Faculty of Computing ,Library and Information Science (FCLIS).

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Browsing Faculty of Computing ,Library and Information Science (FCLIS). by Subject "Competence-Based Medical Education"

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    Assessing Medical Students’ Learning Style Preferences at Kabale University Medical School, Uganda.
    (Kabale University, 2024) Muhaise, Hussein; Businge, Phelix Mbabazi; Ssemaluulu, Paul; Kyomugisha, Patricia
    This article is based on an empirical study conducted to assess and establish the preferred learning styles of medical students in the Kabale University Medical School. The study was prompted by a paradigm shift in teaching-learning strategies from the conventional knowledge-based medical curriculum to competency-based medical education (CMBE). In line with the learners’ diversity and inclusion, CBME liberalizes the learning environment by providing a variety of learning methods. Hence, this study aimed to ascertain the preferences of medical students’ learning styles concerning competency-based learning approaches. Procedurally, the study employed online survey methods, and the respondents included 160 medical (MBChB) students, all from Kabale University School of Medicine. The data collected were captured on SPSS version 26 and subjected to t-test analysis. Besides, Visual, Aural, ReadWrite, and Kinaesthetic (VARK) learning inventory was used to determine the student’s learning preferences, while a t-test was used to establish the relationships between the demographic profiles and the learning styles. Notably, the Aural learning style produced the highest mean score of 7.21 ± 3.61, followed by Kinaesthetic (6.43 ± 3.22), ReadWrite (6.12 ± 2.23) and Visual (4.04 ± 2.42). Relatively, t-test results showed significant (p < 0.05) differences in learning styles between preclinical and clinical students. However, the t-test results for gender factors for all the learning dimensions were insignificant (p > 0.05). Pre-clinical students prefer visual and read-write learning styles, while clinical students prefer kinaesthetic and visual learning styles. Based on the findings, this study believes that identifying the learners’ preferred learning styles will help educators choose the most effective teaching methods.