Generating Vocabulary Sets for Implicit Language Learning using Masked Language Modeling

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dc.contributor.authorEdgar, Vatricia
dc.contributor.authorBansal, Ajay
dc.date.accessioned2021-12-24T17:23:00Z
dc.date.available2021-12-24T17:23:00Z
dc.date.issued2022-01-04
dc.description.abstractA well-balanced language curriculum must include both explicit vocabulary learning and implicit vocabulary learning. However, most language learning applications focus on explicit instruction. Students require support with implicit vocabulary learning because they need enough context to guess and acquire new words. Traditional techniques aim to teach students enough vocabulary to comprehend the text, thus enabling them to acquire new words. Despite the wide variety of support for vocabulary learning offered by learning applications today, few offer guidance on how to select an optimal vocabulary study set. This paper proposes a novel method of student modeling with masked language modeling to detect words that are required for comprehension of a text. It explores the efficacy of using deep learning via a pre-trained masked language model to model human reading comprehension and presents a vocabulary study set generation pipeline (VSGP). Promising results show that masked language modeling can be used to model human comprehension and the pipeline produces reasonably sized vocabulary study sets that can be integrated into language learning systems.
dc.format.extent10 pages
dc.identifier.doi10.24251/HICSS.2022.095
dc.identifier.isbn978-0-9981331-5-7
dc.identifier.urihttp://hdl.handle.net/10125/79425
dc.language.isoeng
dc.relation.ispartofProceedings of the 55th Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectText Analytics
dc.subjectlanguage modeling
dc.subjectmachine learning
dc.subjectvocabulary learning
dc.titleGenerating Vocabulary Sets for Implicit Language Learning using Masked Language Modeling
dc.type.dcmitext

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