Data-driven Feedback Generation
Data-Driven Feedback Generation is a computational approach to automated feedback generation that derives feedback through systematic analysis of empirical data, distinguished from rule-based or expert-defined methods by its reliance on observed patterns and statistical regularities extracted from large-scale datasets.
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229
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83
Institutions
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2017–2026
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Design and Evaluation of a Data-Driven Password Meter
Blase Ur, Felicia Alfieri, Maung Aung et al. · 2017 · 122 citations
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North Carolina State University
Raleigh, United States
4 h-index
13 publications
475 citations
Microsoft (United States)
Redmond, United States
4 h-index
7 publications
192 citations
Carnegie Mellon University
Pittsburgh, United States
3 h-index
14 publications
1.5K citations
University of California, Davis
Davis, United States
3 h-index
5 publications
232 citations

Hanyang University
Seoul, South Korea
2 h-index
6 publications
99 citations
Eindhoven University of Technology
Eindhoven, The Netherlands
2 h-index
3 publications
34 citations
University of Illinois Chicago
Chicago, United States
2 h-index
3 publications
164 citations
Harvard University
Cambridge, United States
2 h-index
2 publications
47 citations
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Conference · 2 publications · 84 citations
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2 publications · 47 citations
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2 publications · 470 citations
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2 publications · 39 citations
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