Aptitude as a Predictor of Senior High School Academic Potential: A Hierarchical Regression Approach

Abstract

Aim/Purpose: This study examined the relative contributions of emotional quotient, interest inventory, study habits, aptitude, and multiple intelligences in predicting the Senior High School (SHS) academic potential of Grade 10 students. Furthermore, it aimed to identify which of these domains offer the most reliable indicators of Senior High School Potential, thereby informing both school-based assessment practices and broader educational policies.

Introduction/Background: The transition from junior to senior high school in the Philippines is a pivotal phase in the K–12 system but continues to present challenges for learners. Many students enter with gaps in reading, writing, and mathematics, making it difficult to cope with the more specialized senior high school curriculum. Adjustment issues are further compounded by limited career guidance, leading some students to choose academic tracks based on external pressures rather than genuine aptitude or interest, often resulting in disengagement and underperformance. Thus, strengthening guidance programs and implementing early diagnostic assessments are critical for smoother transitions. Previous studies have suggested that readiness is multidimensional, shaped not only by cognitive aptitude and study habits but also by emotional intelligence, personality, and goal-setting behaviors. This study incorporated multiple intelligences to capture diverse learner strengths and aimed to identify the most reliable predictors of academic potential, providing evidence-based insights for curriculum, assessment, and policy.

Methodology: This quantitative study investigated the predictors of senior high school academic potential among Grade 10 students using hierarchical linear regression analysis to test theories, show control over variables, provide statistical and practical significance, and report R² changes and F-change tests, thereby making results more convincing and rigorous. From a population of 451 Grade 10 students, 104 male and 104 female students were selected using stratified random sampling. Five models were evaluated to determine which predictors such as Emotional Quotient (EQ), interest inventory, study habits, and aptitude measures might have a significant effect on the dependent variable.

It utilized standardized tests administered by a Philippine assessment corporation to evaluate the academic potential of students. The instruments included an aptitude test measuring verbal, quantitative, abstract, and spatial reasoning; an Emotional Quotient (EQ) assessment evaluating grit, growth mindset, self-management, self-awareness, self-efficacy, and social awareness; an Interest Inventory; and a Study Habits Inventory. Results were summarized in a Scaled Ability Score, which also served as the Senior High School Potential Score.  All instruments demonstrated documented validity and reliability in the Philippine context, with a Cronbach’s alpha of .88, and ethical clearance was obtained from relevant school authorities.

Findings: The regression analysis revealed varying levels of explanatory power across models. Model 0, with gender as the sole control, explained only 1.6% of variance. Models 1–3, which added EQ, interests, and study habits, showed limited improvement. Only Model 4, which introduced aptitude measures—verbal, abstract, quantitative, and spatial reasoning—substantially enhanced predictive power, accounting for 99.7% of the variance in academic potential (R² = .997, p < .001). Importantly, only aptitude scores made statistically significant contributions, while EQ, interests, and study habits did not. The unusually high R² suggested possible overfitting, though acceptable Variance Inflation Factor values and residual patterns mitigate this concern. Model stability was further supported through Adjusted R², Root Mean Squared Error, and F Change statistics.

These findings highlighted the dominant role of cognitive aptitude in predicting academic readiness, positioning aptitude assessments as stronger tools for educational decision-making than socio-emotional or interest-based indicators. However, this raises equity concerns, as students from disadvantaged backgrounds may have fewer cognitively enriching opportunities, limiting their aptitude development and exacerbating achievement gaps. While aptitude emerged as the most robust predictor, socio-emotional and behavioral competencies remain vital for resilience, motivation, and long-term success. Thus, the implications pointed toward a balanced but strategically weighted approach: prioritizing aptitude in curriculum design and assessment frameworks, while integrating complementary interventions to strengthen affective and behavioral skills. This combined strategy can better support holistic learner development while addressing both cognitive foundations and broader equity challenges.

Contribution/Impact on Society: These results will benefit teachers, counselors, policymakers, and curriculum developers in the design of evidence-based interventions. For teachers and counselors, aptitude data guides students into suitable academic tracks, identifies those needing remedial or enrichment support, and complements socio-emotional profiles for personalized guidance. Policymakers and curriculum developers can use the findings to integrate aptitude diagnostics into placement policies and curriculum frameworks, ensuring that instruction is grounded in cognitive foundations while addressing equity gaps. The evidence also supports investments in early diagnostics, remedial programs, and socio-emotional learning. Overall, these results enable stakeholders to craft targeted strategies that enhance readiness, equity, and holistic learner development.

Recommendations: Schools may consider integrating more opportunities to develop cognitive aptitude, particularly in logical reasoning and quantitative skills, during junior high school. Aptitude assessments should continue to be used as part of Senior High School track placement processes but must also be interpreted alongside other holistic indicators. Policymakers might refine readiness criteria by prioritizing evidence-based cognitive metrics in transition programs.

Research Limitation: Findings may not generalize to public schools or other regions, as the study focused on students from a single private school in Northern Mindanao. There is a potential for overfitting due to the large number of predictors relative to the sample size. 

Future Research: Future researchers are encouraged to incorporate longitudinal tracking to explore how predictors influence SHS performance and persistence over time, and to test the model across diverse populations to examine cultural and contextual factors.