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Motivation and Overdependence on ChatGPT: A Correlational Study Among EFL Students

Sep 2026 · ELT Forum: Journal of English Language Teaching · Vol 15, pp. 104-115 · 0 citations

TL;DR

It can be concluded that there are factors that have a greater influence than motivation on the level of EFL students' dependence on ChatGPT and educational institutions and educators can establish structured guidelines for academic writing so that the use of AI in assignments can still be accountable and not violate academic ethics.

Abstract

The rapid development of technology with the advent of AI tools such as ChatGPT in the field of education provides practical steps for EFL students, especially in assisting them in completing academic writing. However, there is still little research focusing on the relationship between student motivation and overdependence on AI tools. To determine the relationship between motivation levels and overdependence on ChatGPT to assist with academic writing among EFL students, the researcher employed a quantitative correlational study. The participants of this study were selected through a purposive sampling method, consisting of 26 EFL students who are currently taking or have completed an academic writing course. The questionnaire data were collected online via Google Forms. The analysis results indicated that there was no significant correlation between motivation levels and overdependence on ChatGPT among EFL students, as evidenced by a Sig. value of 0.454 (p > 0.05). It can be concluded that there are factors that have a greater influence than motivation on the level of EFL students' dependence on ChatGPT. Therefore, educational institutions and educators can establish structured guidelines for academic writing so that the use of AI in assignments can still be accountable and not violate academic ethics. Additionally, the limitations of this study include a small sample size and low variable variance. Therefore, future researchers addressing the same topic may consider adding or utilizing external variables and employing specific research methods to conduct a more in-depth exploration.

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