Abstract:  The current learner model lacks exploration of this dimension of cognitive load, which, as a load generated by the cognitive system during the learning process, has a significant impact on the learning state of learners. Based on the CELTS-11(China E-Learning Technology Standardization-11) proposed by the China E-Learning Technology Standardization Committee, cognitive load is integrated into the learner model as a dimension, and an LMICL ( Learner Model Incorporating Cognitive Load) combining static and dynamic information is constructed. Afterwards, relying on an adaptive learning system, the data of the unmixed cognitive load learner model and the LMICL data were used as the basis for recommending learning resources, resulting in two different learning resource recommendation results. Two classes of learners were randomly selected to learn system, and then their academic performance. The results of cognitive load and satisfaction were used to validate the effectiveness of LMICL , and it was found that the recommendation learning effect based on LMICL was better than that of the learner model without integrating cognitive load.

Key words: learner model, cognitive load, learner model incorporating cognitive load(LMICL)