Coaching, which involves classroom observation and expert feedback, is a widespread and fundamental part of teacher training. However, the majority of teachers do not have access to consistent, high quality coaching due to limited resources and access to expertise. We explore whether generative AI could become a cost-effective complement to expert feedback by serving as an automated teacher coach. In doing so, we propose three teacher coaching tasks for generative AI: (A) scoring transcript segments based on classroom observation instruments, (B) identifying highlights and missed opportunities for good instructional strategies, and (C) providing actionable suggestions for eliciting more student reasoning. We recruit expert math teachers to evaluate the zero-shot performance of ChatGPT on each of these tasks for elementary math classroom transcripts. Our results reveal that ChatGPT generates responses that are relevant to improving instruction, but they are often not novel or insightful. For example, 82% of the model's suggestions point to places in the transcript where the teacher is already implementing that suggestion. Our work highlights the challenges of producing insightful, novel and truthful feedback for teachers while paving the way for future research to address these obstacles and improve the capacity of generative AI to coach teachers.

翻译：教练指导涉及课堂观察和专家反馈，是教师培训中普遍且基础的部分。然而，由于资源和专业知识的限制，大多数教师无法获得持续高质量的指导。我们探讨生成式人工智能能否通过充当自动化教师教练，成为专家反馈的成本效益补充。为此，我们提出生成式人工智能的三项教师教练任务：（A）基于课堂观察工具对转录片段进行评分，（B）识别优质教学策略的亮点与错失机会，（C）为激发更多学生推理提供可操作建议。我们招募数学专家教师，评估ChatGPT在小学数学课堂转录文本上对这些任务的零样本性能。结果显示，ChatGPT生成的回复与改进教学相关，但通常缺乏新颖性和洞察力。例如，模型82%的建议指向转录文本中教师已实施该建议的环节。我们的工作揭示了为教师提供富有洞察力、新颖且真实反馈的挑战，同时为未来研究克服这些障碍、提升生成式AI辅导教师的能力奠定了基础。