Improving Computer-Assisted Language Learning Through the Lens of Cognitive Load
A contemporary review (over a 10-year period) was conducted into studies that used computer-assisted language learning (CALL) strategies to learn a second language (L2) by considering the impact of cognitive load. Twelve affordances were identified that led to enhanced learning, namely, online annot...
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| Veröffentlicht in: | Educational psychology review Jg. 35; H. 2; S. 53 |
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| Hauptverfasser: | , , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
New York
Springer US
01.06.2023
Springer Springer Nature B.V |
| Schlagworte: | |
| ISSN: | 1040-726X, 1573-336X |
| Online-Zugang: | Volltext |
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| Zusammenfassung: | A contemporary review (over a 10-year period) was conducted into studies that used computer-assisted language learning (CALL) strategies to learn a second language (L2) by considering the impact of cognitive load. Twelve affordances were identified that led to enhanced learning, namely, online annotations and glosses, captioning, digital game-based language learning, videoconferencing and video feedback, visualization-based learning approaches, online instructional content and features, online machine translation tools, online interactive collaborative learning, (meta)cognitive learning strategies argument mapping, computer-mediated dictionary assisted learning, and multiple display screens. Associated with these affordances were a number of conditions and learner characteristics that modified the effectiveness of the affordances such as L2 proficiency. Most learning strategies were used to reduce cognitive load, although a limited number fostered germane cognitive load through generative learning practices. A number of issues associated with measuring cognitive load, multimedia learning, and research designs are also discussed. |
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| Bibliographie: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| ISSN: | 1040-726X 1573-336X |
| DOI: | 10.1007/s10648-023-09764-y |