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        <namePart type="given">Stig</namePart>
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        <namePart type="given">Taraka</namePart>
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    <name type="personal">
        <namePart type="given">Lilja</namePart>
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            <title>Proceedings of the Fourteenth Workshop on Innovative Use of NLP for Building Educational Applications</title>
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        <name type="personal">
            <namePart type="given">Helen</namePart>
            <namePart type="family">Yannakoudakis</namePart>
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        <name type="personal">
            <namePart type="given">Ekaterina</namePart>
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        <name type="personal">
            <namePart type="given">Nitin</namePart>
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        <name type="personal">
            <namePart type="given">Ildikó</namePart>
            <namePart type="family">Pilán</namePart>
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            <namePart type="given">Torsten</namePart>
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    <abstract>In this paper we present first results for the task of Automated Essay Scoring for Norwegian learner language. We analyze a number of properties of this task experimentally and assess (i) the formulation of the task as either regression or classification, (ii) the use of various non-neural and neural machine learning architectures with various types of input representations, and (iii) applying multi-task learning for joint prediction of essay scoring and native language identification. We find that a GRU-based attention model trained in a single-task setting performs best at the AES task.</abstract>
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%0 Conference Proceedings
%T Regression or classification? Automated Essay Scoring for Norwegian
%A Johan Berggren, Stig
%A Rama, Taraka
%A Øvrelid, Lilja
%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 johan-berggren-etal-2019-regression
%X In this paper we present first results for the task of Automated Essay Scoring for Norwegian learner language. We analyze a number of properties of this task experimentally and assess (i) the formulation of the task as either regression or classification, (ii) the use of various non-neural and neural machine learning architectures with various types of input representations, and (iii) applying multi-task learning for joint prediction of essay scoring and native language identification. We find that a GRU-based attention model trained in a single-task setting performs best at the AES task.
%R 10.18653/v1/W19-4409
%U https://aclanthology.org/W19-4409
%U https://doi.org/10.18653/v1/W19-4409
%P 92-102

Markdown (Informal)

[Regression or classification? Automated Essay Scoring for Norwegian](https://aclanthology.org/W19-4409) (Johan Berggren et al., BEA 2019)

• Regression or classification? Automated Essay Scoring for Norwegian (Johan Berggren et al., BEA 2019)

ACL

• Stig Johan Berggren, Taraka Rama, and Lilja Øvrelid. 2019. Regression or classification? Automated Essay Scoring for Norwegian. In Proceedings of the Fourteenth Workshop on Innovative Use of NLP for Building Educational Applications, pages 92–102, Florence, Italy. Association for Computational Linguistics.