Student engagement profiles in a mobile app: Links to self-regulated learning and performance

  • Jacqueline Wong*
  • , Mohammad Khalil
  • , Vsevolod Suschevskiy
  • , Martine Baars
  • , Bjorn de Koning
  • , Fred Paas
  • *Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Engaging in independent learning during self-study time is an essential part of learning in higher education. The ubiquity of mobile devices and their applications offer students a flexible, on-the-go learning experience. However, flexible learning environments require students to self-regulate their learning. The current study examined student engagement with a mobile study app intended for students to engage in retrieval practice with feedback as part of self-regulated learning (SRL). Three research questions were addressed: (1) What are the student engagement profiles that can be identified based on students’ activity with the study app? (2) Do the profiles differ in SRL and academic performance? and (3) What is the relationship between the identified student profiles, SRL, and academic performance? Through a learning analytics approach, results identified three distinct student profiles: active, disengaged, and utilitarian. Self-efficacy and time-management positively predicted exam grades, while self-evaluation showed an inverse effect. Active engagement positively influenced exam grades, underscoring individual differences in SRL.
Original languageEnglish
JournalEducational Technology Research and Development
DOIs
Publication statusE-pub ahead of print - 21 Jan 2026

Bibliographical note

Publisher Copyright:
© The Author(s) 2026.

Funding

J. Wong’s work is (partly) supported by the Dutch Research Council (NWO) under the Talent programme with project number VI.Veni.221G.065.

FundersFunder number
Nederlandse Organisatie voor Wetenschappelijk OnderzoekVI.Veni.221G.065

    Keywords

    • Latent profile analysis
    • Mobile applications
    • Retrieval practice
    • Self-regulated learning (SRL)
    • Student engagement
    • Trace data

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