Simple Mouse Attribute Analysis

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Abstract

This work investigates the potential bivariate correlations between selected pattern related mouse attributes and a set of factors for the determination of the satisfaction with the usability. To examine this, a prototype tool for the analyzation and characterization of mouse attributes, Simple Mouse Attribute Analysis (SMATA), within the usage of a cloud-based vertical business software solution for managing soft data, was designed and implemented. A questionnaire was conducted to evaluate the users’ satisfaction with the usability. Following, the potential correlation between those properties was investigated. The findings revealed several statistically significant correlations between the factors of satisfaction with the usability and the examined mouse attributes. Mouse attributes like the number of direct movement, the number of long direct movements, the number of made pauses, as well as the covered distance and the total time of the session could be associated with the perception of the system usefulness, the information and interface quality and the overall impression. The objective of this study was to point out a new interesting research direction of using implicit gathered user data from one of the default communication channels in HCI: the computer mouse.

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APA

Matthiesen, J., & Holte, M. B. (2019). Simple Mouse Attribute Analysis. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11589 LNCS, pp. 95–113). Springer Verlag. https://doi.org/10.1007/978-3-030-22338-0_8

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