Learners' Working Memory Capacity Modeling Based on Fuzzy Logic

Recently, many works have investigated the identification of learner's working memory capacity (WMC) from his/her behavior in learning systems. These works used a mechanism, called dichotomic node network, able to create representation of the learner's WMC taking into account different theories from the literature. However, this mechanism could only provide a binary representation of learner's WMC (High or Low), whereas the WMC is estimated by 7 (plus or minus two) items. This paper presents an alternative based on fuzzy logic for precisely estimate the WMC of the learner while using learning system or playing educational games. The proposed approach can improve the accuracy of learner model and then enable the fine grained recommendations that positively affect the learners' learning.