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 ...
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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 |
Powered By: | BASE |
Link(s) : | https://cris.maastrichtuniversity.nl/en/publications/e9193e3b-4b9b-47ef-ba52-33a05c8d68b0 |