DeepTutor:面向宏观和微观自适应对话式智能辅导

Proceedings of the first ACM conference on Learning @ scale conference Pub Date : 2014-03-04 DOI:10.1145/2556325.2567885

V. Rus, D. Stefanescu, Nobal B. Niraula, A. Graesser

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引用次数: 23

摘要

我们提出了一个基于学习进度框架的会话智能辅导系统的设计概述，称为DeepTutor。学习进步法捕捉学生走向精通的成功路径。所建议的导师的假设是，通过基于学习进度的指导教学，系统将更有效(而且效率更高)。

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DeepTutor: towards macro- and micro-adaptive conversational intelligent tutoring at scale

We present an overview of the design of a conversational intelligent tutoring system, called DeepTutor, based on the framework of Learning Progressions. Learning Progressions capture students' successful paths towards mastery. The assumption of the proposed tutor is that by guiding instruction based on Learning Progressions, the system will be more effective (and efficient for that matter).

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Proceedings of the first ACM conference on Learning @ scale conference

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