Exploring behavioural differences between certificate achievers and explorers in MOOCs

ABSTRACT

Massive open online courses (MOOCs) face the ongoing problem of low pass rates. A number of MOOC learners engage in most or all course activities but fail to pass the course. To improve participation and thereby increase successful completion, this study explores the behavioural differences between certificate achievers and explorers that lead to their different learning outcomes. Eleven behaviours were extracted from more than 80,000 behaviour records for 215 certificate achievers and 456 explorers, which were categorized into four types of activities: graded assessment, content-related, course-related, and interactive activities. Random forest classifier, independent-sample t-testing, and lag sequential analysis were used. The results showed six important behaviours that are highly related to certificate achievement. Certificate achievers engaged in more course-related and graded assessment activities during the course, while explorers engaged in more content-related and interactive activities, and graded assessment activities occurring at the end of the course. Compared to explorers, certificate achievers exhibited more bidirectional behaviours in terms of interactive and course-related activities and more repeated behaviours in terms of course-related and graded assessment activities. The study has significant implications for MOOC learners and instructors in improving learning and teaching performance by implementing appropriate behavioural interventions.

KEYWORDS:

• Behaviour differences
• certificate achievers
• explorers
• academic performance
• behaviour sequence
• MOOCs

Contribution

Bowen Liu conducted the research and drafted the initial manuscript.

Yonghe Wu provided insight and supervision of the research.

Wanli Xing provided insight and editing of the manuscript.

Gexing Cheng conducted the independent-sample T test for examining the behavior frequency differences.

Shengnan Guo conducted the lag sequential analysis for examining the behavior sequence differences.

All authors read and approved the final manuscript.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Notes on contributors

Bowen Liu

Bowen Liu, PhD candidate, Faculty of Education, East China Normal University, Shanghai 200062, China. His research interests are educational data mining and learning analytics.

Yonghe Wu

Yonghe Wu, Doctor, Professor, Faculty of Education, East China Normal University, Shanghai 200062, China. His research interests are artificial intelligence, learning analytics and STEM education.

Wanli Xing

Wanli Xing, Doctor, Assistant Professor, School of Teaching and Learning, University of Florida, Gainesville 32611, USA. His research interests are artificial intelligence, learning analytics, STEM education and online learning.

Gexing Cheng

Gexing Cheng, Master student, Faculty of Education, East China Normal University, Shanghai 200062, China. Her research interests are educational data analysis and learning analytics.

Shengnan Guo

Shengnan Guo, PhD candidate, Faculty of Education, East China Normal University, Shanghai 200062, China. Her research interests are educational data analysis and learning analytics.