Abstract

Despite the growing body of research on pre-service teachers' perceptions and attitudes towards artificial intelligence, little is known about how artificial intelligence-assisted instruction affects pre-service teachers' engagement, problem-solving skills, and mathematics education outcomes at Ghanaian colleges of education. Pre-service teachers need to be attuned to integrate artificial intelligence in their teaching and learning when given the nod. This correlational quantitative study selected 296 Level 300 Mathematics Education students. Data was collected using a structured questionnaire. A structural Equation Modeling was performed to response the hypothesized paths. The study revealed that artificial intelligence usage had a significant positive effect on students’ engagement. Moreover, artificial intelligence usage had a significant positive effect on students’ performance and problem-solving. The findings of this study underscore the transformative potential of artificial intelligence in educational settings.

Keywords

References

• Ajani, O. A. (2024). Enhancing problem‑solving skills among pre‑service teachers in higher education: A systematic literature review. Journal of Pedagogical Sociology and Psychology, 6(2), 98–113. https://doi.org/10.33902/jpsp.202424002
• Akintayo, O. T., Eden, C. A., Ayeni, O. O., & Onyebuchi, N. C. (2024). Evaluating the impact of educational technology on learning outcomes in the higher education sector: A systematic review. Open Access Research Journal of Multidisciplinary Studies, 7(2), 052–072. https://doi.org/10.53022/oarjms.2024.7.2.0026
• Alomari, M. A., & Jabr, M. O. (2020). The effect of the use of an educational software based on the strategy of artificial intelligence on students’ achievement and their attitudes towards it. Management Science Letters, 10(13), 2951–2960. https://doi.org/10.5267/j.msl.2020.5.030
• Altememy, H. A., Mohammed, B. A., Hsony, M. K., Hassan, A. Y., Mazhair, R., Dawood, I. I., Al Jouani, I. S. H., Zearah, S. A., & Sharif, H. R. (2023). The influence of the artificial intelligence capabilities of higher education institutions in Iraq on students’ academic performance: The role of AI-based technology application as a mediator. Eurasian Journal of Educational Research, 104, 267–282. https://doi.org/10.14689/ejer.2023.104.015
• Amoako, T., Sheng, Z. H., Dogbe, C. S. K., & Pomegbe, W. W. K. (2022). Assessing the Moderation Role of ICT in the Relationship between Supply Chain Integration and SME Performance. Journal of Industrial Integration and Management, 7(2), 203–233. https://doi.org/10.1142/S2424862221500160
• Asad, M. M., Hussain, N., Wadho, M., Khand, Z. H., & Churi, P. P. (2020). Integration of e-learning technologies for interactive teaching and learning process: an empirical study on higher education institutes of Pakistan. Journal of Applied Research in Higher Education, 13(3), 649–663. https://doi.org/10.1108/JARHE-04-2020-0103
• Asare, B., & Boateng, F. O. (2025). Self-awareness and self-regulatory learning as mediators between ChatGPT usage and pre-service mathematics teachers’ self-efficacy. Journal of Pedagogical Research, 9(2), 38–54. https://doi.org/10.33902/JPR.202530637
• Asare, B., & Larbi, E. (2025). Nexus between emotional intelligence and mathematics performance: The role of metacognitive awareness. Cogent Education, 12(1), 2450117. https://doi.org/10.1080/2331186X.2025.2450117
• Asare, B., Welcome, N. B., & Arthur, Y. D. (2024). Investigating the impact of classroom management, teacher quality, and mathematics interest on mathematics achievement. Journal of Pedagogical Sociology and Psychology, 6(2), 30–46. https://doi.org/10.33902/jpsp.202426232
• Asim, H. M., Vaz, A., Mansoori, S., Ahmed, A., Akram, R., Sadiq, S., Hussain, H., & Aziz, A. (2022). Designing of questionnaire for factors that impact student learning outcomes in tertiary education system: an analysis from Pakistan. International Education Studies, 16(1), 16. https://doi.org/10.5539/ies.v16n1p16
• Ayeni, O. O., Al Hamad, N. M., Onyebuchi, N. C., Osawaru, B., & Adewusi, O. E. (2024). AI in education: A review of personalized learning and educational technology. GSC Advanced Research and Reviews, 18(2), 261–271. https://doi.org/10.30574/gscarr.2024.18.2.0062
• Bhardwaj, V., Zhang, S., Tan, Y. Q., & Pandey, V. (2025). Redefining learning: student-centered strategies for academic and personal growth. Frontiers in Education, 10, 1518602. https://doi.org/10.3389/feduc.2025.1518602
• Bond, M., Khosravi, H., De Laat, M., Bergdahl, N., Negrea, V., Oxley, E., Chong, S. W., & Siemens, G. (2024). A meta systematic review of artificial intelligence in higher education: A call for increased ethics, collaboration, and rigour. International Journal of Educational Technology in Higher Education, 21, 4. https://doi.org/10.1186/s41239-023-00436-z
• Chaudhry, M. A., & Kazim, E. (2022). Artificial Intelligence in Education (AIEd): a high-level academic and industry note 2021. AI and Ethics, 2(1), 157–165. https://doi.org/10.1007/s43681-021-00074-z
• Chiu, T. K. F., Moorhouse, B. L., Chai, C. S., & Ismailov, M. (2024). Teacher support and student motivation to learn with Artificial Intelligence (AI) based chatbot. Interactive Learning Environments, 32(7), 3240–3256. https://doi.org/10.1080/10494820.2023.2172044
• Davis, C., Bush, T., & Wood, S. (2024). Artificial intelligence in education: enhancing learning experiences through personalized adaptation. International Journal of Cyber and IT Service Management, 4(1), 26–32. https://doi.org/10.34306/ijcitsm.v4i1.146
• Dimitriadou, E., & Lanitis, A. (2025). On the potential of using generative artificial intelligence for geometry educational activities (Publicaiton no: 391230545). arXiv. https://doi.org/10.48550/arXiv.391230545
• Engin, R. A. (2023). The effect of designing educational digital games on pre‑service teachers’ some competencies. Journal of Pedagogical Sociology and Psychology, 5(3), 195–208. https://doi.org/10.33902/jpsp.202323576
• Hair Jr., J. F., Gabriel, M. L. D. da S., & Patel, V. K. (2014). AMOS covariance‑based structural equation modeling (CB‑SEM): Guidelines on its application as a marketing research tool. Brazilian Journal of Marketing, 13(2), 44–55. https://doi.org/10.5585/remark.v13i2.2718
• Hart, S. R., Stewart, K., & Jimerson, S. R. (2011). The student engagement in schools questionnaire (SESQ) and the teacher engagement report form-new (TERF-N): Examining the Preliminary Evidence. Contemporary School Psychology, 15(1), 67–79. https://doi.org/10.1007/bf03340964
• Helmiatin, Hidayat, A., & Kahar, M. R. (2024). Investigating the adoption of AI in higher education: a study of public universities in Indonesia. Cogent Education, 11(1), 2380175. https://doi.org/10.1080/2331186X.2024.2380175
• Hodonu-Wusu, J. O. (2025). The rise of artificial intelligence in libraries: the ethical and equitable methodologies, and prospects for empowering library users. AI and Ethics, 5(2), 755–765. https://doi.org/10.1007/s43681-024-00432-7
• Hopcan, S., Polat, E., Ozturk, M. E., & Ozturk, L. (2023). Artificial intelligence in special education: a systematic review. Interactive Learning Environments, 31(10), 7335–7353. https://doi.org/10.1080/10494820.2022.2067186
• Iyer, S. S., et al. (2024). Key drivers of artificial intelligence influencing student retention in higher education. Biomedical Journal of Scientific & Technical Research, 59(1), 009246. https://doi.org/10.26717/BJSTR.2024.59.009246
• Jiang, M. Y. C., Jong, M. S. Y., Wu, N., Shen, B., Chai, C. S., Lau, W. W. F., & Huang, B. (2022). Integrating automatic speech recognition technology into vocabulary learning in a flipped english class for chinese college students. Frontiers in Psychology, 13, 902429. https://doi.org/10.3389/fpsyg.2022.902429
• Jr, T. G. R., & Shuck, B. (2015). Exploratory factor analysis : implications for theory , research, and practice. Advances in Developing Human Resources, 17(1), 12-25. https://doi.org/10.1177/1523422314559804
• Katenova, M., & Turmaganbetova, K. (2024). Artificial intelligence and business school students’ performance. International Journal of Religion, 5(8), 96–101. https://doi.org/10.61707/6wjvxp71
• Kim, J., Lee, H., & Cho, Y. H. (2022). Learning design to support student-AI collaboration: perspectives of leading teachers for AI in education. Education and Information Technologies, 27(5), 6069–6104. https://doi.org/10.1007/s10639-021-10831-6
• Labadze, L., Grigolia, M., & Machaidze, L. (2023). Role of AI chatbots in education: A systematic literature review. International Journal of Educational Technology in Higher Education, 20, 56. https://doi.org/10.1186/s41239-023-00426-1
• Laranjeira, M., & Teixeira, M. O. (2025). Relationships between engagement, achievement and well-being: validation of the engagement in higher education scale. Studies in Higher Education, 50(4), 756–770. https://doi.org/10.1080/03075079.2024.2354903
• 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), 487. https://doi.org/10.1186/s40359-024-01979-0
• Ma, L., Liu, J., & Li, B. (2022). The association between teacher-student relationship and academic achievement: The moderating effect of parental involvement. Psychology in the Schools, 59(2), 281–296. https://doi.org/10.1002/pits.22608
• Ma’amor, H., Achim, N., Ahmad, N. L., Roszaman, N. S., Anuar, N. N. N. K., Azwa, N. C. A. K., Rahman, S. N., & Hamjah, N. A. A. (2024). The effect of artificial intelligence (AI) on students’ learning. Information Management and Business Review, 16(3), 856–867. https://doi.org/10.22610/imbr.v16i3S(I)a.4178
• McLaren, B. M., & Nguyen, A. (2022). Digital learning games in artificial intelligence in education. In R. Nkambou, R. Azevedo, & J. Vassileva (Eds.), Handbook of artificial intelligence in education (pp. 1–31). Springer.
• Merino-Campos, C. (2025). The impact of artificial intelligence on personalized learning in higher education: A systematic review. Trends in Higher Education, 4(2), Article 17. https://doi.org/10.3390/higheredu4020017
• Muthmainnah, Ibna Seraj, P. M., & Oteir, I. (2022). Playing with AI to Investigate Human-Computer Interaction Technology and Improving Critical Thinking Skills to Pursue 21stCentury Age. Education Research International, 2022, 6468995. https://doi.org/10.1155/2022/6468995
• National Education Association. (2024). Report of the NEA Task Force on artificial intelligence in education. Author.
• Net, W. W. W. P. (2025). The relationship between pre-service teachers’ attitude towards artificial intelligence (AI) and their AI literacy. Pegem Journal of Education and Instruction, 15(3), 121–131. https://doi.org/10.47750/pegegog.15.03.13
• Nguyen, A., Kremantzis, M., Essien, A., Petrounias, I., & Hosseini, S. (2024). Enhancing student engagement through artificial intelligence (ai): understanding the basics, opportunities, and challenges. Journal of University Teaching and Learning Practice, 21(6), 92. https://doi.org/10.53761/caraaq92
• Nyante, F., Mensah, G. B., Addy, A., & Akuffo, E. A. (2024). Digital storm: how Ghana defied doubts in nursing and midwifery assessment reform against the odds. Public Policy and Administration Research, 14(1), 61-71. https://doi.org/10.7176/ppar/14-1-06
• Oktradiksa, A., Bhakti, C. P., Kurniawan, S. J., Rahman, F. A., & Ani. (2021). Utilization artificial intelligence to improve creativity skills in society 5.0. Journal of Physics: Conference Series, 1760(1), 12032. https://doi.org/10.1088/1742-6596/1760/1/012032
• Opesemowo, O. A. G., & Ndlovu, M. (2024). Artificial intelligence in mathematics education: The good, the bad, and the ugly. Journal of Pedagogical Research, 8(3), 333-346. https://doi.org/10.33902/JPR.202426428
• Pacheco-Mendoza, S., Guevara, C., Mayorga-Albán, A., & Fernández-Escobar, J. (2023). Artificial intelligence in higher education: a predictive model for academic performance. Education Sciences, 13(10), 990. https://doi.org/10.3390/educsci13100990
• Pitura, J., Kaplan‑Rakowski, R., & Asotska‑Wierzba, Y. (2024). The VR‑AI–assisted simulation for content knowledge application in pre‑service EFL teacher training. Education and Information Technologies, 29(4), 1501–1522. https://doi.org/10.1007/s11528-024-01022-4
• Pokrivcakova, S. (2023). Pre-service teachers’ attitudes towards artificial intelligence and its integration into EFL teaching and learning. Journal of Language and Cultural Education, 11(3), 100–114. https://doi.org/10.2478/jolace-2023-0031
• Poquet, O., Trenholm, S., & Santolini, M. (2024). Forum posts, communication patterns, and relational structures: A multi-level view of discussions in online courses. Educational Technology Research and Development, 72(5), 2655–2678. https://doi.org/10.1007/s11423-023-10262-9
• Prediger, S. (2024). Fifty ways to work with students’ diverse abilities? A video study on inclusive teaching practices in secondary mathematics classrooms. International Journal of Inclusive Education, 28(2), 124–143. https://doi.org/10.1080/13603116.2021.1925361
• Putra, D. A., Meirza Nanda Faradita, & Dewi Masyita Faradillah. (2023). Problem-based learning (pbl) instructional materials for enhancing mathematics learning outcomes of elementary school students. Education and Human Development Journal, 8(2), 1–9. https://doi.org/10.33086/ehdj.v8i2.5018
• Qurohman, M. (2024). Enhancing high school students problem solving ability inalgebra through artificial intelligence based learning. International Journal of Trends in Mathematics Education Research, 7(4), 9–17. https://doi.org/10.33122/ijtmer.v7i4.358
• Rehman, N., & Kang, M. A. (2024). Exploring the impact of artificial intelligence on students’ engagement and motivation in online learning environments. International Journal of Trends and Innovations in Business & Social Sciences, 2(4), 537–548. https://doi.org/10.48112/tibss.v2i4.959
• Rizvi, M. (2023). Investigating ai-powered tutoring systems that adapt to individual student needs, providing personalized guidance and assessments. The Eurasia Proceedings of Educational and Social Sciences, 31, 67–73. https://doi.org/10.55549/epess.1381518
• Roemer, E., Schuberth, F., & Henseler, J. (2021). HTMT2–an improved criterion for assessing discriminant validity in structural equation modeling. Industrial Management and Data Systems, 121(12), 2637–2650. https://doi.org/10.1108/IMDS-02-2021-0082
• Subramanian, K. P., Abrar, M., Aboraya, W., Abdulghafor, R., & Al Husaini, Y. (2025). AI‑powered learning pathways: Personalized learning and dynamic assessments. International Journal of Advanced Computer Science and Applications, 16(1). http://dx.doi.org/10.14569/IJACSA.2025.0160145
• Tin, T. T., Chor, K. Y., Hui, W. J., Cheng, W. Y., Kit, C. J., Husin, W. N. A. A. W., Aitizaz, A., Tiung, L. K., Afolalu, S. A., & Khattak, U. F. (2024). Demographic factors shaping artificial intelligence (ai) perspectives: exploring their impact on university students’ academic performance. Pakistan Journal of Life and Social Sciences, 22(2), 12248–12264. https://doi.org/10.57239/PJLSS-2024-22.2.00876
• Trochim, W. M. K., & Donnelly, J. P. (2006). The research methods knowledge base. Atomic Dog Publishing.
• Van Mechelen, M., Smith, R. C., Schaper, M. M., Tamashiro, M., Bilstrup, K. E., Lunding, M., Graves Petersen, M., & Sejer Iversen, O. (2023). Emerging technologies in K-12 education: A future HCI research agenda. ACM Transactions on Computer-Human Interaction, 30(3), 3569897. https://doi.org/10.1145/3569897
• Walter, Y. (2024). Embracing the future of Artificial Intelligence in the classroom: The relevance of AI literacy, prompt engineering, and critical thinking in modern education. International Journal of Educational Technology in Higher Education, 21, 15. https://doi.org/10.1186/s41239-024-00448-3
• Wang, H., Wang, C., Chen, Z., Liu, F., Bao, C., & Xu, X. (2025). Impact of AI-agent-supported collaborative learning on the learning outcomes of University programming courses. In Education and Information Technologies. Advance online publication. https://doi.org/10.1007/s10639-025-13487-8
• Wang, Y., & Wang, H. (2024). Mediating effects of artificial intelligence on the relationship between academic engagement and mental health among Chinese college students. Frontiers in Psychology, 15, 1477470. https://doi.org/10.3389/fpsyg.2024.1477470
• Wu, S. Y., & Yang, K. K. (2022). The effectiveness of teacher support for students’ learning of artificial intelligence popular science activities. Frontiers in Psychology, 13, 868623. https://doi.org/10.3389/fpsyg.2022.868623
• Yeung, M. M. Y., Yuen, J. W. M., Chen, J. M. T., & Lam, K. K. L. (2023). The efficacy of team-based learning in developing the generic capability of problem-solving ability and critical thinking skills in nursing education: A systematic review. Nurse Education Today, 122, 105704. https://doi.org/10.1016/j.nedt.2022.105704
• Yurt, E., & Kasarci, I. (2024). A questionnaire of artificial intelligence use motives: a contribution to investigating the connection between ai and motivation. International Journal of Technology in Education, 7(2), 308–325. https://doi.org/10.46328/ijte.725
• Zhou, X., Teng, D., & Al-Samarraie, H. (2024). The mediating role of generative ai self-regulation on students’ critical thinking and problem-solving. Education Sciences, 14(12), 1302. https://doi.org/10.3390/educsci14121302

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