Effects of learner uptake following automatic corrective recast from Artificial Intelligence chatbots on the learning of English caused-motion construction

Date

2024-06-01

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University of Hawaii National Foreign Language Resource Center
Center for Language & Technology

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28

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2

Starting Page

109

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133

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Abstract

This study investigated the instructional effects of learner uptake following automatic corrective recast from artificial intelligence (AI) chatbots on the learning of the English caused-motion construction. 69 novice-level EFL learners in a Korean high school were recruited to investigate the instructional effects of corrective recast from AI chatbots on the learning of the English caused-motion construction. Results from the elicited writing tasks (EWT) revealed that statistically significant gains were observed in both immediate and delayed posttests for the production of the English caused-motion construction by experimental group participants. Also, the relationship between learner uptake from AI chatbots’ corrective recast and the learning of the English caused-motion construction were analyzed. The results demonstrated that learners’ successful repair from AI chatbots’ corrective recast was positively correlated with the learning gains in the two EWT posttests. The study concludes by highlighting the significance of noticeability in AI chatbots’ corrective feedback for foreign language learning.

Description

Keywords

Artificial Intelligence Chatbot, Caused-motion Construction, Corrective Feedback, Crosslinguistic Interference

Citation

Kim, R. (2024). Effects of learner uptake following automatic corrective recast from artificial intelligence chatbots on the learning of English caused-motion construction. Language Learning & Technology, 28(2), 109–133. https://hdl.handle.net/10125/73574

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133

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Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License

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