Relationships between 8 th -grade students’ background characteristics, affect, and achievement in mathematics in the U.S.: A TIMSS 2023 analysis

Although there is substantial research on students’ affective experiences in mathematics, there remains a need for analyses that leverage new, large-scale datasets to explore relationships among key affective, achievement, and background variables, particularly modeling affective variables as outcomes. This study leveraged the Trends in International Mathematics and Science Study (TIMSS) 2023 8th-grade database (n = 8,074) to explore relationships among background characteristics, mathematics-related affect variables, and student achievement within the United States. Hierarchical linear modeling was employed to account for the nested structure of the data, i.e. students within classrooms and classrooms within schools. Findings indicated that socioeconomic status was a significant predictor of interest in mathematics, value toward mathematics, and confidence in mathematics, although these associations leveled off and/or declined at higher levels of SES. Males reported moderately higher levels of interest/confidence in mathematics compared to females, whereas females reported moderately higher levels of value toward mathematics. Confidence emerged as the dominant predictor of student achievement in mathematics compared to interest and value when controlling for covariates. The results reveal important associations that may inform future research and practice, particularly the need to support students from lower SES backgrounds to develop positive affect toward mathematics.

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Publication Details

Journal
Investigations in Mathematics Learning
Published
2026-11-02
DOI
https://doi.org/10.1080/19477503.2026.2751333
Primary Topic
Education, Achievement, and Giftedness
Type
article
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article

Relationships between 8 th -grade students’ background characteristics, affect, and achievement in mathematics in the U.S.: A TIMSS 2023 analysis

Tye G. Campbell, Erin Rich, Sehrish Jabeen, Melissa Barker
Investigations in Mathematics Learning
Education, Achievement, and Giftedness
article

Relationships between 8 th -grade students’ background characteristics, affect, and achievement in mathematics in the U.S.: A TIMSS 2023 analysis

Tye G. Campbell, Erin Rich, Sehrish Jabeen, Melissa Barker
article en

Abstract

Although there is substantial research on students’ affective experiences in mathematics, there remains a need for analyses that leverage new, large-scale datasets to explore relationships among key affective, achievement, and background variables, particularly modeling affective variables as outcomes. This study leveraged the Trends in International Mathematics and Science Study (TIMSS) 2023 8th-grade database (n = 8,074) to explore relationships among background characteristics, mathematics-related affect variables, and student achievement within the United States. Hierarchical linear modeling was employed to account for the nested structure of the data, i.e. students within classrooms and classrooms within schools. Findings indicated that socioeconomic status was a significant predictor of interest in mathematics, value toward mathematics, and confidence in mathematics, although these associations leveled off and/or declined at higher levels of SES. Males reported moderately higher levels of interest/confidence in mathematics compared to females, whereas females reported moderately higher levels of value toward mathematics. Confidence emerged as the dominant predictor of student achievement in mathematics compared to interest and value when controlling for covariates. The results reveal important associations that may inform future research and practice, particularly the need to support students from lower SES backgrounds to develop positive affect toward mathematics.

Investigations in Mathematics Learning
Utah State University (US), Indiana University (US)
Quality education, Reduced inequalities
Openalex Percentile: Top 10%
Education, Achievement, and Giftedness
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