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Determinants of effective hands-on STEM education in higher education institutions in Mogadishu, Somalia

Bibliographic Data

ID22166195
AuthorsAbdirahman Ibrahim Abdi (0009-0004-2935-7510, SIMAD University, corresponding author), Mohamed Ali Osman (0000-0002-3320-8786, SIMAD University), Abdikarim Osman Mahdi (SIMAD University), Abukar Mukhtar Omar (0000-0003-3845-8976, Makerere University), Constance Asiimwe (SIMAD University)
Year2025
Volume10
Publication date2025-06-10
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueFrontiers in Education (JOURNAL)
Journal identifiersISSN: 2504-284X • E-ISSN: 2504-284X
PublisherFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/feduc.2025.1565223
OpenAlexW4411191655
LanguageEN
References cited36

The study investigates the influence of various factors on effective hands-on STEM education in higher education institutions, focusing on faculty expertise, training, pedagogical approaches, curriculum design, and resources. Using partial least squares structural equation modeling (PLS-SEM) with a significance threshold of P < 0.05, 10 hypotheses were tested. The data were gathered from 323 academic staff members in Mogadishu through an online survey employing a stratified random sampling technique. Strata were defined based on faculty specialization (STEM vs. non-STEM) and gender to ensure diversity, and the sample size was justified by power analysis Bootstrapping with 10,000 subsamples was used to assess the statistical significance of the paths. The results show strong support for the majority of the hypotheses. Faculty expertise significantly influences effective hands-on STEM education (H1), with a path coefficient (β) of 0.177, t -value of 2.301, and a 95% confidence interval (CI) between 0.026 and 0.330. Additionally, STEM pedagogical approaches (H2) and curriculum design (H3) significantly impact effective hands-on STEM learning, with path coefficients (β) of 0.165 and 0.121, respectively. The strongest relationship was found between STEM resources and facilities (H4) and effective hands-on education, with a path coefficient (β) of 0.367, t -value of 4.374, and a 95% CI ranging from 0.193 to 0.522. The study further highlights indirect effects, such as the mediation of pedagogical approaches (H8) and curriculum design (H9) on the relationship between faculty expertise and effective hands-on STEM education. The findings suggest that enhancing faculty expertise, pedagogical strategies, curriculum design, and resources will significantly contribute to improved hands-on STEM education outcomes. These insights can guide educators and policymakers in creating more engaging and effective STEM learning environments

Business · Economic growth · Economics · Engineering management · Mathematics education · Computer Science · Engineering · Higher Education Learning Practices · Mathematics Education and Programs · Mobile Learning in Education · Psychology

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