This study examines the effectiveness of an eight-week AI training program aimed at enhancing teacher candidates’ pedagogical competence and AI literacy in rapidly changing and evolving educational environments. As the modern world continues to change and develop, the transformation of education, which is one of the most important elements of our lives, cannot be ignored. Accordingly, the integration of teacher candidates, who constitute key education stakeholders, into technological developments is very important in terms of both efficiency and sustainability. The “parallel–simultaneous design”, one of the mixed research methods in which quantitative and qualitative research methods are used together, was employed. In line with the stated purpose, the study started with a needs analysis conducted with 33 teacher candidates studying in different branches at the faculty of education. As a result of the needs analysis, knowledge gaps, digital skill levels and readiness for integration of artificial intelligence tools in future classrooms were determined. Its application to teacher candidates, instead of teachers in the profession, was determined by the needs analysis. The results indicate that it would be more beneficial to apply the education of the future to the teachers of the future and that they will find it easier to adapt to such training. Accordingly, a pre-test–post-test design was applied to observe how the participants changed, and an artificial intelligence literacy scale was also used. QDA Miner Lite was used for the analysis of the qualitative data, and SPSS 29.0 was used for the analysis of the quantitative data. During the eight-week training, Gamma programs were used for the presentation, Suno for audio, Midjourney for visuals and ChatGPT-4 for a descriptive search in order to provide better quality education to the participants. While practicing with these applications, the aim is to provide more up-to-date education that reveals problem-solving skills that include critical thinking exercises. According to the results, the teacher candidates who expressed that they were undecided or had insufficient knowledge reached a sufficient level in the post-test. In the light of these results, it can be stated that artificial-intelligence-oriented education is effective in developing sustainable pedagogical skills, digital literacy, readiness and professional self-confidence. The study also offers evidence-based recommendations for the design of future teacher training programs.
Erkan et al. (Mon,) studied this question.