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Automatic scoring of an analytical response-to-text assessment

Rahimi, Z and Litman, DJ and Correnti, R and Matsumura, LC and Wang, E and Kisa, Z (2014) Automatic scoring of an analytical response-to-text assessment. In: UNSPECIFIED.

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Abstract

In analytical writing in response to text, students read a complex text and adopt an analytic stance in their writing about it. To evaluate this type of writing at scale, an automated approach for Response to Text Assessment (RTA) is needed. With the long-term goal of producing informative feedback for students and teachers, we design a new set of interpretable features that operationalize the Evidence rubric of RTA. When evaluated on a corpus of essays written by students in grades 4-6, our results show that our features outperform baselines based on well-performing features from other types of essay assessments. © 2014 Springer International Publishing Switzerland.


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Details

Item Type: Conference or Workshop Item (UNSPECIFIED)
Status: Published
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Rahimi, Zzar10@pitt.eduZAR10
Litman, DJdlitman@pitt.eduDLITMAN
Correnti, Rrcorrent@pitt.eduRCORRENT
Matsumura, LClclare@pitt.eduLCLARE
Wang, E
Kisa, Z
Centers: Other Centers, Institutes, or Units > Learning Research & Development Center
Date: 1 January 2014
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: 8474 L
Page Range: 601 - 610
Event Type: Conference
DOI or Unique Handle: 10.1007/978-3-319-07221-0_76
Institution: University of Pittsburgh
Schools and Programs: Dietrich School of Arts and Sciences > Computer Science
Dietrich School of Arts and Sciences > Computer Science > Intelligent Systems Technical Reports
Refereed: Yes
ISBN: 9783319072203
ISSN: 0302-9743
Date Deposited: 14 Aug 2014 15:51
Last Modified: 02 May 2019 13:59
URI: http://d-scholarship.pitt.edu/id/eprint/22681

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