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

TL;DR

This study explores EFL students' attitudes towards AI-assisted writing, revealing mostly positive feelings but also tensions related to AI limitations and students' desire for language autonomy, using Activity Theory.

Contribution

It applies Activity Theory to analyze student attitudes and contradictions in machine-in-the-loop writing, highlighting practical considerations for AI integration in EFL education.

Findings

Students generally have positive attitudes towards AI-assisted writing.

Contradictions arise from AI limitations and students' desire for language autonomy.

Aligning AI tools with student values enhances learning activity.

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.