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

Chieh-Yang Huang, Yi-Ting Huang, MeiHua Chen, Lun-Wei Ku


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 GiveMe-Example 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.
Anthology ID:
W19-4447
Volume:
Proceedings of the Fourteenth Workshop on Innovative Use of NLP for Building Educational Applications
Month:
August
Year:
2019
Address:
Florence, Italy
Venues:
ACL | BEA | WS
SIG:
SIGEDU
Publisher:
Association for Computational Linguistics
Note:
Pages:
461–471
Language:
URL:
https://aclanthology.org/W19-4447
DOI:
10.18653/v1/W19-4447
Bibkey:
Cite (ACL):
Chieh-Yang Huang, Yi-Ting Huang, MeiHua Chen, and Lun-Wei Ku. 2019. From Receptive to Productive: Learning to Use Confusing Words through Automatically Selected Example Sentences. In Proceedings of the Fourteenth Workshop on Innovative Use of NLP for Building Educational Applications, pages 461–471, Florence, Italy. Association for Computational Linguistics.
Cite (Informal):
From Receptive to Productive: Learning to Use Confusing Words through Automatically Selected Example Sentences (Huang et al., 2019)
Copy Citation:
PDF:
https://aclanthology.org/W19-4447.pdf