Exploring the interaction of cognition and emotion in small group collaborative discourse by Heuristic Mining Algorithm (HMA) and Inductive Miner Algorithm (IMA).

Abstract

This study explored the interaction between cognition and emotion in blended collaborative learning. The participants (n = 30) of this study were undergraduate students enrolled in a 16-week course on information technology teaching. These students were divided into six groups of five people each. The behavior modes of the participants were analyzed using a heuristic mining algorithm and inductive miner algorithm. Compared with the groups with low task scores, the high-scoring groups exhibited more reflection phases and cycles in the interaction process and thus more frequent self-evaluation and regulation behavior for forethought and performance. Moreover, the frequency of emotion events unrelated with cognition was higher for the high-scoring groups than for the low-scoring groups. On the basis of the research results, this paper presents suggestions for developing online and offline blended courses.