<![CDATA[The integration of Artificial Intelligence (AI) in education offers new opportunities to address complex science concepts, yet its interaction with learning styles remains underexplored. Objectives: This study aimed to identify the learning styles of pre-service environmental science teachers and examine how AI-based instruction supports their understanding of electric fields. Using a mixed-methods design, 72 undergraduate students completed the VARK questionnaire, pre- and post-tests on electric field concepts, and participated in interviews. The findings showed significant improvement in conceptual understanding after AI-based learning, with visual and kinesthetic learners benefiting most from simulations and interactive tasks, while aural and read/write learners showed limited gains. Implications: The study highlights the potential of AI to enhance learning through multimodal engagement, but also emphasises the need for inclusive designs that move beyond learning styles toward broader pedagogical frameworks.]]>
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