Adaptive Feedback Generation
Adaptive Feedback Generation is a feedback generation approach that dynamically tailors feedback content, timing, and delivery based on individual learner characteristics, performance, and contextual factors to optimize learning outcomes.
48
Publications
1.9K
Citations
172
Authors
81
Institutions
Publications per year
2017–2026
21
Parents
48
Machine Learning for Precise Quantum Measurement
Alexander Hentschel, Barry C. Sanders · Physical Review Letters · 2010 · 196 citations · Full text
Computing, Computer Science, Physics +15
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81
German Sport University Cologne
Cologne, Germany
2 h-index
4 publications
226 citations

University of Macedonia
Thessaloniki, Greece
2 h-index
2 publications
40 citations
Dana-Farber Cancer Institute
Boston, United States
2 h-index
2 publications
53 citations
Maastricht University
Maastricht, The Netherlands
2 h-index
7 publications
288 citations
Humboldt-Universität zu Berlin
Berlin, Germany
2 h-index
4 publications
291 citations
Gates Foundation
Seattle, United States
2 h-index
2 publications
53 citations
Results for Development Institute
Washington, United States
2 h-index
2 publications
53 citations
National Cheng Kung University
Tainan City, Taiwan
1 h-index
5 publications
185 citations
1–8 of 81
4 publications · 126 citations
4
h-index
2 publications · 53 citations
2
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1 publications · 11 citations
1
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1 publications · 38 citations
1
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1 publications · 74 citations
1
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