Mathematics Outcomes and Creative Metacognition in Primary Students: A Quasi-Experimental Study Using AI-Generated Explanations

This exploration examines the impact of supplementary AI-generated explanatory materials on foundational mathematics learning and creative metacognition in primary education. The study followed a quantitative, quasi-experimental pretest–posttest design with a nonequivalent control group. Fourth-grade classes in five schools were assigned to conditions at the classroom level: an intervention group receiving AI-facilitated handouts (n = 135) and a control group using programmatic textbooks (n = 128). Students in the experimental condition received eight supplementary lessons featuring paper-based handouts. These handouts presented explanations, examples, and illustrations of new mathematical topics generated by a large language model (Gemini 2.5 Pro), prompted the inclusion of age-appropriate content and a dedicated section encouraging creative metacognition (reflection and novel idea generation). Baseline equivalence was confirmed. The outcomes assessed included single-digit mental arithmetic, multidigit calculation, arithmetic word problem-solving, and creative metacognition, which were analyzed via multilevel or robust linear modeling accounting for classroom clustering. The results indicated no statistically significant differences between groups on single-digit mental arithmetic tasks. However, students who received AI-generated materials showed significantly greater improvement in multidigit calculation tasks and one-step word problem-solving than did the control group. No significant difference was found for multistep word problems. The intervention group also presented a substantially greater increase in creative metacognition scores than did the control group. The findings provide preliminary quasi-experimental evidence that curated, static AI-generated explanations, when designed to include metacognitive prompts, may be associated with greater gains in specific procedural and applied mathematical skills and creative metacognition among fourth-grade students under the conditions studied. This approach illustrates how generative AI can be leveraged as an authoring tool to supplement standard instruction and cultivate higher-order cognitive skills in young learners.

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Publication Details

Journal
International Journal of Learning Teaching and Educational Research
Published
2026-10-30
DOI
https://doi.org/10.26803/ijlter.25.10.23
Primary Topic
Mathematics Education and Pedagogy
Type
article
Field-Weighted Citation Impact
0.00
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article

Mathematics Outcomes and Creative Metacognition in Primary Students: A Quasi-Experimental Study Using AI-Generated Explanations

Natalya Nikolaevna Khan, Batima Daumova, Aida Ussenova, Tatyana Karatayeva
2 links
International Journal of Learning Teaching and Educational Research
Mathematics Education and Pedagogy
article

Mathematics Outcomes and Creative Metacognition in Primary Students: A Quasi-Experimental Study Using AI-Generated Explanations

Natalya Nikolaevna Khan, Batima Daumova, Aida Ussenova, Tatyana Karatayeva
article en

Abstract

This exploration examines the impact of supplementary AI-generated explanatory materials on foundational mathematics learning and creative metacognition in primary education. The study followed a quantitative, quasi-experimental pretest–posttest design with a nonequivalent control group. Fourth-grade classes in five schools were assigned to conditions at the classroom level: an intervention group receiving AI-facilitated handouts (n = 135) and a control group using programmatic textbooks (n = 128). Students in the experimental condition received eight supplementary lessons featuring paper-based handouts. These handouts presented explanations, examples, and illustrations of new mathematical topics generated by a large language model (Gemini 2.5 Pro), prompted the inclusion of age-appropriate content and a dedicated section encouraging creative metacognition (reflection and novel idea generation). Baseline equivalence was confirmed. The outcomes assessed included single-digit mental arithmetic, multidigit calculation, arithmetic word problem-solving, and creative metacognition, which were analyzed via multilevel or robust linear modeling accounting for classroom clustering. The results indicated no statistically significant differences between groups on single-digit mental arithmetic tasks. However, students who received AI-generated materials showed significantly greater improvement in multidigit calculation tasks and one-step word problem-solving than did the control group. No significant difference was found for multistep word problems. The intervention group also presented a substantially greater increase in creative metacognition scores than did the control group. The findings provide preliminary quasi-experimental evidence that curated, static AI-generated explanations, when designed to include metacognitive prompts, may be associated with greater gains in specific procedural and applied mathematical skills and creative metacognition among fourth-grade students under the conditions studied. This approach illustrates how generative AI can be leveraged as an authoring tool to supplement standard instruction and cultivate higher-order cognitive skills in young learners.

International Journal of Learning Teaching and Educational Research
Abai Kazakh National Pedagogical University (KZ), Zhetysu University named after Ilyas Zhansugurov (KZ), Akhmet Baitursynuly Kostanay Regional University (KZ)
Quality education
Openalex Percentile: Top 7%
Mathematics Education and Pedagogy
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