Diffusion Innovation, Adoption, and Acceptance of Recommender Systems in Higher Education

Recommender systems are widely used to help in reducing information overload through suggesting relevance items to users proactively or reactively. The usefulness of RS has made them to be used in different sectors such as e-commerce, retail environment and even in education sector. RS is penetrating different sectors with different speed and its adoption and acceptance vary in different sectors. Therefore, this study investigated the diffusion, adoption, and acceptance of RS in higher education. A quantitative method was used in this study. The data was collected using questionnaires and a model was proposed. Two hundred and sixty-one usable questionnaires received from participants. Reliability and validity of the study were satisfied. The results have shown that diffusion, adoption, and acceptance of RSs in higher education is not by chance. It also indicated that diffusion has a positive influence on the adoption with beta = 0.625, Sig. = 0.000 and adoption has positive influence on the acceptance with beta = 0.606, sig. = 0.000 of RSs in higher education sector. The benefits being accrued by those using RSs are having a positive effect on the diffusion (beta = 0.695, Sig. 0.000) and adoption (beta = 0.579, Sig. = 0.000) of RSs, this is enabling growth of RSs in higher education sector. RSs are still in their early diffusion stage in higher education as an education tool. There is need to intentionally promote RSs benefits in higher education to enable a speed diffusion of the technology.