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A survey of artificial intelligence techniques employed for adaptive educational systems within e-learning platforms

机译：电子学习平台内用于自适应教育系统的人工智能技术的调查

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The adaptive educational systems within e-learning platforms are built in response to the fact that the learning process is different for each and every learner. In order to provide adaptive e-learning services and study materials that are tailor-made for adaptive learning, this type of educational approach seeks to combine the ability to comprehend and detect a person's specific needs in the context of learning with the expertise required to use appropriate learning pedagogy and enhance the learn ing process. Thus, it is critical to create accurate student profiles and models based upon analysis of their affective states, knowledge level, and their individual personality traits and skills. The acquired data can then be efficiently used and exploited to develop an adaptive learning environment. Once acquired, these learner models can be used in two ways. The first is to inform the pedagogy proposed by the experts and designers of the adaptive educational system. The second is to give the system dynamic self-learning capabilities from the behaviors exhibited by the teachers and students to create the appropriate pedagogy and automatically adjust the e-learning environments to suit the pedagogies. In this respect, artificial intelligence techniques may be useful for several reasons, including their ability to develop and imitate human reasoning and decision-making processes (learning-teaching model) and minimize the sources of uncertainty to achieve an effective learning-teaching context. These learning capabilities ensure both learner and system improvement over the lifelong learning mechanism. In this paper, we present a survey of raised and related topics to the field of artificial intelligence techniques employed for adaptive educational systems within e-learning, their advantages and disadvantages, and a discussion of the importance of using those techniques to achieve more intelligent and adaptive e-learning environments.
机译：电子学习平台中的自适应教育系统是根据每个学习者的学习过程不同而建立的。为了提供针对适应性学习量身定制的适应性电子学习服务和学习材料，这种类型的教育方法旨在将理解和检测人的特定需求的能力与学习所需的专业知识相结合。适当的学习教学法，并改善学习过程。因此，至关重要的是根据对他们的情感状态，知识水平以及他们的个性特征和技能的分析来创建准确的学生档案和模型。然后可以有效地使用和利用所获取的数据来开发自适应学习环境。这些学习者模型一旦获得，便可以两种方式使用。首先是告知自适应教育系统的专家和设计者提出的教学法。第二是根据教师和学生的行为为系统提供动态的自我学习能力，以创建适当的教学法，并自动调整电子学习环境以适应教学法。在这方面，人工智能技术可能出于多种原因而有用，包括其发展和模仿人类推理和决策过程（学习教学模型）的能力，以及最大限度地减少不确定性来源以实现有效学习教学环境的能力。这些学习功能可确保终身学习机制中的学习者和系统得到改善。在本文中，我们对在电子学习中用于自适应教育系统的人工智能技术领域提出的相关主题进行了概述，其优缺点，并讨论了使用这些技术实现更智能，更智能的重要性。自适应电子学习环境。

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