Towards adaptive support for self-regulated learning of causal relations:Evaluating four Dutch word vector models

Advances in computational language models increasingly enable adaptive support for self-regulated learning (SRL) in digital learning environments (DLEs; eg, via automated feedback). However, the accuracy of those models is a common concern for educational stakeholders (eg, policymakers, researchers, teachers and learners themselves). We compared the accuracy of four Dutch language models (ie, spaCy medium, spaCy large, FastText and ConceptNet NumberBatch) in the context of secondary school students' learning of causal relations from expository texts, scaffolded by causal diagram completion. Si... Mehr ...

Verfasser: Pijeira-Diaz, Hector J.
Braumann, Sophia
van de Pol, Janneke
van Gog, Tamara
de Bruin, Anique B. H.
Dokumenttyp: Artikel
Erscheinungsdatum: 2024
Reihe/Periodikum: Pijeira-Diaz , H J , Braumann , S , van de Pol , J , van Gog , T & de Bruin , A B H 2024 , ' Towards adaptive support for self-regulated learning of causal relations : Evaluating four Dutch word vector models ' , British Journal of Educational Technology . https://doi.org/10.1111/bjet.13431
Schlagwörter: automatic scoring evaluation / causal relation learning / computational linguistic models / diagram completion task / semantic similarity
Sprache: Englisch
Permalink: https://search.fid-benelux.de/Record/base-27440537
Datenquelle: BASE; Originalkatalog
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Link(s) : https://cris.maastrichtuniversity.nl/en/publications/e9193e3b-4b9b-47ef-ba52-33a05c8d68b0