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Master thesis written by Casper Hildebrand at the faculty Electrical Engineering, Mathematics and Computer Science to obtain the degree of Master of Science at the Delft University of Technology.

Summary

Within the field of computer science (CS), women are under-represented in the workforce and education settings. As Massive Open Online Courses (MOOCs) grow in popularity, understanding the gender differences in reasons for enrollment and engagement remains crucial to improving learner outcomes. This study investigates why men and women enroll in introductory CS MOOCs and how they interact with these courses. This is done with data from four MOOCs offered by TU Delft between 2015 and 2022.

Using survey data for the learners’ reasons for enrolment and clickstream data for their behavioural engagement, we applied k-means clustering to identify engagement patterns. Our analysis reveals that the three most important reasons for men and women are career-related, interest-related, and degree-related, in that order. Women are more likely to enrol for career-related reasons than men, while men are more driven by interest in the topic than women. Women also tend to show lower engagement levels compared to men, who are more likely to complete the courses. We found no significant association between reasons for enrollment and engagement for men and women.

These findings highlight the need for gender-sensitive course design strategies to enhance engagement and completion rates. Providing mentorship opportunities, fostering peer interaction platforms, and highlighting role models in the field could also help create a more inclusive learning environment. Future research should explore specific learner challenges and incorporate a more comprehensive engagement model.

Keywords

Gender diversity, online learning, computer science, MOOCS, continuing education, motivation, engagement

Reference

Hildebrand, C.W.R. (2024) DEBUGGING THE DIVIDE: EXPLORING MEN’S AND WOMEN’S MOTIVATIONS AND ENGAGEMENT IN COMPUTER SCIENCE MOOCS Master thesis at the TU Delft faculty Electrical Engineering, Mathematics and Computer Science
http://resolver.tudelft.nl/uuid:f4aceeec-5947-4578-834c-4bb43288c91a

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