Educating Aspiring Teachers with AI by Strengthening Sustainable Pedagogical Competence in Changing Educational Landscapes

This study examines the effectiveness of an eight-week AI training program aimed at en-hancing teacher candidates' pedagogical competence and AI literacy in rapidly changing and evolving educational environments. Due to the rapid change and development of our age, the change and transformation of education, which is one of the most important ele-ments of our lives, cannot be ignored. Accordingly, the integration of teacher candidates, one of the stakeholders of education, into technological developments is very important for both the efficiency and sustainability of education. The "parallel–simultaneous de-sign", one of the mixed research methods in which quantitative and qualitative research methods are used together, was employed. Based on this purpose, the study started with a needs analysis conducted with 33 teacher candidates studying in different branches at the faculty of education. Thanks to the needs analysis, knowledge gaps, digital skill levels and readiness for integration into artificial intelligence tools in future classrooms were deter-mined. Its application in teacher candidates instead of teachers in the profession was de-termined by needs analysis. It has been concluded that it will be more beneficial to apply the education of the future to the teachers of the future and that they will be able to adapt to these trainings more easily. Based on all these, a pre-test-posttest design was applied to observe the changes of the participants and an artificial intelligence literacy scale was used. QDA Miner Lite was used for the analysis of qualitative data, and SPSS 29.0 was used for the analysis of quantitative data. During the eight-week training, Gamma pro-grams were used for presentation, Suno for audio, Mindjourney for visual and Chatgpt for descriptive search in order to provide better quality education to the participants. While practicing with these applications, a more up-to-date education is aimed with activities that reveal problem-solving skills that include critical thinking exercises. According to the results obtained, it was revealed that the teacher candidates who thought that they were undecided or had insufficient knowledge reached a sufficient level in the post-test. In the light of these results, it reveals that artificial intelligence-oriented education is effective in developing sustainable pedagogical skills, digital literacy, readiness and professional self-confidence and offers evidence-based recommendations for the design of future teacher training programs.