Co-designing an AI-supported English as a foreign language course for civic engagement: a participatory qualitative study with Algerian learners

• Autor: Tobbi, Saida
• Formato: artículo
• Fecha de Publicación: 2026
• Institución: Universidad de Huánuco
• Repositorio: Revistas - Universidad de Huánuco
• Lenguaje: español; inglés
• OAI Identifier: oai:ojs2.localhost:article/1200
• Enlace del recurso: http://revistas.udh.edu.pe/udh/article/view/1200
• Nivel de acceso: acceso abierto
• Materia: AI literacy; AI-Supported course; civic engagement; participatory co-design; AI interaction logs; alfabetización en IA; curso apoyado por IA; participación cívica; codiseño participativo; registros de interacción con IA

This study foregrounds learner-generated governance practices by co-designing and piloting an AI-supported EFL course for civic engagement with students at University of Batna 2. Using participatory action research (PAR) coupled with micro-analytic analysis of AI interaction logs, interviews, and co-design artifacts, the study traced how students conceived civic aims in English, how generative AI mediated task design and enactment, and which pedagogical heuristics emerged from collaborative work. Results showed that learners articulated three civic orientations—localized community action, institutional advocacy, and knowledge awareness—and experienced AI in three mediational roles: a generative drafting scaffold, an interlocutor for negotiation, and a source of rhetorical templates. Participants developed situated governance strategies (iterative re-prompting to tune tone/audience, deletion or verification of dubious content, and formal documentation protocols such as prompt scripts and verification checklists). These practices shaped course design, integrating AI literacy, action-oriented tasks, mandatory AI documentation, and instructor facilitation. This study extends sociocultural accounts of mediation by treating AI as an active mediational artefact and demonstrates the value of triangulating PAR, micro-log analysis, and artifact study. Practically, it produces learner-authored heuristics and a design template for ethically responsible, context-sensitive AI-enhanced EFL courses suitable for settings with infrastructural and political constraints.