were several collaborative preparation workshops (in 2013).

Notably, most of the industrial partner participants were in senior managerial positions in the companies. They had governing responsibilities and longer-term interests in developing the organizations also prior to and following the N4S program. Such setups can be seen to justify the relevance of the research goals and strengthen the industrial commitments. Furthermore, such resourcing is likely to encourage the academic partners to aim excellence in their research.

In the “Results” section, we have presented the Treasure Chest top-down and outside-in. However, in real life, we constructed it mostly the other way around during the 4-year program:

Publications (parts 5 and 6 in Fig. 2 )

Gold Nuggets

Narratives (part 4 in Fig. 2 )

Treasure Chest structure and compilation (parts 1–3 in Fig. 2 )

Interestingly, the Treasure Chest was initially called just a “toolbox”. However, we realized that a more inspiring nickname would be beneficial, and the name “Treasure Chest” was jointly ideated. Following that, the knowledge items were coined as “Gold Nuggets”. (The English word “nugget” is easy to use also in oral Finnish.)

Overall, the motivation and interests for compiling and publishing the Treasure Chest grew and intensified gradually towards the end of the N4S program. There was a joint quest for collecting as many Gold Nuggets as feasible—even with some healthy competition.

There were certain jointly agreed rulings and policies underlying the creation and population of the Treasure Chest knowledge items. An overarching general idea was the quest to produce actionable knowledge for industrial use. It followed that purely theoretical research publications should be extended with application instructions in the Gold Nuggets (Attachments in Table 2 ). Another shared policy was that each academic research paper should have at least one industrial co-author.

We kept the threshold to submit new Gold Nuggets intentionally low. There were no formal acceptance gates. Instead, we relied on self-organization and self-assessment—and also healthy peer pressure. Basically, the only control rule was that everybody must adhere to the jointly agreed template (see Table 2 ). We firmly encouraged each partner to publish at least one Gold Nugget.

One way of measuring the industry-academia collaboration in practice is to quantify the number of Gold Nuggets created by different industrial and academic partners. For instance, in the focus area, “Beyond DevOps, Organizational Culture, and Human Factors” (see Fig. 2 , part 3), there are altogether 40 items. Thirteen of them were submitted by industrial partners, 27 by research partners (universities and research institutes). Further quantification of the collaborations could be done by calculating, how many organizations (industrial and academic) were involved in creating each Gold Nugget.

Overall, an important part of the N4S industry-academia collaboration was the preparation of doctoral theses. Altogether, there are more than 15 theses done in conjunction to the program. 10 of them were defended during the program in 2014–2017. Markedly, there has also been a “long tail” since 5 theses have been defended after the formal program closing in 2019–2021, and some more are still expected to be completed. Usually, the thesis students (some of them industrial partner employees) worked closely together with industrial practitioners and academic researchers, and in many cases, the industrial companies were the subjects of empirical case studies. Notably, many of the research publications included in the article-based dissertations were parts of the Gold Nuggets.

In general, a principal motivation for all academic researchers is to be able produce new knowledge and publish it in high-quality scientific forums. This applies also in industry-academia collaboration settings. However, in such business-oriented environments industrial partners are typically geared towards shorter time horizons than is typically required by high-quality academic research work and expect readily applicable results for the current problems at hand.

In the N4S program case, that was not a significant problem, though. The relatively long time-span of the program (4 years, 2014–2017) was known in advance, and the resourcing was basically secured from the beginning, so the participating academic partners were able to concentrate on and commit to long-term research relationships with the industrial partners. Such settings are conducive for producing scientifically relevant journal articles, including longitudinal empirical studies. This is even fortified when the industrial participants are co-authors as was usually the case in the N4S.

Comparing and contrasting

The first Finnish SHOK programs were started in 2007. Related to the N4S case, a predecessor was the Cloud Software (CSW) program in 2010–2013. The authors were participants also in that SHOK program.

During the active years, the SHOK program system has been evaluated externally [ 21 , 22 ]. The assessments reported both benefits and challenges with constructive criticism. The assessments concentrated on the SHOK level (TIVIT/DIGILE in our case) rather than individual programs like N4S. In Table 5 , we present general key challenges indicated in those SHOK evaluations and mirror the N4S program case against them.

The overall N4S collaborative RTDI strategy and program management approach has been explained and evaluated in previous publications [ 10 , 11 ]. The present paper adds on them by presenting and scrutinizing the Treasure Chest and its creation process in that context.

In Table 1 , we have summarized typical challenges and success factors in IAC research relationships. With the Gold Nuggets, the academic research efforts and contributions were naturally oriented towards applicable and relevant industrial needs linking to the daily work of the industrial partners since the industry-driven program target was to produce actionable knowledge for distinct purposes. That helped ensuring the practicality and applicability while not overly constraining the academic research. The Treasure Chest facilitated natural close collaboration and was a shared vehicle for being agile toward industry needs and organizing and executing the joint work in agile ways.

Many related investigations on IAC have suggested good practices and recommendations. For instance, it has been recommended to facilitate results that have deployment impact since targeting immediate goals related to current industry needs are more likely to succeed keeping research projects well aligned—while still allowing innovations to emerge [ 13 ]. Those were very much the intentions of the Gold Nuggets. We could also see that the Treasure Chest and the Gold Nugget creation process brought mutually beneficial continuous collaboration ceremonies thriving accomplishments together [ 14 ].

In general, we posit that the forward-looking approach set in the SRIA amplified the role of futures knowledge and futures consciousness both in the research organizations and in the industrial companies [ 23 ]. This could be seen in the titles of the narratives (part 4 in Fig. 2 ), such as:

The need for speed increases all the time

The N4S as a growth enabler

Growth and diversification in ever faster paced markets

Towards real-time business

The Finnish government has emphasized building of internationally attractive knowledge clusters, networks, and innovation systems with leveraging the skills in higher education institutions to accelerate R&D&I for supporting and revitalizing businesses by 2030 [ 24 ]. We maintain that the N4S IAC has advanced such aims.

Overall, from our local self-evaluation perspective and based on our participatory experiences, the N4S program was perceived to be by and large successful. Table 6 contrasts actual outcomes with the original targets stated in the SRIA.

The actual results concentrate on the Real-Time Value Delivery research theme. This is also visible in the Treasure Chest in the sense that the number of the Gold Nuggets is largest in that category (c.f., Fig. 2 , part 1). This is understandable and justified on the grounds that this theme was closest to daily industrial operational practices, and many companies had been working on such developments already prior to the N4S program. Moreover, it creates foundations for the new business capabilities (Mercury Business).

Admittedly, as shown, the planned targets were only partially achieved. However, the intention of the original targets was to be extremely ambitious and even partial achievement may be considered as success. Furthermore, as noted in the external evaluations, many of such performance targets are not straightforward to measure and the overall picture remains partially fuzzy due to the lack of comparative data—perhaps even impossible to assess [ 22 , 25 ].

In addition to the metrics and targets presented in Table 6 , the SRIA stated as an expected outcome that the “results will be packaged as capabilities that can be disseminated and exploited widely in the Finnish economy to enhance global competitiveness that will attract foreign investments in Finland” [ 18 ]. Markedly, the Treasure Chest fulfils exactly that.

Markedly, although the SHOK programs have been criticized and many challenging issues have been noted as discussed above, the assessments have also recognized many positive effects and impacts [ 17 , 21 , 22 ]. One of the main positive aspects has been acknowledged to be the industry-driven large-scale collaboration and with new partners for more ambitious, open, and committed networked research. It has created networks and collaborations between firms, universities, and research institutes that would probably not have been possible otherwise. In our view, that was also one of the principal positive factors in the N4S program.

The Finnish SHOK system was discontinued in 2016 [ 17 ]. We are not in a position to judge, why that governmental decision was made and on which grounds. It was related to the restructuring of the Finnish research and innovation funding system.

The general long-term trends of RD&I investments and industry-academia collaboration in Finland have been downwards in 2010–2020 [ 20 , 26 ]. Both the public funding and the academic research funding received from industry have been decreasing. In addition, industry-academia collaboration as measured in terms of the number of joint publications has been declining.

Naturally, such overall governmental and industrial factors may have influenced the decisions to discontinue the Finnish SHOK system. However, no clearly better new supporting systems have been created since then either [ 20 ]. That has likely had negative consequences for long-term research and achieving the original ambition goals of the SHOK system stated in 2005 in the expected 5–10-year time horizon.

Implications

Lessons learned.

During the entire N4S program period in 2014–2017, we attempted to continuously learn and accordingly improve our I-A collaboration ways of working and practices. Moreover, we sustained several beneficial practices throughout the program. We can now draw several managerial implications from these lessons learned.

Especially the following ones we advocate to adopt, foster and sustain:

Guiding and energizing shared vision from the beginning (picture of the future)

Coaching and uniting leadership—respected by both the academic and industrial partners

Agile ways of working and mindset (e.g., quarterly joint review meetings)

Supporting ICT and communications infrastructures, competences, and resources—considering also the life after the formal closure of the collaboration program (e.g., preserving the repositories and web pages for future access and use; In our N4S case, we managed to secure the technical system availability including hosting the Treasure Chest for a couple of years.)

In addition, the following principles could in our experiences be worth trying and nurturing:

Consciously alternating between exploration (problem definition) and exploitation (problem-solving).

Balancing between theory (e.g., conceptual models) and practice (actionable knowledge)

In contrast, there are also many things to avoid. One of the most critical ones experienced during the our N4S case were external mid-course funding cuts. While such external factors may in practice be beyond the direct control of the I-A collaboration, their detrimental effects for instance on the team spirit should be taken into account and alleviated as much as possible.

Remarkably, even though the actual research program was formally closed in 2017, the IAC networks formed during the program have continued informally—as for instance the co-authoring of this paper exhibits. We have found such resulting networks and connections highly valuable both for academic and industrial organizations and persons alike. In fact, what could be perceived as the “N4S spirit” appears to stay alive (c.f., Twitter: @N4S_fi).

A general, principal problem in IAC research programs tends to be the basically different and sometimes even conflicting motives and incentives of industrial and academic participants. While industrial partners are inclined to solve their immediate practical problems at hand, scholarly academic researchers want to discern the fundamental questions, understand the underlying reasons, and produce new scientific knowledge to publish in academic forums (preferably top journals).

In the N4S program, the SRIA was jointly created by the key academic and industrial participants so that both parties could have their interests incorporated. Many of the large, incumbent industrial partners had been initiated for instance agile/lean improvements and even transformations already prior to the N4S program, so they were also inclined to longer-term research-oriented efforts. Design science was recognized in the SRIA as a viable research method. Overall, the stated strategic research themes (3) with the defined focus areas were ambitious, even world-class goals for high-quality academic research while at the same addressing such areas and questions which served the industrial needs, so the setting allowed “win-win” relationships.

In addition to the SRIA, the jointly created Treasure Chest helped aligning and converging academic and industrial aims. The Gold Nuggets were expected to provide actionable knowledge. Consequently, they required both producing knowledge (i.e., scientific research) and making it exploitable for practical industrial use. Many Gold Nuggets included co-authored empirical case study publications.

A survey study among Finnish doctorates who have exited academic investigated two-way knowledge transfer (information and knowhow) between universities and the “surrounding society” including industry with a dilemma approach [ 27 ]. The prevailing basic dilemma related to the third mission of universities is in doing “pure” scientific research vs. making knowledge applicable. The study suggested three strategies for bridging such gaps: universities’ building stronger stakeholder relationships, knowledge co-production with and by the stakeholders considering the usability of the research results, and enforcing science communication with related incentives. Our N4S experiences and results suggest that the SRIA and the Treasure Chest were primes towards such stronger stakeholder relationships and co-production. The jointly created Treasure Chest was a concrete artefact for publicly communicating the developed knowledge in applicable forms.

Reflections on learning and futures research

We are now in a fitting position to reflect the N4S program IAC and the Treasure Chest from learning and futures research perspectives in more general. This brings up certain theoretical implications.

Considering futures research, the key forward-looking elements were the picture(s) of the futures and their associated scenario paths. In the beginning, the SRIA stated the following grand vision [ 18 ]:

“By 2017, the Finnish software intensive industry is the recognized leader in business innovation and fast implementation of products and services in the digital economy”.

Moreover, it designated the following overall scenario path to reach that desired picture of the future:

“This has been achieved by adopting a real-time experimental business paradigm, providing instant value delivery based upon deep customer insight”.

Following that line of heading, the related research focus areas, concrete goals, and provisionally envisioned results outlined in the SRIA oriented and aligned energetically and enthusiastically the collaborative research, development, and innovation activities right from the beginning.

Markedly, foresight was an intrinsic aspect of the N4S three strategic research themes which create together a real-time business system. Especially, the Deep Customer Insight theme aimed to create advanced capabilities for continuous environment scanning and recognizing new and changing customer/user behaviors and needs. The Mercury Business theme then intended to flexibly and continuously prospect new businesses following the customer insights. The Real-Time Value Delivery theme targeted to bring up high-performing product and service creation capabilities (both technical and organizational) so that the business opportunities can be sized in a continuous yet sustainable fashion. Foresight was explicitly one of the focus areas for the Mercury Business (c.f., Fig. 2 , part 3), and one of the program outputs was a basic guidebook (“cookbook”) for practical foresight activities (c.f., Fig. 4 ). However, of all the SRIA focus areas the Foresight contained the smallest number of Gold Nuggets in the Treasure Chest (7).

In principle, all the over 100 Gold Nuggets in the N4S Treasure Chest can be considered as weak signals in the same manner as for instance the 100 opportunities identified and evaluated in the Radical Technology Inquirer for anticipation of technological breakthroughs [ 28 ]. The Gold Nuggets were—at the time of their discovery and packaging (2017)—considered preferable and prospective for new needs and opportunities. Consequently, they can nowadays (at the time of this writing after 5 years in 2022) be re-evaluated with respect to seeing them as weak signals. Some of them may have remained such, but some may have become current realities and even mainstream. Furthermore, some may include still open research problems and questions serving as inputs for future research agendas. Thus, for example the Gold Nugget illustrated in Table 3 can be evaluated with respect to its (customer satisfaction/experience management) relevance and importance in contemporary and future business environments. It is reasonable to judge now that it has not been outdated—on the contrary, perhaps being even more important today in increasingly customer-centric business models.

Considering learning, the narratives included in the Treasure Chest (part 4 in Fig. 2 ) can be seen as learning reports. For example, the narrative of one industrial partner illustrated the company development path towards real-time business and way of working started already well before the N4S program. That is, the N4S program activities and developments were reflected in the larger context and longer-term time scale. The narrative then shows applications of different N4S research areas at the company during the program with the achieved advancements and improvements.

Finally, the SRIA was also expected to influence curricula development. Especially, the aim was to contribute to the integration of different disciplines. Multidisciplinary collaboration was intended to raise to higher levels. Considering current levels and extends of cross-cutting digitalization, such multidisciplinary curricula can be seen ever more necessary. Notably, altogether the three N4S research themes required competences from multiple disciplines ranging from core software engineering and production to software-oriented business competences. A question remains, which higher education institutes (in Finland) offer such varieties and combination possibilities of study tracks and courses in their curricula.

Future work

In the N4S, the Treasure Chest was essentially created and compiled during the final phase of the program (2016–2017). Consequently, it left room for further development and evaluation. The following ones are such immediate opportunities:

How extensive and intensive was the collaboration (e.g., network density [ 4 ])? This could be illuminated for instance by quantifying, how many co-authors from different industrial and academic organizations there were in the different publications (around 200, see https://n4s.dimecc.com/en/documents/articles/ ). In a similar fashion, the Gold Nuggets could be quantified with respect to with which academic partners each industrial partner collaborated in creating them.

By performing a cross-referencing analysis, it would be possible understand how the different Gold Nuggets are interrelated. Similarly, it is possible to cross-analyze the different narratives (26, see part 4 in Fig. 2 ) for discovering potential interrelationships and synergies. For example, the word continuous appears in 5 titles and the word value in 3 titles.

Assessing the reuse potential of the Treasure Chest and the individual Gold Nuggets

Utilizing the Treasure Chest for software engineering educational and future IAC research purposes

Furthermore, more theoretical advances could be pursued following the previous suggestions on agile IAC and software technology transfer approaches [ 10 , 11 ]. Figure 5 proposes an enhancement of our technology transfer model coupled with the Treasure Chest.

Extended technology transfer model for multi-party IAC research (derived from [ 11 ])

Modern software researchers should exercise even continuous foresight activities especially by scanning the current and also emerging software production and application environments. Currently for instance the EU research agendas are geared towards digitalization and green transitions. Consequently, a future strategic software research agenda quest could be a combination of digital transformations and green sustainability transitions. Notably, many advanced (smart) systems for example in manufacturing environments are increasingly software-intensive. Interestingly enough, the general idea of the N4S program was to advance beyond digitalization. A future “N4S 2.0” SRIA could thereby be envisioned. For instance, the Futures Map approach could potentially be utilized in doing that [ 29 ].

Conclusions

In this paper, we have investigated a recent (2014–2017) large-scale IAC program case (Need for Speed, N4S) from learning and futures research perspectives. We have reviewed, what the program had done and achieved, and evaluated the results of the study. Especially, we have presented a collaboratively created and publicly available shared digital knowledge repository called Treasure Chest produced during our case program. The starting point was a jointly created Strategic Research and Innovation Agenda (SRIA), which defined the main research themes with intended focus areas and listed motivating and orienting research goals and questions to begin with.

The Treasure Chest was ideated and compiled during the last phase of the 4-year program. However, already in the beginning of the program, the SRIA encouraged towards such by stating that the results will be packaged and disseminated for wide exploitation.

In the future, large-scale IAC projects should be more and more commonplace since major innovations are hardly ever done in isolation, not even by the largest companies. Moreover, most current grand research and development challenges require multidisciplinary cooperation and especially software systems are ever more connected and cross-cutting. Both intra-organizational and inter-organizational co-creation and learning networks are increasingly critical success factors. Collaborative learning capabilities will thus be required more often from all the participating parties.

The N4S SRIA defined the main research themes, focus areas and goals with orienting, triggering research questions to begin with. Moreover, it envisioned the desired picture of the future for the entire program consortia. In conclusion, our suggested vision is that such transparently shared, rich outcome goals with continuous integrative collection of the results are keys to effective networked I-A learning in collaborative R&D&I journeys. In the N4S case, the collectively produced Treasure Chest was the concrete manifestation of the successful IAC and its joint learning outcomes at the end of the program and even a couple years after.

Finally, we maintain that the principal research problems stated in the N4S SRIA in 2015 are still (in 2022) very much valid. Interestingly enough, digitalization has significantly accelerated in many fields during the past year of the COVID-19 pandemic. Moreover, the current EU aims for supporting digital and green developments are topical for most every industrial sector for several years to come.

It is perhaps fair to say that the grand vision of the program was not fully was achieved by 2017. However, considering futures research, that is the very idea of a visionary picture of the future as an ideal “dream” state. We maintain that the vision was—and still is—desirable and plausible, and the N4S IAC program progressed significantly in the scenario path towards that vision. During the 4-year journey, we learned a lot together as manifested by the Treasure Chest.

Overall, a key success factor of the industry-driven N4S program was that it created and sustained an environment and atmosphere, which was conducive for mutually beneficial and energizing long-term (4 years) industry-academia collaboration. The jointly created, future-oriented SRIA chartered highly ambitious research goals suitable and attractive for all the academic partners and researchers to contribute on the one hand and the designated focus areas and goals were relevant and rational for the industrial partners on the other hand. With such headings and settings, collaborative participatory research was supported and lucrative.

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Kettunen, P., Järvinen, J., Mikkonen, T. et al. Energizing collaborative industry-academia learning: a present case and future visions. Eur J Futures Res 10 , 8 (2022). https://doi.org/10.1186/s40309-022-00196-5

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Received : 30 September 2021

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DOI : https://doi.org/10.1186/s40309-022-00196-5

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