Analytic score prediction and justification identification in automated short answer scoring

Tomoya Mizumoto, Hiroki Ouchi, Yoriko Isobe, Paul Reisert, Ryo Nagata, Satoshi Sekine, Kentaro Inui

Research output: Chapter in Book/Report/Conference proceedingConference contribution

16 Citations (Scopus)

Abstract

This paper provides an analytical assessment of student short answer responses with a view to potential benefits in pedagogical contexts. We first propose and formalize two novel analytical assessment tasks: Analytic score prediction and justification identification, and then provide the first dataset created for analytic short answer scoring research. Subsequently, we present a neural baseline model and report our extensive empirical results to demonstrate how our dataset can be used to explore new and intriguing technical challenges in short answer scoring. The dataset is publicly available for research purposes.

Original languageEnglish
Title of host publicationACL 2019 - Innovative Use of NLP for Building Educational Applications, BEA 2019 - Proceedings of the 14th Workshop
PublisherAssociation for Computational Linguistics (ACL)
Pages316-325
Number of pages10
ISBN (Electronic)9781950737345
Publication statusPublished - 2019
Event14th Workshop on Innovative Use of NLP for Building Educational Applications, BEA 2019, collocated with ACL 2019 - Florence, Italy
Duration: 2019 Aug 2 → …

Publication series

NameACL 2019 - Innovative Use of NLP for Building Educational Applications, BEA 2019 - Proceedings of the 14th Workshop

Conference

Conference14th Workshop on Innovative Use of NLP for Building Educational Applications, BEA 2019, collocated with ACL 2019
Country/TerritoryItaly
CityFlorence
Period19/8/2 → …

ASJC Scopus subject areas

  • Language and Linguistics
  • Linguistics and Language
  • Software

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