Artificial Intelligence in Tertiary English Pedagogy: A Comparative Study of Urban and Rural Contexts in Bangladesh

Abstract

The growing use of Artificial Intelligence (AI), particularly generative AI, is changing practices of English teaching and learning in higher education. Yet access to AI and the capacity to use it pedagogically remain uneven across geographical and socioeconomic contexts. This qualitative comparative study examines how tertiary English educators and undergraduate students in urban and rural higher education institutions in Bangladesh experience and use AI for teaching and learning. The study draws on semi-structured interviews with 10 English educators and 20 undergraduates from selected urban and rural institutions. Interview data were analyzed thematically using Braun and Clarke’s (2006) approach. The findings reveal that the urban-rural difference in AI-supported English pedagogy is multidimensional, involving connectivity, device availability, affordability, AI literacy, pedagogical guidance, institutional policy, and sociocultural conditions. Urban participants reported more frequent use of AI for writing support, lesson planning, vocabulary development, language practice, translation, and feedback, whereas rural participants described greater difficulties arising from unstable internet connectivity, power interruptions, limited devices, financial constraints, and insufficient institutional training. Academic-integrity concerns affected both contexts but often encouraged more restrictive responses where institutional guidance was weak. The study argues that equitable AI integration requires more than access to AI platforms. It requires infrastructure, teacher development, student AI literacy, clear institutional policies, and context-sensitive support. The study contributes a context-based understanding of AI inequality in tertiary English pedagogy in Bangladesh.