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Academic staff's challenges in adopting blended learning: Reality at a developing university

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Abstract

Higher education institutions (HEIs) are striving to provide effective learning experiences to address the needs of a digital generation of learners. Blended learning has emerged as a solution to address these needs and has been adopted by various HEIs. However, not all academic staff members adopt blended learning when it is introduced by their institutions. Although the blended teaching and learning approach offers various advantages to academic staff, negative perceptions held by academic staff may affect its adoption. The purpose of this case study was to investigate the perceptions of and identify challenged facing academic staff that affected the adoption of blended learning in a faculty of education at a developing university in Southern Africa. The study employed the Technology Acceptance Model (TAM) and the Innovation Diffusion Theory (IDT) in a qualitative exploratory research design. The investigation made use of focus group interviews with lecturers in a faculty of education and individual interviews with heads of academic departments, as well as the dean of the faculty. Data gathered pointed to a variety of perceptions hindering academic staff from adopting blended learning. Amongst these were perceptions pertaining to e-learning or blended learning policy, faculty support by management, computer skills of students and lecturers, as well as inadequate access to computers by students. These seemed to be challenges that the Faculty of Education has to deal with and overcome before academic staff can successfully adopt blended learning. It was not the aim of this study to generalise the findings. In fact, the research was unique in that it applied known knowledge to the new context of a small Southern African university, which is a developing community. It is hoped, however, that lessons learned will make a contribution to the field of higher education and that developing universities will benefit from the research.
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... Perceived ease of use is also measured by supporting indicators from motivation (MO), motivation is a form of prediction of intentions or behavior that is expected to influence the perceived ease of use [12] : perception that the system help learning activities (MO1),experience in using similar system (MO2), self efficacy (SE), self-efficacy is a variable that represents the confidence in the ability to perform a task using a computer [12] : being able to use F-Learn well without assistance of other users (SE1),being able to use F-Learn well if ever saw other users use it (SE2). Facilitating conditions (FC), organizational support as well as adequate infrastructure needed to maximize the role of information technology [13] : good internet connection (FC1), sufficient infrastructure to use F-Learn (computer, human resources) (FC2). and perceived enjoyment (PE), perceived ease of use is expected to reflect the tool of pleasure associated with the system [12] : application display is clear and not confusing (PE1),clear and understandable terms (PE2), well-functioning, fast-response and error-free application (PE3), and number and types of application module that sufficiently satisfies user needs (PE4). ...
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