Exploring Engagement, Performance, and Satisfaction in Online Self-Directed Professional Learning Using LMS Logs

Juan Hu and Wen Xiao ()
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Juan Hu: School of Computer and Software, Anhui Institute of Information Technology, Wuhu 241002, China
Wen Xiao: School of Educational Science, Anhui Normal University, Wuhu 241002, China

Sustainability, 2024, vol. 16, issue 19, 1-18

Abstract: Online self-directed professional learning plays a crucial role in sustainable career development. This study leverages a high-quality log dataset to thoroughly analyze the learning features of online self-directed professional learners, focusing on their engagement, performance, and satisfaction. The study reveals that the engagement levels among learners are predominantly low, with 56% categorized as low, 33% as medium, and 11% as high. The performance is generally strong, with 47% of learners achieving excellent results, although 4% fall into the poor category. The satisfaction levels are largely neutral (76%), with only 17% of learners expressing satisfaction and 7% feeling delighted. Despite high course ratings, the number of courses purchased remains minimal. The analysis found no significant correlations between engagement, performance, and satisfaction, but noted that purchasing additional courses can enhance engagement. Furthermore, lesson learning shows significant day-to-day fluctuations and minimal linear autocorrelation. The most significant predictor of course performance is the number of questions answered in quizzes. These findings help us to understand the patterns and relationships among these variables to inform future improvements in online learning platforms. Future research should expand LMS log collection to encompass a wider array of learning features for a more thorough analysis, and empirical research should be conducted to investigate potential underlying causes.

Keywords: online self-directed professional learning; engagement; performance; satisfaction (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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