The Influence of Architecture Students’ Learning Approaches on their Academic Performance in Two Nigeria Universities

Abstract

The paper was a pilot study that examined learning approaches of architecture students; variability of approaches by university type and gender and; influence of architecture students’ learning approaches on their academic performance. The sample was 349 architecture students from two universities. Descriptive and statistical analyses were used. Results revealed predominant use of deep learning approaches by students. Furthermore, learning approaches neither significantly differed by university type nor gender. Regression analysis revealed that demographic factors accounted for 2.9% of variation in academic performance (F (2,346) = 6.2, p = 0.002, R2 = 0.029, f2 = 0.029) and when learning approaches were also entered the model accounted for 4.4% of variation in academic performance (F (14,334) =2.2, p =0.009, R2 = 0.044, f2=0.044). Deep learning approaches significantly and positively influenced variation in academic performance while surface learning approaches significantly and negatively influenced academic performance. This implies that architectural educators should use instructional methods that encourage deep approaches. Future research needs to use larger and more heterogeneous samples for confirmation of results.