Empowering EFL teachers' perceptions of generative AI-mediated self-professionalism.

This study intends to empower English as a Foreign Language (EFL) teachers' perceptions of generative artificial intelligence (AI)-mediated self-professionalism in engagement, attitudes, constraints, and solutions. Employing the mixed methods research design, the researchers collected data from male and female teachers (N = 278) of eight public universities, utilizing convenience sampling and a set of instruments: a questionnaire and a semi-structured interview. The data analysis combined quantitative and qualitative methods, using SPSS version 26 for statistical analysis (Pearson correlation, Cronbach's alpha, means, standard deviations), and thematic analysis for qualitative data, with data triangulation employed to compare questionnaire and interview responses for a comprehensive understanding of EFL teachers' engagement with generative AI. The results revealed that the study sample engaged in self-professionalism at a medium level, yet they hold high attitudes toward generative AI-mediated self-professionalism. In addition, the content analysis exhibited several constraints, including technological competence and AI literacy, AI-generated content reliability and accuracy, ethical issues, and encroachment on professional autonomy. Moreover, the respondents proposed solutions such as offering AI-driven training programs, establishing clear ethical guidelines and protocols, emphasizing AI as a supplementary tool rather than a substitute, and implementing impartial access mechanisms for AI content to strengthen EFL teachers' self-professionalism mediated by generative AI. Studies in the context of generative AI-driven self-professionalism appear limited, particularly in the context of Arab higher education institutions. This dearth of research presents an opportunity for the current study to make significant improvements in contributing innovative insights to the EFL teachers' self-professionalism landscape.