Gender differences in computation strategies
Evidence across adolescent and adult samples
Bibliographic Data
| ID | 21297103 |
|---|---|
| Authors | Martha B Makowski (0000-0002-1015-3735, Department of Mathematics The University of Alabama Tuscaloosa Alabama USA, corresponding author), Sarah Theule Lubienski (0000-0002-0162-0733, Department of Curriculum and Instruction Indiana University Bloomington Indiana USA), Colleen M Ganley (0000-0002-8902-9189, Department of Psychology Florida State University Tallahassee Florida USA), Iwan A J Sianturi (0000-0003-0770-9349, Department of Curriculum and Instruction State University of New York at Oswego Oswego New York USA), Shilpa A Hart (0000-0001-9793-0420, Department of Psychology University of Waterloo Waterloo Ontario Canada) |
| Year | 2026 |
| Volume | 96 |
| Issue | 2 |
| Pages | 702-732 |
| Publication date | 2026-06-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | British Journal of Educational Psychology (JOURNAL) |
| Journal identifiers | ISSN: 0007-0998 • E-ISSN: 2044-8279 |
| Publisher | Wiley (PUBLISHER • GB) |
| DOI | 10.1111/bjep.70047 |
| PMID | 41317094 |
| OpenAlex | W4416816615 |
| Language | EN |
| Citations received | 1 |
| References cited | 84 |
BACKGROUND: On computation items, young girls tend to use algorithmic approaches more than boys do. However, it is unclear whether these patterns persist as students progress into adulthood. AIMS: In two independent studies using different measures, we examine gender differences in computation strategy use in adolescents (Study 1) and adults (Study 2). We explore factors that might explain differences, and whether they relate to gender differences in math performance. SAMPLES: Study 1 uses data from students at a U.S. public high school (n = 213; 54.5% female). Study 2 uses data from U.S. adults (n = 810; 58.6% women). METHODS: Participants completed computation items, math performance measures and measures commonly found to relate to both gender and math. The unique relations between algorithm use, gender and math performance were examined while accounting for key covariates. RESULTS: Girls and women used an algorithm more often than their male counterparts, as did people with lower mental rotation skills and higher teacher-pleasing tendencies (Study 1) and higher test anxiety (Study 2). After including covariates, the gender difference in algorithm use decreased in Study 1 but not in Study 2. Across both studies, girls and women, and those who use algorithms more, had lower performance on problem-solving measures, as did those with higher teacher-pleasing tendencies and lower confidence (Study 1) and lower math anxiety (Study 2). CONCLUSIONS: Gendered patterns in algorithm use within older samples and the negative relation of algorithm use with math performance point to the need for renewed focus on developing children's computational approaches.
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| Unique citing works | 1 |
|---|---|
| Citations per year | 1 |
| Citation span | 2026 - 2026 (1) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 1 |