IJIET 2026 Vol.16(4): 1076-1088
doi: 10.18178/ijiet.2026.16.4.2577
doi: 10.18178/ijiet.2026.16.4.2577
Evaluation of Teacher Candidates’ Attitudes, Perceptions, and Opinions towards Artificial Intelligence and Project-Based Learning
Yessimbekova Assylzhan1, Zhakipbekova Saule2, Petkova Iliana3, and Zaure Shagatayeva1,*
1. Department of Pedagogy and Psychology, Faculty of Education, Zhetysu University named after I. Zhanugurov, Taldykorgan, Kazakhstan
2. Institute of Pedagogy and Psychology, Abai Kazakh National Pedagogical University, Almaty, Kazakhstan
3. Faculty of Education, Sophia University “St. Kliment Orhidski”, Sofia, Bulgaria
Email: a.yessimbekova@zu.edu.kz (Y.A.); sauleskorpion@mail.ru (Z.S.); i.petkova@fp.uni-sofia.bg (P.I.); zaure.shagatayeva@outlook.com (Z.S.)
*Corresponding author
2. Institute of Pedagogy and Psychology, Abai Kazakh National Pedagogical University, Almaty, Kazakhstan
3. Faculty of Education, Sophia University “St. Kliment Orhidski”, Sofia, Bulgaria
Email: a.yessimbekova@zu.edu.kz (Y.A.); sauleskorpion@mail.ru (Z.S.); i.petkova@fp.uni-sofia.bg (P.I.); zaure.shagatayeva@outlook.com (Z.S.)
*Corresponding author
Manuscript received June 3, 2025; revised June 23, 2025; accepted November 17, 2025; published April 15, 2026
Abstract—With the rapid developments in the field of artificial intelligence in recent years, teachers’ project-based learning skills and attitudes have become very important. This study aims to evaluate primary school teacher candidates’ attitudes, perceptions, and views toward artificial intelligence-supported project-based research within the context of interactive online education. As a result of pilot studies conducted outside the research participants, the measurement tools were standardized. Adopting a mixed-methods research design, the study involved 80 teacher candidates enrolled in primary education programs during the 2024–2025 academic year. Quantitative data was collected using adapted scales measuring attitudes toward project-based learning and general attitudes toward artificial intelligence. An eight-week artificial intelligence-supported project-research interactive online education program was implemented. Pre-test and post-test data were collected to assess changes in attitudes. Qualitative data were gathered through semi-structured interviews designed by the researchers. The Kolmogorov–Smirnov test confirmed normal distribution of the quantitative data, enabling the use of parametric tests. Descriptive analysis was employed for the qualitative data. Findings revealed that prior to the intervention, teacher candidates exhibited moderately positive attitudes toward project-based learning and highly positive attitudes toward artificial intelligence. Following the intervention, attitudes toward both areas became significantly more positive. Most teacher candidates expressed strong support for integrating artificial intelligence and project-based learning in educational settings. Additionally, they identified various advantages and challenges associated with the use of artificial intelligence and project-based learning in education. These findings underscore the potential of innovative, technology-enhanced pedagogical approaches in shaping future educators’ readiness for evolving educational contexts.
Keywords—education program, innovative, primary school, quantitative, qualitative
Copyright © 2026 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
Keywords—education program, innovative, primary school, quantitative, qualitative
Cite: Yessimbekova Assylzhan, Zhakipbekova Saule, Petkova Iliana, and Zaure Shagatayeva, "Evaluation of Teacher Candidates’ Attitudes, Perceptions, and Opinions towards Artificial Intelligence and Project-Based Learning," International Journal of Information and Education Technology, vol. 16, no. 4, pp. 1076-1088, 2026.
Copyright © 2026 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).