Designing “Faster” Progress Bars: Manipulating Perceived Duration

Designing “Faster” Progress Bars: Manipulating Perceived Duration

Chris Harrison (Carnegie Mellon University, Pittsburgh, USA), Zhiquan Yeo (Carnegie Mellon University, Pittsburgh, USA), Brian Amento (AT&T Labs, USA) and Scott E. Hudson (Carnegie Mellon University, Pittsburgh, USA)
DOI: 10.4018/978-1-4666-1628-8.ch016
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Human perception of time is fluid, and can be manipulated in purposeful and productive ways. In this chapter, the authors describe and evaluate how progress bar pacing behaviors and graphical design can alter users’ perceptions of an operation’s duration. Although progress bars are relatively simple, they provide an ideal playground in which to experiment with perceptual effects in user interface design. As a baseline in the experiments, the authors use generic, solid-color progress bars with linear pacing behaviors, prevalent in many user interfaces. In a series of direct comparison tests, they are able to rank how different progress bar designs compare to one another. Using these results, it is possible to craft perceptually-optimized progress bars that appear faster, even though their actual duration remains unchanged. Throughout, the authors include design suggestions that can contribute to an overall more responsive, pleasant, and human-centric computing experience.
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Myers (1985) was the first to investigate the impact of progress indicators on the user experience in graphical user interfaces. He concluded that users have a strong preference for progress indicators during long tasks, and overall, find them useful.

Conn (1995) explored the concept of time affordance. The work enumerates a series of properties an ideal progress bar would embody. This exemplar offers users an accurate and understandable method for gauging progress in interactive systems. Conn also defines another concept: the time tolerance window, which is the length of time a user is willing to wait before deciding a task is not making adequate progress. Conn goes on to describe that predictive algorithms could be applied to set user expectations for longer waits, essentially reporting progress in a non-linear manner to enhance the user experience.

Much of the work presented in this chapter borrows heavily from perceptual effects identified in other fields, but not applied to human-computer interactions. For example, duration neglect and peak-and-end effects (discussed in detail subsequently) can be seen in a variety of domains, including medicine, economics, and advertising (e.g., Redelmeier, 1996; Langer, 2005; Baumgartner, 1997). More than a decade ago, Geelhoed et al. (1995) demonstrated that similar effects are present in user interface design, by manipulating how fax transmissions were displayed over time.

Despite this early success and continued discoveries in psychophysics, there has been remarkably little interest in the broader HCI community. This is now beginning to change as computing performance reaches the limits of Moore’s law. A considerable challenge is how to make computers “faster” if processor performance plateaus. Consequently, there has been a resurgence of interest in “time design”—a discipline that looks at how temporal aspects of interactive systems can be structured and manipulated to improve the user experience (Hildebrandt, 1994; Seow, 2008).

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