Addressing e-Learning Digital Anxiety through Effective User Support: The case of Mount Kenya University, Kenya

The need to embrace e-learning programs in institutions of higher learning was accelerated by the Covid-19 pandemic, which led to the closure of learning institutions and the need to use a variety of different digital platforms and technologies to ensure continuity of learning. Consequently, in many universities, there is increasing pressure to adapt to the teaching of online or blended programs, leading to heightened digital anxiety in both students and faculty. While there is general consensus on the inevitability of e-learning, the need to implement tangible usersupport systemsto address the resultant digital anxiety in both staff and faculty, and ensure quality in e-learning programs, has not been emphasized. The Technology Acceptance Model (TAM) proposed by Davis (1989), as cited by Lin & Yu (2023), underscores user acceptance and support as a critical component for success in the acceptance to use any technology. Thus, students and faculty must be adequately supported to embrace the paradigm shift to the digital classroom; without which there will be continuous resistance to e-learning programs in institutions of higher learning. This resistance will result in ineffective e-learning programs with the release of graduates who are not adequately trained and skilled for the labor market. This paper will present the practical implementation of user support in key areas of e-learning aimed at addressing digital anxiety for both staff and students in Mount Kenya University, Kenya. Specific reference will be made to user support in online content design and development; user support in online teaching and learning; and user support in online assessment and examinations. The information on the implemented user support systems is presented based on an analysis of the actual support mechanisms adopted by the university, from an administrative point of view; and empirical data from students and faculty on their perception of the effectiveness of the implemented user support mechanisms. The empirical data from students and faculty was collected using a concurrent mixed method design; based on quantitative and qualitative responses from an end-user survey, key informant interviews and focus group discussions with the sampled students and faculty at the university. The discussion of findings and recommendations presented should aid other higher learning institutions in conceptualizing the implementation of user support systems for effective elearning; with the ultimate aim of addressing the digital anxiety in staff and students that may impact on the quality of e-learning programs. The data presented can also form a baseline for more extensive studies on user support mechanisms adopted by other higher learning institutions; for comparative analysis and adoption of best practices in e-learning.