Teacher's Perspectives on Integrating Ai Technologies for Large Class Sizes in Secondary Education in Nigeria
Ibebuike, Ursula O1, Obi, Patricia N.1, Duru, Ngozi D.2, Urenyere, Rachael U.1
1Department of Curriculum/Instruction,
2Department of Educational Psychology and Guidance and Counselling
Alvan Ikoku Federal University of Education, Owerri, Imo State, Nigeria
Abstract
This study delves into Nigerian secondary school teachers’ perspectives on the integration of Artificial Intelligence (AI) technologies in large class sizes. The areas of the study were Abia and Imo States. The population of the study comprised all the 477 senior secondary school teachers (182 males and 295 females) in Aba North Local Government Area of Abia State and 285 senior secondary school teachers (65 males and 220 females) in Owerri Municipal Council in Imo State, numbering 762. The sample of the study was 142 respondents Through the analysis of five research questions, the research provides insights into teachers’ perceptions, challenges, opportunities, and professional development needs regarding AI integration. Findings reveal a moderate to high significance placed by participants on AI integration in large classes, indicating a general recognition of its potential benefits. However, significant variability exists in teachers’ opinions and experiences, reflecting the complexity of system integration. Teachers’ concerns encompass technical competency, pedagogical ideals, resource access, and institutional support. While some educators embrace AI to enhance teaching and learning, others express skepticism or apprehension regarding its impact on traditional roles and student outcomes. Ethical and sociological implications of AI in education are recognized, necessitating considerations of justice, openness, accountability, and privacy. Addressing ethical concerns is crucial for ensuring equitable access and mitigating disparities in educational outcomes. Moreover, participants emphasize the importance of targeted professional development to equip teachers with the necessary skills and knowledge for AI integration. Collaborative discourse among educators, policymakers, and researchers is advocated to promote evidence-based strategies and policies. In conclusion, the study underscores the need for inclusive and collaborative approaches to AI adoption in Nigerian secondary education, emphasizing the ethical, pedagogical, and infrastructural considerations. Implementing the recommended strategies such as Creating AI training and support programmes for Nigerian secondary school teachers can help overcome challenges and maximize the benefits of AI integration, ultimately enriching the teaching and learning experiences in large class settings.
Keywords: Teacher’s Perspectives, AI Technologies, Large Class Sizes, Secondary Education, Nigeria.
Impact Statements
This research investigates Nigerian secondary school teachers’ perspectives on integrating AI technologies to manage large class sizes. It provides valuable insights into how AI can enhance educational outcomes and address teaching challenges in crowded classrooms. The study reveals that while many teachers recognize the potential of AI to improve personalized learning, they face several barriers, including limited knowledge, inadequate training, and socio-cultural challenges. Teachers expressed concerns about AI’s impact on teacher-student relationships and ethical considerations. Nonetheless, most participants are optimistic about AI’s role in enhancing instructional efficiency and effectiveness. This study highlights the need for targeted professional development and infrastructure improvements to facilitate the successful integration of AI in Nigerian education. By addressing these challenges, AI technologies can be effectively harnessed to support diverse learners and reduce the workload in large class settings. The findings serve as a foundation for policymakers and educators aiming to promote AI-driven innovations in secondary education.
About The Author
Dr. Ursula Obiageli Ibebuike is a senior lecturer in the department of curriculum and instruction Faculty of Eduaction Alvan Ikoku Federal University of Education, Owerri, Imo State, Nigeria. ). She is a seasoned educator and researcher with expertise in Curriculum Studies, She is a member of Curriculum Organization of Nigeria(CON), member of world Council for Curriculum and Instruction(WCCI), and a member of Teachers’ Registration Council of Nigeria(TRCN). With over two decades of teaching experience, she has made significant contributions to education in Nigeria. Her research focuses on curriculum planning and Implementation, educational research and methodology, and teacher education. Dr. Ibebuike holds a PhD in Curriculum Studies from a reputable institution and has published several scholarly articles in national and international journals.
Obi Patricia Nneka (Ph.D) is a senior lecturer of curriculum and instruction in the department of Alvan Ikoku Federal University of Education, Owerri, Imo State, Nigeria. She is a member of Curriculum Organization of Nigeria(CON), member of world Council for Curriculum and Instruction(WCCI), and a member of Teachers’ Registration Council of Nigeria(TRCN). Her professional practice spans all levels of secondary and tertiary education. She is a seasoned lecturer with research interest in teaching and learning, curriculum development studies, planning, implementation, elements, components and materials in curriculum as well as vocational studies. She believes in collaboration and cross-pollination of ideas to improving teaching and learning at all levels of education.
Duru Ngozi Damasius(Ph.D) is a senior lecturer of educational psychology / Guidance and counselling i department of Alvan Ikoku Federal University of Education, Owerri, Imo State, Nigeria. She is a member of Counselling association of Nigeria and a member of Teachers’ Registration Council of Nigeria(TRCN). Her professional practice spans all levels of secondary and tertiary education. She is a seasoned lecturer with research interest in teaching ,learning and counselling students in their area of personal social educational and vocational studies. She believes in collaboration and cross-pollination of ideas to improving teaching and learning at all levels of education.
Urenyere Rachael Ukachi (Ph.D) is a senior lecturer of Curriculum and Instruction in the department of Alvan Ikoku Federal University of Education, Owerri, Imo State, Nigeria. She is a member of Curriculum Organization of Nigeria(CON), member of world Council for Curriculum and Instruction(WCCI), and a member of Teachers’ Registration Council of Nigeria(TRCN). Her professional practice spans all levels of secondary and tertiary education. She is a seasoned lecturer with in teaching and learning, curriculum studies, planning,and implementation. She believes in collaboration of ideas .
References
Adeleke, M. (2021). Teachers’ attitudes towards the integration of artificial intelligence in the classroom: A Nigerian experience. Journal of Information Systems and Technology Management, 18.
Adetunji, A. B., & Lawal, O. M. (2021). Artificial intelligence and ethics in Nigerian educational system: Exploring teachers’ perspectives. In African Regional Conference on Information Systems and Technology (pp. 1–14). Springer.
Agboola, A. A., & Adebisi, O. (2020). Investigating the readiness of secondary school teachers in Nigeria for technology integration. International Journal of Educational Technology in Higher Education, 17(1), 1–20.
Alake, O. R., & Aderinoye, O. (2020). Design of an intelligent tutoring system for learning secondary school mathematics in Nigeria. International Journal of Emerging Technologies in Learning (iJET), 15(23), 4–20.
Anynwoye, O. K. (2023). Implications of large class size one effective teaching and learning in Nigerian tertiary Institutions: Lecturer’s perception. Qeios, ID: 67mzof. https://doi.org/10.32388/67mzof
Arnold, K. E., & Pistilli, M. D. (2012). Course signals at purdue: Using learning analytics to increase student success. In Proceedings of the 2nd International Conference on Learning Analytics and Knowledge (pp. 267–270). https://doi.org/10.1145/2330601.2330666
Ayeni, O. G., & Olowe, M. O. (2016). The implication of large class size in the teaching and learning of business education in tertiary institutions in Ekiti state. Journal of Education and Practice, 7(34), 65–69.
Brusilovsky, P. (2003). Adaptive and intelligent web-based educational systems. International Journal of Artificial Intelligence in Educa Tion, 13(2–4), 159–172.
Corbett, A. T., & Anderson, J. R. (1995). Knowledge tracing: Modeling the acquisition of procedural knowledge. User Modelling and User-Adapted Interaction, 4(4), 253–278. https://doi.org/10.1007/BF01099821
Dale, R., & Reiter, E. (2000). Building applied natural language generation systems. Cambridge University Press.
Dikli, S. (2006). An overview of automated scoring of essays. Journal of Technology, Learning, and Assessment, 5(1), 1–36.
Ertmer, P. A., Ottenbreit-Leftwich, A. T., & Tondeur, J. (2015). Teachers’ beliefs and uses of technology to support 21st-century teaching and learning. International handbook of research on teachers’ beliefs (pp. 403–418).
Federal Ministry of Education. (2018). Nigeria. Strategic Plan for the Education Sector. Federal Ministry of Education.
Freeman, S., Eddy, S. L., McDonough, M., Smith, M. K., Okoroafor, N., Jordt, H., & Wenderoth, M. P. (2014). Active learning increases student performance in science, engineering, and mathematics. Proceedings of the National Academy of Sciences of the United States of America, 111(23), 8410–8415. https://doi.org/10.1073/pnas.1319030111
Graesser, A. C., Chipman, P., Leeming, F. C., & Biedenbach, S. (2012). Deep learning and emotion in serious games. In Affective computing and intelligent interaction (pp. 145–154). Springer.
Greenwald, R., & Greenwald, R. (2021). The impact of class size on student achievement: A meta-analysis. American Educational Research Journal, 58(5), 1171–1201.
Hartshorne, R., & Berliner, D. C. (2002). Learning about and learning from expert teachers. International handbook of educational research, 1, 833–879.
Jurafsky, D., & Martin, J. H. (2019). Speech and Language processing (3rd ed.). Pearson.
Liu, E., & Johnson, S. M. (2019). Class size and teacher quality. In Handbook of the Economics of Education. Elsevier, 6, 1–59.
Ogunyemi, B., & Abidakun, O. (2020). Artificial intelligence, cloud computing and Nigerian education sector. Journal of King Saud University – Computer and Information Sciences.
Oladipo, O. T., & Adeniran, O. S. (2021). Artificial intelligence and classroom equity in secondary schools: A Nigerian perspective. International Journal of Educational Technology in Higher Education, 18(1), 1–23.
Omolara, A. E., & Eferakeya, T. O. (2019). Perceived factors influencing teachers’ effectiveness in large classes in senior secondary schools in Lagos State, Nigeria. International Journal of Innovative Education Research, 7(2), 17–26.
Onyema, E. (2021). Assessment of e-learning platforms among secondary school students in Nigeria. International Journal of Recent Technology and Engineering (IJRTE), 10(2).
Romero, C., & Ventura, S. (2010). Educational data mining: A review of the state of the art. IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), 40(6), 601–618. https://doi.org/10.1109/TSMCC.2010.2053532
Shute, V. J., & Kim, Y. J. (2014). Automated scoring and feedback systems: Where are we and where are we headed? In Handbook of research on educational communications and technology (pp. 275–293). Springer.
Siemens, G., & Long, P. (2011). Penetrating the fog: Analytics in learning and education. Educause Review, 46(5), 30–32.
Spector, J. M. (Ed.). (2016). Foundations of educational technology: Integrative approaches and interdisciplinary perspectives. Routledge.
United Nations Educational, Scientific and Cultural Organization. (2018). Literature review. Overview of the Education Sector. United Nations Educational, Scientific and Cultural Organization.
VanLehn. (2006). The behavior of tutoring systems. International Journal of Artificial Intelligence in Education, 16(3), 227–265.
VanLehn, K. (2011). The relative effectiveness of human tutoring, intelligent tutoring systems, and other tutoring systems. Educational Psychologist, 46(4), 197–221. https://doi.org/10.1080/00461520.2011.611369
Vygotsky. (1978). Mind in society: The development of higher psychological processes. Harvard University Press.
Wang, & Calvano. (2022). Class size, student behaviours and educational outcomes. Organization Management Journal, 19(4).
Addo, D. E., Efut, E. N., Akpo, D. M., & Egor, O. W. (2023). Innovative instructional design packages for promoting inclusive and participatory interactive learning experience in Nigeria. Shodh Sari-An International Multidisciplinary Journal, 70–87. https://doi.org/10.59231/sari7575
Adeyanju, J. O., & Ajani, I. O. (2023). Educational Counseling Strategies for Curbing academic dishonesty among students in higher Institutions. Edumania-An International Multidisciplinary Journal, 01(02), 210–221. https://doi.org/10.59231/edumania/8985
Anita. (2024). E-Learning initiatives in teacher education. Shodh Sari-An International Multidisciplinary Journal, 03(01), 186–195. https://doi.org/10.59231/SARI7664
Avurakoghene, O. P., & Oredein, A. O. (2023). Educational leadership and artificial intelligence for sustainable development. Shodh Sari-An International Multidisciplinary Journal, 02(03), 211–223. https://doi.org/10.59231/sari7600
Kumar, S., & Simran. (2024). Equity in K-12 STEAM education. Eduphoria, 02(03), 49–55. https://doi.org/10.59231/eduphoria/230412