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Abstract
Background: Educational disparities significantly impact student achievement, particularly in underserved regions like the Rio Grande Valley (RGV). This study aims to identify the grade level where interventions are most necessary to enhance academic motivation and career orientation.
Methods: We conducted a cross-sectional analysis of 1,384 students across 55 schools in 17 districts within the RGV. The study included economically disadvantaged populations (83.7%) with a predominantly Hispanic demographic (95.1%). Students’ motivation, measured using a 5-point Likert scale, was assessed using six domains utilizing (e.g., college readiness, school attendance, academic improvement, homework completion, career exploration and preparation) aggregated into a unified z-score through factor analysis with varimax rotation (KMO: 0.83). Multilevel Tobit regression models accounted for hierarchical data structures, with students nested within schools and districts. Variance was assessed using intraclass correlation coefficients (ICC), and kernel density plots visualized motivation score distributions.
Results: Kernel density plots of the aggregated motivation scores revealed a right-censored distribution at higher motivation levels. This justified the use of Tobit models for robust analysis. Factor analysis confirmed that the six motivation domains were strongly correlated which supported their aggregation into a single factor for further investigation. The analysis showed that with a Kaiser-Meyer-Olkin (KMO) measure of 0.83, indicating excellent sampling adequacy. The aggregated z-score had a median of 0.17 (IQR:-0.61, 0.78) with skewness (-0.85) and kurtosis (3.36) suggesting a concentration of higher motivation scores. Tobit regression models revealed a declining trend in motivation as students advanced through grade levels. By 6th grade, motivation scores dropped significantly compared to lower grades with a coefficient of -1.41 (95% Cl: -2.68, -0.13). The decline became more pronounced in grades 7 and 8 where coefficients were -1.69 (95% CI: -2.98, -0.40) and -1.54 (95% CI: -2.83, -0.25) respectively.
Conclusions: Middle school marks a pivotal stage for addressing educational disparities with motivation scores declining sharply during this period. Targeted interventions should focus on maintaining engagement and supporting students at this critical time. These findings emphasize the role of school-level factors in shaping motivation and providing actionable insights for policy and reform in underserved regions like the RGV. Further research should delve into the implementation of interventions and their effectiveness in improving student motivation.
Recommended Citation
Shaju, Ronald A.; Gutierrez, Yolanda V.; Sepulveda, Alyssa L.; Shaju, Alivia M.; Moon, Sophia L.; Cruz, Melissa M.; and Alvarenga, Juan Carlos, "Middle School as a Nexus for Educational Reform" (2025). Research Symposium. 138.
https://scholarworks.utrgv.edu/somrs/2025/posters/138
Included in
Middle School as a Nexus for Educational Reform
Background: Educational disparities significantly impact student achievement, particularly in underserved regions like the Rio Grande Valley (RGV). This study aims to identify the grade level where interventions are most necessary to enhance academic motivation and career orientation.
Methods: We conducted a cross-sectional analysis of 1,384 students across 55 schools in 17 districts within the RGV. The study included economically disadvantaged populations (83.7%) with a predominantly Hispanic demographic (95.1%). Students’ motivation, measured using a 5-point Likert scale, was assessed using six domains utilizing (e.g., college readiness, school attendance, academic improvement, homework completion, career exploration and preparation) aggregated into a unified z-score through factor analysis with varimax rotation (KMO: 0.83). Multilevel Tobit regression models accounted for hierarchical data structures, with students nested within schools and districts. Variance was assessed using intraclass correlation coefficients (ICC), and kernel density plots visualized motivation score distributions.
Results: Kernel density plots of the aggregated motivation scores revealed a right-censored distribution at higher motivation levels. This justified the use of Tobit models for robust analysis. Factor analysis confirmed that the six motivation domains were strongly correlated which supported their aggregation into a single factor for further investigation. The analysis showed that with a Kaiser-Meyer-Olkin (KMO) measure of 0.83, indicating excellent sampling adequacy. The aggregated z-score had a median of 0.17 (IQR:-0.61, 0.78) with skewness (-0.85) and kurtosis (3.36) suggesting a concentration of higher motivation scores. Tobit regression models revealed a declining trend in motivation as students advanced through grade levels. By 6th grade, motivation scores dropped significantly compared to lower grades with a coefficient of -1.41 (95% Cl: -2.68, -0.13). The decline became more pronounced in grades 7 and 8 where coefficients were -1.69 (95% CI: -2.98, -0.40) and -1.54 (95% CI: -2.83, -0.25) respectively.
Conclusions: Middle school marks a pivotal stage for addressing educational disparities with motivation scores declining sharply during this period. Targeted interventions should focus on maintaining engagement and supporting students at this critical time. These findings emphasize the role of school-level factors in shaping motivation and providing actionable insights for policy and reform in underserved regions like the RGV. Further research should delve into the implementation of interventions and their effectiveness in improving student motivation.
