Ease-of-use—the extent to which a technology is free of effort—is a hallmark of many successful websites and is a predictor of important user outcomes including intentions to use a system and a system’s perceived usefulness. We propose a behavior-based measure of ease-of-use based on the analysis of users’ mouse cursor movements. As a basis for this measure, we explain how ease-of-use influences the precision of users’ mouse cursor movements, extending Attentional Control Theory and the Response Activation Model. We propose two mousing statistics—Normalized Area under the Curve and Normalized Additional Distance—and predict that they are correlated with PEOU and can be used to differentiate ease-of-use among different tasks. We end by describing next steps to test our hypotheses and highlight potential implications.
Jenkins, Jeffrey and Valacich, Joseph, "Behaviorally Measuring Ease-of-Use by Analyzing Users’ Mouse Cursor Movements" (2015). SIGHCI 2015 Proceedings. 17.