论文标题
使用大语言模型自动生成CS学习材料
Automatically Generating CS Learning Materials with Large Language Models
论文作者
论文摘要
现在，大型语言模型（LLMS）（例如GPT-3和Codex）的最新突破，现在使软件开发人员能够根据自然语言提示生成代码。在计算机科学教育中，研究人员正在探索LLMS使用精心制作的提示来生成代码解释和编程任务的潜力。这些进步可能使学生能够以新的方式与代码进行互动，同时帮助讲师扩展学习材料。但是，LLM还引入了对学术诚信，课程设计和软件工程职业的新影响。该研讨会将展示LLM的功能，以帮助与会者评估LLM是否以及如何将LLM纳入其教学法和研究。我们还将吸引与会者集思广益，以考虑LLM将如何影响我们的领域。
Recent breakthroughs in Large Language Models (LLMs), such as GPT-3 and Codex, now enable software developers to generate code based on a natural language prompt. Within computer science education, researchers are exploring the potential for LLMs to generate code explanations and programming assignments using carefully crafted prompts. These advances may enable students to interact with code in new ways while helping instructors scale their learning materials. However, LLMs also introduce new implications for academic integrity, curriculum design, and software engineering careers. This workshop will demonstrate the capabilities of LLMs to help attendees evaluate whether and how LLMs might be integrated into their pedagogy and research. We will also engage attendees in brainstorming to consider how LLMs will impact our field.
