{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,10]],"date-time":"2026-02-10T18:54:45Z","timestamp":1770749685984,"version":"3.50.0"},"reference-count":52,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2026,2,9]],"date-time":"2026-02-09T00:00:00Z","timestamp":1770595200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"UTP-FUI"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>Massive Open Online Courses (MOOCs) have emerged as a popular choice for learners as accessible and flexible education across the globe. Micro -are short skill-focused certifications offered within MOOCs to online learners. The interplay between multiple stakeholders, including universities, MOOCs providers, policy makers and industrial leaders, plays a decisive role in MOOC adoption. This study employed Educational Data Mining techniques to extract patterns in learner behavior, course design, institutional collaboration, etc., from the determinants of adoption and completion of the micro-credentials within MOOCs. The determinants were extracted from major online MOOCs databases, whereas additional parameters not captured in these databases were collected through an online survey from learners, industry professionals, and higher education institutions. A data mining-based framework is proposed to support stakeholders in planning effective course offerings, guiding learners in selecting suitable courses and helping MOOCs providers to align course credentials with market demands. Classification and predictive analysis revealed that course-related attributes, such as course certification type, course organization, course rating, course difficulty level, and whether the course was free or paid, play decisive roles in determining MOOC adoption. The decision tree classifier, based on the information gain and Gini index, ranked these attributes by order of preference with high accuracy, whereas regression analysis predicted multiple independent variables yielding good performance, as reflected in the confusion matrix.<\/jats:p>","DOI":"10.3390\/info17020175","type":"journal-article","created":{"date-parts":[[2026,2,9]],"date-time":"2026-02-09T14:05:15Z","timestamp":1770645915000},"page":"175","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Unveiling the Factors for MOOC Adoption: An Educational Data Mining Perspective"],"prefix":"10.3390","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3647-1261","authenticated-orcid":false,"given":"Muhammad","family":"Shaheen","sequence":"first","affiliation":[{"name":"Faculty of Engineering & Information Technology, Foundation University Islamabad, Islamabad 44000, Pakistan"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-0368-2393","authenticated-orcid":false,"given":"Rabiya","family":"Ghafoor","sequence":"additional","affiliation":[{"name":"Faculty of Engineering & Information Technology, Foundation University Islamabad, Islamabad 44000, Pakistan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6592-0890","authenticated-orcid":false,"given":"Savita K.","family":"Sugathan","sequence":"additional","affiliation":[{"name":"Department of Computing, Positive Computing Center, Universiti Teknologi PETRONAS, Seri Iskandar 32610, Malaysia"}]},{"given":"Pradeep","family":"Isawasan","sequence":"additional","affiliation":[{"name":"College of Computing, Informatics and Mathematics, Universiti Teknologi MARA, Perak Branch 32610, Malaysia"}]},{"given":"Muhammad Akmal Hakim Ahmad","family":"Asmawi","sequence":"additional","affiliation":[{"name":"College of Computing, Informatics and Mathematics, Universiti Teknologi MARA, Perak Branch 32610, Malaysia"}]}],"member":"1968","published-online":{"date-parts":[[2026,2,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"191","DOI":"10.31202\/ecjse.1581942","article-title":"Analysis of MOOC data with educational data mining: A systematic literature review","volume":"12","author":"Orman","year":"2025","journal-title":"El-Cezeri"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Alangari, H. (2024). Transforming learning: The rise of micro-credentials in higher education. Digital Transformation in Higher Education, Part A, Emerald Publishing Limited.","DOI":"10.1108\/978-1-83549-480-620241005"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"373","DOI":"10.1080\/02680513.2022.2072721","article-title":"The value of educational micro-credentials in open access online education: A doctoral education case","volume":"39","author":"West","year":"2024","journal-title":"Open Learn. J. Open Distance e-Learn."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1186\/s41239-023-00381-x","article-title":"A systematic review of the opportunities and challenges of micro-credentials for multiple stakeholders","volume":"20","author":"Varadarajan","year":"2023","journal-title":"Int. J. Educ. Technol. High. Educ."},{"key":"ref_5","unstructured":"Ozbek, E.A. (2019). Digital transformation, MOOCs, micro-credentials and MOOC-based degrees: Implications for higher education. International Open and Distance Learning Conference Proceedings Book, Anadolu University."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"2158244020941858","DOI":"10.1177\/2158244020941858","article-title":"Toward an understanding of university students\u2019 continued intention to use MOOCs: When UTAUT meets TTF","volume":"10","author":"Wan","year":"2020","journal-title":"SAGE Open"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Zaremohzzabieh, Z., Roslan, S., Mohamad, Z., Ismail, I.A., Ab Jalil, H., and Ahrari, S. (2022). Influencing factors in MOOCs adoption in higher education: A meta-analytic path analysis. Sustainability, 14.","DOI":"10.3390\/su14148268"},{"key":"ref_8","unstructured":"Adriaans, P. (1996). Data Mining, Pearson Education India."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"46108","DOI":"10.1038\/srep46108","article-title":"An algorithm of association rule mining for microbial energy prospection","volume":"7","author":"Shaheen","year":"2017","journal-title":"Sci. Rep."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"329","DOI":"10.1016\/j.aej.2022.11.002","article-title":"Relevance-diversity algorithm for feature selection and modified Bayes for prediction","volume":"66","author":"Shaheen","year":"2023","journal-title":"Alex. Eng. J."},{"key":"ref_11","first-page":"1","article-title":"Automatic generation of extended ER diagram using natural language processing","volume":"7","author":"Shahbaz","year":"2011","journal-title":"J. Am. Sci."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"874","DOI":"10.1177\/01655515221108695","article-title":"WisRule: First cognitive algorithm of wise association rule mining","volume":"50","author":"Khan","year":"2024","journal-title":"J. Inf. Sci."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1002\/widm.1075","article-title":"Data mining in education","volume":"3","author":"Romero","year":"2013","journal-title":"WIREs Data Min. Knowl. Discov."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Dol, S.M., and Jawandhiya, P. (2022, January 26\u201327). Review of EDM for analyzing the performance of students in educational settings. Proceedings of the 6th International Conference on Computing, Communication, Control and Automation (ICCUBEA), Pune, India.","DOI":"10.1109\/ICCUBEA54992.2022.10010714"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"84","DOI":"10.1080\/09747338.2024.2303040","article-title":"An overview of MOOCs and blended learning: Integrating MOOC technologies into traditional classes","volume":"65","author":"Williams","year":"2024","journal-title":"IETE J. Educ."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"366","DOI":"10.1007\/s42979-023-01797-y","article-title":"Are micro-credentials valuable for students? Perspective on verifiable digital credentials","volume":"4","author":"Kukkonen","year":"2023","journal-title":"SN Comput. Sci."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Ngoc Ha, N.T., Van Dyke, N., and Spittle, M. (Stud. High. Educ., 2025). Micro-credentials in higher education: Perceived benefits for graduate employability, Stud. High. Educ., in press.","DOI":"10.1080\/03075079.2025.2516709"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"10135","DOI":"10.1007\/s10639-022-11031-6","article-title":"Trends and issues in MOOC learning analytics empirical research","volume":"27","author":"Zhu","year":"2022","journal-title":"Educ. Inf. Technol."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1186\/s40561-022-00192-z","article-title":"Educational data mining for academic performance prediction","volume":"9","year":"2022","journal-title":"Smart Learn. Environ."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"012001","DOI":"10.1088\/1757-899X\/1062\/1\/012025","article-title":"Implementation of the UTAUT model to understand MOOC adoption","volume":"1062","author":"Haron","year":"2021","journal-title":"IOP Conf. Ser. Mater. Sci. Eng."},{"key":"ref_21","first-page":"83","article-title":"Factors influencing behavioural intention to use MOOCs","volume":"13","author":"Khalid","year":"2021","journal-title":"Eng. Manag. Prod. Serv."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1108\/JIEB-10-2018-0049","article-title":"Flow experience of MOOC users","volume":"13","author":"Mulik","year":"2020","journal-title":"J. Int. Educ. Bus."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"62","DOI":"10.4018\/IJWLTT.2018100104","article-title":"Adoption of massive open online courses","volume":"13","author":"Musleh","year":"2018","journal-title":"Int. J. Web-Based Learn. Teach. Technol."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"571","DOI":"10.1177\/0735633118757732","article-title":"Barriers to the use of MOOCs in developing countries","volume":"57","author":"Ma","year":"2019","journal-title":"J. Educ. Comput. Res."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Lee, Y., and Song, H.-D. (2022). Motivation for MOOC learning persistence. Front. Psychol., 13.","DOI":"10.3389\/fpsyg.2022.958945"},{"key":"ref_26","first-page":"15216","article-title":"Perceived ease of use and perceived usefulness of MOOC TITAS platform","volume":"12","author":"Halim","year":"2022","journal-title":"Int. J. Acad. Res. Bus. Soc. Sci."},{"key":"ref_27","unstructured":"Bruguera, C.F., Pag\u00e9s, C., and Antonaci, A. (2023). Learner preferences regarding micro-credential programs. Zenodo Res. Rep., 2.2."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Durak, G., and Cankaya, S. (2025). The rise of micro-credentials. Integrating Micro-Credentials with AI in Open Education, IGI Global.","DOI":"10.4018\/979-8-3693-5488-9"},{"key":"ref_29","unstructured":"Tanaka, K., Angelin, A., and Chandra, Y.U. (2025, January 14\u201316). Determinant factors of behavioral intention using MOOCs. Proceedings of the 14th International Conference on Educational and Information Technology (ICEIT), Guangzhou, China."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"13505","DOI":"10.1007\/s10639-023-11739-z","article-title":"Implementation of micro-credentials in higher education","volume":"28","author":"Ahsan","year":"2023","journal-title":"Educ. Inf. Technol."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1080\/00131881.2022.2157302","article-title":"Micro-credentials and learner empowerment","volume":"65","author":"Pirkkalainen","year":"2023","journal-title":"Educ. Res."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"K\u00f3r\u00f6si, G., Esztelecki, P., Farkas, R., and T\u00f3th, K. (2018, January 11\u201313). Clickstream-based outcome prediction in short video MOOCs. Proceedings of the International Conference on Computer, Information and Telecommunication Systems (CITS), Colmar, France.","DOI":"10.1109\/CITS.2018.8440182"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"154","DOI":"10.4018\/JITR.2019070109","article-title":"Application of EDM to understand online students\u2019 behavior","volume":"12","author":"Bezerra","year":"2019","journal-title":"J. Inf. Technol. Res."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"012005","DOI":"10.1088\/1757-899X\/1051\/1\/012005","article-title":"Predictive analytics model for student grade prediction","volume":"1051","author":"Bujang","year":"2021","journal-title":"IOP Conf. Ser. Mater. Sci. Eng."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Tasnim, N., Paul, M.K., and Sattar, A.S. (2019, January 7\u20139). Identification of dropout students using EDM. Proceedings of the International Conference on Electrical, Computer and Communication Engineering (ECCE), Cox\u2019s Bazar, Bangladesh.","DOI":"10.1109\/ECACE.2019.8679385"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"17","DOI":"10.1186\/s40561-021-00161-y","article-title":"AI-based monitoring of student performance","volume":"8","author":"Khan","year":"2021","journal-title":"Smart Learn. Environ."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"103673","DOI":"10.1016\/j.compedu.2019.103673","article-title":"Learners\u2019 behaviors and discourse content in MOOC reviews","volume":"143","author":"Peng","year":"2020","journal-title":"Comput. Educ."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"13905","DOI":"10.1007\/s10639-023-12398-w","article-title":"Predictive models for student performance in MOOCs","volume":"29","author":"Ani","year":"2024","journal-title":"Educ. Inf. Technol."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"425","DOI":"10.2307\/30036540","article-title":"User acceptance of information technology","volume":"27","author":"Venkatesh","year":"2003","journal-title":"MIS Q."},{"key":"ref_40","unstructured":"Davis, F.D. (1989). Technology acceptance model. Inf. Syst. Theory, 205\u2013219."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"314","DOI":"10.1002\/hbe2.195","article-title":"The theory of planned behavior: Frequently asked questions","volume":"2","author":"Ajzen","year":"2020","journal-title":"Hum. Behav. Emerg. Technol."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"5771","DOI":"10.1007\/s10639-020-10250-z","article-title":"Drivers and barriers to MOOCs adoption","volume":"25","year":"2020","journal-title":"Educ. Inf. Technol."},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Alamri, M.M. (2022). Investigating students\u2019 adoption of MOOCs during COVID-19 pandemic. Sustainability, 14.","DOI":"10.3390\/su14020714"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"100147","DOI":"10.1016\/j.caeo.2023.100147","article-title":"Role of course relevance and course content quality in MOOCs acceptance and use","volume":"5","author":"Ucha","year":"2023","journal-title":"Comput. Educ. Open"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"1589","DOI":"10.1007\/s10639-020-10317-x","article-title":"Toward a model for acceptance of MOOCs in higher education","volume":"26","author":"Altalhi","year":"2021","journal-title":"Educ. Inf. Technol."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"237","DOI":"10.3991\/ijet.v16i02.13639","article-title":"Towards understanding students\u2019 acceptance of MOOCs","volume":"16","author":"Altalhi","year":"2021","journal-title":"Int. J. Emerg. Technol. Learn."},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Li, Y., and Zhao, M. (2021). Influencing factors of continued intention to use MOOCs. Front. Psychol., 12.","DOI":"10.3389\/fpsyg.2021.528259"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"10261","DOI":"10.1007\/s10639-022-11052-1","article-title":"Factors affecting MOOC adoption in Generation Z","volume":"27","author":"Meet","year":"2022","journal-title":"Educ. Inf. Technol."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1023\/A:1022643204877","article-title":"Induction of decision trees","volume":"1","author":"Quinlan","year":"1986","journal-title":"Mach. Learn."},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Breiman, L., Friedman, J., Olshen, R.A., and Stone, C.J. (2017). Classification and Regression Trees, Chapman and Hall\/CRC.","DOI":"10.1201\/9781315139470"},{"key":"ref_51","first-page":"1","article-title":"A technique for the measurement of attitudes","volume":"22","author":"Likert","year":"1932","journal-title":"Arch. Psychol."},{"key":"ref_52","unstructured":"Brownlee, J. (Machine Learning Mastery, 2020). Why One-Hot Encode Data in Machine Learning?, Machine Learning Mastery."}],"container-title":["Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2078-2489\/17\/2\/175\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,9]],"date-time":"2026-02-09T14:24:26Z","timestamp":1770647066000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2078-2489\/17\/2\/175"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,2,9]]},"references-count":52,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2026,2]]}},"alternative-id":["info17020175"],"URL":"https:\/\/doi.org\/10.3390\/info17020175","relation":{},"ISSN":["2078-2489"],"issn-type":[{"value":"2078-2489","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,2,9]]}}}