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Identifying localization in peer reviews of argument diagrams

Nguyen, HV and Litman, DJ (2013) Identifying localization in peer reviews of argument diagrams. In: UNSPECIFIED.

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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. © 2013 Springer-Verlag Berlin Heidelberg.


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Details

Item Type: Conference or Workshop Item (UNSPECIFIED)
Status: Published
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Nguyen, HVhvn3@pitt.eduHVN3
Litman, DJdlitman@pitt.eduDLITMAN
Centers: Other Centers, Institutes, or Units > Learning Research & Development Center
Date: 16 July 2013
Date Type: Publication
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Journal or Publication Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume: 7926 L
Page Range: 91 - 100
Event Type: Conference
DOI or Unique Handle: 10.1007/978-3-642-39112-5-10
Institution: University of Pittsburgh
Schools and Programs: Dietrich School of Arts and Sciences > Computer Engineering
Dietrich School of Arts and Sciences > Computer Science > Computer Science Technical Reports
Refereed: Yes
ISBN: 9783642391118
ISSN: 0302-9743
Related URLs:
Date Deposited: 14 Aug 2014 15:46
Last Modified: 04 Nov 2019 19:58
URI: http://d-scholarship.pitt.edu/id/eprint/22691

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