INTEGRATING ARTIFICIAL INTELLIGENCE INTO COMPUTER SCIENCE EDUCATION: OPPORTUNITIES, PEDAGOGICAL APPROACHES, AND ETHICAL CHALLENGES

Abstract

The rapid development of artificial intelligence (AI) technologies is transforming educational practices and creating new opportunities for teaching and learning. This study examines the pedagogical potential of integrating AI technologies into computer science education, focusing on personalized learning, programming instruction, formative assessment, and the development of computational thinking. It also explores the ethical, pedagogical, and technical challenges associated with the use of generative AI in educational settings, including inaccurate outputs, academic integrity, data privacy, digital inequality, and the potential reduction of independent problem-solving skills. The study employs a theoretical and analytical research approach based on a review of relevant scholarly literature, comparative analysis, and conceptual synthesis. Drawing on existing research and international educational guidelines, the paper proposes a five-stage conceptual model for integrating AI into computer science lessons. The model consists of defining learning objectives, independent problem-solving, guided AI assistance, verification and analysis, and reflection and assessment. The proposed approach emphasizes the importance of maintaining human oversight, promoting critical thinking, and ensuring that AI-generated outputs are independently verified. The findings suggest that AI should be regarded not as a replacement for teachers or learners’ cognitive efforts, but as a complementary pedagogical tool that can support meaningful learning when implemented responsibly. Further empirical research is required to evaluate the effectiveness of the proposed model in different educational contexts.