Abstract:

Studies on students learning approaches in higher education in the past few years have generated a lot of interest. This is, on deep learning and surface learning approaches. It has also been established that students learning approaches are key to critical thinking and creative processes required in higher education. Knowledge of the architecture students' predominant learning approaches will, therefore, equip institutions to optimize architectural learning experiences. The first objective of the study was, to examine the learning approaches that are predominantly adopted by architecture students of Ambrose Ali University Ekpoma, a state public university, Southsouth Nigeria. Secondly, to examine whether these learning approaches vary by gender, age, and levels of study. A Revised Two-Factor Study Process Questionnaire (R-SPQ-2F) was administered in a cross-sectional survey on a sample size of 159 students comprising undergraduate students in years two, three, four and postgraduate students in year two. The sample had 126 (79.2%) male and 33 (20.8%) female students. Results revealed that architecture students predominantly use deep learning approaches (M=33.80, SD=8.09) as compared to surface approaches (M=26.48, SD=7.43). An independent sample T-test revealed that deep learning approaches had no statistically significant variation by gender (m=-0.38, 95% CL (-3.52, 2.78), t(157)=-0.24, p=0.81). Similarly, surface approach had no significant variation by gender (m=-0.96, 95% CL (-3.75, 1.83), t(157)=-0.68, p=0.59). A one-factor ANOVA test revealed homogeneity of variances of age-groups and scores were 15-18 years age-group (M=32.00, SD=6.20), 19-22 years age-group (M=33.75, SD=8.14), 23-28 years age-group (M=34.34, SD=8.05), 27-30 years age-group (M=32.00, SD=12.29) and above 30 years age-group (M=36.50, SD=6.36). There was however no statistical significant variation among age group (F(89.41,10334.74)=0.33, p=0.855). Also for surface learning approach, age group had homogeneity of variances and scores were 15-18 years age group (M=27.73, SD=7.78), 19-22 years age group (M=27.42, SD=7.47), 23-28 years age group (M=25.91, SD=6.43), 27-30 years age group (M=22.71, SD=7.67) and above 30 years age group (M=22.00, SD=12.73). There was no statistical significant variation among age group (F(244.44, 7966.41.74)=1.18, p=0.321). A one-factor ANOVA test revealed for deep learning approaches, homogeneity of variances among years of study and scores were, year 2 (M=34.64, SD=7.89), year 3 (M=35.57, SD=7.3), year 4 (M=33.48, SD=8.66) and M.Sc. 2 (M=31.07, SD=7.92). There was no statistically significant variation among years of study (F (314.61, 10109.54)=1.608, p=0.190). Surface learning approaches also revealed homogeneity of variances among years of study and scores were, year 2 (M=26.31, SD=7.95), year 3 (25.95, SD=7.38), year 4 (M=27.00, SD=6.79) and M.Sc. 2 (27.22, SD=6.34). There was no statistically significant variation among years of study (F(244.44,7966.41)=1.181, p=0.321). The study gave an insight to the learning approaches of architecture students from a university in Nigeria, a culture different from that prevalent in literature. The study revealed that architecture students from Nigerian cultural settings like other parts of the world adopt deeper learning approaches irrespective of gender, age and years of study. This is encouraging but there is a need for promotion of yet deeper learning approaches among the architecture students.

Keywords:

Surface learning approaches, deep learning approaches, and architectural learning experiences