1. Identifying Localization in Peer Reviews of Argument Diagrams
- Author
-
Huy Nguyen and Diane J. Litman
- Subjects
Computer science ,business.industry ,Argument ,Feature (machine learning) ,Artificial intelligence ,Machine learning ,computer.software_genre ,business ,computer - Abstract
Peer-review systems such as SWoRD lack intelligence for detecting and responding to problems with students’ reviewing performance. While prior work has demonstrated the feasibility of automatically identifying desirable feedback features in free-text reviews of student papers, similar methods have not yet been developed for feedback regarding argument diagrams. One desirable feedback feature is problem localization, which has been shown to positively correlate with feedback implementation in both student papers and argument diagrams. In this paper we demonstrate that features previously developed for identifying localization in paper reviews do not work well when applied to peer reviews of argument diagrams. We develop a novel algorithm tailored for reviews of argument diagrams, and demonstrate significant performance improvements in identifying problem localization in an experimental evaluation.
- Published
- 2013