Adaptive Recommendations to Students Based on Working Memory Capacity

Abstract

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.