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dc.contributor.authorKayizzi, Geofrey
dc.date.accessioned2022-06-08T05:50:18Z
dc.date.available2022-06-08T05:50:18Z
dc.date.issued2019-09-23
dc.identifier.citationKayizzi, G. (2018). Social networks in gross anatomy dissection room and students' performance at Makerere University College of Health Sciences (Unpublished Master's Dissertation). Makerere University, Kampala, Uganda.en_US
dc.identifier.urihttp://hdl.handle.net/10570/10597
dc.descriptionA dissertation submitted to the Directorate of Research and Graduate Training in partial fulfillment of the requirements for the award of the degree of Master of Science in Human Anatomy of Makerere University.en_US
dc.description.abstractIntroduction: Social interactions between students in the gross anatomy dissection room are a major and underexplored part of undergraduate education. Yet understanding how learning relationships form inside the dissection room, as well as the impacts these relationships have on learning outcomes, can inform educators in unique ways and improve student’s performance in cadaveric dissection based- anatomy. This study therefore, set out to determine the nature of undergraduate students’ study networks within the gross anatomy dissection room and to determine the association between these networks and student’s performance in cadaveric dissection-based anatomy examinations at Makerere University College of Health Sciences. Methodology: A cross sectional study design was used on first year undergraduate students of the 2017/18 intake from the different health professional programs offered at university. A sample size of 175 students was selected by stratified random sampling technique from the 20 dissection groups allocated to students at beginning of their first academic year of study. Information about students’ networks within the gross anatomy dissection room was obtained using a roster type of questionnaire adopted from a similar study done in a different setting. The data entry generated edge list matrices for ties between the different respondents. To this set of matrices, we added unique respondent’s attributes to create a ‘network object’. This network object was used with help of the statenet and igraph software packages to identify and describe the nature of student’s networks. The association between performance and the different components of the network was established by regression analysis using the Exponential random graph model (ERGMs), with additional Monte Carlo Markov chain maximum-like hood estimation (MCMCML). Results: the study found out that students tend to form clusters (networks) based on their program of study, dissection group (table), and male gender. Clusters of poor performing students were also identified. By contrast, we found no such clusters (networks) formed on basis of age or nationality. Results also revealed that student’s performance had a strong association (p<0.05) with the networks in the gross anatomy dissection room. Program of study and dissection group were strongly associated with one’s performance. Conclusions: The study networks in the gross anatomy dissection room are based on program of study, male sex & dissection group (table). The networks within the dissection room are strongly associated with performance in cadaveric-dissection based anatomy practical examination.en_US
dc.description.sponsorshipEbenezer Community Health Centreen_US
dc.language.isoenen_US
dc.publisherMakerere Universityen_US
dc.subjectSocial networksen_US
dc.subjectperformanceen_US
dc.subjectstudentsen_US
dc.subjectgross anatomy dissection roomen_US
dc.subjectMakerere University College of Health Sciencesen_US
dc.subjectUgandaen_US
dc.titleSocial networks in gross anatomy dissection room and students' performance at Makerere University College of Health Sciencesen_US
dc.typeThesisen_US


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