TOWARD AI-MEDIATED MATHEMATICAL REPRESENTATION

Abstract

Recent advances in generative artificial intelligence (AI) have created new opportunities for enhancing mathematics education, particularly in supporting students’ engagement with abstract concepts through digital representations. This evaluative action research study examines the effectiveness of integrating generative AI as a mediating cognitive tool within a projectbased learning (PBL) framework to foster mathematical thinking and digital inquiry skills among Arab secondary school students in Israel.

The study employed a mixed methods design, combining quantitative survey data with qualitative analysis of students’ AI interaction logs, reflective teacher observations, and a concluding focus discussion. Participants were nine Grade 11 students with no prior programming experience, who were tasked with designing an interactive web based mathematical application using natural language interaction with large language models. The project emphasized the construction and interpretation of multiple digital representations to support conceptual understanding and problem solving.

Findings indicate that students successfully developed functional digital applications and demonstrated significant growth in mathematical thinking, representational fluency, and strategic interaction with AI tools. Qualitative evidence revealed a clear progression from initial confusion to increasingly sophisticated inquiry strategies, highlighting the central role of conceptual understanding in guiding effective AI mediated learning.

The study contributes a practical and theoretically grounded model for integrating generative AI into mathematics education in linguistically diverse and resource limited contexts, emphasizing that pedagogical design rather than technological availability alone is critical to meaningful learning outcomes.