AI能生成高质量课件，学生难分辨真伪。
AI-Generated Slides: Are They Good? Can Students Tell?
- 用编码助手生成的幻灯片最准确完整。
- 学生评分显示AI幻灯片质量与人工相当。
- 学生更倾向认为非AI生成的课件更好。
随着生成式AI工具日益普及，其在教学中的应用潜力受到关注。本研究评估了利用GenAI从教师课程笔记生成幻灯片的效果，重点关注教师与学生的感知。实验涉及端到端教育工具NotebookLM、两款通用大模型Claude和M365 Copilot，以及两款代码辅助工具Cursor和Claude Code。首先通过教育者叙事评估判断生成幻灯片的质量，筛选出最优结果并经少量修改后应用于真实课程。对比学生对人工与AI生成幻灯片的评价发现：编码助手生成的幻灯片在准确性、完整性与教学设计上表现最佳；学生对两类幻灯片的质量评分无显著差异，且无法可靠识别哪些是AI生成的。但高评分的幻灯片反而被标记为低AI生成概率，表明学生将质量差与来源为AI相关联。研究揭示了将GenAI融入教学设计的潜力，并呼吁进一步探索教师如何负责任、高效地使用此类工具。
原文摘要 · Abstract (English)
As generative AI (GenAI) tools become easily accessible, there is promise in using such tools to support instructors. To that end, this paper examines using GenAI to help generate slides from instructor authored course notes, emphasizing instructor and student perceptions. We examine an end-to-end education tool (NotebookLM), two general-purpose LLMs (Claude, M365 Copilot), and two coding assistants (Cursor, Claude Code). We first analyze whether GenAI generated slides are ``good'' via narrative assessment by educators. We choose the best slides to use (with some modification) in a real course setting, and compare the student perception of human vs. AI generated slides. We find that coding assistant tools produce slides that were most accurate, complete, and pedagogically sound. Additionally, students rate GenAI slides to be of similar quality as instructor-created slides, and cannot reliably identify which slides are AI-generated. Additionally, we find a negative correlation between a high quality rating and a high ``AI-generated'' rating, suggesting students associate poor quality with the source of the slides being AI. These findings highlight promising opportunities for integrating GenAI into instructional design workflows and call for further research on how educators can best harness such tools responsibly and effectively.
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