## 4 Discussion
### AI-Assisted Programming and Transformation of Educational Approaches  
The integration of AI-assisted programming, particularly through LLMs and generative AI tools, is transforming programming education [10; 11; 12; 13; 15; 16; 17; 18; 19; 20; 21; 22; 24; 25; 26; 27; 29; 30; 31; 32; 33; 34; 35; 36; 37]. These technologies facilitate personalized learning experiences by adapting to diverse student needs, offering support across different programming languages, learning styles, and proficiency levels [10; 11; 31; 35]. By providing real-time feedback and customized explanations, AI tools enhance student engagement, promote self-efficacy, and provide a more interactive and autonomous learning environment [31; 35].  
AI-assisted programming has been shown to mitigate common learning barriers such as a lack of confidence, frustration, and programming anxiety [31; 35]. The non-judmental nature of AI support encourages experimentation and reduces fear of failure, allowing students to develop problem-solving skills in a supportive setting [35]. Additionally, AI has been shown to enhance learning by automating routine tasks such as debugging, syntax correction, and code explanation, thereby enabling students to focus on conceptual understanding and algorithmic thinking rather than on rote code implementation [32; 37].  
Furthermore, AI technologies are transforming the development of educational materials. The automated generation of programming exercises, detailed explanations, and personalized feedback reduces educators' workload while making curricula more adaptive and responsive [32; 34]. These tools demonstrate multiple solutions to coding problems, reinforcing diverse problem-solving strategies and improving comprehension [32].  
Additionally, AI-powered tutoring systems and chatbots facilitate dynamic assessment methods, enhancing educational outcomes and promoting greater accessibility to programming [25; 27].  
However, the integration of AI in programming education presents challenges that require careful consideration. A significant concern is the potential for overreliance on AI-generated solutions, which may hinder the development of critical thinking and problem-solving skills [10; 16; 24; 30]. The effectiveness of AI tools is heavily dependent on the quality of the prompts and user interactions, emphasizing the need for educators to guide students in effectively leveraging these technologies [10]. Ethical considerations, such as academic integrity and the risk of plagiarism, also necessitate pedagogical strategies that prioritize comprehension, debugging, and algorithmic reasoning over mere code generation [20].  
Is it evident that programming education is undergoing a shift towards higher-order skills such as code analysis, debugging strategies, and AI utilization [15; 17; 18]. This evolution underscores the need to strike a balance between leveraging AI assistance and fundamental learning, ensuring that students develop a robust understanding of programming principles [37]. By strategically integrating AI-assisted programming into curricula, educators can maximize its benefits while maintaining essential skill development and a critical approach to AI in software engineering [29; 30].  
AI-assisted programming has been identified as a promising avenue for enhancing education through personalized support, automated learning resources, and interactive engagement [18; 19; 20; 21; 22]. However, its implementation must be meticulously managed to preserve essential programming competencies and encourage independent problem-solving [10; 11; 12; 13; 15; 16; 17]. A thoughtful integration of AI in programming education has the potential to empower students and prepare them for the evolving technological landscape [29; 30].