College Students' Learning Decision-Making Based on Group Learning Behavior

Abstract

In learning groups, individuals have a few similarities in terms of the regularity of learning time, requirement for learning resources, and requirement for tutoring and accompanying. Analyzing the differences and connections of the learning behavior of different groups is helpful for generating more effective, targeted, and comprehensive learning decisions, however, existing studies are not extensive or deep enough in analyzing the learning behavior of different type learning groups. For this reason, this paper attempts to explore a learning decision-making model based on the influence of group learning behavior. At first, this paper made use of the advantages of Q-learning to improve the conventional behavior tree model, constructed a new model and used it to research the group learning behavior; then, this paper combined decisionmaking idea with the game model, and adopted a complex network structure to explore the evolution law of group learning decision-making based on multiple games. At last, this paper used experimental results to prove the effectiveness of the constructed model