Correlation of Student Engagement in Bluebonnet Learning and Academic Performance in Middle School Mathematics
Authors
Manor Independent School District, United States (America)
Article Information
DOI: 10.47772/IJRISS.2026.10100304
Subject Category: Mathematics
Volume/Issue: 10/1 | Page No: 3875-3881
Publication Timeline
Submitted: 2026-01-17
Accepted: 2026-01-22
Published: 2026-02-04
Abstract
Student engagement is a key factor influencing academic performance, particularly in middle school mathematics, where motivation and active participation are often challenging. This study examined the relationship between eighth-grade students’ engagement with Bluebonnet Learning mathematics materials and their academic performance. Using a correlational design, 56 eighth-grade students participated through universal sampling during the first semester of the 2025–2026 academic year. Engagement was measured using the validated Student Engagement with Bluebonnet Learning (SEBL) instrument (α = 0.87), and mathematics performance was assessed via a teacher-made midterm examination aligned with the Texas Essential Knowledge and Skills (TEKS; α = 0.85). Descriptive analyses indicated moderate to high engagement across behavioral, cognitive, and emotional domains, with cognitive engagement scoring highest (M = 3.27, SD = 0.48). Pearson correlations showed positive relationships between all engagement domains and mathematics performance, with cognitive engagement exhibiting the strongest correlation (r = .56, p < .01). Multiple regression analysis revealed that cognitive engagement was the only statistically significant unique predictor of mathematics performance (β = .41, t = 3.28, p = .002), accounting for the largest proportion of variance (R² = .36, adjusted R² = .32). These findings suggest that deeper cognitive involvement with structured, standards-aligned materials supports higher academic achievement, highlighting the importance of instructional strategies that promote behavioral, cognitive, and emotional engagement in middle school mathematics classrooms.
Keywords
student engagement, Bluebonnet Learning, mathematics performance
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References
1. Alrajeh, T. S., & Shindel, B. W. (2020). Student engagement and math teacher support. Journal on Mathematics Education, 11(2), 167–180. https://eric.ed.gov/?id=EJ1252000 [Google Scholar] [Crossref]
2. American Psychological Association. (2020). Publication manual of the American Psychological Association (7th ed.). https://apastyle.apa.org/products/publication-manual-7th-edition [Google Scholar] [Crossref]
3. Appleton, J. J., Christenson, S. L., Kim, D., & Reschly, A. L. (2006). Measuring cognitive and psychological engagement: Validation of the Student Engagement Instrument. Journal of School Psychology, 44(5), 427–445. https://doi.org/10.1016/j.jsp.2006.04.002 [Google Scholar] [Crossref]
4. Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Routledge. https://doi.org/10.4324/9780203771587 [Google Scholar] [Crossref]
5. Creswell, J. W., & Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). SAGE Publications. https://edge.sagepub.com/creswellrd5e [Google Scholar] [Crossref]
6. Fredricks, J. A., Blumenfeld, P. C., & Paris, A. H. (2004). School engagement: Potential of the concept, state of the evidence. Review of Educational Research, 74(1), 59–109. https://doi.org/10.3102/00346543074001059 [Google Scholar] [Crossref]
7. Huang, L., & Wang, D. (2023). Teacher support, academic self-efficacy, student engagement, and academic achievement in emergency online learning. Behavioral Sciences, 13(9), Article 704. https://www.mdpi.com/2076-328X/13/9/704 [Google Scholar] [Crossref]
8. Maamin, M., Mistima, S., & Iksan, Z. H. (2021). The influence of student engagement on mathematical achievement among secondary school students. Mathematics, 10(1), 41. https://doi.org/10.3390/math10010041 [Google Scholar] [Crossref]
9. Sen, E. Ö. (2022). Middle school students’ engagement in mathematics and learning approaches: Structural equation modelling. Pedagogical Research, 7(2), Article em0124. https://doi.org/10.29333/pr/11908 [Google Scholar] [Crossref]
10. Texas Education Agency. (2025). Bluebonnet Learning instructional materials. https://tea.texas.gov/academics/instructional-materials/bluebonnet-learning [Google Scholar] [Crossref]
11. Zhang, L. J., & Zhou, Y. (2023). The correlation of students’ mathematics learning engagement on their academic performance in junior high school. Journal on Education, 2(1), 309–321. https://doi.org/10.31004/joe.v2i1.309 [Google Scholar] [Crossref]
12. Yang, Y., Li, G., Su, Z., & Yuan, Y. (2021). Teacher's emotional support and math performance: The chain mediating effect of academic self-efficacy and math behavioral engagement. Frontiers in psychology, 3611.https://doi.org/10.3389/fpsyg.2021.651608 [Google Scholar] [Crossref]
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