A Technology Adoption Framework and a Digital Literacy Model of Cloud Computing Services in Higher Education in Nigeria

Background: One of several cutting-edge innovations that can help higher education institutions increase the effectiveness and efficiency of their processes for delivering learning outcomes, notably in terms of lowering costs and opening access to larger student pools, is cloud computing. Although it has been widely embraced in developed countries, it has a relatively low adoption rate in underdeveloped nations, and there is limited empirical research looking at the factors that affect its adoption in higher education institutions. Objectives: This study proposed a technology adoption framework and digital literacy model of cloud computing services in higher education in Nigeria that aggregate models such as the Diffusion of Innovation (DOI), Unified Theory of Acceptance and use of Technology (UTAUT), Technology Acceptance Model (TAM), Desire Framework (DF) and Technology Readiness (TR) with three aspects:(a) technological, (b) organizational and (c) environmental aspects to identify the variables influencing cloud computing adoption in higher education institutions in Nigeria. Methods: A survey research design was adopted for this study. Data were collected from both primary and secondary sources. A simple systematic random sampling technique was adopted in administering a set of questionnaires to 384staff and students of selected Nigeria Higher Institutions out of which only 260 (67.7%) pieces of the questionnaire were returned in an analysable manner. Secondary data were sourced from published and unpublished sources. Data collected were analysed using both descriptive and inferential statistics regression and correlation test at p > 0.05. Results: The logistic regression indicates that computer efficiency, subjective norms, perceived innovation, perceived usefulness, attitude towards technology and external pressure are the factors that are enhancing the adoption of cloud computing by Nigerian public and private universities. The linear regression and correlation analysis showed that higher institutions in Nigeria have a positive perception of cloud computing as well as high levels of readiness for adoption. In order to test for the potency of the three factors/components of the model, the study confirmed that the External factor (Beta = .369; t = 9.235; p < .05) was the most potent determinant, followed by Technological factor (Beta = .248; t = 7.538; p < .05) and individual factor (Beta = .122; t = 3.701; p < 0.05) is the third determining factors of cloud adoption among students and staff in Nigeria higher institution as This finding leads to the recommendation that higher institutions in Nigeria should intensify efforts in making wider adoptions of cloud computing for all staff and students in educational settings. Conclusion: The proposed CTRAM Model enables us to assess the level of cloud computing acceptance as well as provision of guidance on factors that determine CTRAM adoption among staff and students of Nigerian universities. The Model received expert validation, as the domain experts had agreed that the proposed Model was well applicable as a veritable tool in supporting and delivering successful and thriving digital education. The extent of the Model's generalizability and acceptability were done through the model iterations.