<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="wang-andersen-2016-grammatical">
    <titleInfo>
        <title>Grammatical Templates: Improving Text Difficulty Evaluation for Language Learners</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Shuhan</namePart>
        <namePart type="family">Wang</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Erik</namePart>
        <namePart type="family">Andersen</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2016-12</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Yuji</namePart>
            <namePart type="family">Matsumoto</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Rashmi</namePart>
            <namePart type="family">Prasad</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>The COLING 2016 Organizing Committee</publisher>
            <place>
                <placeTerm type="text">Osaka, Japan</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>Language students are most engaged while reading texts at an appropriate difficulty level. However, existing methods of evaluating text difficulty focus mainly on vocabulary and do not prioritize grammatical features, hence they do not work well for language learners with limited knowledge of grammar. In this paper, we introduce grammatical templates, the expert-identified units of grammar that students learn from class, as an important feature of text difficulty evaluation. Experimental classification results show that grammatical template features significantly improve text difficulty prediction accuracy over baseline readability features by 7.4%. Moreover,we build a simple and human-understandable text difficulty evaluation approach with 87.7% accuracy, using only 5 grammatical template features.</abstract>
    <identifier type="citekey">wang-andersen-2016-grammatical</identifier>
    <location>
        <url>https://aclanthology.org/C16-1159</url>
    </location>
    <part>
        <date>2016-12</date>
        <extent unit="page">
            <start>1692</start>
            <end>1702</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T Grammatical Templates: Improving Text Difficulty Evaluation for Language Learners
%A Wang, Shuhan
%A Andersen, Erik
%Y Matsumoto, Yuji
%Y Prasad, Rashmi
%S Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers
%D 2016
%8 December
%I The COLING 2016 Organizing Committee
%C Osaka, Japan
%F wang-andersen-2016-grammatical
%X Language students are most engaged while reading texts at an appropriate difficulty level. However, existing methods of evaluating text difficulty focus mainly on vocabulary and do not prioritize grammatical features, hence they do not work well for language learners with limited knowledge of grammar. In this paper, we introduce grammatical templates, the expert-identified units of grammar that students learn from class, as an important feature of text difficulty evaluation. Experimental classification results show that grammatical template features significantly improve text difficulty prediction accuracy over baseline readability features by 7.4%. Moreover,we build a simple and human-understandable text difficulty evaluation approach with 87.7% accuracy, using only 5 grammatical template features.
%U https://aclanthology.org/C16-1159
%P 1692-1702

Markdown (Informal)

[Grammatical Templates: Improving Text Difficulty Evaluation for Language Learners](https://aclanthology.org/C16-1159) (Wang & Andersen, COLING 2016)

• Grammatical Templates: Improving Text Difficulty Evaluation for Language Learners (Wang & Andersen, COLING 2016)

ACL

• Shuhan Wang and Erik Andersen. 2016. Grammatical Templates: Improving Text Difficulty Evaluation for Language Learners. In Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers, pages 1692–1702, Osaka, Japan. The COLING 2016 Organizing Committee.