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Generative Artificial Intelligence and Early Math Abilities: Improving Young children’s Pattern Skills with a GenAI-Supported Intervention
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DOI：10.1080/10447318.2026.2678539.png)
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Abstract
En 中文
Patterning is a foundational aspect of early mathematical development that supports algebraic reasoning and generalization. However, intervention studies aimed at improving patterning skills in early childhood are limited. This study examined the effect of a GenAI-supported intervention on children’s patterning skills. This quasi-experimental study involved three groups: two experimental groups and one control group. The participants were 76 preschool children. One group received an intervention that included GenAI support, while the other received an intervention based entirely on concrete materials without GenAI support. Patterning skills were assessed using a pretest, a post-test, and a follow-up measure four weeks later. The findings showed that both interventions were more effective than the control group, but those receiving GenAI support achieved larger and more sustained improvements. Overall, our findings suggest that a teacher-mediated human–AI collaborative approach may be feasible and promising for supporting preschool children’s pattern skills within an early mathematics context.
Keywords:
GenAI
human–AI interaction
hybrid intelligence
pattern
learning trajectories
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