Generative AI's Transformative Role in Computer Science Education: Opportunities, Challenges, and Pedagogical Reform

The advent of Generative Artificial Intelligence (GenAI), particularly large language models (LLMs) capable of generating coherent text and functional code, is catalyzing a paradigm shift in Computer Science (CS) education. This paper presents a comprehensive analysis of GenAI's dual impact, examining its immense potential to optimize teaching content, personalize learning, and innovate instructional models, while concurrently investigating its profound challenges to academic integrity, assessment authenticity, and learning outcomes. Through systematic review of empirical studies and theoretical frameworks, we analyze pedagogical opportunities afforded by GenAI tools like code assistants and intelligent tutors, and document the rising incidence of AI-assisted plagiarism. Our findings emphasize the critical need for educators to reform curricula, redesign assessments to focus on higher-order thinking, and establish clear ethical guidelines to harness GenAI's transformative power while preserving the integrity and quality of CS education. The study concludes with evidence-based recommendations for sustainable GenAI integration that balances innovation with pedagogical responsibility.