Artificial Intelligence Integration in Teaching and Learning: Investigating Retirement-date and Self-efficacy of in-service Teachers in Higher Education Institutions
Adebowale Oluwasegun Adebagbo
Department of Educational Foundations, School of Technical Education, Yaba College of Technology, In affiliation with University of Nigeria, Nsukka Email: ade_adebagbo@yahoo.com
Abstract
Artificial intelligence (AI) technology is recalibrating teaching and learning activities. Higher education institution teachers have different perceptions and different “self-efficacy” on the need to integrate AI to enhance their tasks. This could affect their readiness to embrace AI to develop instructional resources. Moreover, the number of years left for them to spend in the teaching service could affect how they embrace AI or otherwise. This is a problem because it could affect level of learning satisfaction given to the learners in the digital age. Getting empirical data would help to understand the complexity of the problem and specific actions to take towards solutions. Hence, this study focused on artificial intelligence integration in teaching and learning regarding retirement-date and self-efficacy of in-service teachers in higher education institutions. Online questionnaire on Teachers’ AI Self-efficacy (TASQ) with 0.86 reliability co-efficient was used for data collection. Data were analysed with Chi-squire. The results revealed that impact of retirement-dates were not significant on the self-efficacy of the academics. Based on the results, recommendations were made, among others, that conscious advocacy should be embarked upon to encourage teachers to embrace integration of AI in their career practices to increase their professional relevance during their career and post-career.
Keywords
Artificial intelligence, Integration, Retirement-date expectation, Self-efficacy, HEI’s
Reference
Baimuldina, N., Tsay, Y., Khakimova, T., Myrzabayeva, A., & Naimanbaiev, A. (2019). The Main Aspects of Digitalization in the System of Professional Development of Teachers. Advances in Social Science, Education, and Humanities Research, 315(Icpcs), 75–77. https://doi.org/10.2991/icpcs-19.2019.17
Balić, N., Grubišić, A., & Granić, A. (2024). Perceptions of Digital Learning and Teaching: The Case of a Croatian University Transition to an Emergency Digital Environment. Technology, Knowledge and Learning, 29(1), 453–481. https://doi.org/10.1007/s10758-023-09692-4
Benedek, A., & Molnár, Gy. (2015). E-teaching and Digitalization at BME. New Technologies and Innovation in Education for Global Business: 19th International Conference on Engineering Education, August 2015, 349–356.
Bandura, A. (1997). Self-efficacy: The exercise of control. Worth Publishers.
Capa‐Aydin, Y., Uzuntiryaki‐Kondakci, E., & Ceylandag, R. (2018). The relationship between vicarious experience, social persuasion, physiological state, and chemistry self‐efficacy: The role of mastery experience as a mediator. Psychology in the Schools, 55(10), 1224–1238.
Chen, X., Zou, D., Xie, H., & Cheng, G. (2021). Twenty years of personalized language learning: Topic modeling and knowledge mapping. Educational Technology & Society, 24(1), 205–222.
Darling-Hammond, L., Hyler, M. E., Gardner, M., & Learning, P. I. (2017). Effective teacher professional development. Learning Policy Institute. Retrieved from https://learningpolicyinstitute.org/sites/default/files/product-files/Effective_Teacher_Professional_Development_REPORT.pdf
Hussain, M. S., Khan, S. A., & Bidar, M. C. (2022). Self-efficacy of teachers: A review of the literature. Jamshedpur Research Review, 1(50), 110–116.
Hwang, G. J., Xie, H., Wah, B. W., & Gaˇsevi´c, D. (2020). Vision, challenges, roles and research issues of artificial intelligence in education. Computers & Education: Artificial Intelligence, 1, Article 100001. https://doi.org/10.1016/j.caeai.2020.100001
Luan, H., Geczy, P., Lai, H., Gobert, J., Yang, S. J., Ogata, H., … Tsai, C. C. (2020). Challenges and future directions of big data and artificial intelligence in education. Frontiers in Psychology, 2748. https://doi.org/10.3389/fpsyg.2020.580820
Mislevy, R. J., Yan, D., Gobert, J., & Sao Pedro, M. (2020). Automated scoring in intelligent tutoring systems. In Handbook of automated scoring (pp. 403–422). Chapman and Hall/CRC.
Montebello, M. (2018). AI injected e-learning: The future of online education. Springer. https://doi.org/10.1007/978-3-319-67928-0
Netherlands Council for Government Policy (2023). Research for Policy. Edited by J. E. J. Prins, and F. W. A. Brom, WRR, Scientific Council for Government Policy, The Hague, Zuid-Holland, The Netherlands. ISBN 978-3-031-21447-9 ISBN 978-3-031-21448-6 (eBook). https://doi.org/10.1007/978-3-031-21448-6 p. 20.
Pozo, J. I., Pérez Echeverría, M. P., Cabellos, B., & Sánchez, D. L. (2021). Teaching and Learning in Times of COVID-19: Uses of Digital Technologies During School Lockdowns. Frontiers in Psychology, 12(April), 1–13. https://doi.org/10.3389/fpsyg.2021.656776
Shum, S. J. B., & Luckin, R. (2019). Learning analytics and AI: Politics, pedagogy and practices. British Journal of Educational Technology, 50(6), 2785–2793. https://doi. org/10.1111/bjet.12880
Thoring, A., Rudolph, D., & Vogl, R. (2017). Digitalization of Higher Education from a Student’s Point of View. EUNIS 2017 – Shaping the Digital Future of Universities, 279–288. https://www.eunis.org/download/2017/EUNIS_2017_paper_47.pdf
Wang, Y., & Zhao, P. (2020). A probe into spoken English recognition in English education based on computer-aided comprehensive analysis. International Journal of Emerging Technologies in Learning (iJET), 15(3), 223–233.
Xu, L. (2020). The Dilemma and countermeasures of AI in educational application. In 2020 4th international conference on computer science and artificial intelligence (pp. 289–294).
Yigezu, M. (2021). Digitalization in teaching and education in Ethiopia. Digitalization, the future of work, and the teaching profession project. International Labour Organization. www.ilo.org/publns
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(1), 1–27. https://doi.org/10.1186/s41239-019-0171-0