2026-09-18T21:08:17Zhttps://openscholar.dut.ac.za/server/oai/request

oai:openscholar.dut.ac.za:10321/62482025-10-28T12:10:52Zcom_10321_11col_10321_12

Experiences of biomedical sciences students and staff in blended learning during the COVID-19 pandemic lockdown in a University of Technology, Durban, KwaZulu-Natal Ntimbane, Nonkululeko Protasia Orton, Penelope Margaret Blended learning COVID-19 pandemic Blended Learning in universities Blended Learning in higher education Medical sciences Blended learning COVID-19 Pandemic, 2020-2023 Universities and colleges--South Africa--KwaZulu-Natal--Employees--Attitudes College students--South Africa--KwaZulu-Natal--Attitudes Dissertation submitted in partial compliance with the requirements for the Master’s Degree in Medical Laboratory Medicine, Durban University of Technology, Durban, South Africa, 2025. This study explored and described the experiences of biomedical sciences students and staff who used blended teaching and learning during COVID-19 pandemic. To follow social distancing protocol, limited number of students and staff were permitted on campus at a time, while others were online to limit the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 virus). The objective of this study was to determine and recommend the necessary resources and skills needed by biomedical sciences students and staff for blended learning at a historically disadvantaged university of technology and better prepare for future pandemics. The aim is to help the university stakeholders to budget, invest, and direct resources and skills for blended teaching and learning appropriately. Purposeful sampling was used to select 14 participants from biomedical science population of 100 students and 14 staff (eight lecturers, 3 laboratory technicians, two laboratory assistants and one secretary). Purposeful sampling was chosen as it is characterized by the intentional selection of units pertinent to the study issue as it strategically focuses on traits within a population, enabling researchers to gather rich, contextual data. Qualitative descriptive content analysis research method was chosen to make replicable and valid inferences of the phenomenon from texts. Semi structured individual interviews were used to collect data and data was analyzed continuously using descriptive content analysis. Participants were interviewed until data reached data saturation. The results of this study showed that staff and students were unprepared for the emergency transformation. There were disparities in students’ device access and availability, students' digital skills; some had basic knowledge of computers, while others had none. Students and staff had challenges of poor internet connection due to load shedding and poor infrastructure, but students in rural areas had worse network connections than those in urban areas. Students and staff had to learn how to navigate iv the learning management systems (LMSs) on the run, as most of them were unfamiliar with those systems. Laboratory practical experiments took longer as students were divided into small groups to observe social distancing protocol of COVID-19 pandemic, students worked individually rather than in pairs, and load shedding occasionally caused tests to be postponed. Online assessments compromised the quality of education, and some students cheated as staff could not monitor students online due to a lack of electronic proctoring tools. At times, students could not submit assignments and tests on time due to poor network connections or load shedding. Despite the challenges and unpleasant experience that students and staff faced during COVID-19 blended teaching and learning, blended learning achieved the learning objectives. The report makes several recommendations for infrastructure support, including giving out laptops and/or data to students in need, upgrading lecture halls to smart classrooms, offering computer training on learning management systems and continuous support to students and staff, to increase proficiency and preparedness, and lastly designing a blended learning approach suitable for biomedical science M 2025-10-27T10:12:27Z 2025-10-27T10:12:27Z 2024-12-02 Thesis https://hdl.handle.net/10321/6248 https://doi.org/10.51415/10321/6248 en 158 p application/pdf