Artificial Intelligence in Mathematics Teacher Education: A Systematic Review and Qualitative Synthesis of Contemporary Research Literature

Abstract

This qualitative review critically examines the burgeoning influence of AI on pre-service and in-service mathematics teacher education. Amidst rapid technological advancements, this study leverages a systematic qualitative analysis to distill insights from various scholarly articles, book chapters, and conference proceedings published since 2015. The selection process prioritized peer-reviewed, English-language literature that directly addresses the integration and implications of AI technologies within mathematics teacher education programs. Our methodology entailed an exhaustive search across prominent academic databases, utilizing a refined set of keywords to ensure comprehensive coverage of relevant studies. The literature was meticulously coded and analyzed, facilitating a nuanced thematic analysis that identifies, categorizes, and synthesizes the complex interplay between AI and mathematics teacher education. This review sheds light on the diverse applications of AI technologies in these contexts, ranging from virtual simulations and intelligent tutoring systems to personalized learning environments and their pedagogical implications. Key findings reveal AI's benefits, including enhanced pedagogical strategies, personalized learning pathways, and improved student engagement and outcomes. Concurrently, the review elucidates significant challenges such as the digital divide, privacy concerns, and the pressing need for teacher professional development on AI utilization. The analysis culminates in a discussion on the implications of these findings for practice, highlighting the transformative potential of AI in fostering innovative educational practices while cautioning against uncritical adoption. By offering a comprehensive Synthesis of the current state of research, this review contributes to the academic discourse on technology integration in teacher education. It provides practical insights for stakeholders involved in curriculum design and professional development. Furthermore, it delineates fruitful avenues for future research, underscoring the necessity for longitudinal studies to understand AI's long-term impact on teaching practices and learning outcomes in mathematics education.