Cognitive load theory and its relationships with motivation: A self-determination theory perspective
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Abstract Although cognitive load theory research has studied factors associated with motivation, these literatures have primarily been developed in isolation from each other. In this contribution, we aimed to advance both fields by examining the effects of instructional strategies on learners’ experience of cognitive load, motivation, engagement, and achievement. Students ( N = 1287) in years 7–10 in four Australian high schools completed survey measures of motivation, engagement, cognitive load, and their teachers’ perceived instructional strategies and motivating style. Results suggest that teachers’ load-reducing instructional strategies were related to lower cognitive load and were positively associated with relative autonomous motivation, engagement, and achievement. Teachers’ motivating styles characterized by autonomy support and structure were also associated with reduced extraneous and intrinsic cognitive load, as well as motivation and engagement. We conclude that by using load-reducing strategies and a motivating style characterized by structure and autonomy support, teachers can reduce students’ cognitive load and improve their self-regulated motivation, engagement, and achievement. In so doing, we discuss a number of future avenues for the joint study of self-determination theory and cognitive load theory, with the aim of refining and extending both perspectives.
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The AIGF-TGF order aligns with cognitive load theory, as students first address less cognitively demanding issues (surface-level concerns) before progressing to more complex tasks (higher-order revisions).
“Moreover, this order aligns with cognitive load theory (Evans et al., 2024), as students first address less cognitively demanding issues (surface-level concerns) before progressing to more complex tasks (higher-order revisions).”
From Enhancing EFL Writing Revision Practices: The Impact of AI- and Teacher-Generated Feedback and Their Sequences (2025) · cites this paper as Evans et al., 2024
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- Authors
- Evans, P., Vansteenkiste, M., Parker, P., Kingsford-Smith, A., & Zhou, S.
- Affiliations
- UNSW Sydney (AU)
- Ghent University (BE)
- Australian Catholic University (AU)
- The University of Melbourne (AU)
- Corresponding author
- Evans, Paul
- Venue
- Educational Psychology Review
- Published
- 2024-01-15
- Volume
- 36
- Issue
- 1
- ISSN
- 1040-726X (ISSN-L)
- 1573-336X
- OpenAlex
- W4390863507
- Cited by
- 200
- References
- 94
- Citations by year
- 2026: 92 · 2025: 88 · 2024: 20
- FWCI
- 82.20
- Type
- journal article
- Language
- en
- Update notices
- correction (2024-02-06)
- Open access
- hybrid
- doi.org
- Locations
- Educational Psychology Review (publishedVersion, cc-by)
- Minerva Access (University of Melbourne) (submittedVersion, cc-by)
- Funders
- University of New South Wales
- Topics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Visual and Cognitive Learning Processes
- Social Sciences › Psychology › Developmental and Educational Psychology › Innovative Teaching and Learning Methods
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Education, Achievement, and Giftedness
- Keywords
- cognitive load theory, self-determination theory, motivation, teaching methods, autonomous motivation, student engagement, academic performance, autonomy support, structure, extraneous cognitive load, intrinsic cognitive load, high school students
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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