Designing Ethical Intelligent Learning Ecologies for English Language Education: A Qualitative Study of Farhangian University Teachers' Experiences of Professional Agency and AI Governance

The purpose of the present study was to design ethical intelligent learning ecologies for English language education, focusing on Farhangian University teachers’ experiences of professional agency and AI governance. This study used a qualitative approach with an interpretive-critical orientation. The research population consisted of English language teachers from Farhangian University campuses in Isfahan Province. Participants were selected through purposive sampling from among teachers who had experience using intelligent technologies, digital tools, or AI-based systems in English language teaching. Data were collected through semi-structured interviews, classroom observation, field notes, and instructional documents. The data were analyzed using open, axial, and selective coding. In the open coding stage, initial concepts were extracted from interview transcripts and field data. In the axial coding stage, similar codes were organized into 13 axial codes. In the selective coding stage, these codes were integrated into five main components. The findings revealed that ethical intelligent learning ecologies in English language education consist of five components: teacher agency, AI governance and accountability, reconfiguration of educational interactions, cognitive and pedagogical consequences of AI use, and human-centered and context-sensitive technology design. The results indicate that artificial intelligence in language education should not be viewed merely as a supportive instructional tool, but as a socio-technical force that can reorganize teachers’ roles, educational interactions, ethical responsibility, and learning experiences. Therefore, ethical AI use requires preserving teachers’ professional judgment, algorithmic transparency, data governance, and design aligned with the actual classroom context.