The Dire Cost of Early Disengagement: A Four-Year Learning Analytics Study over a Full Program
2021 (English)In: EC-TEL 2021: Technology-Enhanced Learning for a Free, Safe, and Sustainable World, Springer Nature , 2021, p. 122-136Conference paper, Published paper (Refereed)
Abstract [en]
Research on online engagement is abundant. However, most of the available studies have focused on a single course. Therefore, little is known about how students’ online engagement evolves over time. Previous research in face-to-face settings has shown that early disengagement has negative consequences on students’ academic achievement and graduation rates. This study examines the longitudinal trajectory of students’ online engagement throughout a complete college degree. The study followed 99 students over 4 years of college education including all their course data (15 courses and 1383 course enrollments). Students’ engagement states for each course enrollment were identified through Latent Class Analysis (LCA). Students who were not engaged at least one course in the first term was labeled as “Early Disengagement”, whereas the remaining students were labeled as “Early Engagement”. The two groups of students were analyzed using sequence pattern mining methods. The stability (persistence of the engagement state), transition (ascending to a higher engagement state or descending to a lower state), and typology of each group trajectory of engagement are described in this study. Our results show that early disengagement is linked to higher rates of dropout, lower scores, and lower graduation rates whereas early engagement is relatively stable. Our findings indicate that it is critical to proactively address early disengagement during a program, watch the alarming signs such as presence of disengagement during the first courses, declining engagement along the program, or history of frequent disengagement states.
Place, publisher, year, edition, pages
Springer Nature , 2021. p. 122-136
Keywords [en]
Early disengagement, Learning analytics, Trajectories of engagement, E-learning, Students, Academic achievements, College education, Face to face, Graduation rates, Latent class analysis, Learning analytic, Sequence pattern mining, Student engagement, Trajectory of engagement, Trajectories
National Category
Educational Sciences Information Systems Pedagogy
Identifiers
URN: urn:nbn:se:kth:diva-311807DOI: 10.1007/978-3-030-86436-1_10ISI: 000791071400010Scopus ID: 2-s2.0-85115441530OAI: oai:DiVA.org:kth-311807DiVA, id: diva2:1655888
Conference
European Conference on Technology Enhanced Learning, 20 September 2021 through 24 September 2021
Note
Part of proceedings: ISBN 9783030864354, QC 20230117
2022-05-042022-05-042025-02-18Bibliographically approved