IJIET 2025 Vol.15(11): 2476-2484
doi: 10.18178/ijiet.2025.15.11.2443
doi: 10.18178/ijiet.2025.15.11.2443
A Comparative Analysis of MOOC Platforms Using Educational Data Mining Techniques
K. S. Savita1, Pradeep Isawasan2, Muhammad Akmal Hakim Ahmad Asmawi2,*, Muhammad Shaheen3,
and Rabiya Ghafoor4
1. Department of Computing, Positive Computing Center, Universiti Teknologi PETRONAS, Malaysia
2. Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA, Perak Branch, Malaysia
3. Faculty of Engineering and IT, Foundation University Islamabad, Pakistan
4. Department of Software Engineering, Foundation University Islamabad, Pakistan
Email: savitasugathan@utp.edu.my (K.S.S.); pradeep@uitm.edu.my (P.I.); 2024655976@student.uitm.edu.my (M.A.H.A.A.); dr.shaheen@fui.edu.pk (M.S.); rabiya.ghafoor@fui.edu.pk (R.G.)
*Corresponding author
2. Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA, Perak Branch, Malaysia
3. Faculty of Engineering and IT, Foundation University Islamabad, Pakistan
4. Department of Software Engineering, Foundation University Islamabad, Pakistan
Email: savitasugathan@utp.edu.my (K.S.S.); pradeep@uitm.edu.my (P.I.); 2024655976@student.uitm.edu.my (M.A.H.A.A.); dr.shaheen@fui.edu.pk (M.S.); rabiya.ghafoor@fui.edu.pk (R.G.)
*Corresponding author
Manuscript received April 10, 2025; revised April 27, 2025; accepted May 28, 2025; published November 19, 2025
Abstract—Massive Open Online Courses (MOOCs) and microcredential have transformed education by providing flexible and accessible learning opportunities. This study conducts a comparative analysis of MOOC platforms, focusing on Coursera and Udemy, using Educational Data Mining (EDM) techniques. The research examines differences in course volume, subject trends, learner engagement, and course structure across platforms. The findings reveal that Coursera offers fewer but more structured and academically rigorous courses, often linked to university and corporate partnerships. Udemy, in contrast, provides a vast number of shorter, skill-focused courses with greater variability in quality due to its open-marketplace model. Coursera’s courses have higher ratings and more consistent engagement, while Udemy follows a winner-takes-most pattern, where a few popular courses dominate learner interest. Text analysis of course titles highlight distinct subject preferences. Both platforms prioritize technology and business topics, but Coursera’s content aligns with long-term career pathways, whereas Udemy quickly adapts to emerging industry trends, such as blockchain and artificial intelligence. The study also identifies differences in learning pathways, with Coursera structuring its content into beginner, intermediate, and advanced levels, while Udemy heavily relies on “all-level” courses to attract a broad audience. These insights provide valuable implications for educators, policymakers, and online learning providers. Structured platforms like Coursera can strengthen their credibility through academic rigor and industry partnerships, while market-driven platforms like Udemy can enhance content discovery and quality control. Future research should explore the role of course pricing, instructor expertise, and microcredential effectiveness in learner success.
Keywords—Massive Open Online Courses (MOOCs), microcredential, educational data mining, Coursera, Udemy, text analysis, online education
Copyright © 2025 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
Keywords—Massive Open Online Courses (MOOCs), microcredential, educational data mining, Coursera, Udemy, text analysis, online education
Cite: K. S. Savita, Pradeep Isawasan, Muhammad Akmal Hakim Ahmad Asmawi, Muhammad Shaheen, and Rabiya Ghafoor, "A Comparative Analysis of MOOC Platforms Using Educational Data Mining Techniques," International Journal of Information and Education Technology, vol. 15, no. 11, pp. 2476-2484, 2025.
Copyright © 2025 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).