RELATIONSHIP BETWEEN LEARNING APPROACHES AND ACADEMIC PERFORMANCE IN MATRIX AND VECTOR COURSES AMONG CIVIL ENGINEERING STUDENTS
Padang, Indonesia
DOI:
https://doi.org/10.36085/math-umb.edu.v13i3.10311Abstract
This study examines how different learning approaches are associated with students’ academic performance in the context of engineering mathematics, based on a case study of the Matrix and Vector course. A quantitative correlational research design was used in the study. Data were collected from 101 civil engineering students at Institut Teknologi Padang. Students’ learning approaches were measured using a structured questionnaire based on Biggs’ theory. Students’ academic performance was obtained from the course records in the form of midterm and final exam results. Data were analyzed using descriptive statistics, Pearson correlation, and multiple regression. The results showed that all learning approaches (surface, deep, and achieving) have a significant positive correlation with midterm exam results. However, in the final exam results, only the deep and achieving approaches have a significant positive correlation with the final exam results. Despite the positive correlation found in the study, the multiple regression analysis showed that the learning approaches have no significant predictive relationship with the students’ academic performance. Additionally, the results showed a low explanatory power of the model (R² = 0.100 for the midterm and R² = 0.054 for the final exam results). These findings suggest that learning approaches are associated with academic performance but have a limited contribution when considered simultaneously. These results highlight that other factors, such as prior knowledge, motivation, and instructional design, may play a more dominant role in shaping students’ academic outcomes in engineering mathematics.
Keywords: learning approaches, academic performance, engineering mathematics, matrix and vector, multiple regression
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