Learner-generated content, task engagement, affective response, and memory on technology-mediated conversation tasks

Abstract

This study provides insight into the role of learner-generated content (LGC) in affective response and engagement during interactive tasks on a video conferencing platform. It also examines task content, affect and conation with respect to recall of the language used on tasks. The performances of four learners on recommendation tasks are analyzed in detail, comparing LGC with teacher-generated content (TGC). Results reveal that when listening to technology-mediated recommendations based on LGC, the information-receivers in the study took a more active role in the online tasks, interacted more with the speakers, displayed more positive emotions, felt more interested and focused, and were better able to recall the language and content that the speakers used. The results also revealed that the impact of LGC was consistent across learners of different first languages (Chinese, Indonesian), genders (female, male) and cultures (Confucian, Muslim) and that the effect of LGC in one technology-mediated context was comparable to the effects of LGC documented in previous research in face-to-face contexts. The study expands research on the role of the learner in task-based language teaching to measures of affect via facial analysis as well as language retention by learners in the receptive role of technology-mediated interactive tasks