Artificial Intelligence and Academic Achievement in Higher Education: A Conceptual Review
Keywords:
Artificial Intelligence; academic achievement; higher education; personalised learning and Technology Acceptance Model
Abstract
Artificial Intelligence (AI) is transforming higher education by reshaping how students access information, engage with learning materials, undertake academic tasks, and achieve educational outcomes. This conceptual review examines the relationship between AI and academic achievement in higher education, with particular attention to the opportunities, challenges, and conditions that shape the educational value of AI technologies. The study adopts a secondary research method, based on existing scholarly literature and organising the reviewed studies thematically around the concepts, applications, educational benefits, academic achievement, human learning interaction, ethical concerns, and technology acceptance associated with AI. The paper argues that AI has considerable potential to enhance academic achievement by supporting personalised learning, providing immediate feedback, facilitating access to educational resources, assisting research and academic writing, and improving students’ engagement with complex learning tasks. However, the paper also identifies important challenges that may limit these benefits. Excessive dependence on AI may weaken students’ critical thinking, independent reasoning, creativity, and meaningful interaction with educators, while concerns relating to academic integrity, data privacy, fairness, transparency, and responsible use remain significant. The Technology Acceptance Model provides a useful conceptual lens for understanding the adoption of AI through perceived usefulness, perceived ease of use, behavioural intention, and actual technology use. The study concludes that AI can contribute meaningfully to academic achievement when deployed as a supportive educational resource rather than a substitute for human teaching, critical thinking, and student–educator interaction.
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References
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Aondover, P. O., Aondover, E. M., & Babele, A. M. (2022). Two nations, same technology, different outcomes: Analysis of technology application in Africa and America. Journal of Educational Research and Review, 1(1), 001-008.
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Cakir, R. (2019). The effect of artificial intelligence-supported learning environments on student achievement in computer science education. Computers in Human Behavior, 95, 221–231.
Chang, C. Y., Kuo, Y. C., & Hwang, G. J. (2022). Artificial intelligence-supported nursing education and learning effectiveness. Nurse Education Today, 108, 105174.
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Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial intelligence in education: Promises and implications for teaching and learning. Center for Curriculum Redesign.
Huong, N. T., Hiep, N. H., & Anh, P. T. (2020). Artificial intelligence and machine learning applications in education. International Journal of Emerging Technologies in Learning, 15(18), 4–17.
Ikus-Silan, M., Aksu, G., & Demir, Y. (2023). Artificial intelligence applications in biology education: Opportunities and challenges. Journal of Biological Education, 57(4), 568–582.
Kumar, V., & Thakur, G. S. M. (2012). Advanced applications of neural networks and artificial intelligence: A review. International Journal of Information Technology and Computer Science, 4(6), 57–68.
Lee, H., & Hwang, G. J. (2022). Artificial intelligence-supported learning environments and student achievement: A meta-analysis. Computers & Education: Artificial Intelligence, 3, 100080.
Lin, C. H., & Chang, C. Y. (2020). Artificial intelligence-assisted language learning: A systematic review. Educational Technology & Society, 23(4), 1–15.
Lu, O. H. T., Huang, A. Y. Q., Huang, J. C. H., Lin, A. J. Q., Ogata, H., & Yang, S. J. H. (2021). Applying learning analytics for improving student learning performance in computer science education. Interactive Learning Environments, 29(7), 1111–1127.
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Obasi, M. C., Msughter, A. E., & Maiwada, A. A. (2025). Artificial Intelligence (Ai), A Deep Learning Or Cheating Tool Among Nigerian University Students In Film And Media Studies. Communication and Media Codes, 273-285
Onyejelem, T. E., Aondover, E. M., Ezeonyejiaku, N. P., & Maiwada, A. A. (2025). Reassessing the dynamics and utilization of learning management systems for sustainable communication education in Nigeria. The Nigerian Journal of Communication, 21, 1-2.
Rahman, M. M., & Chowdhury, A. H. (2024). Students’ perceptions of artificial intelligence and academic performance in higher education. Education and Information Technologies, 29(2), 1157–1175.
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Rossi, F. (2019). Artificial intelligence: A modern perspective on intelligent systems. Cambridge University Press.
Russell, S., & Norvig, P. (2021). Artificial intelligence: A modern approach (4th ed.). Pearson.
Saint, E. J., Aondover, E. M., Ebele, U. C., & Onyejelem, T. E. (2024). Influence of social media on newspaper patronage among lecturers in University of Nigeria, Nsukka. LingLit Journal Scientific Journal for Linguistics and Literature, 5(3), 142-157.
Selwyn, N. (2019). Should robots replace teachers? AI and the future of education. Polity Press.
Tai, M. C. (2020). The impact of artificial intelligence on higher education learning outcomes. International Journal of Educational Technology in Higher Education, 17(1), 1–15.
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Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186–204. https://doi.org/10.1287/mnsc.46.2.186.11926
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540
Vitalis, P. O., Aondover, E. M., Ogunbola, O., Onyejelem, T. E., & Ridwan, M. (2025). Accessing digital divide and implications in Nigeria: The media dimension. Budapest International Research and Critics Institute-Journal (BIRCI-Journal), 8(1), 1-12.
Wellington, N., Onyike, I. E., Njoku, C., Akintaro, M. G., Maduka, N., & Owoeye, T. J. (2026). Economic and Employment Benefits of Using AI for Enhancing Media Production Skills in African Classrooms. In Artificial Intelligence in African Media and Communication (pp. 263-279). Routledge.
Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education. International Journal of Educational Technology in Higher Education, 16(1), Article 39. https://doi.org/10.1186/s41239-019-0171-0
Ademosu, I., Aondover, E. M., Osadolor, B., & Abraham, B. (2025). Divisive politics: analysis of ethnic rhetoric and hate speech in the 2023 Lagos Governorship elections. Frontiers in Political Science, 7, 1663797.
Adiguzel, T., Kaya, M. H., & Cansu, F. K. (2023). Revolutionizing education with AI: Exploring the transformative potential of ChatGPT. Contemporary Educational Technology, 15(3), ep429. https://doi.org/10.30935/cedtech/13152
Ahmed, M. O., & Msughter, A. E. (2022). Assessment of the spread of fake news of Covid-19 amongst social media users in Kano State, Nigeria. Computers in Human Behavior Reports, 6, 100189.
Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-T
Akintayo, A. O., Adewale, O. C., Tsenongo, M., & Akintaro, M. G. (2026). Integration of Artificial Intelligence and Performance of Broadcasting Companies in Nigeria. Britain International of Humanities and Social Sciences (BIoHS) Journal, 8(1), 1-9.
Akintayo, A. O., Ezeoye, C. S., Akintaro, M. G., & Adewale, O. C. (2026). The Use of Sign Language in News Presentations for Hearing Impaired Viewers to Promote Sustainable and Inclusive Media. SIASAT, 11(1), 51-63.
Almelweth, A. A. (2022). The effectiveness of artificial intelligence-based learning applications in improving student learning outcomes. Education and Information Technologies, 27(7), 1–19.
Alneyadi, S., & Wardat, Y. (2023). Artificial intelligence applications in personalized learning environments. Education Sciences, 13(5), 1–18.
Aondover, E. M., & Ademosu, I. (2025). E-learning practices of journalism education in Nigerian higher education institutions: Conceptual context and challenges. In Media and communication systems for sustainability in Nigeria (pp. 451-464). Cham: Springer Nature Switzerland.
Aondover, E. M., Aondover, P. O., & Maiwada, A. A. (2025). Reconfiguration of Media Communication in the Age of AI and Inequality. Feedback International Journal of Communication, 2(3), 194-204.
Aondover, E. M., Igwe, E. C., Akin-Odukoya, O. O., & Ridwan, M. (2024). Influence of Social Media on News Consumption and Credibility in Nigeria. Konfrontasi: Jurnal Kultural, Ekonomi dan Perubahan Sosial, 11(2), 80-92.
Aondover, E. M., Tosin, Y. A. N., Akin-Odukoya, O. O., Onyejelem, T. E., & Ridwan, M. (2025). Exploring the application of social media in governance in Nigeria. SIASAT, 10(1), 30-43.
Aondover, P. O., Aondover, E. M., & Babele, A. M. (2022). Two nations, same technology, different outcomes: Analysis of technology application in Africa and America. Journal of Educational Research and Review, 1(1), 001-008.
Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Prentice Hall.
Cakir, R. (2019). The effect of artificial intelligence-supported learning environments on student achievement in computer science education. Computers in Human Behavior, 95, 221–231.
Chang, C. Y., Kuo, Y. C., & Hwang, G. J. (2022). Artificial intelligence-supported nursing education and learning effectiveness. Nurse Education Today, 108, 105174.
Chen, L., Chen, P., & Lin, Z. (2020). Artificial intelligence in education: A review. IEEE Access, 8, 75264–75278. https://doi.org/10.1109/ACCESS.2020.2988510
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
del Olmo-Muñoz, J., Cózar-Gutiérrez, R., González-Calero, J. A., & Sáez-López, J. M. (2022). Artificial intelligence and mathematics education: A systematic review. Education Sciences, 12(7), 1–20.
Eze, S. C., Chinedu-Eze, V. C., & Bello, A. O. (2018). The utilisation of e-learning facilities in Nigerian universities: A case study. Education and Information Technologies, 23(1), 293–315. https://doi.org/10.1007/s10639-017-9617-9
Facione, P. A. (2020). Critical thinking: What it is and why it counts (2020 update). Insight Assessment.
Fetzer, J. H., & Fetzer, J. H. (1990). Artificial intelligence: Its scope and limits. Kluwer Academic Publishers.
Hermann, M., & Weigert, J. (2024). Artificial intelligence systems and data-driven decision making: Concepts and applications. AI and Society, 39(1), 1–15.
Holmes, W., & Tuomi, I. (2022). State of the art and practice in AI in education. European Journal of Education, 57(4), 542–570.
Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial intelligence in education: Promises and implications for teaching and learning. Center for Curriculum Redesign.
Huong, N. T., Hiep, N. H., & Anh, P. T. (2020). Artificial intelligence and machine learning applications in education. International Journal of Emerging Technologies in Learning, 15(18), 4–17.
Ikus-Silan, M., Aksu, G., & Demir, Y. (2023). Artificial intelligence applications in biology education: Opportunities and challenges. Journal of Biological Education, 57(4), 568–582.
Kumar, V., & Thakur, G. S. M. (2012). Advanced applications of neural networks and artificial intelligence: A review. International Journal of Information Technology and Computer Science, 4(6), 57–68.
Lee, H., & Hwang, G. J. (2022). Artificial intelligence-supported learning environments and student achievement: A meta-analysis. Computers & Education: Artificial Intelligence, 3, 100080.
Lin, C. H., & Chang, C. Y. (2020). Artificial intelligence-assisted language learning: A systematic review. Educational Technology & Society, 23(4), 1–15.
Lu, O. H. T., Huang, A. Y. Q., Huang, J. C. H., Lin, A. J. Q., Ogata, H., & Yang, S. J. H. (2021). Applying learning analytics for improving student learning performance in computer science education. Interactive Learning Environments, 29(7), 1111–1127.
Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence unleashed: An argument for AI in education. Pearson Education.
McCarthy, J., Minsky, M. L., Rochester, N., & Shannon, C. E. (2006). A proposal for the Dartmouth summer research project on artificial intelligence. AI Magazine, 27(4), 12–14. (Original work published 1955)
O’Neil, C. (2016). Weapons of math destruction: How big data increases inequality and threatens democracy. Crown Publishing Group.
Obasi, M. C., Msughter, A. E., & Maiwada, A. A. (2025). Artificial Intelligence (Ai), A Deep Learning Or Cheating Tool Among Nigerian University Students In Film And Media Studies. Communication and Media Codes, 273-285
Onyejelem, T. E., Aondover, E. M., Ezeonyejiaku, N. P., & Maiwada, A. A. (2025). Reassessing the dynamics and utilization of learning management systems for sustainable communication education in Nigeria. The Nigerian Journal of Communication, 21, 1-2.
Rahman, M. M., & Chowdhury, A. H. (2024). Students’ perceptions of artificial intelligence and academic performance in higher education. Education and Information Technologies, 29(2), 1157–1175.
Reagan, P. (2018). Artificial intelligence: Concepts, applications and future directions. Routledge.
Rossi, F. (2019). Artificial intelligence: A modern perspective on intelligent systems. Cambridge University Press.
Russell, S., & Norvig, P. (2021). Artificial intelligence: A modern approach (4th ed.). Pearson.
Saint, E. J., Aondover, E. M., Ebele, U. C., & Onyejelem, T. E. (2024). Influence of social media on newspaper patronage among lecturers in University of Nigeria, Nsukka. LingLit Journal Scientific Journal for Linguistics and Literature, 5(3), 142-157.
Selwyn, N. (2019). Should robots replace teachers? AI and the future of education. Polity Press.
Tai, M. C. (2020). The impact of artificial intelligence on higher education learning outcomes. International Journal of Educational Technology in Higher Education, 17(1), 1–15.
Thomas, M., Reinders, H., & Warschauer, M. (2020). Contemporary computer-assisted language learning. Bloomsbury Academic.
UNESCO. (2021). AI and education: Guidance for policymakers. UNESCO Publishing.
Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186–204. https://doi.org/10.1287/mnsc.46.2.186.11926
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540
Vitalis, P. O., Aondover, E. M., Ogunbola, O., Onyejelem, T. E., & Ridwan, M. (2025). Accessing digital divide and implications in Nigeria: The media dimension. Budapest International Research and Critics Institute-Journal (BIRCI-Journal), 8(1), 1-12.
Wellington, N., Onyike, I. E., Njoku, C., Akintaro, M. G., Maduka, N., & Owoeye, T. J. (2026). Economic and Employment Benefits of Using AI for Enhancing Media Production Skills in African Classrooms. In Artificial Intelligence in African Media and Communication (pp. 263-279). Routledge.
Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education. International Journal of Educational Technology in Higher Education, 16(1), Article 39. https://doi.org/10.1186/s41239-019-0171-0
Published
2026-09-23
How to Cite
Mobolaji Grace Akintaro, Okuchemiya Success, & Joseph Ifeoluwa Joy. (2026). Artificial Intelligence and Academic Achievement in Higher Education: A Conceptual Review. Konfrontasi: Jurnal Kultural, Ekonomi Dan Perubahan Sosial, 13(3), 278-291. Retrieved from https://www.konfrontasi.net/index.php/konfrontasi2/article/view/390
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