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  • 标题:NLTML: A Mark-up Language for Transformation-based Question Generation
  • 作者:Zhiqiang Cai ; Xiangen Hu ; Arthur C. Graesser
  • 期刊名称:Learning Technology
  • 印刷版ISSN:1438-0625
  • 出版年度:2006
  • 卷号:8
  • 期号:1-2
  • 出版社:IEEE Computer Society
  • 摘要:AutoTutor is a dialog-based tutoring system that has been used by colleges to teach conceptual physics and computer literacy. ASAT is an authoring tool created to facilitate the authoring of curriculum scripts so that AutoTutor can teach other knowledge to learners. AutoTutor teaches by helping learners to solve problems. In the curriculum script, the ideal answer of a problem is split into single sentence elements, called “expectations”. The system “expects” a learner to speak out all the expectations. The system forms some questions for each expectation and asks a learner these questions until the learner covers the expectation. These questions are called “hints” and prompts. The following example shows an expectation and the hints and prompts associated with it in the physics tutor curriculum:
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