Capturing Self-Efficacy Behavioral Outcomes Through Human-Computer Interaction Devices

Abstract

Mouse cursor tracking (MCT) is increasingly being used in human-computer interaction studies in fields such as information systems, psychology, and cognitive science. MCT allows researchers to more closely study how cognitive processes such as uncertainty are expressed through physical movements like hesitation, speed of performing an action, or switching answers in a multiple-choice response. Researchers have codified these movements into four variables: Additional Distance; Maximum Deviation; Area Under the Curve; and Speed. In this dissertation, we study the effects of mouse cursor movements on the relationship between a user’s self-efficacy score and task performance. We propose that mouse cursor movements moderate this relationship and how well a self-efficacy score can predict successful task performance. We designed three studies and used a proprietary MCT system. We specified the context for each study: mental multiplication in Study 1, verbal concept formation in Study 2, and word-processing software skill assessment in Study 3. In Study 1, we found that changes in Additional Distance and Maximum Deviation significantly influenced the accuracy of using a self-efficacy score to predict task performance. We did not find any significant results in Study 2. In Study 3, we found that changes in Additional Distance and Area Under the Curve significantly influenced the accuracy of using a self-efficacy score to predict task performance. We suggest that Additional Distance may be a fruitful variable for deeper study and analysis. We also identified limitations in the MCT system and in study designs across different contexts. We propose changes and future work avenues to better study cognitive processes using MCT.