A Learning Analytics View on Dispersion of Learning in MOOCs - Yasmin Khairani Zakaria, Nur; Norman, Helmi; Md Yunus, Melor; Hashim, Harwati; Nordin, Norazah (International Journal of Engineering and Technology, 2018)
Learning analytics of massive open online courses (MOOCs) can assist educators and researchers to understand learning patterns in MOOCs. As learning in these types of environments are still relatively understudied, learning analytics can help in visualizing patterns of learning which include dispersion of learning. Previous studies have indicated that a higher level of dispersion of learning may indicate that a learner is actively participating in a MOOC. As such, the study aims to investigate the dispersion of learning in MOOCs from a learning analytics view and identify the relationships among factors such as total active learning time, peak learning times, and number of comments. The study involved investigating learning analytics of a MOOC for postgraduate studies learning about educational technology with an enrolment of over 660 students. The findings of the study show that high dispersion of learning could indicate that student require a slower pace of learning, while a lower one could indicate vice versa. Results also show that learners with lower completion rates and high dispersion of learning were one who contributed more to the community (i.e. had the greatest number of comments). In sum the findings suggest that dispersion of learning is related to studentsâ€™ overall engagement in MOOCs and dispersion of learning cannot be made the sole measure of learning as it could be related to pace of learning.Â Â