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A Survey on Recent Approaches to Question Difficulty Estimation from Text

Accepted version
Peer-reviewed

Type

Article

Change log

Abstract

jats:pQuestion Difficulty Estimation from Text (QDET) is the application of Natural Language Processing techniques to the estimation of a value, either numerical or categorical, which represents the difficulty of questions in educational settings. We give an introduction to the field, build a taxonomy based on question characteristics, and present the various approaches that have been proposed in recent years, outlining opportunities for further research. This survey provides an introduction for researchers and practitioners into the domain of question difficulty estimation from text and acts as a point of reference about recent research in this topic to date.</jats:p>

Description

Keywords

Question difficulty estimation, question calibration, student assessment

Journal Title

ACM Computing Surveys

Conference Name

Journal ISSN

0360-0300
1557-7341

Volume Title

Publisher

Association for Computing Machinery (ACM)
Sponsorship
Cambridge Assessment (unknown)