Cognitive Engagement, Learning Strategies, Adjustment to College and Academic Motivation: A Structural Equation Model on Academic Success Among College Students
Abstract
This study examined the relationships among cognitive engagement, learning strategies, adjustment to college, academic motivation, and academic success to determine the best-fit structural equation model among Bachelor of Elementary Education students in Region XIII (Caraga), Philippines. Anchored in Self-Regulated Learning Theory and Academic Adjustment Theory, the study employed a quantitative, non-experimental descriptive-correlational design involving 470 second-, third-, and fourth-year students from three state universities, selected through proportional stratified random sampling. Data were collected using five adapted, validated, and reliability-tested questionnaires and analyzed through descriptive statistics, Pearson correlation, and structural equation modeling. Results revealed very high levels of cognitive engagement (M = 4.27), learning strategies (M = 4.32), college adjustment (M = 4.34), academic motivation (M = 4.32), and academic success (M = 4.31). All four predictors demonstrated significant positive correlations with academic success, with academic motivation exhibiting the strongest relationship (r = .519). The final structural model demonstrated excellent fit (CMIN/DF = .845, CFI = 1.000, RMSEA = .000) and explained 32.5% of the variance in academic success. Academic motivation (β = .270, p = .020) and learning strategies (β = .262, p = .017) emerged as significant direct predictors, whereas college adjustment and cognitive engagement showed nonsignificant direct effects. The findings emphasize the importance of strengthening academic motivation and effective learning strategies through learner-centered instruction and institutional support programs. The study supports Sustainable Development Goal 4 (Quality Education) by providing evidence to inform educational practices and student success initiatives. Its sustainability contribution lies in supporting evidence-based academic planning, student retention, and continuous improvement in higher education.