InputLogger: General-purpose logging of keyboard and mouse events on an Apple Macintosh

Timing records of the way users interact with applications can lead to useful insights into human behavior and an application's usability. Timing records can be useful for comparing different software applications and are also necessary for building and testing user models.Westerman et al. (1996) described three different methods through which user information can be obtained. The first method, using videotape or a human recorder, is not always feasible. The video recording must be analyzed, and the human recorder has known limitations. Camtasia (TechSmith) is an example of a tool to record and replay user interactions as a video file. However, timing information cannot be directly obtained, and the tool creates logs that, being videos, are resource intensive.The second method, instrumentation, is the augmentation of an interface so that it records the user's actions. This approach can be used only if the system studied includes logging or can be modified to include logging, so it is not a general solution; information collected in this way is limited to software that can be instrumented. For example, some commercial applications, such as Microsoft Word and many games, cannot be instrumented to record user behavior.The third method is to include an unobtrusive application that exists in the background, can be used generically across all applications, and can record and timestamp user behavior. In this article, we introduce such a program: Recording User Input (RUI), which belongs to the set of programs known as keystroke logging tools. Several such tools currently exist, but there are few that record both mouse and key events and even fewer that give logs in a form that would be useful to researchers and practitioners of human-computer interaction. Several of these recording and playback tools can be downloaded from the Web, but typically these were developed as malicious "spyware" to provide keystroke logs without timing information.A tool similar to RUI was developed (Westerman et al., 1996) for the Windows 3.1 platform, but it appears no longer to be available. MICELAB (Baccino & Kennedy, 1995) is another similar tool, but it does not run on modern computers, although Baccino and Kennedy's analysis approach is still helpful in analyzing mouse movements. Another tool, InputLogger, can be used to obtain user interactions across generic interfaces, but it works only on the Classic Macintosh (pre-Mac OS X) platform (Trewin, 1998). Several large commercial products are also available. Description of RUIRUI is a keystroke and mouse action logger for the Windows (2000 and XP) and Mac OS X (10.3 and later versions) platforms. RUI's user interface includes options for which types of actions to record, including keystrokes and mouse movements. The data collected is stored in a log file (see Figure 1) as a list of the timestamps, actions, and arguments (if any), such as key pressed or move location. To start and stop recording, the hot keys Ctrl R and Ctrl S, respectively, are provided. The amount of data recorded with...

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confidence: 99%

RUI: Recording user input from interfaces under Windows and Mac OS X

Kukreja

Stevenson

Ritter

2006

“…In general, the ability to record and replay both eye movements and mouse clicks over screens is extremely useful. Moreover, many problems of UIs can be determined through task-completion times and the amount of mouse behavior necessary to fulfill an assignment (Alexander et al, 2008;Cooke, 2006;Kukreja et al, 2006;Trewin, 1998;Westerman et al, 1996).…”

Section: Methodsmentioning

confidence: 99%

“…. Throughout the years, Behavior Research Methods has published various programs that were able to log these interactions (e.g., Alexander et al, 2008;Kukreja et al, 2006;Trewin, 1998;Westerman et al, 1996).…”

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confidence: 99%

“…In the present study, we use Noldus Information Technology's uLog (Noldus Information Technology, 2008) to record user-system interactions, including mouse clicks, mouse traces, and keyboard input. Such data can help to determine the usability of existing UIs and to develop guidelines for interface design, as is illustrated in Alexander et al (2008), Cooke (2006), Kukreja et al (2006), Nielsen (1993), Trewin (1998), and Westerman et al (1996). For example, the parts of the UI that draw people's attention can be revealed.…”

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confidence: 99%

See 1 more Smart Citation

Exploring workload and attention measurements with uLog mouse data

Drunen

Broek

Spink

et al. 2009

User-system interactions (e.g., mouse clicks and movements) can be logged with the uLog computer program. A Web-based study with 20 participants was conducted to investigate the feasibility of using uLog data as an indicator of workload and attention. Eye fixation, heart rate variability (HRV), and skin conductance were used to unveil users' workload and attention and, hence, to validate uLog data as indicators of these. Results on one of the Tasks did indeed show correlations between uLog data and HRV. This is a promising first step toward the validation of uLog mouse data as indicators of workload and attention.

“…Several client-side event logging systems have been developed by researchers, but all have been simple keyboard and mouse loggers. These include Datalogger (Westerman et al, 1996) for Windows 3.1 and DOS; InputLogger (Trewin, 1998) for the Apple Macintosh; and RUI (Kukreja, Stevenson, & Ritter, 2006) for Windows and Mac OS X. All of these examples provide timing logs for keystrokes, mouse clicks, and mouse moves, but none provide information regarding the semantics of the application and the user's action, such as the name of the button that was pressed, the state of the scrollbar, the current interface view, and so on.…”

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confidence: 99%

AppMonitor: A tool for recording user actions in unmodified Windows applications

Alexander

Cockburn

Lobb

2008

Interface designers and human-computer interaction (HCI) researchers need to understand how users interact with systems in order to improve them. Several strategies are commonly used to gain such insights, including controlled experiments run in research labs, field studies, and contextual inquiry (Holtzblatt & Jones, 1993). Client-side logging of user actions is another technique that has several advantages over other methods: It is highly scalable, since software is easily disseminated over the Web; it is low-cost to the participants and experimenters, because, once it has been installed, the logs are generated and stored automatically; it readily allows longitudinal analysis of weeks, months, or years of use; and it allows finegrain analysis of subsecond events and low-level actions. The two primary disadvantages of client-side logging are, first, that it cannot record the user's high-level goals or context; and second, that developing logging software can be prohibitively complex.The difficulty in implementing logging software has discouraged and impaired its use. For example, in analyzing Web navigation behavior, participants have been asked to abandon their preferred proprietary Web browsers in favor of customized logging versions of open-source software (e.g., Tauscher & Greenberg, 1997) or to use "roll your own" systems (e.g., Kellar, Hawkey, Inkpen, & Watters, in press). Clearly, logging analyses should measure interaction with the users' preferred software rather than with a surrogate that supports a subset of the real system features or that presents the features in a different manner.In this article, we describe AppMonitor, a tool that allows logging of user interaction with unmodified applications running under Microsoft Windows. Once installed, AppMonitor requires no intervention from the user. It silently records all user actions of interest (from low-level mouse movements to the selection of items in combo/ dialog boxes), and periodically uploads them to a remote Web server. AppMonitor's logs provide a terse but semantically rich description of interaction. As well as capturing a description of low-level user events, such as mouse movement and button-or keypresses, it can also record semantic aspects of interaction, discriminating between the different interface components used and their modes. This capability distinguishes AppMonitor's logs from the video logs generated by screen recorders (such as TechSmith's Camtasia Studio, www.techsmith.com), because video logs require human interpretation to determine the semantics connecting their key logs and mouse logs with the video.To assist researchers in developing their own logging software, we explain how we implemented AppMonitor. The following section reviews related work on tools supporting event logging. We then describe AppMonitor's underlying architecture and implementation and give an example of the output it generates. Finally, we provide some preliminary analyses of the total output from our six beta testers, who used AppMonitor to record ...