Artificial intelligence in educational assessment: ‘Breakthrough? Or buncombe and ballyhoo?’-Reference-Cited by-同舟云学术

Artificial intelligence in educational assessment: ‘Breakthrough? Or buncombe and ballyhoo?’

Published:2021-07-05 Issue:5 Volume:37 Page:1207-1216
ISSN:0266-4909
Container-title:Journal of Computer Assisted Learning
language:en
Short-container-title:J Comput Assist Learn

Author:

Gardner John¹^ORCID,O'Leary Michael²^ORCID,Yuan Li³^ORCID

Affiliation:

1. Faculty of Social Sciences University of Stirling Stirling UK

2. Centre for Assessment Research, Policy and Practice in Education (CARPE), Institute of Education Dublin City University Dublin Ireland

3. College of Education for the Future Beijing Normal University Zhuhai Guangdong China

Publisher

Wiley

Subject

Computer Science Applications,Education

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/jcal.12577

Reference61 articles.

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3. Computerized Adaptive Test (CAT) Applications and Item Response Theory Models for Polytomous Items

4. Beigman Klebanov B. Leong C. W.&Flor M. (2015).Supervised word‐level metaphor detection experiments with concreteness and reweighting of examples.Proceedings of the Third Workshop on Metaphor in NLP 11–20. Association for Computational Linguistics.

5. Beigman Klebanov B. Madnani N. Burstein J.&Somasundara S.(2014).Content importance models for scoring writing from sources.Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics 247‐252.

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