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ERIC Number: EJ1248038
Record Type: Journal
Publication Date: 2020
Pages: 12
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-1939-1382
EISSN: N/A
Automatic Multiple Choice Question Generation From Text: A Survey
Rao, Dhawaleswar; Saha, Sujan Kumar
IEEE Transactions on Learning Technologies, v13 n1 p14-25 Jan-Mar 2020
Automatic multiple choice question (MCQ) generation from a text is a popular research area. MCQs are widely accepted for large-scale assessment in various domains and applications. However, manual generation of MCQs is expensive and time-consuming. Therefore, researchers have been attracted toward automatic MCQ generation since the late 90's. Since then, many systems have been developed for MCQ generation. We perform a systematic review of those systems. This paper presents our findings on the review. We outline a generic workflow for an automatic MCQ generation system. The workflow consists of six phases. For each of these phases, we find and discuss the list of techniques adopted in the literature. We also study the evaluation techniques for assessing the quality of the system generated MCQs. Finally, we identify the areas where the current research focus should be directed toward enriching the literature.
Institute of Electrical and Electronics Engineers, Inc. 445 Hoes Lane, Piscataway, NJ 08854. Tel: 732-981-0060; Web site: http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=4620076
Publication Type: Journal Articles; Reports - Research
Education Level: Higher Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A