发表机构
Stanford University（斯坦福大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
研究人工智能时代课程设计，构建边做边学模型，探讨学生面对任务选择及教师设计课程情况。无AI时教师合理安排任务，有AI时需扭曲课程激励努力，AI质量提升对高低技能学生学习速度有不同影响。
AI 中文摘要
我构建了一个边做边学和课程设计的模型，并用以研究人工智能（AI）的影响。目光短浅的学生面临一系列任务，他可以自己完成或委托给AI。完成任务需付出代价但能提升技能，委托则无需付出但无技能提升。教师设计任务序列（“课程”）以在学生选择工作或委托时最大化其技能发展。没有AI时，教师使早期任务更需努力，后期任务更注重技能。有AI时，教师必须扭曲课程以激励努力，导致技能发展减少。如果AI补充努力，那么AI质量的提高会使高技能学生学习更快，低技能学生学习更慢。
英文摘要
I develop a model of learning-by-doing and course design, and use it to study the impacts of artificial intelligence (AI). A myopic student faces a sequence of tasks that he can work on or delegate to AI. Work requires costly effort but builds skill; delegation requires no effort but builds no skill. A teacher designs the task sequence ("course") to maximize the student's skill development, given his choices to work or delegate. Without AI, the teacher makes earlier tasks more effort-intensive and later tasks more skill-intensive. With AI, the teacher must redesign early tasks to induce effort, leading to less skill development. If AI complements effort, then improvements in AI quality make high-skill students learn faster but low-skill students learn slower.
Comments59 pages, 8 figures. v3 makes cosmetic changes
