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Evaluating an Authoring Tool for Model-Tracing Intelligent Tutoring Systems

机译:评估模型跟踪智能辅导系统的创作工具

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We have been creating an authoring tool, the Cognitive Model SDK, which allows non-cognitive scientists and non-programmers to produce a cognitive model for model-tracing tutors [1, 2]. The SDK is in use by developers at Carnegie Learning to produce their commercial Cognitive Tutors for math. However, it has never been evaluated with regards to the strong claim that non-cognitive scientists and non-programmers could, without much effort, produce useful cognitive models with it. The research presented here shows that this can be done, using a task that past researchers have used [3]. The models are evaluated across several metrics to see what characteristics of either them or their creators may distinguish better models from worse models. The goal of this work is to establish a baseline for future work examining how cognitive modeling can be opened up to a wider class of people.
机译:我们一直在创建一个创作工具,认知模型SDK,允许非认知科学家和非程序员为模型跟踪导师制作认知模型[1,2]。 SDK正在Carnegie学习的开发人员使用,以生产他们的商业认知导师进行数学。但是,它从未评估过强大声称,即非认知科学家和非程序员可以在没有大量努力的情况下产生有用的认知模型。这里提出的研究表明,使用过去研究人员使用的任务可以完成这一点[3]。这些模型在几个指标上进行了评估,以查看它们的特征或其创建者可以区分从更糟糕的模型中的更好模型。这项工作的目标是为未来的工作建立一个基线,检查认知建模如何可以向更广泛的人开放。

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