Mouse tracking

Mouse tracking (also known as cursor tracking) is the use of software to collect users' mouse cursor positions on the computer. This goal is to automatically gather richer information about what people are doing, typically to improve the design of an interface. Often this is done on the Web and can supplement eye tracking in some situations.

When mouse tracking takes place without the user's consent, for example on a website, there may be privacy implications.

The computer mouse was first invented in 1968 by Douglas Engelbart. The term mouse tracking originally referred to how movements were captured and transmitted to the computer. For example, the original tracker ball mouse used a metal bearing pressed against two rollers to track movement. Much research and technology has gone into what type of tracker provides the most accurate depiction of the user's movement.

With the advent of the World Wide Web, mouse tracking was expanded to include click data. Researchers and developers would track and record each time a user used the mouse to click something on the website, as well as the location of the event. Web developers use these mouse clicks to assess what information users are interested in and how they interact with a page. Additionally, advertisers are interested in click data in terms of banner advertisements and where to place their ads on pages to get the most click-throughs.

More recently, the term mouse tracking has been expanded even more to develop a much broader area of research in helping understand the human-computer interaction (HCI). This development began with eye tracking. While eye tracking has been around since the 1800s, it was not used in HCI until the 1980, primarily to help answer questions about how users search for commands in computer menus and to develop systems to help disabled users. More recently, eye tracking has been used in usability testing on web pages to understand a user's point of focus as well as test the usability of different features of a site, such as dropdown menus. This information can influence Web design so it meets the researcher's goals yet is user friendly.

The problem with using eye tracking in usability testing is the required hardware and then expense. Additionally, eye tracking is limited to small sample sizes and abnormal browsing environments. Mouse tracking, on the other hand, is inexpensive and the data can be collected from any computer. It is in this capacity that mouse tracking was re-invented in HCI research. Eye tracking researchers in the late 1990s noticed patterns between the eye and mouse movements. Based on these findings, researchers who had been tracking click data realized there might be more to learn from the mouse. In 2001 Mon-Chu Chen, John Anderson, and Myeong-Ho Sohn at Carnegie Mellon University, began explicitly investigating whether tracking mouse movements could be used as a proxy for tracking eye movements. This research has continued through the 2000s and to the present. The general findings in the research are that the correlation is not one to one, but there is a relationship between eye and mouse movements, which, in turn suggests mouse movements can in fact be used to determine a user's focus of attention. More recent research has shown that the correlation depends strongly on the user behavior at that time, such as whether the user is reading with the mouse, moving it to perform a click, or leaving it idle. Furthermore, the mouse position actually correlates better with past eye-gaze positions, meaning that people will typically look somewhere before moving their mouse there about 700ms later. Generally, tracking mouse positions can lead to a vast improvement to understanding the user compared with relying on mouse clicks only. In other words, click data informed researchers of a users' primary focus of attention, or their end choice. However, looking at all of the mouse movements can inform the researcher to other options that were of interest to the user but were not selected by clicking, which can lead to better overall understanding of the user's thought process.

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