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Item Response Theory for Peer Assessment
https://uec.repo.nii.ac.jp/records/8874
https://uec.repo.nii.ac.jp/records/887411a20701-7d24-4946-85b9-efa7bff3754c
名前 / ファイル | ライセンス | アクション |
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IEEE2016_Uto (846.3 kB)
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Item type | 学術雑誌論文 / Journal Article(1) | |||||
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公開日 | 2019-01-15 | |||||
タイトル | ||||||
言語 | en | |||||
タイトル | Item Response Theory for Peer Assessment | |||||
言語 | ||||||
言語 | eng | |||||
キーワード | ||||||
言語 | en | |||||
主題 | Peer assessment | |||||
キーワード | ||||||
言語 | en | |||||
主題 | rater characteristics | |||||
キーワード | ||||||
言語 | en | |||||
主題 | reliability | |||||
キーワード | ||||||
言語 | en | |||||
主題 | item response theory | |||||
キーワード | ||||||
言語 | en | |||||
主題 | hierarchical Bayes model | |||||
資源タイプ | ||||||
資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||
資源タイプ | journal article | |||||
著者 |
Uto, Masaki
× Uto, Masaki× Ueno, Maomi |
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抄録 | ||||||
内容記述タイプ | Abstract | |||||
内容記述 | As an assessment method based on a constructivist approach, peer assessment has become popular in recent years. However, in peer assessment, a problem remains that reliability depends on the rater characteristics. For this reason, some item response models that incorporate rater parameters have been proposed. Those models are expected to improve the reliability if the model parameters can be estimated accurately. However, when applying them to actual peer assessment, the parameter estimation accuracy would be reduced for the following reasons. 1) The number of rater parameters increases with two or more times the number of raters because the models include higher-dimensional rater parameters. 2) The accuracy of parameter estimation from sparse peer assessment data depends strongly on hand-tuning parameters, called hyperparameters. To solve these problems, this article presents a proposal of a new item response model for peer assessment that incorporates rater parameters to maintain as few rater parameters as possible. Furthermore, this article presents a proposal of a parameter estimation method using a hierarchical Bayes model for the proposed model that can learn the hyperparameters from data. Finally, this article describes the effectiveness of the proposed method using results obtained from a simulation and actual data experiments. | |||||
書誌情報 |
en : IEEE Transactions on Learning Technologies 巻 9, 号 2, p. 157-170, 発行日 2016-04 |
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出版者 | ||||||
出版者 | IEEE | |||||
ISSN | ||||||
収録物識別子タイプ | ISSN | |||||
収録物識別子 | 1939-1382 | |||||
DOI | ||||||
関連タイプ | isVersionOf | |||||
識別子タイプ | DOI | |||||
関連識別子 | 10.1109/TLT.2015.2476806 | |||||
権利 | ||||||
権利情報 | © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | |||||
関連サイト | ||||||
識別子タイプ | DOI | |||||
関連識別子 | https://doi.org/10.1109/TLT.2015.2476806 | |||||
著者版フラグ | ||||||
出版タイプ | AM | |||||
出版タイプResource | http://purl.org/coar/version/c_ab4af688f83e57aa |