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    <titleInfo>
        <title>A Multi-aspect Analysis of Automatic Essay Scoring for Brazilian Portuguese</title>
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    <name type="personal">
        <namePart type="given">Evelin</namePart>
        <namePart type="family">Amorim</namePart>
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    <name type="personal">
        <namePart type="given">Adriano</namePart>
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            <title>Proceedings of the Student Research Workshop at the 15th Conference of the European Chapter of the Association for Computational Linguistics</title>
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        <name type="personal">
            <namePart type="given">Florian</namePart>
            <namePart type="family">Kunneman</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Uxoa</namePart>
            <namePart type="family">Iñurrieta</namePart>
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            <namePart type="given">John</namePart>
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            <namePart type="family">Camilleri</namePart>
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            <publisher>Association for Computational Linguistics</publisher>
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    <abstract>Several methods for automatic essay scoring (AES) for English language have been proposed. However, multi-aspect AES systems for other languages are unusual. Therefore, we propose a multi-aspect AES system to apply on a dataset of Brazilian Portuguese essays, which human experts evaluated according to five aspects defined by Brazilian Government to the National Exam to High School Student (ENEM). These aspects are skills that student must master and every skill is assessed apart from each other. Besides the prediction of each aspect, the feature analysis also was performed for each aspect. The AES system proposed employs several features already employed by AES systems for English language. Our results show that predictions for some aspects performed well with the features we employed, while predictions for other aspects performed poorly. Also, it is possible to note the difference between the five aspects in the detailed feature analysis we performed. Besides these contributions, the eight millions of enrollments every year for ENEM raise some challenge issues for future directions in our research.</abstract>
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%0 Conference Proceedings
%T A Multi-aspect Analysis of Automatic Essay Scoring for Brazilian Portuguese
%A Amorim, Evelin
%A Veloso, Adriano
%Y Kunneman, Florian
%Y Iñurrieta, Uxoa
%Y Camilleri, John J.
%Y Ardanuy, Mariona Coll
%S Proceedings of the Student Research Workshop at the 15th Conference of the European Chapter of the Association for Computational Linguistics
%D 2017
%8 April
%I Association for Computational Linguistics
%C Valencia, Spain
%F amorim-veloso-2017-multi
%X Several methods for automatic essay scoring (AES) for English language have been proposed. However, multi-aspect AES systems for other languages are unusual. Therefore, we propose a multi-aspect AES system to apply on a dataset of Brazilian Portuguese essays, which human experts evaluated according to five aspects defined by Brazilian Government to the National Exam to High School Student (ENEM). These aspects are skills that student must master and every skill is assessed apart from each other. Besides the prediction of each aspect, the feature analysis also was performed for each aspect. The AES system proposed employs several features already employed by AES systems for English language. Our results show that predictions for some aspects performed well with the features we employed, while predictions for other aspects performed poorly. Also, it is possible to note the difference between the five aspects in the detailed feature analysis we performed. Besides these contributions, the eight millions of enrollments every year for ENEM raise some challenge issues for future directions in our research.
%U https://aclanthology.org/E17-4010
%P 94-102

Markdown (Informal)

[A Multi-aspect Analysis of Automatic Essay Scoring for Brazilian Portuguese](https://aclanthology.org/E17-4010) (Amorim & Veloso, EACL 2017)

• A Multi-aspect Analysis of Automatic Essay Scoring for Brazilian Portuguese (Amorim & Veloso, EACL 2017)

ACL

• Evelin Amorim and Adriano Veloso. 2017. A Multi-aspect Analysis of Automatic Essay Scoring for Brazilian Portuguese. In Proceedings of the Student Research Workshop at the 15th Conference of the European Chapter of the Association for Computational Linguistics, pages 94–102, Valencia, Spain. Association for Computational Linguistics.