International Journal For Multidisciplinary Research

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Determinants of Extended Reality Adoption in Universities within Kampala, Uganda: A Mixed Methods Study of Internal Factors and Institutional Support

Author(s) Mr. Thilak Kumar Devaraj, Dr. Vaibhav Bhushan Tyagi, Dr. Kapil Dev Tyagi
Country India
Abstract The adoption of Extended Reality in higher education has been studied extensively in well-resourced settings, but far less is known about how immersive technology is taken up in universities that operate under infrastructural and financial constraints. This study examined the internal institutional factors that influence Extended Reality adoption in universities within Kampala, Uganda, and tested whether institutional support strengthens or weakens those relationships. A sequential explanatory mixed methods design was used. Quantitative data were collected from 389 respondents drawn from four Kampala universities and analyzed using IBM SPSS Statistics, and qualitative data from lecturers, students and policymakers were analyzed thematically. Multiple linear regression showed that four internal factors, namely technological readiness, human capacity, contextual adaptability and economic viability, jointly explained 49.5 percent of the variance in adoption, with technological readiness the strongest predictor. A moderated regression showed that institutional support significantly strengthened only the relationship between technological readiness and adoption, raising the explained variance to 55.2 percent. The qualitative findings explained these patterns, with device shortages, unreliable internet and power interruptions cited as the most frequent barriers. It is concluded that adoption in resource-constrained universities is best understood as a staged process in which infrastructure is the primary condition and institutional support is most valuable where infrastructure investment is concerned.
Keywords Extended Reality, Technology Adoption, Higher Education, Institutional Support, Moderated Regression, Mixed Methods, Uganda
Field Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In Volume 8, Issue 4, July-August 2026
Published On 2026-07-09
DOI https://doi.org/10.36948/ijfmr.2026.v08i04.83286
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CrossRef DOI prefix of IJFMR is 10.36948/ijfmr

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