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    Using Crowdsourced Exercises for Vocabulary Training to Expand ConceptNet


    Rodosthenous, Christos and Lyding, Verena and Sangati, Federico and König, Alexander and ul Hassan, Umair and Lionel, Nicolas and Horbacauskiene, Jolita and Katinskaia, Anisia and Aparaschivei, Lavinia (2020) Using Crowdsourced Exercises for Vocabulary Training to Expand ConceptNet. Proceedings of the 12th Conference on Language Resources and Evaluation (LREC 2020). pp. 307-316.

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    Abstract

    In this work, we report on a crowdsourcing experiment conducted using the V-TREL vocabulary trainer which is accessed via a Telegram chatbot interface to gather knowledge on word relations suitable for expanding ConceptNet. V-TREL is built on top of a generic architecture implementing the implicit crowdsourding paradigm in order to offer vocabulary training exercises generated from the commonsense knowledge-base ConceptNet and – in the background – to collect and evaluate the learners’ answers to extend ConceptNet with new words. In the experiment about 90 university students learning English at C1 level, based on Common European Framework of Reference for Languages (CEFR), trained their vocabulary with V-TREL over a period of 16 calendar days. The experiment allowed to gather more than 12,000 answers from learners on different question types. In this paper we present in detail the experimental setup and the outcome of the experiment, which indicates the potential of our approach for both crowdsourcing data as well as fostering vocabulary skills.

    Item Type: Article
    Keywords: vocabulary trainer; commonsense knowledge; language learning;
    Academic Unit: Faculty of Social Sciences > School of Business
    Item ID: 16004
    Depositing User: Souleiman Hasan
    Date Deposited: 25 May 2022 10:37
    Journal or Publication Title: Proceedings of the 12th Conference on Language Resources and Evaluation (LREC 2020)
    Publisher: European Language Resources Association
    Refereed: Yes
    URI:

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