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

doi:10.18653/v1/W19-4433

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

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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.

Anthology ID:: W19-4433
Volume:: Proceedings of the Fourteenth Workshop on Innovative Use of NLP for Building Educational Applications
Month:: August
Year:: 2019
Address:: Florence, Italy
Editors:: Helen Yannakoudakis, Ekaterina Kochmar, Claudia Leacock, Nitin Madnani, Ildikó Pilán, Torsten Zesch
Venue:: BEA
SIG:: SIGEDU
Publisher:: Association for Computational Linguistics
Note:
Pages:: 316–325
Language:
URL:: https://aclanthology.org/W19-4433/
DOI:: 10.18653/v1/W19-4433
Bibkey:
Cite (ACL):: Tomoya Mizumoto, Hiroki Ouchi, Yoriko Isobe, Paul Reisert, Ryo Nagata, Satoshi Sekine, and Kentaro Inui. 2019. Analytic Score Prediction and Justification Identification in Automated Short Answer Scoring. In Proceedings of the Fourteenth Workshop on Innovative Use of NLP for Building Educational Applications, pages 316–325, Florence, Italy. Association for Computational Linguistics.
Cite (Informal):: Analytic Score Prediction and Justification Identification in Automated Short Answer Scoring (Mizumoto et al., BEA 2019)
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PDF:: https://aclanthology.org/W19-4433.pdf

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@inproceedings{mizumoto-etal-2019-analytic,
    title = "Analytic Score Prediction and Justification Identification in Automated Short Answer Scoring",
    author = "Mizumoto, Tomoya  and
      Ouchi, Hiroki  and
      Isobe, Yoriko  and
      Reisert, Paul  and
      Nagata, Ryo  and
      Sekine, Satoshi  and
      Inui, Kentaro",
    editor = "Yannakoudakis, Helen  and
      Kochmar, Ekaterina  and
      Leacock, Claudia  and
      Madnani, Nitin  and
      Pil{\'a}n, Ildik{\'o}  and
      Zesch, Torsten",
    booktitle = "Proceedings of the Fourteenth Workshop on Innovative Use of NLP for Building Educational Applications",
    month = aug,
    year = "2019",
    address = "Florence, Italy",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/W19-4433/",
    doi = "10.18653/v1/W19-4433",
    pages = "316--325",
    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."
}

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%0 Conference Proceedings
%T Analytic Score Prediction and Justification Identification in Automated Short Answer Scoring
%A Mizumoto, Tomoya
%A Ouchi, Hiroki
%A Isobe, Yoriko
%A Reisert, Paul
%A Nagata, Ryo
%A Sekine, Satoshi
%A Inui, Kentaro
%Y Yannakoudakis, Helen
%Y Kochmar, Ekaterina
%Y Leacock, Claudia
%Y Madnani, Nitin
%Y Pilán, Ildikó
%Y Zesch, Torsten
%S Proceedings of the Fourteenth Workshop on Innovative Use of NLP for Building Educational Applications
%D 2019
%8 August
%I Association for Computational Linguistics
%C Florence, Italy
%F mizumoto-etal-2019-analytic
%X 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.
%R 10.18653/v1/W19-4433
%U https://aclanthology.org/W19-4433/
%U https://doi.org/10.18653/v1/W19-4433
%P 316-325

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Markdown (Informal)

[Analytic Score Prediction and Justification Identification in Automated Short Answer Scoring](https://aclanthology.org/W19-4433/) (Mizumoto et al., BEA 2019)

Analytic Score Prediction and Justification Identification in Automated Short Answer Scoring (Mizumoto et al., BEA 2019)

ACL

Tomoya Mizumoto, Hiroki Ouchi, Yoriko Isobe, Paul Reisert, Ryo Nagata, Satoshi Sekine, and Kentaro Inui. 2019. Analytic Score Prediction and Justification Identification in Automated Short Answer Scoring. In Proceedings of the Fourteenth Workshop on Innovative Use of NLP for Building Educational Applications, pages 316–325, Florence, Italy. Association for Computational Linguistics.