Abstract:

Artificial Intelligence (AI) is increasingly being integrated into teacher education programmes, yet limited empirical research has examined how pre-service English as a Foreign Language (EFL) teachers incorporate AI tools in distance education contexts. This study investigates the selection and integration of AI tools, their pedagogical purposes, and the technical and pedagogical challenges pre-service EFL teachers encountered during micro-teaching sessions.

The research employed a qualitative case study approach within a teacher education programme at a Slovak university. The participants were 22 pre-service EFL teachers enrolled in a master's programme. Data were collected through structured observation of recorded micro-teachings conducted in synchronous distance education lessons via Google Meet.

The findings show that AI image generation was the most frequently selected AI tool type across sessions, reflecting a preference for creative and visually engaging activities over language development. Engagement was the dominant pedagogical function, accounting for the largest share of tool uses, though it rarely deepened content or advanced the central lesson goal. When mapped against the Substitution, Augmentation, Modification, and Redefinition (SAMR) model, most sessions remained at the Substitution or Augmentation levels. This finding suggests enhancement rather than transformation of learning tasks. Only one presenter reached the Redefinition level, while several others achieved Modification through AI-assisted creative work. Across the dataset, the novelty of AI tools appeared to take precedence over pedagogical intentionality.

The most common challenges were a lack of specific AI tool guidance for learners, observed in nine of the twenty-two sessions, insufficient contingency planning and abrupt transitions between lesson phases. A tendency to end lessons without consolidation or feedback occurred in seventeen of the twenty-two sessions. Viewed through the Technological Pedagogical Knowledge (TPK) lens, tool choices frequently prioritised engagement over lesson goals, and technical difficulties were often left unresolved during delivery.

These findings point to the need for stronger technical preparation, pedagogical scaffolding, and contingency planning in teacher education programmes that aim to equip future EFL teachers for AI-supported online instruction.

Keywords:

Artificial intelligence, teacher education, pre-service teachers, distance education, EFL teaching, SAMR model, TPACK.