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

Erscheinungsjahr:

2018

Erschienen:

2018

Enthalten in:

Zur Gesamtaufnahme - volume:32

Enthalten in:

Applied cognitive psychology - 32(2018), 2 vom: 03. März, Seite 270-277

Sprache:

Englisch

Beteiligte Personen:

Raaijmakers, Steven F [VerfasserIn]
Baars, Martine [VerfasserIn]
Paas, Fred [VerfasserIn]
van Merriënboer, Jeroen J G [VerfasserIn]
van Gog, Tamara [VerfasserIn]

Links:

Volltext

Themen:

Example‐based learning
Journal Article
Self‐assessment
Self‐regulated learning
Task selection
Transfer

Anmerkungen:

Date Revised 14.03.2024

published: Print-Electronic

Citation Status PubMed-not-MEDLINE

doi:

10.1002/acp.3392

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM282599770