A Survey on Recent Approaches to Question Difficulty Estimation from Text
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Peer-reviewed
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Abstract
Question 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.
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ACM Computing Surveys
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0360-0300
1557-7341
1557-7341
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Association for Computing Machinery (ACM)
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Except where otherwised noted, this item's license is described as Attribution 4.0 International
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Cambridge Assessment (unknown)