Intense, turbulent, or wallowing in the mire: a longitudinal study of cross-course online tactics, strategies, and trajectories

Mohammed Saqr, Sonsoles López-Pernas, Jelena Jovanović, Dragan Gašević

Research output: Contribution to journalArticleResearchpeer-review

9 Citations (Scopus)

Abstract

Research has repeatedly demonstrated that students with effective learning strategies are more likely to have better academic achievement. Existing research has mostly focused on a single course or two, while longitudinal studies remain scarce. The present study examines the longitudinal sequence of students' strategies, their succession, consistency, temporal unfolding, and whether students tend to retain or adapt strategies between courses. We use a large dataset of online traces from 135 students who completed 10 successive courses (i.e., 1350 course enrollments) in a higher education program. The methods used in this study have shown the feasibility of using trace data recorded by learning management systems to unobtrusively trace and model the longitudinal learning strategies across a program. We identified three program-level strategy trajectories: a stable and intense trajectory related to deep learning where students used diverse strategies and scored the highest grades; a fluctuating interactive trajectory, where students focused on course requirements, scored average grades, and were relatively fluctuating; and a light trajectory related to surface learning where students invested the least effort, scored the lowest grades, and had a relatively stable pathway. Students who were intensely active were more likely to transfer the intense strategies and therefore, they were expected to require less support or guidance. Students focusing on course requirements were not as effective self-regulators as they seemed and possibly required early guidance and support from teachers. Students with consistent light strategies or low effort needed proactive guidance and support.

Original languageEnglish
Article number100902
Number of pages16
JournalInternet and Higher Education
Volume57
DOIs
Publication statusPublished - Apr 2023

Keywords

  • Learning analytics
  • Learning strategies
  • Longitudinal studies
  • Sequence analysis

Cite this