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Computer mouse tracking offers a simple and cost-efficient way to gather continuous behavioral data and has mostly been utilized in psychological science to study cognitive processes. The present study extends the potential applicability of computer mouse tracking and investigates the feasibility of using computer mouse tracking for stress measurement. Drawing on first empirical results and theoretical considerations, we hypothesized that stress affects sensorimotor processes involved in mouse usage. To explore the relationship between stress and computer mouse usage, we conducted a between-participant field experiment in which N = 994 participants worked on four mouse tasks in a high-stress or low-stress condition. In the manipulation check, participants reported different stress levels between the two conditions. However, frequentist and machine learning data analysis approaches did not reveal a clear and systematic relationship between mouse usage and stress. These findings challenge the feasibility of using straightforward computer mouse tracking for generalized stress measurement.

Investigation of cognitive processes and visual attention during problem-solving tasks is an important part of understanding human reasoning. Eyetracking technology has proven to have many benefits in revealing visual attention patterns. However, the high price of accurate eyetrackers and the difficulties associated with using them represent major obstacles to their wider application. Therefore, previous studies have sought to find alternatives to eyetracking. The Restricted Focus Viewer (RFV) brings a small part of an otherwise blurred display to the focus of visual attention: A user controls what part of the screen is in focus by using a computer mouse and explicitly selecting the area to be shown in focus. Recently, some studies have employed the RFV to investigate cognitive behavior of users, and some researchers have even enhanced the tool to study usability. We replicated a previous RFV-based study while also recording gaze data. We compared the attention allocation in time and space as reported by the RFV and an eyetracker. Further, we investigated the effects of RFV’s display blurring on the visual attention allocation of 18 novice and expert programmers. Our results indicate that the data obtained from the two tools differ. Also, the RFV-blurring interferes with the strategies utilized by experts, and has an effect on fixation duration. However, task performance was preserved.