AI-Assisted Collaborative Learning in Mathematics Education: A Qualitative Approach

Abstract

The integration of Artificial Intelligence (AI) in collaborative learning environments has transformed educational practices, yet little is known about pre-service mathematics teachers’ perceptions and engagement with such technology. This study aims to address this gap by exploring how pre-service teachers perceive and engage with AI-assisted collaborative learning, identifying factors that influence their experiences. Using a qualitative phenomenological design, we conducted semi-structured interviews with a purposive sample of ten pre-service mathematics teachers. Data were analyzed thematically, yielding three primary themes: engagement in AI-assisted learning, technology comfort and experience, and design of AI tools. Findings reveal that while participants recognize the potential of AI to enhance collaborative learning, their engagement is shaped by prior technology exposure, ease of tool use, and group dynamics. Participants cited the benefits of AI for facilitating peer interaction but also raised concerns regarding technical support and usability. This study contributes to the literature by highlighting the unique challenges pre-service teachers face with AI tools in collaborative settings. Recommendations include the integration of comprehensive technology training within teacher education programs and the development of user-friendly AI tools tailored for collaborative learning to support effective engagement and pedagogical outcomes.