Institution	Approaches	Objectives	Source
1. Albany Technical College	Monitoring, intervention	Identify at-risk students and provide them with counselling
2. Ball State University	Monitoring, intervention	Identify at-risk students and provide them with counselling Increase effectiveness by reducing the time required to diagnose problems and targeting specific issues Help the institution to make informed decisions about student success programmes and retention services Allow students to become aware of the gaps between their behaviours and expected outcomes, to understand elements of their academic success, and to utilize on-campus resources to solve their problems
3. Bowie State University	Monitoring, intervention	Support student retention Track students’ progress towards graduation to facilitate decision making Provide early alerts for staff to intervene to prevent dropout	(2012)
4. Bridgewater College	Monitoring, intervention	Track students’ attainment level Support students to do better than the national average	(2016)
5. California State University	Monitoring	Analyse how students use the learning management system	(2012)
6. Drexel University	Updating data and curriculum	Measure the effectiveness of specific course components through maintaining data records aligned with the curriculum, courses and syllabi, course learning objectives and assessment strategies Manage student learning outcomes and performance criteria
7. Edith Cowan University	Monitoring, intervention	Identify students who need support Establish a system to contact a large number of students and manage interventions Improve student retention Improve graduation rates	(2016)
8. Georgia Institute of Technology and Carnegie Mellon University	Monitoring, analysis	Better scaffolded online discussion to improve learning in a MOOC context Explore effects of higher-order thinking behaviours in learning Identify kinds of discussion behaviours associated with learning Investigate types of learning materials which trigger richer discussion	(2016)
9. Harvard University	Monitoring, prediction	Analyse the extent to which students’ responses about motivation and utility value can predict persistence and completion of study	(2016)
10. Lancaster University	Monitoring, intervention, feedback	Allow tutors to access the transcripts of their students Allow early intervention Ensure student work is graded and feedback given to students in a timely manner	(2016)
11. Loughborough University	Feedback	Provide academics with a better and more holistic picture of student engagement Provide staff with actionable insights into student learning experience Provide students with their own educational data in a meaningful way	(2016)
12. Manchester Metropolitan University	Monitoring, curriculum design	Improve student experience as reflected in the National Student Survey Provide data for improving the undergraduate curriculum	(2016)
13. Marist College	Prediction, intervention	Predict academic success Provide interventions	(2014)
14. McGill University	Monitoring, analysis	Identify misconceptions of medical students as reflected in their interactions in the online learning environment	(2016)
15. New York Institute of Technology	Prediction, intervention	Create an at-risk model to identify students in need of support Improve student retention in their first year of study Provide information that could support counsellor in their work	(2016)
16. Northern Arizona University	Feedback	Facilitate online interaction between students and instructors Allow students to receive direct feedback on issues such as academic concerns and grades
17. Nottingham Trent University	Intervention	Enhance retention and improve attainment Increase students’ sense of belonging within the course community, particularly with tutors	(2016)
18. Open Universities Australia	Intervention	Identify at-risk students Suggest alternative modules to students which are more appropriate for their needs	(2013)
19. Open University of Catalonia	Information collection and management	Identify automatically pieces of knowledge taught in each subject Gather students’ information Keep information updated	(2015)
20. Oxford Brookes University	Monitoring	Improve student experience Support progress evaluation of modules and programmes, and the identification of priorities at an institutional level	(2016)
21. Paul Smith’s College	Monitoring, intervention	Identify at-risk students and prioritize outreach for them Provide more efficient and effective interventions for student success
22. Portland State University	Information management	Make information more accessible and easier to use
23. Purdue University	Monitoring, intervention	Give students early and frequent performance notifications Help faculty members to steer students towards additional campus resources as needed
24. Rio Salado College	Prediction	Identify factors having a significant statistical correlations with final course outcomes
25. San Diego State University	Intervention	Identify methods and interventions that would alleviate students’ failure Discover approaches that could be applied with minimal support and are scalable to a large number of courses	(2015)
26. The Hong Kong Institute of Education	Monitoring, feedback	Provide insights into predicting students’ performance Develop measures to assess students’ online learning Boost teachers’ and students’ interaction Allow students to realize their knowledge discovery Facilitate teachers to assess students’ performance
27. The Open University (UK)	Monitoring, intervention, personalization	Identify learners at risk and needing support Improve learning design Deliver personalized intervention for students Achieve cost-effectiveness	(2016)
	Identifying patterns	Identify common patterns in course design Find out pedagogical implications for various patterns and learning designs
28. The Technical University of Madrid	Monitoring, evaluation	Support teachers’ monitoring and evaluation of individual students’ progress within a team	(2015)
29. The University of Adelaide	Monitoring, feedback	Analyse students’ online discussion data, such as team mood, role distribution and emotional climate Develop students’ soft skills necessary for collaborative work	(2015)
30. The University of East London	Monitoring, feedback	Monitor student attendance and learning activities Collect student data, such as demographic information, library activities, coursework, and download of free books Send automated e-mails to students showing their attendance, and warnings to students without satisfactory attendance	(2016)
31. The University of Melbourne	Monitoring, analysis	Investigate how motivation and participation influence students’ performance in a MOOC	Barba (2016)
		Analyse how MOOC participants use online forums to support learning
		Investigate how students interpret feedback delivered via learning analytics dashboard and the relevant influence on their learning strategies and motivation
32. Universidad a Distancia de Madrid	Monitoring, analysis	Find predictors of teamwork and commitment as cross-curricular competences	(2015)
33. University of Edinburgh	Analysis, prediction	Examine MOOC data about students who enroled in the same course at least twice Identify changes in their behaviours between the two enrolments to the same course	(2016)
34. University of Maryland, Baltimore County	Monitoring, feedback, reflection	Reduce student barriers Create a community of learners Improve students’ self-awareness by providing feedback Provide early alerts to students if their GPA falls below a level	(2012)
35. University of Michigan	Monitoring, personalization, reflection	Identify at-risk students Provide personalized feedback to students	(2012)
36. University of New England	Monitoring, intervention	Foster a sense of community among students studying part-time, at a distance as well as on-campus Identify students who are struggling in order to provide timely support Develop a dynamic, systematic and automated process to capture the learning well-being status of students Encourage peer-to-peer student networking Disseminate information and connect support staff with the students	(2016)
37. University of North Bengal	Prediction	Examine the predictive relationship between learners’ pre-entry demographic information and their dropout behaviours
38. University of Rijeka	Data mining, analysis	Find out factors leading to student success in study Identify problems timely and increase the course pass rate	(2015)
39. University of Salamanca	Information extraction, analysis	Extract information useful for teaching/administrative staff, such as interaction of students with peers, teachers, the system, and course contents Provide teachers with tools to facilitate managerial tasks	(2015)
		Support practical learning in a 3D virtual environment, analyse the problems that arisen, and report relevant data to students and teachers	(2014)
40. University of Santiago de Compostela	Analysis, evaluation	Generate automatically reports of learners’ activities that take place in a virtual learning environment Improve the efficiency of the evaluation process	(2014)
41. University of Sydney	Analysis, observation	Identify the relationship among student performance, choices of programming languages for study, and times at which a student starts and stops working on an assignment	(2016)
42. University of the South Pacific	Monitoring	Track individual learners’ online and offline interactions with open learning resources	(2016)
43. University of Wollongong	Analysis, intervention, reflection	Visualize patterns of student interactions on discussion forums Allow instructors to identify at-risk students and potentially high and low performing students for planning interventions, and the extent to which a learner community is developing in a class	(2013)

Allen , W.R. , Fernandes , K. and Whitmer , J. ( 2012 ), “ Analytics in progress: technology use, student characteristics, and student achievement ”, EDUCAUSE Review , 12 August, available at: http://er.educause.edu/articles/2012/8/analytics-in-progress-technology-use-student-characteristics-and-student-achievement (accessed 28 December 2016 ).

Arnold , K.E. and Pistilli , M.D. ( 2012 ), “ Course signals at Purdue: using learning analytics to increase student success ”, The 2nd International Conference on Learning Analytics and Knowledge , Vancouver , pp. 267 - 270 .

Arroway , P. , Morgan , G. , O’Keefe , M. and Yanosky , R. ( 2016 ), “ Learning analytics in higher education ”, EDUCAUSE, available at: https://library.educause.edu/~/media/files/library/2016/2/ers1504la.pdf (accessed 28 February 2017 ).

Atif , A. , Richards , D. , Bilgin , A. and Marrone , M. ( 2013 ), “ A panorama of learning analytics featuring the technologies for the learning and teaching domain ”, The 30th Ascilite Conference , Sydney , pp. 68 - 72 .

Barba , P.D. , Kennedy , G. and Ainley , M. ( 2016 ), “ The role of students’ motivation and participation in predicting performance in a MOOC ”, Journal of Computer Assisted Learning , Vol. 32 No. 3 , pp. 218 - 231 .

Blanton , S.E. ( 2012 ), “ Datamaster: success and failure on a journal of business intelligence ”, EDUCAUSE case studies, available at: http://er.educause.edu/articles/2012/7/datamaster-success-and-failure-on-a-journey-to-business-intelligence (accessed 28 December 2016 ).

Campbell , J.P. and Oblinger , D.G. ( 2007 ), “ Academic analytics ”, EDUCAUSE, available at: https://net.educause.edu/ir/library/pdf/PUB6101.pdf (accessed 28 December 2016 ).

Chacon , F. , Spicer , D. and Valbuena , A. ( 2012 ), “ Analytics in support of student retention and success ”, available at: https://net.educause.edu/ir/library/pdf/ERB1203.pdf (accessed 28 December 2016 ).

Cohen , J. ( 1988 ), Statistical Power Analysis for the Behavioral Sciences , 2nd ed. , Lawrence Erlbaum , Hillsdale, NJ .

Conde , M.A. , Garcia-Penalvo , F.J. , Gomez-Aguilar , D. and Theron , R. ( 2015 ), “ Exploring software engineering subjects by using visual learning analytics techniques ”, IEEE Revista Iberoamericana De Tecnologias Del Aprendizaje , Vol. 10 No. 4 , pp. 242 - 252 .

Corrin , L. and Barba , P. ( 2015 ), “ How do students interpret feedback delivered via dashboards? ”, Proceedings of the 5th International Conference on Learning Analytics and Knowledge, Poughkeepsie, New York, NY, 16-20 March , pp. 430 - 431 .

Cruz-Benito , J. , Theron , R. , Garcia-Penalvo , F.J. , Maderuelo , C. , Perez-Blanco , J.S. , Zazo , H. and Martin-Suarez , A. ( 2014 ), “ Monitoring and feedback of learning processes in virtual worlds through analytics architectures: a real case ”, The 9th Iberian Conference on Information Systems and Technologies , Barcelona , pp. 1126 - 1131 .

Dodge , B. , Whitmer , J. and Frazee , J.P. ( 2015 ), “ Improving undergraduate student achievement in large blended courses through data-driven interventions ”, The 5th International Conference on Learning Analytics and Knowledge , New York, NY , pp. 412 - 413 .

Dyckhoff , A.L. ( 2011 ), “ Implications for learning analytics tools: a meta-analysis of applied research questions ”, International Journal of Computer Information Systems and Industrial Management Applications , Vol. 3 , pp. 594 - 601 .

Fidalgo-Blanco , Á. , Sein-Echaluce , M.L. , García-Peñalvo , F.J. and Conde , M.Á. ( 2015 ), “ Using learning analytics to improve teamwork assessment ”, Computers in Human Behavior , Vol. 47 , June , pp. 149 - 156 .

Firat , M. and Yuzer , T.V. ( 2016 ), “ Learning analytics: assessment of mass data in distance education ”, International Journal on New Trends in Education and their Implications , Vol. 7 No. 2 , available at: www.ijonte.org/FileUpload/ks63207/File/01.mehmet_firat_.pdf (accessed 28 December 2016 ).

Fritz , J. and Kunnen , E. ( 2010 ), “ Using analytics to intervene with underperforming college students ”, available at: www.educom.edu/eli/events/eli-annual-meeting/2010/using-analytics-intervene-underperforming-college-students-innovative-practice (accessed 28 December 2016 ).

Gašević , D. , Dawson , S. and Pardo , A. ( 2016 ), “ How do we start? State and directions of learning analytics adoption ”, International Council for Open and Distance Education, available at: https://icde.memberclicks.net/assets/RESOURCES/dragan_la_report%20cc%20licence.pdf (accessed 28 February 2017 ).

Gewerc , A. , Montero , L. and Lama , M. ( 2014 ), “ Collaboration and social networking in higher education ”, Media Education Research Journal , Vol. 21 No. 42 , pp. 55 - 63 .

Gramoli , V. , Charleston , M. , Jeffries , B. , Koprinska , I. , McGrane , M. , Radu , A. , Viglas , A. and Yacef , K. ( 2016 ), “ Mining autograding data in computer science education ”, The Eighteenth Australasian Computing Education Conference, Canberra , 1-5 February , available at: http://dl.acm.org/citation.cfm?id=2843070 (accessed 28 December 2016 ).

Grush , M. ( 2011 ), “ Monitoring the PACE of student learning: analytics at Rio Salado College ”, Campus Technology , 14 December, available at: https://campustechnology.com/articles/2011/12/14/monitoring-the-pace-of-student-learning-analytics-at-rio-salado-college.aspx

Guitart , I. , More , J. , Duran , J. , Conesa , J. , Baneres , D. and Ganan , D. ( 2015 ), “ A semi-automatic system to detect relevant learning content for each subject ”, The 7th International Conference on Intelligent Networking and Collaborative Systems , Taipei , pp. 301 - 307 .

Harvey , F. ( 2013 ), “ Technology tools for developing, delivering, updating and assessing sustainable high-quality academic programs ”, Society for Information Technology & Teacher Education International Conference , New Orleans, LA , pp. 2131 - 2133 .

Iglesias-Pradas , S. , Ruiz-de-Azcárate , C. and Agudo-Peregrina , Á.F. ( 2015 ), “ Assessing the suitability of student interactions from moodle data logs as predictors of cross-curricular competencies ”, Computers in Human Behavior , Vol. 47 , June , pp. 81 - 89 .

Ihantola , P. , Vihavainen , A. , Ahadi , A. , Butler , M. , Börstler , J. , Edwards , S.H. , Isohanni , E. , Korhonen , A. , Petersen , A. , Rivers , K. , Rubio , M.Á. , Sheard , J. , Skupas , B. , Spacco , J. , Szabo , C. and Toll , D. ( 2015 ), “ Educational data mining and learning analytics in programming: literature review and case studies ”, The 20th Annual Conference on Innovation and Technology in Computer Science Education – Working Group Reports, ACM , New York, NY , pp. 41 - 63 , available at: http://dl.acm.org/citation.cfm?doid=2858796.2858798 (accessed 28 December 2016 ).

Jayaprakash , S.M. , Moody , E.W. , Lauria , E.J.M. , Regan , R. and Baron , J.D. ( 2014 ), “ Early alert of academically at-risk students: an open source analytics initiative ”, Journal of Learning Analytics , Vol. 1 No. 1 , pp. 6 - 47 .

Jones , D. and Woosley , S. ( 2011 ), “ The foundation of MAP-Works: research and theoretical underpinnings of MAP-Works ”, Educational Benchmarking (EBI), available at: www2.indstate.edu/studentsuccess/pdf/The Foundation of MAP-Works.pdf (accessed 28 December 2016 ).

Karkhanis , P.S. and Dumbre , S.S. ( 2015 ), “ A study of application of data mining and analytics in education domain ”, International Journal of Computer Applications , Vol. 120 No. 22 , pp. 23 - 29 .

Kovanović , V. , Joksimović , S. , Gašević , D. , Owers , J. , Scott , A. and Woodgate , A. ( 2016 ), “ Profiling MOOC course returners: how does student behavior change between two course enrollments? ”, The Third ACM Conference on Learning @ Scale , Edinburgh , pp. 269 - 272 .

McAleese , V. and Taylor , L. ( 2012 ), “ Beyond retention: using targeted analytics to improve student success ”, EDUCAUSE Review , 17 July, available at: http://er.educause.edu/articles/2012/7/beyond-retention-using-targeted-analytics-to-improve-student-success (accessed 28 December 2016 ).

Mat , U.B. , Buniyamin , N. , Arsad , P.M. and Kassim , R. ( 2013 ), “ An overview of using academic analytics to predict and improve students’ achievement: a proposed proactive intelligent intervention ”, IEEE 5th Conference on Engineering Education (ICEED) , pp. 126 - 130 .

Mattingly , K.D. , Rice , M.C. and Berge , Z.L. ( 2012 ), “ Learning analytics as a tool for closing the assessment loop in higher education ”, Knowledge Management & E-learning: An International Journal , Vol. 4 No. 3 , pp. 236 - 247 .

Milligan , S. ( 2015 ), “ Crowd-sourced learning in MOOCs ”, The 5th International Conference on Learning Analytics and Knowledge , New York, NY , pp. 151 - 155 .

Nunn , S. , Avella , J.T. , Kanai , T. and Kebritchi , M. ( 2016 ), “ Learning analytics methods, benefits, and challenges in higher education: a systematic literature review ”, Online Learning , Vol. 20 No. 2 , available at: https://olj.onlinelearningconsortium.org/index.php/olj/article/view/790 (accessed 28 December 2016 ).

Papamitsiou , Z. and Economides , A.A. ( 2014 ), “ Learning analytics and educational data mining in practice: a systematic literature review of empirical evidence ”, Educational Technology & Society , Vol. 17 No. 4 , pp. 49 - 64 .

Poitras , E.G. , Naismith , L.M. , Doleck , T. and Lajoie , S.P. ( 2016 ), “ Using learning analytics to identify medical student misconceptions in an online virtual patient environment ”, Online Learning , Vol. 20 No. 2 , pp. 239 - 250 .

Prasad , D. , Totaram , R. and Usagawa , T. ( 2016 ), “ Development of open textbooks learning analytics system ”, International Review of Research in Open and Distributed Learning , Vol. 17 No. 5 , pp. 215 - 234 .

Prinsloo , P. and Slade , S. ( 2014 ), “ Educational triage in open distance learning: walking a moral tightrope ”, International Review of Research in Open and Distance Learning , Vol. 15 No. 4 , pp. 306 - 331 .

Rienties , B. , Boroowa , A. , Cross , S. , Kubiak , C. , Mayles , K. and Murphy , S. ( 2016 ), “ Analytics4action evaluation framework: a review of evidence-based learning analytics interventions at the Open University UK ”, Journal of Interactive Media in Education , Vol. 1 No. 2 , pp. 1 - 13 .

Rienties , B. , Boroowa , A. , Cross , S. , Farrington-Flint , L. , Herodotou , C. , Prescott , L. , Mayles , K. , Olney , T. , Toetenel , L. and Woodthorpe , J. ( 2016 ), “ Reviewing three case-studies of learning analytics interventions at the Open University UK ”, The 6h International Conference on Learning Analytics & Knowledge, ACM , New York, NY , pp. 534 - 535 .

Robinson , C. , Yeomans , M. , Reich , J. , Hulleman , C. and Gehlbach , H. ( 2016 ), “ Forecasting student achievement in MOOCs with natural language processing ”, The 6th International Conference on Learning Analytics & Knowledge , Edinburgh , pp. 383 - 387 .

Sclater , N. and Mullan , J. ( 2017 ), “ Jisc briefing: learning analytics and student success – assessing the evidence ”, available at: http://repository.jisc.ac.uk/6560/1/learning-analytics_and_student_success.pdf (accessed 28 February 2017 ).

Sclater , N. , Peasgood , A. and Mullan , J. ( 2016 ), “ Learning analytics in higher education: a review of UK and international practice ”, available at: www.jisc.ac.uk/reports/learning-analytics-in-higher-education (accessed 28 December 2016 ).

Sisovic , S. , Matetic , M. and Bakaric , M.B. ( 2015 ), “ Mining student data to assess the impact of moodle activities and prior knowledge on programming course success ”, The 16th International Conference on Computer Systems and Technologies , Dublin , pp. 366 - 373 .

Smith , V.C. , Lange , D.R.H. and Huston , D.R. ( 2012 ), “ Predictive modelling to forecast student outcomes and drive effective interventions in online community college courses ”, Journal of Asynchronous Learning Networks , Vol. 16 No. 3 , pp. 51 - 61 .

Star , M. and Collette , L. ( 2010 ), “ GPS: shaping student success one conversation at a time ”, EDUCAUSE, available at: http://er.educause.edu/articles/2010/12/gps-shaping-student-success-one-conversation-at-a-time (accessed 28 December 2016 ).

Tarmazdi , H. , Vivian , R. , Szabo , C. , Falkner , K. and Falkner , N. ( 2015 ), “ Using learning analytics to visualise computer science teamwork ”, The 2015 ACM Conference on Innovation and Technology in Computer Science Education , Vilnius , pp. 165 - 170 .

Toetenel , L. and Rienties , B. ( 2016 ), “ Analysing 157 learning designs using learning analytic approaches as a means to evaluate the impact of pedagogical decision making ”, British Journal of Educational Technology , Vol. 47 No. 5 , pp. 981 - 992 .

Wang , X. , Wen , M. and Rosé , C.P. ( 2016 ), “ Towards triggering higher-order thinking behaviors in MOOCs ”, The 6th International Conference on Learning Analytics & Knowledge , Edinburgh , pp. 398 - 407 .

Wong , G.K.W. and Li , S.Y.K. ( 2016 ), “ Academic performance prediction using chance discovery from online discussion forums ”, IEEE 40th Annual Computer Software and Applications Conference , GA , pp. 706 - 711 .

Yasmine , D. ( 2013 ), “ Application of the classification tree model in predicting learner dropout behaviour in open and distance learning ”, Distance Education , Vol. 34 No. 2 , pp. 218 - 231 .

Further reading

Pirani , J.A. and Albrecht , B. ( 2005 ), University of Phoenix: Driving decisions Through Academic Analytics , Educause Center for Applied Research , available at: https://net.educause.edu/ir/library/pdf/ers0508/cs/ecs0509.pdf (accessed 28 December 2016 ).

Acknowledgements

The work described in this paper was partially supported by a grant from the Research Grants Council of the Hong Kong Special Administrative Region, China (UGC/IDS16/15).

Corresponding author

Related articles, all feedback is valuable.

Please share your general feedback

Report an issue or find answers to frequently asked questions

Contact Customer Support

Metaverse Integration in COIL to Improve Intercultural Competence in Higher Education: A Case Study

New citation alert added.

This alert has been successfully added and will be sent to:

You will be notified whenever a record that you have chosen has been cited.

To manage your alert preferences, click on the button below.

New Citation Alert!

Please log in to your account

Information & Contributors

Bibliometrics & citations, index terms.

Social and professional topics

User characteristics

Cultural characteristics

Recommendations

The use of metaverse for intercultural collaboration in higher education.

The development of intercultural competencies enables individuals to have appropriate knowledge and understanding of diverse cultures and to interact and relate effectively in different multicultural settings. This document aims to present the status of ...

Flipped Classroom Method in Higher Education: A Case of Kazakhstan

This study is set to explore flipped classroom method in Kazakhstan higher education. Teachers from eleven universities participated in the survey. Observation, questioning, counting, and comparison were used as the main research methods. The ...

Exploring the Use of Metaverse for Collaborative Learning in Higher Education: A Scoping Review

Student engagement in higher education is strongly associated with positive learning outcomes; however, not all learning methods are equally engaging or stimulating. Recent technological developments hold the potential to make learning more ...

Information

Published in.

Association for Computing Machinery

New York, NY, United States

Publication History

Permissions, check for updates, author tags.

• Collaborative online international learning
• Educational innovation
• Higher education
• Immersive technology
• Intercultural education
• Research-article
• Refereed limited

Contributors

Other metrics, bibliometrics, article metrics.

• 0 Total Citations
• 0 Total Downloads
• Downloads (Last 12 months) 0
• Downloads (Last 6 weeks) 0

View Options

Login options.

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

View options.

View or Download as a PDF file.

View online with eReader .

HTML Format

View this article in HTML Format.

Share this Publication link

Copying failed.

Share on social media

Affiliations, export citations.

• Please download or close your previous search result export first before starting a new bulk export. Preview is not available. By clicking download, a status dialog will open to start the export process. The process may take a few minutes but once it finishes a file will be downloadable from your browser. You may continue to browse the DL while the export process is in progress. Download
• Download citation
• Copy citation

We are preparing your search results for download ...

We will inform you here when the file is ready.

Your file of search results citations is now ready.

Your search export query has expired. Please try again.

Information

• Author Services

Initiatives

You are accessing a machine-readable page. In order to be human-readable, please install an RSS reader.

All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess .

Feature papers represent the most advanced research with significant potential for high impact in the field. A Feature Paper should be a substantial original Article that involves several techniques or approaches, provides an outlook for future research directions and describes possible research applications.

Feature papers are submitted upon individual invitation or recommendation by the scientific editors and must receive positive feedback from the reviewers.

Editor’s Choice articles are based on recommendations by the scientific editors of MDPI journals from around the world. Editors select a small number of articles recently published in the journal that they believe will be particularly interesting to readers, or important in the respective research area. The aim is to provide a snapshot of some of the most exciting work published in the various research areas of the journal.

Original Submission Date Received: .

• Active Journals
• Find a Journal
• Proceedings Series
• For Authors
• For Reviewers
• For Editors
• For Librarians
• For Publishers
• For Societies
• For Conference Organizers
• Open Access Policy
• Institutional Open Access Program
• Special Issues Guidelines
• Editorial Process
• Research and Publication Ethics
• Article Processing Charges
• Testimonials
• Preprints.org
• SciProfiles
• Encyclopedia

Article Menu

• Subscribe SciFeed
• Google Scholar
• on Google Scholar
• Table of Contents

Find support for a specific problem in the support section of our website.

Please let us know what you think of our products and services.

Visit our dedicated information section to learn more about MDPI.

JSmol Viewer

Systematic review: revisiting challenge-based learning teaching practices in higher education.

1. Introduction

1.1. entrepreneurial mindset and innovative capabilities, 1.2. teaching practices, 2. materials and methods, 2.1. protocol, 2.2. eligibility criteria, information sources, and search strategy, 2.3. selection process, 2.4. analysis, 2.5. study risk of bias assessment, 3.1. teaching practice insights from each reviewed paper, 3.2. four dimensions of teaching practices in challenge-based learning, 3.2.1. pedagogical approaches in cbl, 3.2.2. technological integration in cbl, 3.2.3. industry and professional engagement in cbl, 3.2.4. support and development in cbl, 3.3. core teaching practices within the context of cbl, 4. discussion, limitations, 5. conclusions, supplementary materials, author contributions, institutional review board statement, informed consent statement, data availability statement, acknowledgments, conflicts of interest.

• Van den Beemt, A.; Vázquez-Villegas, P.; Puente, S.G.; O’Riordan, F.; Gormley, C.; Chiang, F.K.; Leng, C.T.; Caratozzolo, P.; Zavala, G.; Membrillo-Hernández, J. Taking the Challenge: An Exploratory Study of the Challenge-Based Learning Context in Higher Education Institutions across Three Different Continents. Educ. Sci. 2023 , 13 , 234. [ Google Scholar ] [ CrossRef ]
• Leijon, M.; Gudmundsson, P.; Staaf, P.; Christersson, C. Challenge-Based Learning in Higher Education–A Systematic Literature Review. Innov. Educ. Teach. Int. 2022 , 59 , 609–618. [ Google Scholar ] [ CrossRef ]
• Gyldendahl, C.; Georgsen, M.; Dau, S. A Systematic Review of Concepts Related to Reflective Practice-Based Learning with a Focus on Theoretical Positions. In Proceedings for the European Conference on Reflective Practice-Based Learning ; Georgsen, M., Dau, S., Helverskov, L., Eds.; Aalborg University Press: Aalborg, Denmark, 2023; pp. 31–51. [ Google Scholar ]
• Gallagher, S.; Savage, T. Challenge-Based Learning in Higher Education: An Exploratory Literature Review. Teach. High. Educ. 2020 , 28 , 1135–1157. [ Google Scholar ] [ CrossRef ]
• Pepin, B.; Kock, Z.J. Students’ Use of Resources in a Challenge-Based Learning Context Involving Mathematics. Int. J. Res. Undergrad. Math. Educ. 2021 , 7 , 306–327. [ Google Scholar ] [ CrossRef ]
• López-Caudana, E.; Ruiz, S.; Calixto, A.; Nájera, B.; Castro, D.; Romero, D.; Luna, J.; Vargas, V.; Legorreta, I.; Lara-Prieto, V.; et al. A Personalized Assistance System for the Location and Efficient Evacuation in Case of Emergency: TECuidamos, A Challenge-Based Learning Derived Project Designed to Save Lives. Sustainability 2022 , 14 , 4931. [ Google Scholar ] [ CrossRef ]
• Gudoniene, D.; Paulauskaite-Taraseviciene, A.; Daunoriene, A.; Sukacke, V. A Case Study on Emerging Learning Pathways in SDG-Focused Engineering Studies through Applying CBL. Sustainability 2021 , 13 , 8495. [ Google Scholar ] [ CrossRef ]
• Nizami, M.Z.I.; Xue, V.W.; Wong, A.W.Y.; Yu, O.Y.; Yeung, C.S.; Chu, C.H. Challenge-Based Learning in Dental Education. Dent. J. 2023 , 11 , 14. [ Google Scholar ] [ CrossRef ]
• Darsø, L. Is There a Formula for Innovation? In Børsens Ledelseshåndbøger ; Børsen Forlag: Copenhagen, Denmark, 2003. [ Google Scholar ]
• Drucker, P. Innovation and Entrepreneurship ; HarperCollins: New York, NY, USA, 1985. [ Google Scholar ]
• Scharmer, O. Theory U: Leading from the Future as It Emerges. In The Social Technology of Presencing ; Berrett-Koehler Publishers: San Francisco, CA, USA, 2009. [ Google Scholar ]
• Sørensen, E.; Torfing, J. Enhancing Collaborative Innovation in the Public Sector. Adm. Soc. 2011 , 43 , 842–868. [ Google Scholar ] [ CrossRef ]
• Kirketerp, A. Fortagsomhedsdidaktik. Ph.D. Thesis, Aarhus University, Aarhus, Denmark, 2010. Available online: http://cei.au.dk/fileadmin/cei/Billeder/Publikationer/PHD_Foretagsomhedsdidaktik_310510.pdf (accessed on 12 June 2024).
• Bandura, A. Perceived Self-Efficacy in Cognitive Development and Functioning. Educ. Psychol. 1993 , 28 , 117–148. [ Google Scholar ] [ CrossRef ]
• Fardella, C.; Carvajal, F. Los Estudios Sociales de la Práctica y la Práctica Como Unidad de Estudio. Psicoperspectivas 2018 , 17 , 91–102. [ Google Scholar ] [ CrossRef ]
• Galdames-Calderón, M. Prácticas Directivas de Liderazgo Distribuido: Creación de Oportunidades de Desarrollo Profesional Docente para la Mejora Escolar. Ph.D. Thesis, Universitat Autònoma de Barcelona, Barcelona, Spain, 2021. Available online: http://hdl.handle.net/10803/671984 (accessed on 12 June 2024).
• Galdames-Calderón, M. Distributed Leadership: School Principals’ Practices to Promote Teachers’ Professional Development School Improvement. Educ. Sci. 2023 , 13 , 715. [ Google Scholar ] [ CrossRef ]
• Stavnskær, A. The Innovation Circle: A Guide to Innovative Learning Processes ; Huset Venture: Aalborg, Denmark, 2019. [ Google Scholar ]
• Lozano Rodríguez, A.; Alvarado García, M.; Llaven Aguilar, M. Desarrollo de Competencias en el Contexto del Semestre i: Un Estudio de Caso. Educ. Knowl. Soc. 2019 , 20 , 14. [ Google Scholar ] [ CrossRef ]
• Doulougeri, K.; Vermunt, J.; Bombaerts, G.; Bots, M. Analyzing Student-Teacher Interactions in Challenge-Based Learning. In Towards a New Future in Engineering Education, New Scenarios that European Alliances of Tech Universities Open Up ; Universitat Politècnica de Catalunya: Barcelona, Spain, 2022; pp. 252–262. [ Google Scholar ] [ CrossRef ]
• Campos, E.; Núñez, S.; Enríquez, J.; Castaño, R.; Escamilla, J.; Hosseini, S. Educational Model Transition: Student Evaluation of Teaching Amid the COVID-19 Pandemic. Front. Educ. 2022 , 7 , 991654. [ Google Scholar ] [ CrossRef ]
• Page, M.J.; McKenzie, J.E.; Bossuyt, P.M.; Boutron, I.; Hoffmann, T.C.; Mulrow, C.D.; Shamseer, L.; Tetzlaff, J.; Akl, E.; Brennan, S.; et al. The PRISMA 2020 Statement: An Updated Guideline for Reporting Systematic Reviews. BMJ 2021 , 372 , n71. [ Google Scholar ] [ CrossRef ]
• Newman, M.; Gough, D. Systematic Reviews in Educational Research Methodology, Perspectives, and Application. In Systematic Reviews in Educational Research Methodology, Perspectives, and Application ; Zawacki-Richter, O., Kerres, M., Bedenlier, S., Bond, M., Buntins, K., Eds.; Springer: Berlin/Heidelberg, Germany, 2020; pp. 3–22. [ Google Scholar ]
• Galdames-Calderón, M. Protocol for Systematic Review: Revisiting Challenge-Based Learning—Teaching Practices in Higher Education. INSPLAY Protocol 2024 , 202450140. [ Google Scholar ] [ CrossRef ]
• Barrington, M.; D’Souza, R.; Mascha, E.; Narouze, S.; Kelley, G. Systematic Reviews and Meta-Analyses in Regional Anesthesia and Pain Medicine (Part I): Guidelines for Preparing the Review Protocol. Anesth. Analg. 2023 , 138 , 379–394. [ Google Scholar ] [ CrossRef ]
• Pranckute, R. Web of Science (WoS) and Scopus: The Titans of Bibliographic Information in Today’s Academic World. Publications 2021 , 9 , 12. [ Google Scholar ] [ CrossRef ]
• Zhu, J.; Liu, W. A Tale of Two Databases: The Use of Web of Science and Scopus in Academic Papers. Scientometrics 2020 , 123 , 321–335. [ Google Scholar ] [ CrossRef ]
• Haddaway, N.R.; Page, M.J.; Pritchard, C.C.; McGuinness, L.A. PRISMA2020: An R Package and Shiny App for Producing PRISMA 2020-Compliant Flow Diagrams, with Interactivity for Optimized Digital Transparency and Open Synthesis. Campbell Syst. Rev. 2022 , 18 , e1230. [ Google Scholar ] [ CrossRef ]
• Braun, V.; Clarke, V. Conceptual and Design Thinking for Thematic Analysis. Qual. Psychol. 2022 , 9 , 3. [ Google Scholar ] [ CrossRef ]
• Sundler, A.J.; Lindberg, E.; Nilsson, C.; Palmér, L. Qualitative Thematic Analysis Based on Descriptive Phenomenology. Nurs. Open 2019 , 6 , 733–739. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Abril-López, D.; Carrillo, D.L.; González-Moreno, P.M.; Delgado-Algarra, E.J. How to Use Challenge-Based Learning for the Acquisition of Learning to Learn Competence in Early Childhood Preservice Teachers: A Virtual Archaeological Museum Tour in Spain. Front. Educ. 2021 , 6 , 714684. [ Google Scholar ] [ CrossRef ]
• Agüero, M.; López, L.; Pérez, J. Challenge-Based Learning as a Professional Learning Model: Universidad Europea and Comunica +A Program Case Study. Rev. Comun. 2019 , 149 , 1–24. [ Google Scholar ] [ CrossRef ]
• De Aldecoa, C.Y.; Gómez-Trigueros, I.M. Challenges with Complex Situations in the Teaching and Learning of Social Sciences in Initial Teacher Education. Soc. Sci. 2022 , 11 , 295. [ Google Scholar ] [ CrossRef ]
• De Stefani, P.; Han, L. An Inter-University CBL Course and Its Reception by the Student Body: Reflections and Lessons Learned (in Times of COVID-19). Front. Educ. 2022 , 7 , 853699. [ Google Scholar ] [ CrossRef ]
• Dieck-Assad, G.; Ávila-Ortega, A.; Peña, G. Comparing Competency Assessment in Electronics Engineering Education with and without Industry Training Partner by Challenge-Based Learning Oriented to Sustainable Development Goals. Sustainability 2021 , 13 , 10721. [ Google Scholar ] [ CrossRef ]
• Franco, E.; González-Peño, A.; Trucharte, P.; Martínez-Majolero, V. Challenge-Based Learning Approach to Teach Sports: Exploring Perceptions of Teaching Styles and Motivational Experiences among Student Teachers. J. Hosp. Leis. Sport Tour. Educ. 2023 , 32 , 100432. [ Google Scholar ] [ CrossRef ]
• Gaskins, W.B.; Johnson, J.; Maltbie, C.; Kukreti, A.R. Changing the Learning Environment in the College of Engineering and Applied Science Using Challenge-Based Learning. Int. J. Eng. Pedagogy 2015 , 5 , 33–41. [ Google Scholar ] [ CrossRef ]
• Khambari, M.N.M. Instilling Innovativeness, Building Character, and Enforcing Camaraderie through Interest-Driven Challenge-Based Learning Approach. Res. Pract. Technol. Enhanc. Learn. 2019 , 14 , 19. [ Google Scholar ] [ CrossRef ]
• Kohn Rådberg, K.; Lundqvist, U.; Malmqvist, J.; Svensson, O.H. From CDIO to Challenge-Based Learning Experiences—Expanding Student Learning as Well as Societal Impact? Eur. J. Eng. Educ. 2020 , 45 , 22–37. [ Google Scholar ] [ CrossRef ]
• Membrillo-Hernández, J.; Ramírez-Cadena, M.D.J.; Caballero-Valdés, C.; Ganem-Corvera, R.; Bustamante-Bello, R.; Ordoñez-Díaz, J.A.B.; Elizalde, H. Challenge-Based Learning: The Case of Sustainable Development Engineering at the Tecnologico de Monterrey, Mexico City Campus. Int. J. Eng. Pedagogy 2018 , 8 , 137–144. [ Google Scholar ] [ CrossRef ]
• Mesutoglu, C.; Bayram-Jacobs, D.; Vennix, J.; Limburg, A.; Pepin, B. Exploring Multidisciplinary Teamwork of Applied Physics and Engineering Students in a Challenge-Based Learning Course. Res. Sci. Technol. Educ. 2022 , 42 , 639–657. [ Google Scholar ] [ CrossRef ]
• Meyer, H. Teachers’ Thoughts on Student Decision Making during Engineering Design Lessons. Educ. Sci. 2018 , 8 , 9. [ Google Scholar ] [ CrossRef ]
• Nguyen, H.; Gijlers, H.; Pisoni, G. Identifying Struggling Teams in Online Challenge-Based Learning. High. Educ. Skills Work.-Based Learn. 2023 , 13 , 233–248. [ Google Scholar ] [ CrossRef ]
• Piccardo, C.; Goto, Y.; Koca, D.; Aalto, P.; Hughes, M. Challenge-Based, Interdisciplinary Learning for Sustainability in Doctoral Education. Int. J. Sustain. High. Educ. 2022 , 23 , 1482–1503. [ Google Scholar ] [ CrossRef ]
• Tang, A.C.Y.; Chow, M.C.M. Learning Experience of Baccalaureate Nursing Students with Challenge-Based Learning in Hong Kong: A Descriptive Qualitative Study. Int. J. Environ. Res. Public Health 2021 , 18 , 6293. [ Google Scholar ] [ CrossRef ]
• Yoong, S.; Turon, H.; Grady, A.; Hodder, R.; Wolfenden, L. The Benefits of Data Sharing and Ensuring Open Sources of Systematic Review Data. J. Public Health 2022 , 44 , e582–e587. [ Google Scholar ] [ CrossRef ]
• Galdames-Calderón, M.; Stavnskær Pedersen, A.; Rodriguez Gomez, D. Replication Data for: “Systematic Review: Revisiting Challenge-Based Learning Teaching Practices in Higher Education”. CORA. Repositori de Dades de Recerca 2024 , V1 . [ Google Scholar ] [ CrossRef ]
• Sablatzky, T. The Delphi Method. Hypothesis: Res. J. Health Inf. Prof. 2022 , 34 , 1–6. [ Google Scholar ] [ CrossRef ]
• Lozano, R.; Barreiro-Gen, M.; Lozano, F.; Sammalisto, K. Teaching Sustainability in European Higher Education Institutions: Assessing the Connections Between Competences and Pedagogical Approaches. Sustainability 2019 , 11 , 1602. [ Google Scholar ] [ CrossRef ]
• Oyetade, K.; Zuva, T.; Harmse, A. Technology Adoption in Education: A Systematic Literature Review. Adv. Sci. Technol. Eng. Syst. J. 2020 , 5 , 108–112. [ Google Scholar ] [ CrossRef ]
• Wagino, W.; Maksum, H.; Purwanto, W.; Krismadinata, K.; Suhendar, S.; Koto, R. Exploring the Full Potential of Collaborative Learning and E-Learning Environments in Universities: A Systematic Review. TEM J. 2023 , 12 , 1772–1785. [ Google Scholar ] [ CrossRef ]
• Alonso-Muñoz, S.; Torrejón-Ramos, M.; Medina-Salgado, M.S.; González Sánchez, R. Trends in Mentoring at Higher Education: A Bibliometric Analysis. In Proceedings Book: International Conference on Innovation, Documentation and Education ; INNODOCT/22 ; Editorial Universitat Politècnica de València: Valencia, Spain, 2022. [ Google Scholar ] [ CrossRef ]
• Roberts, C.; Khanna, P.; Bleasel, J.; Lane, S.; Burgess, A.; Charles, K.; Howard, R.; O’Mara, D.; Haq, I.; Rutzou, T. Student Perspectives on Programmatic Assessment in a Large Medical Programme: A Critical Realist Analysis. Med. Educ. 2022 , 56 , 901–914. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Børte, K.; Nesje, K.; Lillejord, S. Barriers to Student Active Learning in Higher Education. Teach. High. Educ. 2023 , 28 , 597–615. [ Google Scholar ] [ CrossRef ]
• Oonk, C.; Gulikers, J.T.; den Brok, P.J.; Wesselink, R.; Beers, P.J.; Mulder, M. Teachers as Brokers: Adding a University-Society Perspective to Higher Education Teacher Competence Profiles. High. Educ. 2020 , 80 , 701–718. [ Google Scholar ] [ CrossRef ]

Click here to enlarge figure

	Reference	Title	Country	Context	Study Design
1	Abril-López et al. [ ]	How to Use Challenge-Based Learning for the Acquisition of Learning to Learn Competence in Early Childhood Preservice Teachers: A Virtual Archaeological Museum Tour in Spain	Spain	Education level: Higher Education Field of degree: Teaching and learning of social sciences and teaching and learning of natural sciences with early childhood preservice teachers Format: Presential	Quantitative, quasi-experimental design
2	Agüero et al. [ ]	Challenge based learning as a professional learning model. Universidad Europea and Comunica +A program case study	Spain	Education level: Higher Education Field of degree: Advertising communication degree Format: Presential	Qualitative, questionnaire data
3	De Aldecoa and Gómez-Trigueros [ ]	Challenges with Complex Situations in the Teaching and Learning of Social Sciences in Initial Teacher Education	Andorra	Education level: Higher Education Field of degree: Bachelor’s degree in teaching and learning Format: Presential	Qualitative.
4	De Stefani and Han [ ]	An Inter-University CBL Course and Its Reception by the Student Body: Reflections and Lessons Learned (in Times of COVID-19)	Austria, France, Germany, Italy, Lithuania, Norway, and Spain	Education level: Higher Education Field of degree: Many disciplinary fields, including social sciences and natural sciences Format: Online	Qualitative
5	Dieck-Assad et al. [ ]	Comparing competency assessment in electronics engineering education with and without industry training partner by Challenge-Based Learning oriented to sustainable development goals	Mexico	Education level: Higher Education Field of degree: Mechatronics engineering, digital systems and robotics engineering, biomedical engineering, and other engineering such as innovation engineering Format: Presential	Quantitative
6	Franco et al. [ ]	Challenge-Based Learning approach to teach sports: Exploring perceptions of teaching styles and motivational experiences among students teachers	Spain	Education level: Higher Education Field of degree: Physical activity and sport sciences Format: Presential	Quasi-experimental study with experimental and control groups
7	Gaskins et al. [ ].	Changing the Learning Environment in the College of Engineering and Applied Science Using Challenge Based Learning	USA	Education level: Higher Education Field of degree: Department of biomedical, chemical, and environmental engineering Format: Presential	Experimental design
8	Gudoniene et al. [ ].	A Case Study on Emerging Learning Pathways in SDG-Focused Engineering Studies through Applying CBL	Lithuania	Education level: Higher Education Field of degree: Engineering education Format: Presential	Qualitative, case study
9	Khambari [ ]	Instilling innovativeness, building character, and enforcing camaraderie through interest-driven Challenge-Based Learning approach	Malaysia	Education level: Higher Education Field of degree: Educational technology course Format: Presential	Qualitative
10	Kohn Radberg et al. [ ]	From CDIO to Challenge-Based Learning experiences-expanding student learning as well as societal impact?	Sweden	Education level: Higher Education Field of degree: Engineering degree Format: Presential	Qualitative, case study
11	López-Caudana et al. [ ].	A Personalized Assistance System for the Location and Efficient Evacuation in Case of Emergency: TECuidamos, a Challenge-Based Learning Derived Project Designed to Save Lives	Mexico	Education level: Higher Education Field of degree: Telecommunications and electronic systems engineering Format: Presential	Experimental design
12	Membrillo-Hernández et al. [ ]	Challenge-Based Learning: The Case of Sustainable Development Engineering at the Tecnologico de Monterrey, Mexico City Campus.	Mexico	Education level: Higher Education Field of degree: Sustainable development engineering Format: Presential (i-week and i-semester)	Experimental design
13	Mesutoglu et al. [ ]	Exploring multidisciplinary teamwork of applied physics and engineering students in a Challenge-Based Learning course	Netherlands	Education level: Higher Education Field of degree: Applied physics and engineering Format: Presential	Qualitative, case study
14	Meyer [ ]	Teachers’ Thoughts on Student Decision Making During Engineering Design Lessons	USA	Education level: Higher Education Field of degree: Engineering design Format: Presential	Mixed methods
15	Nguyen et al. [ ]	Identifying struggling teams in online Challenge-Based Learning	Netherlands	Education level: Higher Education Field of degree: Financial technology course Format: Online	Qualitative, questionnaire data
16	Nizami et al. [ ]	Challenge-Based Learning in Dental Education.	China	Education level: Higher Education Field of degree: Dental education	Conceptual design
17	Pepin and Kock [ ]	Students’ Use of Resources in a Challenge-Based Learning Context Involving Mathematics	Netherlands	Education level: Higher Education Field of degree: Mechanical Engineering, data science, industrial engineering, psychology, and technology Format: Online	Qualitative, case study
18	Piccardo et al. [ ]	Challenge-Based, interdisciplinary learning for sustainability in doctoral education.	Finland and Sweden	Education level: Higher Education Field of degree: Life sciences, physical sciences and engineering, and social sciences and humanities Format: Presential	Qualitative, questionnaire data
19	Tang and Chow [ ]	Learning Experience of Baccalaureate Nursing Students with Challenge-Based Learning in Hong Kong: A Descriptive Qualitative Study	China	Education level: Higher Education Field of degree: Nursing program Format: Presential	Qualitative
20	Van den Beemt et al. [ ]	Taking the Challenge: An Exploratory Study of the Challenge-Based Learning Context in Higher Education Institutions across Three Different Continents	Mexico, Netherlands, Ireland, and China	Education level: Higher Education Field of degree: Engineering education Format: Presential	Comparative case study

Authors	Perspectives on Teaching Practices in CBL
Abril-López et al. [ ]; Dieck-Assad et al. [ ]; Gaskins et al. [ ]; Van den Beemt et al. [ ]	Emphasize the teacher’s role as a facilitator and guide, integrating support with resources to enhance students’ autonomous learning, critical thinking, problem-solving, and readiness for future challenges. Mention the need for teachers to adapt teaching strategies and develop “learning to learn” competencies.
Agüero et al. [ ]; De Stefani and Han, [ ]; Tang and Chow [ ]	Highlight the transition from knowledge source to facilitator, fostering a collaborative, participatory experience and preparing students for professional demands through the integration of theory and practice.
De Aldecoa and Gómez-Trigueros [ ]; Mesutoglu et al. [ ]	Discuss the multifaceted role of teachers in promoting interdisciplinary work and guiding students through social challenges using ICTs, enhancing digital competencies, and involving students in decision-making and innovative solution development.
Franco et al. [ ]; Gudoniene et al. [ ]; Meyer [ ]; Nguyen et al. [ ]	Describe the adaptive roles of teachers in enhancing engagement, supporting autonomy, and balancing structured support with student-led learning. Stress the importance of training for teachers and professional development.
Khambari [ ]; López-Caudana et al. [ ]; Membrillo Hernández et al. [ ]; Nizami et al. [ ]; Piccardo et al. [ ]	Focus on the critical importance of tutors as resources themselves, organizing project implementation, connecting students with external stakeholders, and guiding multidisciplinary collaboration.
Pepin and Kock [ ]; Kohn Radberg et al. [ ]	Detail the shift of teachers to coach-like roles, fostering learning through feedback, taking a process-oriented perspective, and guiding students with different disciplinary backgrounds through challenges.

Teaching Practices	Description and Conceptualization
Shifting from instructor to facilitator	Teachers’ roles evolve to focus on learning facilitation and support rather than direct instruction and shifting from a traditional teaching role to that of a coach or facilitator [ , , , , , ].
Facilitating the learning process	Teachers guide students through CBL, fostering autonomy in learning [ ], nurturing entrepreneurial skills [ , ], and enhancing critical thinking abilities, thereby shaping proactive and dedicated community members [ , ].
Creating collaborative learning environments	Teachers enhance collaborative learning [ ] by establishing positive classrooms that promote teamwork and guide problem-solving [ ] while also supporting student autonomy through valuing their feelings and choices and creating an open environment for expression [ ] and decision-making [ ].
Promoting critical thinking and innovation	Teachers promote critical thinking and innovation [ ] through holistic methodologies, enhancing the practical application of theoretical knowledge beyond the confines of the classroom [ , ] and involving students in taking action and developing innovative solutions [ , ] for sustainable development [ , , ].
Guiding research questions and problem-solving	Educators guide students through a multifaceted process in CBL [ ], where they assist in navigating complex questions and solving problems by immersing students in a mix of conceptual, procedural, and attitudinal learning [ ]. This approach includes an iterative cycle [ , ] of three phases of CBL framework: “engage”, “investigate”, and “act” [ ] and the related processes, such as analysis, diagnosis, observation, research, strategy development, decision-making, design, evaluating feasibility and environmental impact, implementation, and assessment. Consequently, it cultivates essential skills in research, analysis, and information management among students [ ].
Encouraging active learning	The teacher’s role encompasses empowering students to become self-directed learners [ , ] co-responsible for the creation of knowledge [ ] who take ownership of their education [ , ], preparing them to master the skill of learning to learn [ ] and fulfilling meaningful and lifelong learning [ ] through active learning [ ] or learning by doing [ ].
Designing challenges	By connecting students with real-world problems observed in their communities [ ], teachers create engaging [ ] and motivating challenges with global importance [ , ] based on students’ interests [ ], integrating adaptable difficulty levels to cater to diverse abilities [ ] and ensuring personalized and inclusive learning experiences [ ].

Teaching Practices	Description and Conceptualization
Using digital technology	In response to the shift from face-to-face to online delivery of CBL [ ] prompted by COVID-19 [ ] or the use of blended formats [ ], teachers have been pivotal in incorporating technology [ ] and ICTs to cultivate students’ digital competencies [ , , ], establishing ICT integration as an essential element of modern teaching practices in CBL [ ].

Teaching Practices	Description and Conceptualization
Collaborating with industry professionals	Teachers work with industry to define real-world challenges, integrating professional standards or stakeholders and resources into the learning experience [ , , , , , , ].
Facilitating the integration of professional practices	Teachers guide students in crafting projects that comply with both professional and ecological standards, thus supporting the Sustainable Development Goals (SDGs) [ , , , ] and enhancing student employability [ , ].
Guiding students in managing project resources	Teachers have emerged as the pivotal resource [ ], securing and utilizing both external materials and their specialized knowledge to support practical learning effectively [ , ]. By collaborating with industrial partners and leveraging their expertise in technical domains, tutors form an integral part of the instructional team that significantly enhances the practical learning experience [ ].

Teaching Practices	Description and Conceptualization
Encouraging self-regulated learning	Teachers encourage students to regulate their own learning processes, fostering autonomy and self-regulated learning [ , ] and enhancing motivation [ , ] and persistence [ ].
Engaging in continued professional development	Teachers undergo professional development to become facilitators and coaches in CBL environments [ , , , ], and additional training is useful to ensure a comprehensive understanding of CBL processes and their successful implementation [ , ].
Facilitating interdisciplinary communication	Teachers facilitate communication among students from different disciplines [ ], encouraging multidisciplinary collaboration [ , , , , , ] and inter-/transdisciplinary learning [ ].
Fostering resilience and providing support	Teachers aid students in overcoming challenges with supportive feedback [ ] and resilience-building [ ] while striving to develop their competence, fostering a sense of capability and accomplishment [ ].
Preparing learners for future challenges	Teachers equip students for the demands of the real world, nurturing skills such as leadership [ , ], creativity [ , ], ethical problem-solving [ ], teamwork [ ], interpersonal skills [ ], and entrepreneurial skills [ , , ] to acquire 21st-century skills [ , , ].
Supporting student decision-making	Teachers engage students in decision-making processes [ ], though they may require further training to support internal cognitive processes [ ].
Providing feedback	Teachers bear the responsibility of assessing student performance, offering structured guidance, and confirming that learning objectives are achieved [ ], striking a balance between the industrial partner’s needs and the competencies that students must acquire [ ]. Evaluations should prioritize learning, considering the shift away from simply meeting exam criteria [ ].

The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

Galdames-Calderón, M.; Stavnskær Pedersen, A.; Rodriguez-Gomez, D. Systematic Review: Revisiting Challenge-Based Learning Teaching Practices in Higher Education. Educ. Sci. 2024 , 14 , 1008. https://doi.org/10.3390/educsci14091008

Galdames-Calderón M, Stavnskær Pedersen A, Rodriguez-Gomez D. Systematic Review: Revisiting Challenge-Based Learning Teaching Practices in Higher Education. Education Sciences . 2024; 14(9):1008. https://doi.org/10.3390/educsci14091008

Galdames-Calderón, Marisol, Anni Stavnskær Pedersen, and David Rodriguez-Gomez. 2024. "Systematic Review: Revisiting Challenge-Based Learning Teaching Practices in Higher Education" Education Sciences 14, no. 9: 1008. https://doi.org/10.3390/educsci14091008

Article Metrics

Supplementary material.

ZIP-Document (ZIP, 665 KiB)

Further Information

Mdpi initiatives, follow mdpi.

Subscribe to receive issue release notifications and newsletters from MDPI journals

Academia.edu no longer supports Internet Explorer.

To browse Academia.edu and the wider internet faster and more securely, please take a few seconds to  upgrade your browser .

Enter the email address you signed up with and we'll email you a reset link.

• We're Hiring!
• Help Center

Issues in Higher Education Program Evaluation

Related Papers

New Directions for Institutional Research

Elizabeth Wroblewski

American Journal of Evaluation

Yvonna Lincoln

Canadian Journal of Higher Education

Colin P Neufeldt

Post-secondary institutions carry out cyclical program reviews (CPRs) to assess educational effectiveness. CPRs often use both qualitative and quantitative data analyses with the aim of improving teaching and learning. Though most of the CPR review studies identify various factors for this purpose, they fail to identify measures/indicators that are relevant and practical for the institutional decision-making process. Our main objectives for this article are two-fold: first, we identify and list variables that are measurable and sort them into clusters/groups that are relevant to all programs, and second, we critically assess the relevance of these indicators to program review in a small-sized, post-secondary institution.

Ana Maria Graffigna

Evaluative practices at Argentine Universities have been realized in two ways: the first related to the accreditation of university programs and the second related to the evaluation of the universities as educational institutions. Bearing this in mind, this study presents an analysis of the concepts of evaluation, explicit and implicit in the processes, revealing the underlying logics. Also the procedures carried out by the institutions for implementing self-assessment processes and their relationships to the external evaluation are categorized focusing on the subjects and objects of evaluation in each case. A categorical discourse analysis is carried out, which is crossed with the documental study. The present work provides input for the strategic situational planning of the University, as a starting point to strenghten the evaluation process in the institutional context, thus enabling the articulation of practices, economy of effort and quality assurance of the assessment at the institutional level.

BMC Medical Education

Monica Lypson

Alan Lindsay

Munir Majdalawieh

The aim of this book is to propose a holistic conceptual framework for “program review” to assess the effectiveness and viability of an academic program and to improve the academic program and the education of the students. The proposed framework consists of three main components: program review process, program review principles and the program review measurement matrix. The framework and the methods used to create it will provide an opportunity to colleges and universities to undertake a robust and targeted approach to proactively and continuously review their academic programs to ensure that programs are functioning at the highest possible levels of academic quality and are consistent with the mission of the college or the university. The framework will transform the “program review” process into a continuing assessment activity rather than a periodic event.

Association For Institutional Research

Gita Pitter

JIm Carifio

Yüksek Öğretim

Prof. Dr. Nurdan Kalayci

Changing economic, cultural, political, and social conditions worldwide have a big impact on higher education. Under the influence of changing conditions, the functional scope of higher education institutions has expanded and new functions have been added. In addition to these changes, the demand for higher education institutions is increasing day by day in terms of education, research, and service to society. The expanding functions of higher education and its deepening impact on society call for quality activities of higher education institutions. Therefore, institutional quality evaluation processes are carried out in higher education institutions. This study aims to analyze and compare institutional quality evaluation processes applied in Turkish, European, and American higher education systems. The findings obtained are important as they will contribute to the Higher Education Quality Council of Turkey, quality commissions in higher education institutions, and other researchers who will conduct scientific studies on this subject. It is a descriptive and qualitative study whose sample consists of institutional quality evaluation agencies from Turkey, England, Norway, Finland, and the United States of America. The data in the study were collected and analyzed by applying the document analysis method. The findings indicate that institutional external evaluation or audit models are used in Turkey, England, Norway, and Finland while an institutional accreditation system is used in the USA. Although the quality evaluation processes applied are generally similar in terms of basic objectives, assessed dimensions, assessment approach, people involved in the implementation of the assessment, and assessment type, there are differences in aspects such as the management, coordination, and recognition practices of the countries’ higher education systems. Taking into account national circumstances, the institutional quality evaluation processes in the Turkish higher education system should be organized and implemented in a systematic way to ensure quality higher educational practice. Keywords: Higher education, higher education evaluation, institutional quality evaluation.

Loading Preview

Sorry, preview is currently unavailable. You can download the paper by clicking the button above.

RELATED TOPICS

•   We're Hiring!
•   Help Center
• Find new research papers in:
• Health Sciences
• Earth Sciences
• Cognitive Science
• Mathematics
• Computer Science
• Academia ©2024

• DOI: 10.69593/ajahe.v4i03.84
• Corpus ID: 271079373

Assessing English Language Proficiency: A Case Study of English Version Students of Higher Secondary Level of Bangladesh

• Alia Rawshan Banu
• Published in ACADEMIC JOURNAL ON ARTS &amp… 8 July 2024
• Education, Linguistics
• ACADEMIC JOURNAL ON ARTS & HUMANITIES EDUCATION

Related Papers

Showing 1 through 3 of 0 Related Papers