The Impact of AI Chatbot-Supported Guided Discovery Learning on Pre-service Teachers’ Learning Performance and Motivation

The emergence of AI chatbots brings new opportunities for active and personalized learning. Integrating AI chatbots into instruction requires guidance from the teacher to scaffold students’ purposeful scientific discovery. The present study framed the AI chatbot within guided discovery learning (GDL) and integrated the ARCS motivational model to create an innovative instructional strategy. The impact of this AI chatbot-supported GDL approach on pre-service teachers’ learning performance and motivation in global warming education was investigated. A pre-experimental design was employed with 59 sophomore teacher education majors at a public university in southern China. Data were collected through pre- and post-tests of global warming knowledge, an ARCS model survey, and focus group interviews. Results showed a significant improvement in students’ global warming knowledge and positive motivation across all ARCS categories. Qualitative analysis revealed that the approach enhanced students’ attention, perceived relevance, confidence, and satisfaction in learning about global warming. The integration of AI chatbots with GDL facilitated active engagement, personalized learning, and the development of critical thinking skills. The findings suggest that combining emerging AI technologies with established pedagogical frameworks can create engaging and effective learning experiences in environmental education. This study contributes to the potential of AI-supported learning approaches to empower future educators in addressing global environmental challenges.