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Dynamic Detection of Learning Modalities Using Fuzzy Logic in Students' Interaction Activities

机译:在学生互动活动中使用模糊逻辑动态检测学习方式

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E-learning software is oriented to a heterogeneous group of learners. Thus, such systems need to provide personalization to students' needs and preferences so that their knowledge acquisition could become more effective. One personalization mechanism is the adaptation to the students' learning modalities. However, this process requires a lot of time when happening manually and is error-prone. In view of the above, this paper presents a novel technique for learning modalities detection. Our approach utilizes the Honey-Mumford model, which classifies students in activists, reflectors, theorists and pragmatists. Furthermore, the automatic detection uses the fuzzy logic technique taking as input the students' interaction with the learning environment, namely the kind of learning units visited, their type of media, the comments made by students on learning units and their participation in discussions. Our novel technique was incorporated is a tutoring system for learning computer programming and was evaluated with very promising results.
机译:电子学习软件面向的是一群异类的学习者。因此,这样的系统需要针对学生的需求和喜好提供个性化设置,以使他们的知识获取变得更加有效。一种个性化机制是适应学生的学习方式。但是,手动进行此过程需要很多时间,并且容易出错。有鉴于此,本文提出了一种新的学习方式检测技术。我们的方法利用了Honey-Mumford模型,该模型将学生分为活动家,反思者,理论家和实用主义者。此外,自动检测使用模糊逻辑技术,将学生与学习环境的互动作为输入,即访问的学习单元的种类,他们的媒体类型,学生对学习单元的评论以及他们对讨论的参与。我们的新技术被纳入了一个用于学习计算机程序的辅导系统,并得到了非常有希望的结果评估。

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