ArticleFrontiers in psychology2020
Students' Motivation and Affection Profiles and Their Relation to Mathematics Achievement, Persistence, and Behaviors.
Article in Frontiers in psychology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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Who cites it
7 citing papers in PubMed, 39 citations in OpenAlex.
- Relative Sense of Belonging and the Academic Achievement of Chinese Adolescents.Journal of youth and adolescence · 2026Article
- Profiles of growth mindset and grit among rural Chinese students and their associations with math anxiety, motivation, and self-efficacy.Scientific reports · 2025Article
- Factors Influencing College Students' Generative Artificial Intelligence Usage Behavior in Mathematics Learning: A Case from China.Behavioral sciences (Basel, Switzerland) · 2025Article
- Applying Machine Learning and SHAP Method to Identify Key Influences on Middle-School Students' Mathematics Literacy Performance.Journal of Intelligence · 2024Article
- Attitudes toward mathematics/statistics, anxiety, self-efficacy and academic performance: an artificial neural network.Frontiers in psychology · 2023Article
- Impact of Self-Concept, Self-Imagination, and Self-Efficacy on English Language Learning Outcomes Among Blended Learning Students During COVID-19.Frontiers in psychology · 2022Article
- A Study on the Relationship Between Consumer Motivations and Subjective Well-Being: A Latent Profile Analysis.Frontiers in psychology · 2022Article
Corrections and comments
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Authors and funding
2 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveWe aimed to explore profiles of subgroups of United States students based on their motivational and affective characteristics and investigate the differences in math-related behaviors, persistence, and math achievement across profiles.
methodWe used 1,464 United States students (male 743 51%, female 721 49%, age 15.82 ± 0.28) from PISA 2012 United States data in our study. First, we employed latent profile analysis and secondary clustering to identify subgroups of students based on motivational (math self-concept, interest in math, perceived control, and instrumental motivation) and affective factors (math anxiety). Next, we used regression to compare differences in math behavior, persistence, and achievement among all identified subgroups.
resultsWe found five distinct groups of students with different patterns of motivation and affection. The subgroup of students with the lowest math anxiety and the highest motivation levels showed the highest math achievement and levels of persistence. The groups with high math interest, math self-concept, and instrumental motivation showed the most frequent math-related behaviors.
conclusionsOur findings reveal the complexity of the students' motivational and affective profiles. Our findings are significant for teachers and educators to understand the diversity of students and provide theoretical and practical support for individualized and differentiated instruction.
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