学习风格识别与预测技术的探索研究

Mohammed Jebbari, B. Cherradi, Oussama El Gannour, S. Hamida, A. Raihani
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引用次数: 1

摘要

学习风格通过了解每个学习者的行为和习惯来帮助确定他们喜欢的方法和内容。这就是为什么学习风格在学习(或学习系统)中很重要,因为它显示了学习者在学习过程中的长处和短处。也允许教师(或系统)投资,发展这些学习者的能力。我们将通过分析和讨论学习者行为的结果,对大多数用于检测学习风格的技术进行概述。静态技术(传统)用于根据问卷调查或测试来确定学习者的学习风格。由于这种技术的局限性和不太准确的结果,已经提出了几个自动模型(动态)来检测学习者在在线学习过程中的学习风格,基于从教育系统中收集的数据。因此,已经提出了几种混合检测学习风格的方法,将静态和自动技术结合在一起。在每种技术中,我们都提出了一个模型来描述检测学习风格的过程。这项研究对学习风格研究领域的研究人员有一定的帮助。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Exploration Study on Learning Styles Identification and Prediction Techniques
A learning style helps determine each learner preferred method and content by knowing their behaviors and habits. This is why learning style is important in learning (or learning systems), because it shows the learner its strengths and weaknesses in learning process. Also allows the teacher (or system) to invest, develop the competence of these learners. We will give an overview of most of the techniques used to detect learning styles, by analyzing and discussing results of learners' behavior. The static techniques (traditional) used to identify learners' learning styles based on questionnaires or tests. Due to the limitations and less accurate results of this technique, several automatic models (dynamic) have been proposed to detect the learning styles of learners during the online learning, based on the data collected from them in the educational system. Thus, several approaches have been proposed for the hybrid detection of learning styles, bringing together Static and automatic techniques. In each technique, we propose a model that describes the process for detecting the learning style. This study can be helpful to researchers working in the field of learning styles.
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