Modern Technologies Application And Students’ Academic Performance In Tourism Studies In Tertiary Institutions In Cross River State, Nigeria
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Abstract
The study examined modern technologies application and student’s academic performance in tourism studies in tertiary institutions in Cross River State, Nigeria. The independent variables (Modern technology applications) examined were cloud and edge computing and artificial intelligence while the dependent variable was students’ academic performance. To achieve the purpose of the study, two hypotheses were formulated respectively to guide the study. Review related literature was based on the sub-variables of the study. The research design adopted for this study was correlational research design. Three hundred and eighty-one tourism studies students from three universities were selected using the purposive sampling technique. Two instruments the questionnaire and Students’ Academic Performance Test in Tourism Studies were used for data collection. The face validity was established by using one expert in Environmental Education and two expert in measurement and evaluation in the Faculty of Educational Foundations Studies, University of Calabar. The reliability of the instruments were done using Cronbach Alpha reliability and Kuder-Richardson 21 and the instruments yield a reliable co-efficient estimate ranging from .72 to .91. Simple linear regression was used as statistical tool for data analysis. Each of the hypothesis was tested at .05 level of significance. The findings revealed that cloud and edge computing and artificial intelligence (AI) have relationship with academic performance of tourism students in the universities. Based on the findings of the study, it was recommended amongst others that educational institutions should prioritize the development of ICT infrastructure and resources to support the adoption and implementation of technology applications in tourism studies.
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References
Achar, S. (2021). An Overview of Environmental Scalability and Security in Hybrid Cloud Infrastructure Designs. Asia Pacific Journal of Energy and Environment, 8(2), 39-46
Achar, S. (2021). Leveraging cloud technologies to enhance student academic performance. Sage Science Review of Education Technology (SSRET), 6(4), 39-52
Alfailakawi, A. (2021). The reality of using cloud computing in university education from the point of view of faculty members in Kuwait. International Journal of Business, Humanities and Technology, 11(1), 8-25
Aniella, W. & Gabriel, A. (2025). The impact of Artificial Intelligence (AI) on student’s academic Development. Educational Science, 14(%), 20-30
Dheeba, Veysel, B., Aishathh, R. & Aishath S. (2024). The effects of artificial intelligence literacy on students’ perceptions of academic performance in the Maldives. Beyder, 19(2), 163-174
Hairunnisa, M., Nurain, A., Nor, A., Nabilla, S., & Najwa, A. (2024). The effects of artificial intelligence on students learning. Information Management and Business Review, 16(3), 856-867
Haliru, M. & Abdullahi, A. (2025). Assessing the Impact of AI-driven Personalized Learning Platforms on Chemistry Students’ Academic Performance in Federal University of Education, Nigeria.
Muzaffa, K., Hussaini, T., Ali, H., Ibrahim, M., & Daniya, D. (2020). Understanding and predicting academic performance through Cloud computing adoption. MPRA Paper 104638, University Library of Munich, Germany
Obarisiagbon, E. I. (2018). Impact of Modern Technologies Gadgets on Edo Woman’s Activities in Benin City, Nigeria: A Sociological Analysis. South-South Journal of Humanities and International Studies, 1(2), 147-164
Riedman, A. (2024). Integration of a social robot and gamification in adults learning and effects on motivation, engagement and performance. AI and Society, 39(1)
Surmelioglu, Y. & Seteroghi, S. (2019). An examination of digital footprints awareness and digital experiences of higher education students. World Journal of Educational Technology Current Issues, 11(1), 48-64
Thakkar, D. (2020). Towards an AI-powered future that works for vocational workers. Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems
Wakil, K., Rahman, R., Hasan, D., & Mahmood, P. (2019). Phenomenon-based learning for teaching ICT subject through other subjects in primary schools. Journal of Computer and Educational Research, 7(13), 205-212