Enhancing Pre-Service Mathematics Teachers’ English Mathematical Communication through AI-Assisted Differentiated Instruction: An Explanatory Sequential Mixed-Methods Study
DOI:
https://doi.org/10.30659/kontinu.10.2.%25pAbstract
English mathematical communication is a required competence for pre-service mathematics teachers in the era of global education. However, many students have trouble expressing mathematical thinking in English academic language. The purpose of this study was to examine the impact of AI-assisted Differentiated Instruction (DI) on the English mathematical communication of pre-service mathematics teachers and to investigate students’ learning experiences throughout the intervention. An explanatory sequential mixed-methods design was utilized. 21 pre-service mathematics teachers participated in the study. The quantitative data were analysed using the Wilcoxon Signed-Rank Test, effect size, and N-gain analysis. Additionally, qualitative data were collected through semi-structured interviews with six purposively selected participants and were analysed using thematic analysis. The quantitative results revealed a statistically significant improvement in English mathematical communication (Z = 2.385, p = 0.017) with a large effect size (r = 0.52) after the intervention. However, the N-gain analysis results showed low gains in all dimensions of communication, with the least gain in communicating the problem-solving steps. In qualitative findings, generative AI was conducive to reflective mathematical communication, while DI alleviated communication anxiety by catering to different readiness levels, interests, and learning styles. However, limited English mathematical vocabulary remained a challenge.
Keywords: AI-assisted learning, differentiated instruction, English mathematical communication skills
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