EFL Students' Attitudes and Contradictions in a Machine-in-the-loop Activity System

July 13, 2023 Β· Declared Dead Β· πŸ› arXiv.org

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Authors David James Woo, Hengky Susanto, Kai Guo arXiv ID 2307.13699 Category cs.HC: Human-Computer Interaction Cross-listed cs.AI, cs.CL Citations 3 Venue arXiv.org Last Checked 4 months ago
Abstract
This study applies Activity Theory and investigates the attitudes and contradictions of 67 English as a foreign language (EFL) students from four Hong Kong secondary schools towards machine-in-the-loop writing, where artificial intelligence (AI) suggests ideas during composition. Students answered an open-ended question about their feelings on writing with AI. Results revealed mostly positive attitudes, with some negative or mixed feelings. From a thematic analysis, contradictions or points of tension between students and AI stemmed from AI inadequacies, students' balancing enthusiasm with preference, and their striving for language autonomy. The research highlights the benefits and challenges of implementing machine-in-the-loop writing in EFL classrooms, suggesting educators align activity goals with students' values, language abilities, and AI capabilities to enhance students' activity systems.
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