Mutual Affects in Computer-mediated Collaborative Learning: Positive Feelings Shared by Collaborators Enhance System Evaluations

Abstract

The authors employ behavioral theories of human motivation and affect and present an explanation for why some computer-mediated collaborative learning is satisfying for a user. In a longitudinal experiment, participants were divided into four groups and solved two open-ended problems together using a video-conference system. Traditional metrics of usability and product acceptance were examined with respect to psychological variables such as personality, background knowledge, and feelings toward group members (mutual affect). The results show that group-level mutual affect is a strong predictor of system acceptability judgments, even after controlling for other pragmatic variables such as opinion convergence. It is proposed that evaluating one’s experience with a computer-mediated collaborative system is a sensemaking process and that the variables that modulate this process also influence subjective judgments of usability and acceptability of a system.


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