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A conception for use of user profile to prediction learning effects in Intelligent Tutoring Systems

机译:使用用户个人资料预测智能辅导系统中的学习效果的概念

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Intelligent Tutoring Systems (ITS) offer adaptivity to user abilities, personal character trait, learning styles and preferences. The user modelling is one of the major factors that can influence an adaptivity. The content and structure of user profile should allow to recommend learning material suitable for student's needs. In this work a user profile is designed and a method for predicting learner's abilities is proposed. We use a Naive Bayes classifier in order to predict student's learning results. A prediction of user's abilities could be very useful for determining an initial learning scenario or assigning a student to a suitable collaborative learning group.
机译:智能辅导系统(ITS)提供了对用户能力,个人性格特征,学习方式和偏好的适应性。用户建模是可能影响适应性的主要因素之一。用户资料的内容和结构应允许推荐适合学生需求的学习材料。在这项工作中,设计了用户配置文件,并提出了一种预测学习者能力的方法。我们使用朴素贝叶斯分类器来预测学生的学习结果。用户能力的预测对于确定初始学习方案或将学生分配给合适的协作学习小组可能非常有用。

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