Suminar, Elis (2026) AI Dependency and Independent Learning: A Sequential Explanatory Mixed-Methods Analysis of Students’ Perceptions in English Language Education. Masters thesis, Universitas Muhammadiyah Gresik.
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Abstract
The advancement of Artificial Intelligence (AI) technology is reshaping education, particularly in English language learning at the university level. AI tools such as grammar checkers, automated translators, and generative text platforms assist students in understanding materials and improving language skills autonomously. This study examines university students’ perceptions of their AI dependency in supporting independent English learning. Employing a mixed-methods approach, data were gathered via questionnaires from 30 EFL undergraduates and semi-structured interviews with five purposively selected participants. Findings reveal that students appreciate AI tools like Grammarly, Google Translate, and ChatGPT for providing instant feedback, personalized learning experiences, and enhanced language proficiency. However, Findings reveal that students appreciate AI tools like Grammarly, Google Translate, and ChatGPT for providing instant feedback, personalized learning experiences, and enhanced language proficiency. Overall, the effectiveness of AI in supporting independent learning depends greatly on responsible use and balanced integration with traditional instructional methods. This study contributes valuable insights for educational stakeholders in harnessing AI to promote learner autonomy and digital literacy. Keywords: Artificial Intelligence (AI), AI Dependence, Independent Learning, EFL Learning and Technology
| Item Type: | Thesis (Masters) |
|---|---|
| Uncontrolled Keywords: | Artificial Intelligence (AI), AI Dependence, Independent Learning, EFL Learning and Technology |
| Subjects: | English Education English Education > English |
| Divisions: | Postgraduate Programs > Master Program in Teaching as a Foreign Language |
| Depositing User: | Elis Suminar |
| Date Deposited: | 08 Jul 2026 07:24 |
| Last Modified: | 08 Jul 2026 07:24 |
| URI: | http://eprints.umg.ac.id/id/eprint/16707 |
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