JSAI Technical Report, SIG-ALST
Online ISSN : 2436-4606
Print ISSN : 1349-4104
102nd (Dec.2024)
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Item difficulty estimation method using deep-learning-based virtual examinees
Yuya KURITAMasaki UTO
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Pages 48-53

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Abstract
[in Japanese]
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© 2024 The Japaense Society for Artificial Intelligence
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