Correctness- and Confidence-based Adaptive Feedback of Kit-Build Concept Map with Confidence Tagging
Lecture Notes in Computer Science 10947 巻
395-408 頁
2018-06-20 発行
アクセス数 : 821 件
ダウンロード数 : 169 件
今月のアクセス数 : 4 件
今月のダウンロード数 : 4 件
この文献の参照には次のURLをご利用ください : https://ir.lib.hiroshima-u.ac.jp/00046381
ファイル情報(添付) |
AIED2018_395.pdf
437 KB
種類 :
全文
エンバーゴ :
2019-06-20
|
タイトル ( eng ) |
Correctness- and Confidence-based Adaptive Feedback of Kit-Build Concept Map with Confidence Tagging
|
作成者 |
Pailai Jaruwat
Wunnasri Warunya
|
収録物名 |
Lecture Notes in Computer Science
|
巻 | 10947 |
開始ページ | 395 |
終了ページ | 408 |
抄録 |
In this paper, we present an adaptive feedback of Kit-Build concept map with confidence tagging (KB map-CT) for improving the understanding of learners in a reading situation. KB map-CT is a digital tool that supports the concept maps strategy where learners can construct concept maps for representing their understanding as learner maps and can identify their confidence in each proposition of the learner maps as a degree of their understanding. Kit-Build concept map (KB map) has been already realized the propositional level automatic diagnosis of the learner maps. Therefore, KB map-CT can utilize both correctness and confidence information for each proposition to design and distinguish feedback, that is, (1) correct and confident, (2) correct and unconfident, (3) incorrect and confident, and (4) incorrect and unconfident. An experiment was conducted to investigate the effectiveness of the adaptive feedback. The results suggest that learners can revise their maps after receiving feedback appropriately. In “correct and unconfident” case, adaptive feedback is useful to improve the confidence. In the case of “incorrect and confident,” improvement of the propositions was the same ratio with the case of “incorrect and unconfident.” The results of the delay test demonstrate that learners can retain their understanding and confidence one week later.
|
著者キーワード |
Adaptive feedback
Kit-Build concept map
Confidence tagging
|
内容記述 |
This work was supported by JSPS KAKENHI Grant Number 17H0183901.
'Artificial Intelligence in Education' 19th International Conference, AIED 2018, London, UK, June 27–30, 2018, Proceedings, Part I
|
NDC分類 |
教育 [ 370 ]
|
言語 |
英語
|
資源タイプ | 会議発表論文 |
出版者 |
Springer, Cham
|
発行日 | 2018-06-20 |
権利情報 |
The final authenticated version is available online at https://doi.org/10.1007/978-3-319-93843-1_29.
This is not the published version. Please cite only the published version. この論文は出版社版でありません。引用の際には出版社版をご確認ご利用ください。
|
出版タイプ | Author’s Original(十分な品質であるとして、著者から正式な査読に提出される版) |
アクセス権 | オープンアクセス |
収録物識別子 |
[ISBN] 978-3-319-93842-4
[ISBN] 978-3-319-93843-1
[DOI] 10.1007/978-3-319-93843-1_29
[ISSN] 0302-9743
[ISSN] 1611-3349
|
備考 | Post-print version/PDF may be used in an institutional repository after an embargo period of 12 months. |