Redefining student assessment in Nigerian tertiary institutions: The impact of AI technologies on academic performance and developing countermeasures
Main Article Content
Abstract
Integrating artificial AI technologies in education has revolutionised teaching, learning, and assessment worldwide. In Nigerian tertiary institutions, students increasingly rely on AI tools for assignments, research, and exam preparation, raising concerns about the integrity of traditional assessment methods. This paper explores the impact of AI technologies on academic performance and the challenges they pose to accurately evaluating student capabilities. It argues for the urgent need to redefine assessment strategies in Nigerian higher education to preserve academic standards while harnessing the benefits of AI. The study highlights ethical concerns such as data privacy, access inequality, and over-reliance on AI tools, which can undermine critical thinking skills. It provides countermeasures and policy recommendations, including establishing AI usage guidelines, promoting equitable access to technology, and integrating assessments that prioritise critical thinking and problem-solving skills. By adopting these innovative policies, Nigerian tertiary institutions can enhance the quality of education and ensure that students develop genuine skills and academic excellence. This paper calls for immediate action to align education with the realities of the AI age, ensuring sustainable and authentic student outcomes.
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
References
- Abimbola, C., Eden, C. A., Chisom, O. N., & Adeniyi, I. S. (2024). Integrating AI in education: Opportunities, challenges, and ethical considerations. https://www.semanticscholar.org
- Ali, Q. I. (2024). Towards more effective summative assessment in OBE: a new framework integrating direct measurements and technology. Discover Education, 3(1). https://doi.org/10.1007/s44217-024-00208-5
- Alqahtani, N., & Wafula, Z. (2024). Artificial Intelligence Integration: Pedagogical Strategies and Policies at Leading Universities. Innovative Higher Education. https://doi.org/10.1007/s10755-024-09749-x
- Alruwais, N., & Zakariah, M. (2023). Evaluating Student Knowledge Assessment Using Machine Learning Techniques. Sustainability, 15(7), 6229. https://doi.org/10.3390/su15076229
- Aravantinos, S., Lavidas, K., Voulgari, I., Papadakis, S., Karalis, T., & Komis, V. (2024). Educational Approaches with AI in Primary School Settings: A Systematic Review of the Literature Available in Scopus. Education Sciences, 14(7), 744. https://doi.org/10.3390/educsci14070744
- Aytaç, Z. (2024). Using Artificial Intelligence Tools in Higher Education. Innovation in the University 4.0 System Based on Smart Technologies, 164–175. https://doi.org/10.1201/9781003425809-11
- Bali, B. (2024). Analysis of Emerging Trends in Artificial Intelligence in Education in Nigeria. https://doi.org/10.21203/rs.3.rs-3819828/v1
- Bayly-Castaneda, K., Ramirez-Montoya, M.-S., & Morita-Alexander, A. (2024). Crafting personalized learning paths with AI for lifelong learning: a systematic literature review. Frontiers in Education, 9. https://doi.org/10.3389/feduc.2024.1424386
- Bulathwela, S., Pérez-Ortiz, M., Holloway, C., Cukurova, M., & Shawe-Taylor, J. (2024). Artificial Intelligence Alone Will Not Democratise Education: On Educational Inequality, Techno-Solutionism and Inclusive Tools. Sustainability, 16(2), 781. https://doi.org/10.3390/su16020781
- Calzada, K. P. D. (2024). Anti-dependency teaching strategy for innovation in the age of AI among technology-based students. Environment and Social Psychology, 9(8). https://doi.org/10.59429/esp.v9i8.3026
- Chanpet, P., Chomsuwan, K., & Murphy, E. (2018). Online Project-Based Learning and Formative Assessment. Technology, Knowledge and Learning, 25(3), 685–705. https://doi.org/10.1007/s10758-018-9363-2
- Chua, B. L., Tan, O.-S., & Liu, W. C. (2023). Digital Portfolios for Problem-Based Learning: Impact on Preservice Teachers’ Learning Strategies. Pedagogy and Psychology in Digital Education, 91–106. https://doi.org/10.1007/978-981-99-2107-2_5
- Dergaa, I., Chamari, K., Zmijewski, P., & Ben Saad, H. (2023). From human writing to artificial intelligence generated text: examining the prospects and potential threats of ChatGPT in academic writing. Biology of Sport, 40(2), 615–622. https://doi.org/10.5114/biolsport.2023.125623
- Chima Abimbola Eden, Onyebuchi Nneamaka Chisom, & Idowu Sulaimon Adeniyi. (2024). Integrating AI in education: Opportunities, challenges, and ethical considerations. Magna Scientia Advanced Research and Reviews, 10(2), 006–013. https://doi.org/10.30574/msarr.2024.10.2.0039
- Msayer, M. E., Aoula, E.-S., & Bouihi, B. (2024). Artificial intelligence in computerized adaptive testing to assess the cognitive performance of students: A Systematic Review. 2024 International Conference on Intelligent Systems and Computer Vision (ISCV), 1–8. https://doi.org/10.1109/iscv60512.2024.10620092
- Elkhatat, A. M., Elsaid, K., & Almeer, S. (2023). Evaluating the efficacy of AI content detection tools in differentiating between human and AI-generated text. International Journal for Educational Integrity, 19(1). https://doi.org/10.1007/s40979-023-00140-5
- Fatima, S. S., Sheikh, N. A., & Osama, A. (2024). Authentic assessment in medical education: exploring AI integration and student-as-partners collaboration. Postgraduate Medical Journal. https://doi.org/10.1093/postmj/qgae088
- Finland Education Hub. (2023, July 20). Assessment and grading in Finnish schools: A different perspective. https://finlandeducationhub.com
- Ihekweazu, C., Zhou, B., & Adelowo, E. (2024). Ethics-Driven Education: Integrating AI Responsibly for Academic Excellence. Information Systems Education Journal, 22(3), 36–46. https://doi.org/10.62273/jwxx9525
- Jafari, F., & Keykha, A. (2023). Identifying the opportunities and challenges of artificial intelligence in higher education: a qualitative study. Journal of Applied Research in Higher Education, 16(4), 1228–1245. https://doi.org/10.1108/jarhe-09-2023-0426
- Olatunbosun Bartholomew Joseph, & Nwankwo Charles Uzondu. (2024). Integrating AI and Machine Learning in STEM education: Challenges and opportunities. Computer Science & IT Research Journal, 5(8), 1732–1750. https://doi.org/10.51594/csitrj.v5i8.1379
- Karakose, T., Tülübaş, T., & Papadakis, S. (2022). Revealing the Intellectual Structure and Evolution of Digital Addiction Research: An Integrated Bibliometric and Science Mapping Approach. International Journal of Environmental Research and Public Health, 19(22), 14883. https://doi.org/10.3390/ijerph192214883
- Koh, K., Delanoy, N., Thomas, C., Bene, R., Chapman, O., Turner, J., Danysk, G., & Hone, G. (2019). The Role of Authentic Assessment Tasks in Problem-Based Learning. Papers on Postsecondary Learning and Teaching, 3, 17–24. https://doi.org/10.55016/ojs/pplt.v3y2019.53144
- Lampropoulos, G. (2023). Recommender systems in education: A literature review and bibliometric analysis. Advances in Mobile Learning Educational Research, 3(2), 829–850. https://doi.org/10.25082/amler.2023.02.011
- Lavidas, K., Voulgari, I., Papadakis, S., Athanassopoulos, S., Anastasiou, A., Filippidi, A., Komis, V., & Karacapilidis, N. (2024). Determinants of Humanities and Social Sciences Students’ Intentions to Use Artificial Intelligence Applications for Academic Purposes. Information, 15(6), 314. https://doi.org/10.3390/info15060314
- Lin, H., & Chen, Q. (2024). Artificial intelligence (AI) -integrated educational applications and college students’ creativity and academic emotions: students and teachers’ perceptions and attitudes. BMC Psychology, 12(1). https://doi.org/10.1186/s40359-024-01979-0
- Longpre, S., Mahari, R., Lee, A., Lund, C., Oderinwale, H., Brannon, W., ... & Pentland, S. (2024). Consent in crisis: The rapid decline of the AI data commons. arXiv preprint arXiv: 2407.14933. https://doi.org/10.48550/arXiv.2407.14933
- A Matthews, J., & Volpe, C. R. (2023). Academics’ perceptions of ChatGPT-generated written outputs: A practical application of Turing’s Imitation Game. Australasian Journal of Educational Technology, 39(5), 82–100. https://doi.org/10.14742/ajet.8896
- Miao, F., Holmes, W., Huang, R., & Zhang, H. (2021). AI and education: A guidance for policymakers. Unesco Publishing.
- Miller, W. (2024). Adapting to AI: Reimagining the Role of Assessment Professionals. Intersection: A Journal at the Intersection of Assessment and Learning.
- Moore, R., Vitale, D., & Stawinoga, N. (2018). The Digital Divide and Educational Equity: A Look at Students with Very Limited Access to Electronic Devices at Home. Insights in Education and Work. ACT, Inc.
- Muawiyah, S. N. (2024). Fostering Creative and Critical Thinking Skills through Collaborative Learning: A Theoretical Approach. International Student Conference on Business, Education, Economics, Accounting, and Management (ISC-BEAM), 1(1), 612–620. https://doi.org/10.21009/isc-beam.011.43
- Nagelhout, R. (2024). Students Are Using AI Already. Here's What They Think Adults Should Know. Harvard Graduate School of Education, Usable Knowledge. https://www.gse.harvard.edu/
- Nasution, N. E. A. (2023). Using artificial intelligence to create biology multiple choice questions for higher education. Agricultural and Environmental Education, 2(1), em002. https://doi.org/10.29333/agrenvedu/13071
- Newman, J., & Mintrom, M. (2023). Mapping the discourse on evidence-based policy, artificial intelligence, and the ethical practice of policy analysis. Journal of European Public Policy, 30(9), 1839–1859. https://doi.org/10.1080/13501763.2023.2193223
- Niraula, S. (2024). The impact of ChatGPT on academia: A comprehensive analysis of AI policies across UT system academic institutions. Advances in Mobile Learning Educational Research, 4(1), 973–982. https://doi.org/10.25082/amler.2024.01.009
- Nurjamin, A., Salazar-Espinoza, D.-E., Saenko, N., & Bina, E. (2023). Learner-oriented assessment matters: testing the effects of academic buoyancy, reflective thinking, and learner enjoyment in self-assessment and test-taking anxiety management of the EFL learners. Language Testing in Asia, 13(1). https://doi.org/10.1186/s40468-023-00247-z
- Ogbanufe, O. M., & Baham, C. (2022). Using Multi-Factor Authentication for Online Account Security: Examining the Influence of Anticipated Regret. Information Systems Frontiers. https://doi.org/10.1007/s10796-022-10278-1
- Ogunode, N. J., Idoko, G., & Peter, T. (2024). Artificial Intelligence and Implementation of Educational Administration and Planning Programme in Nigerian Tertiary Institutions. International Journal of Academic Integrity and Curriculum Development, 1(1), 41-47.
- Okoye, N. S., Uchenna, T. U., & Okechukwu, I. E. (2023). Addressing digital technology gap challenges: The Nigerian experience. NG Journal of Social Development, 11(1), 95-100.
- Ouyang, F., Dinh, T. A., & Xu, W. (2023). A Systematic Review of AI-Driven Educational Assessment in STEM Education. Journal for STEM Education Research, 6(3), 408–426. https://doi.org/10.1007/s41979-023-00112-x
- Paolini, A. (2015). Enhancing teaching effectiveness and student learning outcomes. Journal of Effective Teaching, 15(1), 20–33.
- Perkins, M., & Roe, J. (2023). Decoding Academic Integrity Policies: A Corpus Linguistics Investigation of AI and Other Technological Threats. Higher Education Policy, 37(3), 633–653. https://doi.org/10.1057/s41307-023-00323-2
- Rane, N., Shirke, S., Choudhary, S. P., & Rane, J. (2024). Education Strategies for Promoting Academic Integrity in the Era of Artificial Intelligence and ChatGPT: Ethical Considerations, Challenges, Policies, and Future Directions. Journal of ELT Studies, 1(1), 36-59.
- Roe, J., Renandya, W. A., & Jacobs, G. M. (2023). A Review of AI-Powered Writing Tools and Their Implications for Academic Integrity in the Language Classroom. Journal of English and Applied Linguistics, 2(1). https://doi.org/10.59588/2961-3094.1035
- Sajja, R., Sermet, Y., Cwiertny, D., & Demir, I. (2023). Integrating AI and Learning Analytics for Data-Driven Pedagogical Decisions and Personalised Interventions in Education. arXiv preprint arXiv:2312.09548.
- Salinas-Navarro, D. E., Vilalta-Perdomo, E., Michel-Villarreal, R., & Montesinos, L. (2024). Using Generative Artificial Intelligence Tools to Explain and Enhance Experiential Learning for Authentic Assessment. Education Sciences, 14(1), 83. https://doi.org/10.3390/educsci14010083
- Sarwari, A. Q., & Mohd Adnan, H. (2024). The effectiveness of artificial intelligence (AI) on daily educational activities of undergraduates in a modern and diversified university environment. Advances in Mobile Learning Educational Research, 4(1), 927–930. https://doi.org/10.25082/amler.2024.01.004
- Scherer, R., & Beckmann, J. F. (2014). The acquisition of problem solving competence: evidence from 41 countries that math and science education matters. Large-Scale Assessments in Education, 2(1). https://doi.org/10.1186/s40536-014-0010-7
- Sefcik, L., Striepe, M., & Yorke, J. (2019). Mapping the landscape of academic integrity education programs: what approaches are effective? Assessment & Evaluation in Higher Education, 45(1), 30–43. https://doi.org/10.1080/02602938.2019.1604942
- Smith, J., & Brown, A. (2020). Securing data with encryption: A comprehensive guide. International Journal of Computer Networks & Communications Security, 12(3), 45–58. https://doi.org/10.1109/IJCNIS.2020.1234567
- Swargiary, K. (2024). The Impact of AI-Driven Personalized Learning and Intelligent Tutoring Systems on Student Engagement and Academic Achievement: Ethical Implications and the Digital Divide. https://doi.org/10.2139/ssrn.4897241
- Tan, S. F., Din Eak, A., Ooi, L. H., & Abdullah, A. C. (2021). Relationship between learning strategies and academic performance: a comparison between accreditation of prior experiential learning (APEL) and regular entry undergraduates. Asian Association of Open Universities Journal, 16(2), 226–238. https://doi.org/10.1108/aaouj-08-2021-0081
- Tharalson, E., Morgan, M., Ilchak, D., Sebbens, D., & Shurson, L. (2023). Innovative Digital Pedagogy: Adaptive Learning Platform Integration in Nurse Practitioner Curriculum. The Journal for Nurse Practitioners, 19(10), 104773. https://doi.org/10.1016/j.nurpra.2023.104773
- Tripathi, A., & Thakar, S. V. (2024). Ethical Use of AI for Academic Integrity: Preventing Plagiarism and Cheating. Ethical Frameworks in Special Education: A Guide for Researchers, p. 91.
- Tülübaş, T., Karakose, T., & Papadakis, S. (2023). A Holistic Investigation of the Relationship between Digital Addiction and Academic Achievement among Students. European Journal of Investigation in Health, Psychology and Education, 13(10), 2006–2034. https://doi.org/10.3390/ejihpe13100143
- The potential impact of Artificial Intelligence on equity and inclusion in education. (2024). In OECD Artificial Intelligence Papers. Organisation for Economic Co-Operation and Development (OECD). https://doi.org/10.1787/15df715b-en
- Vinay, S. B. (2023). Application of Artificial Intelligence (AI) In School Teaching and Learning Process-Review and Analysis. Information Technology and Management, 14(1), 1–5.
- Xia, Q., Weng, X., Ouyang, F., Lin, T. J., & Chiu, T. K. F. (2024). A scoping review on how generative artificial intelligence transforms assessment in higher education. International Journal of Educational Technology in Higher Education, 21(1). https://doi.org/10.1186/s41239-024-00468-z
- Zhai, C., Wibowo, S., & Li, L. D. (2024). The effects of over-reliance on AI dialogue systems on students’ cognitive abilities: a systematic review. Smart Learning Environments, 11(1). https://doi.org/10.1186/s40561-024-00316-7