Abstract
Mathematics development draws on various cognitive and mathematics skills, which may have distinct influence on students at different achievement levels. The current study explored how students' skill profiles contribute to their mathematics achievement levels. Two-hundred-and-seventy-two fourth graders completed assessments on various cognitive and mathematics abilities. Latent profile analysis identified four math achievement classes, namely, mathematics learning disability (MLD), average achievers, high achievers, and mathematical giftedness. Multinomial logistic regression further revealed that, compared to average achievers, students struggling with fraction magnitude understanding and number sentence construction in word problems are more likely to have MLD, students with better spatial skills and fraction magnitude understanding are more likely to be high achievers, and students with better arithmetic principle understanding are more likely to be mathematically gifted. The current findings illustrate the unique cognitive characteristics of students at different achievement levels, which allow practitioners to make level-specific adjustments to their teaching. Education relevance statement: The current study identified four mathematics achievement classes and examined the skills that contributed to the cognitive profile of these ability groups. Our results revealed the critical skills that differentiated between these achievement groups. Notably, number sentence construction and fraction number line differentiated students with mathematics learning difficulties from average performers. Understanding of abstract arithmetic principles was also found to be the distinctive skill for the highest achievers. The findings informed assessment and subsequent intervention for learners at different mathematics achievement levels. Further research and educational practices (remediation, curriculum differentiation, acceleration) could be developed to tailor their unique learning needs.
Original language | English |
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Article number | 102645 |
Journal | Learning and Individual Differences |
Volume | 119 |
Early online date | 10 Feb 2025 |
DOIs | |
Publication status | E-pub ahead of print - 10 Feb 2025 |
Bibliographical note
Publisher Copyright:© 2025 The Authors
Funding
This work was supported by the General Research Fund of the Research Grants Council of Hong Kong (Project Numbers: 17605721, 17607323, 18600318) awarded to the corresponding author.
Keywords
- ANOVA
- Latent profile analysis
- Logistic regression
- Mathematics achievement
- Mathematics learning disability