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A Qualitative Approach to EFL Postgraduates’ GenAI-Assisted Research Writing Within Social Sciences

Publié
Serveur de preprints
Preprints.org
DOI
10.20944/preprints202509.1514.v1

In academic L2 English / EFL (English as a Foreign Language) writing, GenAI (Generative Artificial Intelligence) and other digital tools are being extensively explored. However, this AI exploration for academic / research writing has been addressed less at postgraduate levels, and even less so, according to different scientific fields. This study examines this topic within Social Sciences at University of Extremadura, Spain. Seven participants with a B2 English level or higher enrolled in a 10-hour hybrid course about GenAI for academic English writing in October and November of 2024, focusing on AI tools and Broad Data-Driven Learning (BDDL) resources (e.g., simple online corpora tools) to assist their writing. Participants’ feedback was collected by qualitative means (in-class discussions, task writing annotation, and final survey). Overall findings indicate notably positive responses and usage of these tools for the improvement of their texts (e.g., linguistic analysis, lexical-grammatical refinement, and text style improvement). Participants also revealed miscellaneous approaches and strategies in their management of GenAI. Despite the study’s small sample, these preliminary findings suggest that postgraduate researchers in Social Sciences combine expert and linguistic knowledge effectively, demonstrating linguistic awareness and digital literacy concerns.

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