From Receptive to Productive: Learning to Use Confusing Words through Automatically Selected Example Sentences

June 06, 2019 ยท Declared Dead ยท ๐Ÿ› BEA@ACL

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Authors Chieh-Yang Huang, Yi-Ting Huang, Mei-Hua Chen, Lun-Wei Ku arXiv ID 1906.02782 Category cs.CL: Computation & Language Citations 2 Venue BEA@ACL Last Checked 5 months ago
Abstract
Knowing how to use words appropriately has been a key to improving language proficiency. Previous studies typically discuss how students learn receptively to select the correct candidate from a set of confusing words in the fill-in-the-blank task where specific context is given. In this paper, we go one step further, assisting students to learn to use confusing words appropriately in a productive task: sentence translation. We leverage the GiveMeExample system, which suggests example sentences for each confusing word, to achieve this goal. In this study, students learn to differentiate the confusing words by reading the example sentences, and then choose the appropriate word(s) to complete the sentence translation task. Results show students made substantial progress in terms of sentence structure. In addition, highly proficient students better managed to learn confusing words. In view of the influence of the first language on learners, we further propose an effective approach to improve the quality of the suggested sentences.
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