Analyzing AI-based educational platforms for supporting personalized mathematics learning

This study aimed to explore how AI-based educational platforms can support personalized mathematics learning. The three prominent AI-based educational platforms for mathematics were analyzed using a framework based on four dimensions: source, target, time, and adaptation method. Specifically, this study focused on providing illustrative examples for each dimension to gain insights into the potential of such platforms to support personalized mathematics learning in classroom settings. The findings revealed that all three platforms employed a variety of elements as sources of adaptation to facilitate personalized mathematics learning. They also adopted a dual-pathway approach to determine when to adapt, as well as a shared-controlled approach to how adaptation occurs. In terms of what to adapt, the platforms varied in their approaches to content, presentation format and degree of instructional support. However, KnowRe Math and ALEKS did not offer flexibility in terms of presentation format. Based on these findings, the implications for educators of integrating AI-based platforms for personalized mathematics learning in the classroom are discussed.