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Please use this identifier to cite or link to this item:https://repository.isls.org//handle/1/987
Title: Making the Most Out of It: Maximizing Learners’ Benefits from Expert, Peer and Automated Feedback across Domains
Authors: Wichmann, Astrid
McNamara, Danielle S.
Bolzer, Markus
Strijbos, Jan-Willem
Fischer, Frank
Leiba, Moshe
Funk, Alexandra
Rummel, Nikol
Ronen, Michaela
Peters, Olaf
Narciss, Susanne
Körndle, Hermann
Roscoe, Rod D.
Varner, Laura K.
Snow, Erica L.
Quintana, Chris
Issue Date: Jun-2014
Publisher: Boulder, CO: International Society of the Learning Sciences
Citation: Wichmann, A., McNamara, D. S., Bolzer, M., Strijbos, J., Fischer, F., Leiba, M., Funk, A., Rummel, N., Ronen, M., Peters, O., Narciss, S., Körndle, H., Roscoe, R. D., Varner, L. K., Snow, E. L., & Quintana, C. (2014). Making the Most Out of It: Maximizing Learners’ Benefits from Expert, Peer and Automated Feedback across Domains. In Joseph L. Polman, Eleni A. Kyza, D. Kevin O'Neill, Iris Tabak, William R. Penuel, A. Susan Jurow, Kevin O'Connor, Tiffany Lee, and Laura D'Amico (Eds.). Learning and Becoming in Practice: The International Conference of the Learning Sciences (ICLS) 2014. Volume 3. Colorado, CO: International Society of the Learning Sciences, pp. 1416-1425.
Abstract: Across a variety of domains, formative feedback is often regarded as beneficial, if not crucial to learning. Yet studies show that this assumption does not always hold true: some types of feedback do not benefit learners. This symposium brings together researchers investigating how feedback can be optimized to maximize potential benefits. The four papers include studies investigating the effectiveness of feedback from various sources including expert, peer and automatically generated feedback in the domains of writing and math. The studies use a variety of methodological approaches including behavioral studies, eye tracking, and data mining. The discussion emanating from the results to be reported during the symposium will focus on how these empirical findings can help to inform feedback delivery in the classroom and how to more effectively design automated feedback.
URI: https://doi.dx.org/10.22318/icls2014.1416
https://repository.isls.org//handle/1/987
Appears in Collections:ICLS2014

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