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Adaptive Recommendations to Students Based on Working Memory Capacity

机译:基于工作记忆容量的学生的自适应建议

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An adaptive learning system is able to consider students' cognitive characteristics and then provide them with personalized content, presentation, and navigation supports. Working memory capacity (WMC) is one of the important cognitive characteristics to keep active a limited amount of information for a very brief period of time. Students might forget the important information or the learning guidelines from their limited working memory among all the information available in learning systems. Therefore, this paper proposes a mechanism to provide students with suitable and timely recommendations in learning systems based on individual student's WMC. Six types of adaptive recommendations are used to remind and suggest additional learning activities to students based on their WMC. In this mechanism, we also consider different types of objects in different situations to suit different learning scenarios.
机译:自适应学习系统能够考虑学生的认知特性,然后为他们提供个性化内容,演示和导航支持。工作存储器容量(WMC)是在非常短暂的时间内保持有限信息的重要认知特性之一。学生可能会在学习系统中的所有信息中忘记其有限的工作记忆中的重要信息或学习指南。因此,本文提出了一种机制,为学生提供基于个别学生WMC的学习系统中的适当和及时的建议。六种类型的适应性建议用于提醒并根据WMC提出额外的学习活动。在这种机制中,我们还在不同情况下考虑不同类型的物体以适应不同的学习场景。

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