Work place: The Institute of Finance Management, Department of Computer Science, Dar es Salaam, Tanzania
E-mail: herman.mandari@ifm.ac.tz
Website:
Research Interests: E-learning, Computer Science & Information Technology
Biography
Herman E. Mandari is a senior lecturer from the Department of Computer Science at the Institute of Finance Management (IFM) in Tanzania. He holds a Bachelor of Science in Computer Science (BSc. Hons) from the University of Dar es Salaam (Tanzania, 2006); MSc in Web Technology from the University of Southampton (England, 2008); Doctor of Philosophy (PhD) in Information Systems from UTAR University (Malaysia, 2018). His primary research and consulting interests are based in Web Technologies, which include Computer Programming (Web, Mobile, Java and Visual Basic), Hypertext, Accessibility, Usability, Web Science, e-learning, e-government, and m-government, adoption, usage and acceptance of technologies, Hypermedia, Semantic Web, Web Services and Web 2. Furthermore, he has published several papers in the areas listed above. He is actively involved in several projects, including designing and developing various information systems, particularly systems used in higher learning institutions.
By Herman E. Mandari Daniel N. Koloseni
DOI: https://doi.org/10.5815/ijeme.2024.02.01, Pub. Date: 8 Apr. 2024
Web 2.0 has been widely adopted to share learning resources among higher learning institutions (HLIs) learners. However, its persistence utilisation has been less researched in Tanzania. Addressing this gap, the study examines the intention to continue using Web 2.0 to share learning resources in higher learning institutions in Tanzania. The paper used the Expectation Confirmation Model for IS (ECM-IS) and Social Cognitive Theory (SCT) integrated with a knowledge-sharing attitude to develop a research framework for this study. The snowball sampling technique was employed to collect 210 valid responses from users of Web 2.0 in Tanzania's higher learning institutions. Structural Equation Modelling (SEM) was adopted for data analysis using Smart PLS. The results show that community identification, satisfaction, trust, collaboration norms, self-efficacy, confirmation, knowledge sharing, and perceived usefulness significantly affect the intention to continue using Web 2.0. However, contrary to IS literature, the study found that self-efficacy does not moderate the relationship between predictors and continuance usage intention. The study offers valuable implications and future directions in light of these findings.
[...] Read more.Subscribe to receive issue release notifications and newsletters from MECS Press journals