Distractor Generation
Distractor Generation is a methodological construct in educational assessment that systematically produces plausible incorrect responses for multiple-choice items by leveraging cognitive or linguistic models of misconception and error.
96
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3.6K
Citations
292
Authors
138
Institutions
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2017–2026
56
Parents
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Computer-aided generation of multiple-choice tests
Ruslan Mitkov, Le An Ha · 2003 · 257 citations · Full text
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University of Wolverhampton
Wolverhampton, United Kingdom
4 h-index
11 publications
1.5K citations
Tencent (China)
Shenzhen, China
3 h-index
7 publications
271 citations
Carnegie Mellon University
Pittsburgh, United States
3 h-index
7 publications
204 citations
University of Maryland, College Park
College Park, United States
3 h-index
4 publications
129 citations
Chinese University of Hong Kong
Hong Kong, Hong Kong
2 h-index
6 publications
231 citations

Peking University
Beijing, China
2 h-index
2 publications
50 citations
Beijing Academy of Artificial Intelligence
Beijing, China
2 h-index
2 publications
37 citations
University of California, Berkeley
Berkeley, United States
2 h-index
5 publications
170 citations
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4 publications · 124 citations
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Conference · 3 publications · 133 citations
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3 publications · 92 citations
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2 publications · 244 citations
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