Enhancing e-learning effectiveness based on student preferences and actual learning behaviors: a data-driven analysis of LMS usage - Kartiwi, Mira; Gunawan, Teddy Surya; Abdullah, Zainatul Shima; Abdullah, Lili Marziana; Subiyakto, Aang (IEEE, 2026)
E-learning has become an integral part of higher education, yet there remains a gap between students’ expectations of e-learning content and their actual engagement with the learning materials provided in Learning Management Systems (LMS). Focusing on courses with varying instructional designs, i.e. guided versus unguided activity sequences, the research investigates discrepancies between anticipated and actual elearning behaviors. The study identifies key engagement trends, revealing that courses with guided sequences achieve nearuniversal access rates and more consistent student interactions compared to unguided courses, which exhibit higher variability and selective engagement. The findings underscore the effectiveness of structured learning pathways in promoting balanced and deeper engagement across all content types. These results highlight the importance of intentional course design in digital learning environments, suggesting that guided sequences mitigate inconsistent participation and enhance overall learning outcomes. The study provides actionable recommendations for optimizing e-learning frameworks through scaffolded instructional strategies.