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Undergraduate EFL Students’ Experiences Using Perplexity AI in Academic Writing Assignments: A Qualitative Study Hatmanto, Endro Dwi; Purwanti, Eko; Diwyacitta, Duhita Kalyana
Proceedings International Conference on Sustainable Innovation (ICoSI) Vol. 6 No. 1 (2026)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/icosi.v6i1.156

Abstract

This qualitative descriptive research investigates the experiences of undergraduate EFL students utilizing Perplexity AI to enhance their academic writing assignments in a private university in Yogyakarta, Indonesia. Six students, were selected as the participants. Data collection took place in March 2025 through semi-structured interviews lasting 15 to 20 minutes, transcribed, and analyzed through inductive thematic analysis. The findings reveal that students primarily regarded Perplexity AI as a generative search-and-synthesis tool instead of a complete text generator. The advantages included quicker retrieval of potential academic sources, easily digestible summaries of extensive materials, assistance with idea generation and outlining when they felt “stuck,” enhanced efficiency when working under deadlines, perceived improvements in organization and phrasing, and the convenience of free access without stringent query limitations. Nevertheless, students also faced challenges: uncertainty regarding the accuracy and credibility of cited materials (including a mix of quality sources), difficulty in aligning suggested references with academic standards and paywalled access, initial confusion with intricate features, risks of dependency or overreliance, and perceived disparities between free and premium functionalities. In conclusion, Perplexity AI can effectively support source-based writing when combined with explicit instruction on verification, citation practices, and a transparent, process-oriented assessment approach