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.

Massive Open Online Courses (MOOCs) and micro-credentials have emerged as key innovations in modern education, offering scalable, flexible access to learning and skill development. Despite their potential, challenges such as low learner engagement, high dropout rates, and uncertainty over the value of digital credentials remain. This study analyzes 3,743 publications from 1970 to 2024 using bibliometric and text analytics to uncover research trends, influential studies, and dominant themes in the field. Results show a surge in research from 2014 to 2020 driven by digital technology adoption and the COVID-19 pandemic followed by a decline as hybrid learning models became normalized. Key themes include learner motivation, engagement strategies, digital badges, and ethical concerns tied to data-driven education. While advancements in learning analytics and personalization show promise, the study underscores the need for standardized credentialing, scalable engagement frameworks, and ethical governance in online education. Critical gaps remain, particularly in evaluating the long-term impact of micro-credentials on employability and understanding adoption differences across regions and socioeconomic groups. Limitations include reliance on the Web of Science and author-provided keywords, which may narrow the scope. Despite this, the study provides a systematic overview and offers practical insights for improving MOOCs and micro-credentials as tools for lifelong learning and global educational equity.

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.