Biodata

Fouzia Rouaghe: is an Associate Professor of English Applied Linguistics at the University of Sétif, Algeria, with over 15 years of teaching experience. She has taught a diverse range of modules, including English for Specific Purposes (ESP), oral expression, grammar, phonology, cross-cultural communication, and pragmatics. A CELTA-certified Teacher Trainer, she has also served as a peer reviewer for national and international academic journals in Algeria, Turkey, and the Kingdom of Saudi Arabia.She is the author of multiple manuscripts published in Scopus-indexed journals and an active reviewer for prestigious publishers such as Elsevier and SAGE. In addition, she has chaired numerous webinars and on-site conferences, where she has invited renowned speakers at both local and international levels.

Plenary talk title: Enhancing Thematic Analysis with Ethical AI Enrichment and Human Insight
Thematic analysis (TA) is crucial but challenging qualitative research approach, especially for beginners, being interpretive rather than statistical (Braun & Clarke, 2006). Students will find it challenging to be fully consistent in coding, producing themes, and evading researcher subjectivity that affects reliability (Nowell et al., 2017). With the introduction of artificial intelligence, tools like ChatGPT and AI-powered software in NVivo offer new ways to aid or complement human-led analysis. This paper contrasts traditional TA with AI-enhanced ones, highlighting differences in pace, consistency, bias, and depth of interpretation. Although there is the possibility to extend efficiency and pattern recognition through AI, human interpretation is still required for constructing rich and contextual themes (Saldanha et al., 2023). We recommend a hybrid model that encourages students to use AI ethically and strategically. AI can assist with early-stage coding or clustering, but students should critically evaluate outputs and remain aware of ethical concerns, such as over-reliance or lack of transparency. Ultimately, the human touch cannot be substituted when it comes to comprehending emotions, cultural background, and theoretical relevance. We propose triangulating AI tools with human judgment to strengthen the depth and credibility of findings, while fostering ethical and reflective learning in qualitative analysis.
References
Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101.
Nowell, L. S., Norris, J. M., White, D. E., & Moules, N. J. (2017). Thematic analysis: Striving to meet the trustworthiness criteria. International Journal of Qualitative Methods, 16(1).
Saldanha, J., Smith, K., & Garcia, R. (2023). AI-assisted qualitative data analysis: Opportunities and challenges. Qualitative Inquiry, 29(1), 15–28.