Guiding collaborative revision of science explanations
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Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
AI can evaluate students' responses and provide feedback based on the evaluation in formative assessment.
“In formative assessment, AI can evaluate students’ responses and provide feedback based on the evaluation [15, 18, 43, 50].”
From Comparing Student Preferences for AI-Generated and Peer-Generated Feedback in AI-driven Formative Peer Assessment (2025) · cites this paper as [15]
Cites
Restructuring the Classroom: Conditions for Productive Small Groups
Cohen, E. G. (1994) · Review of Educational Research · doi:10.3102/00346543064001001 · Cited by 2,120 · see citing works
Thagard, P. (1992) · doi:10.1515/9780691186672 · Cited by 1,066 · see citing works
Classroom Orchestration: Synthesis
Roschelle, J., Dimitriadis, Y., & Hoppe, U. (2013) · Computers & Education · doi:10.1016/j.compedu.2013.04.010 · Cited by 150 · see citing works
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Applying machine learning in science assessment: A systematic review
Zhai, X., Yin, Y., Pellegrino, J. W., Haudek, K. C., & Shi, L. (2020) · Studies in Science Education · doi:10.1080/03057267.2020.1735757 · Cited by 257 · see citing works
Ding, A.-C. E., Shi, L., Yang, H., & Choi, I. (2024) · Computers and Education Open · doi:10.1016/j.caeo.2024.100178 · Cited by 228 · see citing works
Shin, I., Hwang, S. B., Yoo, Y. J., Bae, S., & Kim, R. Y. (2025) · Proceedings of the 15th International Learning Analytics and Knowledge Conference · doi:10.1145/3706468.3706488 · Cited by 16 · see citing works
“In formative assessment, AI can evaluate students’ responses and provide feedback based on the evaluation [15, 18, 43, 50].”
- Authors
- Gerard, L., Kidron, A., & Linn, M. C.
- Affiliations
- University of California, Berkeley (US)
- Corresponding author
- Gerard, Libby
- Venue
- International Journal of Computer-Supported Collaborative Learning
- Published
- 2019-05-02
- Volume
- 14
- Issue
- 3
- Pages
- 291-324
- ISSN
- 1556-1607 (ISSN-L)
- 1556-1615
- OpenAlex
- W2943445133
- Cited by
- 58
- References
- 3
- Citations by year
- 2026: 6 · 2025: 8 · 2024: 16 · 2023: 10 · 2022: 6 · 2021: 7 · 2020: 5
- FWCI
- 2.08
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- International Journal of Computer-Supported Collaborative Learning (publishedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- National Science Foundation (DRL-1119670, DRL-1418423, and DRL-01451604)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Social Sciences › Psychology › Developmental and Educational Psychology › Innovative Teaching and Learning Methods
- Social Sciences › Education › Science Education and Pedagogy
- Keywords
- collaborative revision, teacher guidance, computer-supported collaborative learning, automated grading, adaptive guidance, plate tectonics, teacher-student relationship, teacher professional development, virtual learning environments
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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