Investigating the effect of generative artificial intelligence-assisted programming education on various variables

This study aims to examine the effects of generative artificial intelligence support on various variables in programming education at the high school level. The vast majority of Vocational and Technical Anatolian High Schools in our country have an Information Technologies field, and compulsory or elective Information Technologies courses are also offered in high schools other than Vocational and Technical Anatolian High Schools. Programming education constitutes the most significant part of these courses. In today's rapidly digitalizing world, programming education is becoming increasingly important. In this context, the integration of advanced technologies such as Artificial Intelligence into educational processes can help students enhance their digital skills, improve their understanding of programming courses, and be better prepared for future technologies. Artificial Intelligence has begun to permeate all educational processes or shows strong potential to do so. Academic studies have started to focus on programming education with the support of generative artificial intelligence in our country. Teachers, students, and curriculum developers need to understand the impacts of this technology, which is likely to become widespread in the near future, and be prepared for this transformation. The primary aim of this study is to analyze the impact of generative artificial intelligence support on various variables in the programming education of students in the Information Technologies Department of a Vocational and Technical Anatolian High School located in the Mamak district of Ankara. This study focuses on the effects of generative artificial intelligence support on computational thinking, self-efficacy perceptions in computer programming, and learning motivation in computer programming courses. The study results indicate that generative AI-supported programming education has significant effects on cognitive skills such as algorithmic thinking, problem-solving, and critical thinking. Additionally, substantial improvements were observed in variables like learning motivation and programming self-efficacy perception. Particularly notable is the positive impact on subdimensions of learning motivation, including attitude, expectations, clear goals, and social interaction. Future studies can provide a more detailed framework by addressing the long-term effects and ethical dimensions of AI-supported programming education. Expanding research in this field not only enhances students' digital skills but also offers significant benefits in terms of equity and accessibility in education.