As Generative AI (GenAI) models continue to gain prominence, a new frontier is emerging in the field of computer science education. Results from initial anonymous surveys reveal that nearly half (48.5%) of our students now turn to GenAI for academic assignments, highlighting its growing role in modern education. With educators facing challenges in creating dynamic and unique course content, the potential of GenAI becomes evident. It offers not only a quicker method for content development but also paves the way for diversified, high-quality educational resources, countering traditional cheating methods and catering to varied student needs. Key questions thus arise: "How can GenAI assist instructors in creating meaningful content and problems quickly, and can it reduce the instructional staff's workload?" Addressing the first question, we unveil the "GenAI Content Generation Framework". This novel tool equips educators to tap into the prowess of GenAI for course content design. The framework presents a systematic and practical blueprint for generating university-level course material through chat-based GenAI. Drawing from our first-hand experiences, we provide strategic guidance on formulating inquiries and organizing GenAI sessions to elicit quality content that aligns with specific educational goals and context. Our work stands apart by outlining a specific workflow and offering concrete suggestions for harnessing GenAI in course material development, backed by a strong case for its adoption. Armed with the framework and insights presented in this paper, educators and course content developers can move forward with assurance, tapping into GenAI's vast potential for innovative content creation.

翻译：随着生成式人工智能（GenAI）模型持续获得广泛关注，计算机科学教育领域正迎来全新前沿。初步匿名调查结果显示，近半数（48.5%）学生现已借助GenAI完成学术作业，凸显其在现代教育中日益增长的作用。面对教师创建动态且独特课程内容的挑战，GenAI的潜力愈发显著：它不仅能提供更高效的内容开发方法，还能为多样化、高质量教育资源的开发铺平道路，从而应对传统作弊手段并满足学生差异化需求。由此引发关键问题："GenAI如何协助教师快速创建有意义的内容与题目，能否减轻教学人员的工作负担？"针对第一个问题，我们提出了"GenAI内容生成框架"。这一创新工具使教育工作者能够利用GenAI的强大能力进行课程内容设计。该框架通过基于聊天的GenAI，为生成大学层次课程材料提供了系统且实用的蓝图。基于第一手经验，我们提供了关于制定查询策略与组织GenAI会话的战略指导，以激发符合特定教育目标与场景的高质量内容。我们的研究独到之处在于，通过明确具体工作流程、提出利用GenAI开发课程材料的切实建议，并以充分证据支持其应用推广。借助本文提出的框架与见解，教育工作者与课程内容开发者可自信前行，充分挖掘GenAI在创新内容创作中的巨大潜力。