Explore the interrelationship of cognition, emotion and interaction when learners engage in online discussion

Abstract

Online learning community provides abundant semantic text information for investigating learning behaviors. Despite the increasing of learning behavior in higher education, few previous researches have studied online learning from multidimensional behavior. This study mainly explores the interrelationship of cognition, emotion and interaction when learners engage in online discussion. The research object is online discussion textual from a certain course. First, lag sequence analysis is adopted to analyze the dynamic of cognition from the micro perspective, and the relationship between cognition and emotion combined with emotion analysis is investigated. Furthermore, this study proposes the standards of quantifying cognition and emotion from the macro perspective, and the cognition, emotion and interaction are analyzed in a unified framework by using social network analysis. Our findings suggest that: (1) Cognitive level is stable during the learning process, and can be improved by continuous thinking and analysis. (2) Positive emotion plays a significant role in developing higher-level cognition, and its value increases gradually with the improvement of cognition level. (3) Network structure has important influence on individual cognition, who with higher cognitive levels are usually in the center of the network and have larger interaction quality. (4) The learning community with more intensive interactions show higher positive emotion, indicating that emotion transmission is realized by means of network structure. This study might give theoretical and technical supports for helping learners improve the learning quality and efficiency in the online learning.