Cited by 12Online Learning and AnalyticsInnovative Teaching and Learning MethodsOnline and Blended Learning

A multi-modal study into students’ timing and learning regulation: time is ticking

Tempelaar, Dirk, Rienties, Bart, Nguyen, Quan·2018·Interactive Technology and Smart Education

Abstract

Purpose This empirical study aims to demonstrate how the combination of trace data derived from technology-enhanced learning environments and self-response survey data can contribute to the investigation of self-regulated learning processes. Design/methodology/approach Using a showcase based on 1,027 students’ learning in a blended introductory quantitative course, the authors analysed the learning regulation and especially the timing of learning by trace data. Next, the authors connected these learning patterns with self-reports based on multiple contemporary social-cognitive theories. Findings The authors found that several behavioural facets of maladaptive learning orientations, such as lack of regulation, self-sabotage or disengagement negatively impacted the amount of practising, as well as timely practising. On the adaptive side of learning dispositions, the picture was less clear. Where some adaptive dispositions, such as the willingness to invest efforts in learning and self-perceived planning skills, positively impacted learning regulation and timing of learning, other dispositions such as valuing school or academic buoyancy lacked the expected positive effects. Research limitations/implications Due to the blended design, there is a strong asymmetry between what one can observe on learning in both modes. Practical implications This study demonstrates that in a blended setup, one needs to distinguish the grand effect on learning from the partial effect on learning in…

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Crossref · 10.1108/itse-02-2018-0015

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  • A substantial number of studies demonstrated strong theoretical grounding by integrating established engagement frameworks into their analyses.

    “A substantial number of studies demonstrated strong theoretical grounding by integrating established engagement frameworks into their analyses (e.g., Tempelaar et al., 2018;Wong & Chong, 2018).”
  • Tempelaar et al. (2018) utilised the Epistemic Emotion Scales and Achievement Emotions Questionnaire to explore the interplay between learning cognition, behaviour, and regulation among undergraduate students.

    “For instance, Tempelaar et al. (2018) utilised the Epistemic Emotion Scales and Achievement Emotions Questionnaire to explore the interplay between learning cognition, behaviour, and regulation among undergraduate students.”

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References 23 · Cited by 12

Authors
Tempelaar, D., Rienties, B., & Nguyen, Q.
Affiliations
  • Maastricht University (NL)
  • The Open University (GB)
Venue
Interactive Technology and Smart Education
Publisher
Emerald
Published
2018-07-01
Volume
15
Issue
4
Pages
298-313
ISSN
1741-5659 (ISSN-L)
OpenAlex
W2796449575
Cited by
12
References
23
Citations by year
2025: 2 · 2024: 2 · 2022: 1 · 2021: 2 · 2020: 1 · 2019: 4
FWCI
2.21
Type
journal article
Language
en
Open access
closed
Locations
  • Interactive Technology and Smart Education (publishedVersion)
  • Research Publications (Maastricht University) (publishedVersion)
  • Open Research Online - ORO (The Open University) (acceptedVersion)
  • Research Publications (Maastricht University) (submittedVersion)
Topics
  • Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
  • Social Sciences › Psychology › Developmental and Educational Psychology › Innovative Teaching and Learning Methods
  • Social Sciences › Education › Online and Blended Learning
Keywords
student self-regulation, trace data, blended learning, technology-enhanced learning, learning dispositions, self-sabotage, disengagement, academic buoyancy, effort investment

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