Decoding EFL Learners’ Intention to Use ChatGPT for Academic Writing: Cognitive and Emotional Drivers
ChatGPT, a groundbreaking open artificial intelligence technological development, is revolutionizing academic writing practice across the globe. The effectiveness of technology integration in language learning depends on learners’ attitudes toward it. Hence, the current research investigated Bangladeshi English as a Foreign Language (EFL) learners’ cognitive and affective attitudes and their behavioral intentions to utilize ChatGPT for academic writing. The study was conducted among 159 first-year students in Bangladeshi public and private universities. Data were collected by implementing a Likert scale questionnaire. The study used a quantitative approach to explore individual relationships between cognitive and affective attitudes and behavioral intentions. Also, it probed the mediating role of affective and cognitive attitudes on their relationship with behavioral intention. The Pearson correlation coefficient, multiple regression analysis, and bootstrapping were used for data analysis. Findings reveal that both cognitive and affective attitudes, as independent constructs, significantly influenced the EFL learners’ behavioral intentions to use ChatGPT for academic writing. Cognitive and affective attitudes significantly predicted EFL learners’ intentions to use ChatGPT in academic writing, and the affective attitude was found to be the stronger predictor. Results indicate that affective attitude moderately mediates the relationship between cognitive attitude and behavioral intentions. Likewise, cognitive attitude has a moderate influence on the relationship between affective attitude and behavioral intention to use ChatGPT for EFL academic writing. The study suggests that educators promote the use of ChatGPT in academic writing as a cognitive and emotional support tool. Education policymakers are recommended to create a supportive environment for fostering positive attitudes to ChatGPT as an academic writing tool.
Authors
- Hafizah Binti Hajimia (ORCID: https://orcid.org/0000-0002-9235-9357)
- Nousin Laila Bristi (ORCID: https://orcid.org/0000-0001-9526-0531)
- Latisha Asmaak Shafie (ORCID: https://orcid.org/0000-0003-1188-8095)
- Md. Kamrul Hasan (ORCID: https://orcid.org/0000-0003-2353-4673)
Publication Details
- Journal
- International Journal of Learning Teaching and Educational Research
- Published
- 2025-03-30
- DOI
- https://doi.org/10.26803/ijlter.24.3.1
- Primary Topic
- Online Learning and Analytics
- Type
- article
- Field-Weighted Citation Impact
- 0.00