E-Learning oriented emotion regulation Mechanism and strategies in interactive text applications

Aiming at compensating the lack of affect interaction between teachers and students in e-Learning systems/environments, this paper presents an architecture of interactive text-oriented affect compensation Mechanism in e-Learning. Based on which, a hierarchical emotion regulation agent (ERA) is proposed to perceive the emotion state of an individual or group from sentences, make decisions on how to adjust their emotions in a way of on-line discussion group, and control the compensation behaviors. In which, inspired by the strategies that have been widely used in the fields of psychology and sociology, the emotion regulation polices are designed for textual interaction applications. Moreover, two curves for emotion intensity change over time are introduced into predict the emotion intensity for individual and when a group effort takes, respectively. Finally, an emotion regulation chatroom is designed and implemented to validate and verify the proposed model and mechanism. Different from the video- and audio-data based emotion classification, our method is suitable for interactive texts that widely exist in e- Learning. The emotion regulation strategies can especially benefit the interacting sides in the text-based communication.