Automatic item generation: foundations and machine learning-based approaches for assessments
Article Status
Published
Authors/contributors
- Circi, Ruhan (Author)
- Hicks, Juanita (Author)
- Sikali, Emmanuel (Author)
Title
Automatic item generation: foundations and machine learning-based approaches for assessments
Abstract
This mini review summarizes the current state of knowledge about automatic item generation in the context of educational assessment and discusses key points in the item generation pipeline. Assessment is critical in all learning systems and digitalized assessments have shown significant growth over the last decade. This leads to an urgent need to generate more items in a fast and efficient manner. Continuous improvements in computational power and advancements in methodological approaches, specifically in the field of natural language processing, provide new opportunities as well as new challenges in automatic generation of items for educational assessment. This mini review asserts the need for more work across a wide variety of areas for the scaled implementation of AIG.
Publication
Frontiers in Education
Volume
8
Pages
858273
Date
2023-5-10
Journal Abbr
Front. Educ.
ISSN
2504-284X
Short Title
Automatic item generation
Accessed
05/12/2023, 17:29
Library Catalogue
DOI.org (Crossref)
Extra
Citation Key: circi2023
<标题>: 自动题目生成:评估的基础与基于机器学习的方法
<AI Smry>: This mini review asserts the need for more work across a wide variety of areas for the scaled implementation of AIG and discusses key points in the item generation pipeline.
Citation
Circi, R., Hicks, J., & Sikali, E. (2023). Automatic item generation: foundations and machine learning-based approaches for assessments. Frontiers in Education, 8, 858273. https://doi.org/10.3389/feduc.2023.858273
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