Training self-assessment and task-selection skills to foster self-regulated learning : Do trained skills transfer across domains?
Students' ability to accurately self-assess their performance and select a suitable subsequent learning task in response is imperative for effective self-regulated learning. Video modeling examples have proven effective for training self-assessment and task-selection skills, and-importantly-such training fostered self-regulated learning outcomes. It is unclear, however, whether trained skills would transfer across domains. We investigated whether skills acquired from training with either a specific, algorithmic task-selection rule or a more general heuristic task-selection rule in biology would transfer to self-regulated learning in math. A manipulation check performed after the training confirmed that both algorithmic and heuristic training improved task-selection skills on the biology problems compared with the control condition. However, we found no evidence that students subsequently applied the acquired skills during self-regulated learning in math. Future research should investigate how to support transfer of task-selection skills across domains.
Medienart: |
E-Artikel |
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Erscheinungsjahr: |
2018 |
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Erschienen: |
2018 |
Enthalten in: |
Zur Gesamtaufnahme - volume:32 |
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Enthalten in: |
Applied cognitive psychology - 32(2018), 2 vom: 03. März, Seite 270-277 |
Sprache: |
Englisch |
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Beteiligte Personen: |
Raaijmakers, Steven F [VerfasserIn] |
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Links: |
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Themen: |
Example‐based learning |
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Anmerkungen: |
Date Revised 14.03.2024 published: Print-Electronic Citation Status PubMed-not-MEDLINE |
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doi: |
10.1002/acp.3392 |
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funding: |
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Förderinstitution / Projekttitel: |
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PPN (Katalog-ID): |
NLM282599770 |
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