High-fidelity, AI-based simulated classroom systems enable teachers to rehearse effective teaching strategies. However, dialogue-oriented open-ended conversations such as teaching a student about scale factor can be difficult to model. This paper presents a high-fidelity, AI-based classroom simulator to help teachers rehearse research-based mathematical questioning skills. We take a human centered approach to designing our system, relying advances in deep-learning, uncertainty quantification and natural language processing while acknowledging the limitations of conversational agents for specific pedagogical needs. Using experts' input directly during the simulation, we demonstrate how conversation success rate and high user satisfaction can be achieved.
翻译：以AI为基础的高忠诚度模拟课堂系统使教师能够排练有效的教学战略。然而,面向对话的开放式对话,如对学生进行规模因素教育等,可能很难进行模拟。本文展示了一种高忠诚度的、以AI为基础的课堂模拟器,帮助教师练习基于研究的数学质询技巧。我们用以人为本的方法设计我们的系统,依靠深层学习、不确定性量化和自然语言处理方面的进步,同时承认对话代理器在特定教学需求方面的局限性。在模拟期间直接使用专家的投入,我们展示了对话成功率和用户满意度如何实现。
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