Fostering Mathematical Conceptual Understanding through ChatGPT-Assisted Discovery Learning
Abstract
This study examines the impact of the Discovery Learning model assisted by ChatGPT on students’ mathematical conceptual understanding. Employing a quasi-experimental Non-Equivalent (Pretest–Posttest) Control Group design, two classes participated: one received instruction through Discovery Learning integrated with ChatGPT, while the control group was taught using Direct Instruction. The conceptual understanding test, validated and confirmed reliable, assessed five indicators of mathematical understanding. The results revealed that the experimental group achieved significantly higher posttest scores and greater normalized gains (N-Gain = 0.212) compared to the control group (N-Gain = 0.131). Notably, the most substantial improvement occurred in transforming mathematical representations. These findings suggest that incorporating ChatGPT within Discovery Learning fosters deeper conceptual understanding through adaptive feedback, guided reasoning, and reflective engagement, highlighting its potential as an effective pedagogical innovation for mathematics education in the digital era.
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DOI: http://dx.doi.org/10.18415/ijmmu.v12i12.7200
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