AI-Supported Design of Teaching Units for English to Young Learners: A Case Study in Initial Teacher Education

Abstract

While generative artificial intelligence (GenAI) is increasingly used by university students for writing support, less is known about its role in discipline-specific professional tasks. This study examines how pre-service primary teachers integrate and conceptualise GenAI when designing Teaching Units for English for Young Learners (EYL), with a focus on whether AI is positioned as a substitute for pedagogical reasoning or as a support within teacher decision-making. The qualitative study involved 75 fifth-year pre-service teachers at the Free University of Bozen-Bolzano (Italy), working in 23 groups. Data included 23 Teaching Units and 10 AI Use Reports, analysed through document analysis and thematic coding. GenAI was used mainly for material production (visual and text generation, idea generation, and text revision) and resource adaptation, with limited evidence of use for macro- or micro-planning decisions (objectives, sequencing, assessment). Prompts were often underspecified, but reports described iterative refinement and critical adaptation to improve age appropriateness and reduce lexical overload. Overall, within a transparent course framework, pre-service teachers retained pedagogical ownership while using GenAI as a supplementary resource, underscoring the need to develop pedagogically grounded AI literacy (prompt design, evaluation, and disclosure).

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