The High Five Model as a predictor of academic performance over conventional psychological predictors in university students

Abstract

IntroductionThe High Five Model (HFM) categorizes five positive human characteristics-erudition, peace, joviality, honesty, and tenacity-utilizing an inductive psycholexic approach. This study examines the predictive power of HFM on academic performance among university students, hypothesizing that it surpasses conventional predictors such as academic motivation, exam anxiety, and academic procrastination.MethodsA non-experimental cross-sectional correlational design was implemented using a non-probabilistic convenience sample of 1,007 Ecuadorian university students (403 females). Self-reported measures of the “high factors,” academic motivation, exam anxiety, and academic procrastination were collected. Linear regression analysis was utilized to evaluate the predictive capacity of the HFM on academic performance.ResultsThe analysis revealed that the high factors of the HFM significantly predict academic performance, demonstrating a stronger predictive ability than traditional psychological predictors.DiscussionThe findings suggest that incorporating the HFM into academic settings could enhance understanding and prediction of student performance. This could potentially inform targeted interventions that leverage these high factors, thereby fostering better academic outcomes. Further research could explore the integration of the HFM with other educational strategies and its applicability across diverse educational contexts.