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Probabilistic Student Modelling to Improve Exploratory Behaviour

机译：概率学生建模以改善探索行为

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摘要

This paper presents the details of a student model that enables an open learning environment to provide tailored feedback on a learner's exploration. Open learning environments have been shown to be beneficial for learners with appropriate learning styles and characteristics, but problematic for those who are not able to explore effectively. To address this problem, we have built a student model capable of detecting when the learner is having difficulty exploring and of providing the types of assessments that the environment needs to guide and improve the learner's exploration of the available material. The model, which uses Bayesian Networks, was built using an iterative design and evaluation process. We describe the details of this process, as it was used to both define the structure of the model and to provide its initial validation.
机译：本文介绍了一个学生模型的详细信息，该模型使开放学习环境能够针对学习者的探索提供量身定制的反馈。开放式学习环境已被证明对具有适当学习风格和特征的学习者有利，但对于那些无法有效探索的人而言却是个难题。为了解决这个问题，我们建立了一个学生模型，该模型能够检测学习者何时难以进行探索，并提供环境所需的评估类型，以指导和改进学习者对可用材料的探索。使用贝叶斯网络的模型是通过迭代设计和评估过程构建的。我们将描述此过程的细节，因为它既用于定义模型的结构，又用于提供其初始验证。

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