Self-Regulated Learning and Academic Achievement: A Phenomenological View
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Suggested explanations for learning benefits of granting control include deeper processing of relevant information, error estimation, self-regulation strategies, and increased motivation.
“For example, it has been suggested that a more active involvement of the learner in the learning process promotes deeper processing of relevant information (McCombs, 1989;Watkins, 1984;Chen & Singer, 1992); encourages error estimation (Chiviacowsky & Wulf, 2005); fosters the use of self-regulation strategies (Kirschenbaum, 1984); or that giving the learner control over the practice conditions”
From Optimizing performance through intrinsic motivation and attention for learning: The OPTIMAL theory of motor learning (2016) · cites this paper as McCombs, 1989
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- Authors
- McCombs, B. L.
- Corresponding author
- McCombs, Barbara L.
- Venue
- Springer Series in Cognitive Development
- Publisher
- Springer New York
- Published
- 1989
- Pages
- 51-82
- ISSN
- 1431-8555 (ISSN-L)
- OpenAlex
- W182709558
- Cited by
- 281
- References
- 73
- Citations by year
- 2025: 4 · 2024: 12 · 2023: 8 · 2022: 10 · 2021: 6 · 2020: 6 · 2019: 5 · 2018: 5 · 2017: 17 · 2016: 12 · 2015: 11 · 2014: 7 · 2013: 16 · 2012: 16
- FWCI
- 8.50
- Type
- book chapter
- Language
- en
- Open access
- closed
- Locations
- Springer series in cognitive development (publishedVersion)
- Topics
- Social Sciences › Psychology › Developmental and Educational Psychology › Innovative Teaching and Learning Methods
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Education, Achievement, and Giftedness
- Social Sciences › Psychology › Developmental and Educational Psychology › Psychology of Development and Education
- Keywords
- student self-regulation, phenomenology of the self, self-system, self-experience, student motivation, academic performance, teaching practice
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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.
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