Incorporate explicit spatial strategies into mathematics instruction to help narrow sex differences in later-grade, spatially intensive content¶

Strategy · All strategies
Evidence · 5 claims (5 for) · 4 studies (2 quant-synthesis, 2 associational), q3–q4 · 1 of 4 report an effect size · 5 claims rest on one study

Description¶

The authors' forward-looking recommendation is that the content- and grade-specific gaps they document might be narrowed through instruction that explicitly builds spatial strategies in relevant mathematics areas. They state that "the gap might be narrowed with the development of interventions that explicitly incorporate the use of spatial strategies into instruction in some mathematics areas." This targets the growing male advantage in geometry and spatially intensive content in later grades. The recommendation is grounded in the meta-analytic patterns rather than a tested intervention in this article.

Design Implications¶

Context¶

Requirements¶

• Interventions must be developed that explicitly incorporate spatial strategies into instruction in the affected mathematics areas

Constraints¶

• The article did not itself test such interventions; the recommendation is inferred from the meta-analytic patterns

Target Learners¶

• students in later primary and secondary grades

Target Learning Goals¶

• geometry and other spatially intensive mathematics content

Claims¶

• The male advantage in geometry, broad mathematics, and computation increases across grades, reaching approximately d = 0.541, d = 0.255, and d = 0.207 by the end of secondary schooling, but grade slopes are flat for advanced mathematics, basic numeracy, and national tests [+W]
• Spatial Training Improves Math Performance [+M]
• Spatial skills uniquely predict 27% of the variance in preschool mathematics over and above executive function [+W]
• Some aspects of spatial skills are more predictive of mathematical development than others, so the construct must be differentiated [+W]
• Executive function and spatial skills jointly predict 70% of the variance in age-4 mathematics performance without an explicit number-knowledge measure [+W]

Related Strategies¶

Examples¶

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Key Sources¶

• Sara Caviola, David Giofrè, Enrico Toffalini, Lorenzo Esposito, Irene Tonizzi, David C. Geary. (2026). Sex Differences in Mathematics: A Meta-analytic Review Across Content, Grades, and Geographic Regions. Educational Psychology Review. https://doi.org/10.1007/s10648-026-10125-8