Background:
This study aimed to investigate the effect of the motor game “Treasure Game” (TG) on first-grade children’s level of geometric thinking and post-learning mood tracking (PLMT).
Methods:
The study employed 24 first-grade children aged 6.1 ± 0.7 years from a public primary school in Tunisia, all classified at Level 1 of van Hiele geometric thinking (GT). Participants were randomly in a counterbalanced, randomized crossover design in 2 groups and engaged in both the TG during physical education sessions and the conventional geometry course (CGC) during mathematics sessions over a 3-week period, with sessions counterbalanced to avoid order effects. The Van Hiele geometry test was administered to assess GT, and a mood chart was used to track PLMT. Data were analyzed using the SPSS software (Chicago), applying paired and independent samples t-tests to compare the effects of TG and CGC on GT and mood, with significance set at P < .05 and effect sizes calculated using Cohen D and Hedges g.
Results:
The results indicated that the TG had a significant positive impact on both GT and PLMT in first-grade children. In group 1, there was no significant difference in GT after the CGC compared to TG; however, group 2 showed a significant improvement in GT after TG compared to CGC, with a large effect size. Additionally, PLMT scores were significantly higher after TG than after CGC in both groups, with mood scores increasing when transitioning from CGC to TG and decreasing when transitioning from TG to CGC. Overall, the data demonstrate that TG significantly enhances both cognitive and emotional outcomes in young learners compared to traditional geometry instruction.
Conclusion:
The study confirms that participation in the TG significantly enhances GT and improves post-learning mood in first-grade children. This suggests that integrating motor activities like TG into the curriculum could be a viable strategy for enhancing early geometric education. Further research with larger sample sizes and considerations of gender differences is recommended.