Sep 2026· Technology in Language Teaching & Learning· 1 citation
TL;DR
This study examined how EFL teachers in rural Indonesian secondary schools enact agency, construct professional identity, and position themselves in relation to the emergence of GenAI, and offers insights for supporting AI integration in under-resourced educational contexts.
Abstract
The rapid emergence of Generative Artificial Intelligence (GenAI) is reshaping educational practices, including language education. While existing research has largely examined GenAI’s instructional affordances and ethical implications, less attention has been paid to how teachers experience, interpret, and respond to these changes, particularly in under-resourced contexts. This study examined how EFL teachers in rural Indonesian secondary schools enact agency, construct professional identity, and position themselves in relation to the emergence of GenAI. A qualitative case study was employed to examine three rural EFL teachers using a series of semi-structured interviews conducted over a nine-month period. The data were then analysed using reflexive thematic analysis. Informed by positioning theory and teacher identity and agency, the analysis explores how teachers discursively construct their professional roles, position students, and assign pedagogical meaning to GenAI. Three interrelated themes were identified. First, teachers negotiate GenAI’s pedagogical value, recognising its efficiency for instructional support while expressing concern about superficial learning and cognitive development. Second, they preserve professional identity by positioning themselves as guardians of students’ cognitive integrity, enacting protective agency against premature reliance on GenAI. Third, they adapt to rural realities of integration, where infrastructural constraints, school policies, and students’ informal digital practices shape the conditions of use. The study advances theoretical understandings of teacher agency by highlighting how identity and positioning processes mediate teachers’ responses to GenAI and offers insights for supporting AI integration in under-resourced educational contexts.
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