Diffusion innovation, adoption, and acceptance of a recommender systems in higher education
dc.contributor.author | Hlungwane, Ntsako Morgen | |
dc.contributor.co-supervisor | Sehume, Odilia M. M., Dr. | |
dc.contributor.supervisor | Zuva, Tranos, Prof. | |
dc.date.accessioned | 2024-05-02T12:19:37Z | |
dc.date.available | 2024-05-02T12:19:37Z | |
dc.date.issued | 2022-04-21 | |
dc.description | M. Tech. (Department of Information and Communication Technology, Faculty of Applied and Computer Sciences), Vaal University of Technology. | en_US |
dc.description.abstract | Recommender systems (RS) are widely used to help with reducing information overload by suggesting relevant items to users proactively or reactively. The usefulness of RS has made them used in different sectors, such as e-commerce, retail environments, and even the education sector. RS is penetrating different sectors with varying speeds, 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 were received from participants. The requirements for the study's reliability and validity were both met. The results have shown that diffusion, adoption, and acceptance of RSs in higher education do not occur by chance. They also indicated that diffusion has a positive influence on the adoption with β= 0.625, Sig. = 0.000, and adoption has a positive influence on the acceptance with β = 0.606, Sig. = 0.000 of RSs in the higher education sector. The benefits gained by those who use RSs have a positive effect on RS diffusion (= 0.695, Sig. = 0.000) and adoption (= 0.579, Sig. = 0.000), allowing RSs to grow in the higher education sector. RS are still in their early diffusion stage in higher education as an educational tool. There is a need to intentionally promote RS benefits in higher education to enable a faster diffusion of the technology. | en_US |
dc.identifier.uri | https://hdl.handle.net/10352/711 | |
dc.language.iso | en | en_US |
dc.publisher | Vaal University of Technology | en_US |
dc.subject | Rodgers’s theory of innovation | en_US |
dc.subject | Technology acceptance model | en_US |
dc.subject | Recommender systems | en_US |
dc.subject | Higher education | en_US |
dc.subject.lcsh | Dissertations, Academic -- South Africa. | en_US |
dc.subject.lcsh | Educational technology. | en_US |
dc.subject.lcsh | Education, Higher -- Effect of technological innovations on. | en_US |
dc.subject.lcsh | Recommender systems (Information filtering). | en_US |
dc.subject.lcsh | Information filtering systems. | en_US |
dc.title | Diffusion innovation, adoption, and acceptance of a recommender systems in higher education | en_US |
dc.type | Thesis | en_US |
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