Artificial Intelligence Technologies Integration and Global Competitiveness in Higher Education: Evidence from Sub-Saharan Africa
DOI:
https://doi.org/10.33687/ijef.003.04.00156Keywords:
Artificial Intelligence, Integration, Learning Strategies, Global CompetitivenessAbstract
Sustainable learning outcomes are vital for developing strong critical thinking skills, which lead to positive life results and career success, ultimately enhancing global competitiveness. Achieving these outcomes relies on instructional methods that offer meaningful experiences to learners. This study explores the use of Artificial Intelligence (AI) technologies as learning strategies to boost the global competitiveness of higher education institutions and students in Sub-Saharan Africa. The research aimed to evaluate how AI impacts sustainable learning outcomes and to identify challenges that hinder their implementation in higher education, based on evidence from the region. A mixed-method research design was adopted, with stratified and simple random sampling techniques used to determine the sample size. The population of respondents was 3840 with the sample size of 384 that included students and an academic staff. Data collection involved questionnaires named Artificial Intelligence Technologies Integration Questionnaires (AITIQ) and Global Competitiveness in Higher Education (GCIEQ) with Artificial Intelligence Technologies Integration interview guides (AITII) and Global Competitiveness in Higher Education Interview guides (GCHEI). Quantitative responses analyzed using SPSS Version 27 because it is easy accessible for researcher. That generated descriptive statistics and reliability calculated while qualitative data from interview guides were subjected to thematic and narrative analysis. The results show that 355(92.45%) with mean of 4.35 of students agreed that, integrating AI technologies can greatly improve sustainable learning outcomes by increasing administrative efficiency, enabling personalized learning, automating assessments and feedback, and enhancing global competitiveness. However, super majority of students above 75% agreed that,at study area there are challenges such as limited technical expertise and infrastructure, low digital literacy among staff, and concerns that AI can decrease critical thinking among students. The study concludes that the successful integration of AI in higher education, need to be guided by strategic policies, can transform learning practices and improve academic results.It recommends investing in AI infrastructure, offering regular staff training, and continuously evaluating AI tools to ensure fairness and effectiveness.
References
Adeoye, I. A., & Jimoh, M. A. (2022). Digital skills, technology integration, and instructional effectiveness in Nigerian universities in the post-COVID-19 era. Journal of Educational Technology and Online Learning, 5(2), 201-219.
Biggs, J., & Tang, C. (2020). Teaching for quality learning at university (5th ed.). Open University Press.
Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77-101.
Creswell, J. W., & Plano Clark, V. L. (2018). Designing and conducting mixed methods research (3rd ed.). SAGE Publications.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008
Hattie, J., & Timperley, H. (2007). The power of feedback. Review of Educational Research, 77(1), 81-112.
Holmes, W., Persson, J., Chounta, I.-A., Wasson, B., & Dimitrova, V. (2022). Artificial intelligence and education: A critical view through the lens of human rights, democracy and the rule of law. Council of Europe.
Holmes, W., Porayska-Pomsta, K., Holstein, K., Sutherland, E., Baker, T., Santos, O. C., Rodrigo, M. M. T., Cukurova, M., Bittencourt, I. I., & Koedinger, K. R. (2022). Ethics of AI in education: Towards a community-wide framework. International Journal of Artificial Intelligence in Education, 32(3), 504-526.
Krejcie, R. V., & Morgan, D. W. (1970). Determining sample size for research activities. Educational and Psychological Measurement, 30(3), 607-610.
Marginson, S. (2022). Global higher education in the post-COVID era. Globalization, Societies and Education, 20(3), 281-297.
Marginson, S. (2022). What is global higher education? Oxford Review of Education, 48(4), 492–506. https://doi.org/10.1080/03054985.2022.2074654
Mkude, D., & Cooksey, B. (2022). ICT integration and academic performance in Tanzanian universities: Challenges and opportunities. East African Journal of Education Studies, 5(1), 34-51.
Mugo, J., & Muthee, M. (2021). E-learning integration and sustainable learning outcomes in Kenyan public universities. Kenya Journal of Educational Planning, 5(2), 78-94.
Ndukwe, I. G., & Daniel, B. K. (2020). Teaching analytics, value and tools for teacher data literacy: A systematic and tripartite approach. International Journal of Educational Technology in Higher Education, 17(1), 1-31.
Ng'ambi, D., Brown, C., Bozalek, V., Gachago, D., & Wood, D. (2020). Technology enhanced teaching and learning in South African higher education: A rearview of a 20 year journey. British Journal of Educational Technology, 47(5), 843-858.
OECD. (2025). Results from TALIS 2024: The state of teaching. OECD Publishing. https://www.oecd.org/en/publications/results-from-talis-2024_90df6235-en.html
Russell, S. J., & Norvig, P. (2021). Artificial intelligence: A modern approach (4th ed.). Pearson Education.
Siemens, G. (2005). Connectivism: A learning theory for the digital age. International Journal of Instructional Technology and Distance Learning, 2(1), 3-10.
Spaull, N. (2019). Priorities for education reform in South Africa. Input document for the Presidential Economic Advisory Council. University of Stellenbosch.
UNESCO. (2021). Recommendation on the ethics of artificial intelligence. United Nations Educational, Scientific and Cultural Organization.
UNESCO. (2023). Guidance for generative AI in education and research. UNESCO.
UNESCO. (2025). UNESCO survey: Two-thirds of higher education institutions have or are developing guidance on AI use. UNESCO.
Uwamariya, A., & Musengimana, T. (2021). University lecturers' capacity for AI-integrated teaching in Rwanda's digital transformation context. African Journal of Higher Education Studies, 9(2), 88-104.
Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision Sciences, 39(2), 273-315.
World Bank. (2024). Digital transformation drives development in Africa. World Bank.
World Bank. (2026). Individuals using the Internet (% of population): Sub-Saharan Africa. World Bank.
Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education—Where are the educators? International Journal of Educational Technology in Higher Education, 16, Article 39. https://doi.org/10.1186/s41239-019-0171-0
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Copyright (c) 2026 Karol Robert, Felista Tangi, Clara Rupia (Author)
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