SEN, GABRIEL IWUA and Covenant University, Theses (2021) PERCEPTION OF ARCHITECTURE STUDENTS’ LEARNING ENVIRONMENT AND APPROACHES ON ACADEMIC PERFORMANCE OF ARCHITECTURE STUDENTS IN UNIVERSITIES IN SOUTHSOUTH NIGERIA. ["eprint_fieldopt_thesis_type_phd" not defined] thesis, Covenant University.
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Abstract
Architectural education has been accused of falling standard as evident in the failure of architecture graduates in their professional examinations besides other deficiencies. This, from previous studies is traceable to poor academic performance which could be from several factors like students’ learning environment and their learning approaches. The study investigated effects of architecture students’ learning environment and their learning approaches on their academic performance. The objectives were: To examine the demographic characteristics of architecture students; to investigate how architecture students perceive their learning environment; to examine the predominance and disparity in learning approaches of students; to examine the academic performance of architecture students and lastly; to examine the effects of the architecture students’ demographic characteristics, their perceptions of learning environment and, their learning approaches on, their academic performance. Census sampling technique was used. The sample was undergraduate architecture students in years two, three, four and second year architecture post graduate students from four universities in Southsouth Nigeria namely: Rivers State University, Port Harcourt (RSU); Ambrose Ali University, Ekpoma (AAU); University of Uyo, Uyo (UNIUYO) and Cross River State University of Technology, Calabar(CRUTECH). Thematic analysis, Descriptive analysis, t-test, one way ANOVA and categorical regression were used for data analysis. Self-report questionnaires and Interview guides were used. Two Factor Study Process (R-SPQ-2F) questionnaires were used to measure students learning approaches. Results revealed factors of students learning environment as; Quality Teaching, Students Collaborative Learning, Academic Organization, Shared Control and Assessment. Furthermore, students’ predominantly used deep learning approaches (M =32.71, SD = 6.99) over surface learning approaches (M =27.95, SD = 6.58). The difference of means between students’ deep learning approaches of RSU and CRUTECH was statistically significant (3.06, 95% CI (1.36, 4.77), p < 0.0005) and that of AAU and CRUTECH was statistically significant (3.47, 95%, CI (1.51, 5.42), p < 0.0005) similarly, that of UNIUYO and CRUTECH was statistically significant (3.37, 95%, CI (1.71, 5.04), p < 0.0005). Furthermore, that of surface learning approaches of CRUTECH and AAU (2.35, 95%, CI (0.54, 4.17), p = 0.005) was statistically significant. Categorical regression revealed that, demographic characteristics accounted for 6.6% (R2 = 0.066, p< 0.0005) of the variance in academic performance while students’ demographic characteristics, their learning environment and their learning approaches collectively accounted for 12.9% (R2 = 0.129, p< 0.0005) of academic performance. Qualitative teaching (β = -0.467, p< 0.0005) and surface learning approaches negatively and uniquely contributed to a proportion of variance in academic performance (β = -0.289, p< 0.0005). Students collaborative learning (β = 0.176, p<0.0005) and deep learning approaches (β = 0.321, p< 0.0005) uniquely and positively contributed to the variance in academic performance. Recommendation is that architecture educators adopt and increase instructional methods for social learning and deep learning approaches like; field trips, group assignments and problembased learning particularly for theory-based courses. The study recommends further research using lager samples including private owned universities for comparison of results.
Item Type: | Thesis (["eprint_fieldopt_thesis_type_phd" not defined]) |
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Uncontrolled Keywords: | Architecture education; Learning environment; Learning approaches; Academic performance, Nigeria |
Subjects: | N Fine Arts > NA Architecture |
Divisions: | Faculty of Engineering, Science and Mathematics > School of Engineering Sciences |
Depositing User: | Mrs Hannah Akinwumi |
Date Deposited: | 28 Oct 2021 12:50 |
Last Modified: | 28 Oct 2021 12:50 |
URI: | http://eprints.covenantuniversity.edu.ng/id/eprint/15416 |
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