Thinking Styles, Triarchic Intelligence, and Mathematics Performance

Abstract Students differ in how they use their abilities and approach learning tasks, and these differences may help explain variation in mathematics performance. This study examined the relationships among thinking styles, triarchic intelligence, and mathematics performance among students enrolled in a university mathematics course. Using a correlational-predictive design, data were obtained from 92 randomly selected students from the College of Engineering and Technology of a state university in the Philippines. Thinking styles were measured using a Thinking Styles Questionnaire, triarchic intelligence was assessed through a revised Triarchic Intelligence Inventory, and mathematics performance was evaluated using a researcher-developed test covering achievement and problem-solving skills. Data were analyzed using descriptive statistics, Pearson correlation, and multiple linear regression. Results showed that several thinking styles were significantly associated with triarchic intelligence dimensions. Profile-specific regression analyses further revealed that selected thinking styles significantly predicted achievement and problem-solving performance among students with particular dominant intelligence profiles. The findings suggest that students’ stylistic preferences and ability patterns may provide useful bases for designing more responsive mathematics instruction and learner support in higher education.