An interactive application’s overall pace of interaction is a combination of the user’s pace and the system’s pace, and if the system’s pace is mismatched to the user’s pace (e.g., timeouts or animations are too fast or slow for the user), usability and user experience can be impaired. Through a series of four studies, we investigated whether users prefer systems where the system’s pace better matches their own pace. All of the studies used common drag-and-drop interactions with hierarchical folder widgets, in which a folder would expand when the cursor hovered over it for a timeout period. If the system pace in these interactions is too fast (i.e., the timeout is too short), then the user’s performance and subjective experience is likely to be impaired because of unintended expansions; and if the system pace is too slow (i.e., the timeout is too long), then performance and experience could be impaired by unnecessary delay before folders expand. The first experiment was designed to validate the premise that fast-paced users prefer a fast system pace to a slow one (and the inverse for slow-paced users), and results confirmed this premise. The second study used the first experiment’s data to look for measures of user pace that could enable automatic adaptation of system pace, and also examined whether participants adjusted their pace towards that of the system. The study found reliable measures of user pace and showed that participants do entrain to the system’s pace. The third and fourth studies examined whether users would prefer a system that adapted its pace to the user over a system that used a static baseline pace. Results indicated that a majority of fast-paced users preferred the adaptive interface, but that slow-paced users generally preferred the static baseline interface. We discuss several design implications, including opportunities for systems to improve user experience for fast users by automatically adapting system pace to user pace.

The ‘Barnum effect’ is a psychological phenomenon under which people assign higher quality ratings to personality descriptions developed ‘specially for you’ than the same descriptions described as ‘generally true of people.’ This effect suggests that recommender interfaces could elevate the perceived quality of recommendations simply by indicating that they are explicitly personalised. We therefore conducted a crowd-sourced experiment (n=492) that examined the perceived quality of personalised versus non-personalised movie recommendations for good and bad movies – importantly, the actual recommendations were identical, and were merely presented as being either personalised or not. Contrary to the Barnum effect, results showed numerically lower mean quality scores for personalised recommendations, but with no significant difference. Our findings suggest that Barnum-like effects of personalisation have at most a small influence on perceived quality, and that designers should not rely on this effect to improve user experience (despite online design guidance suggesting the opposite).

The effective use of assistive interfaces (i.e. those that offer suggestions or reform the user’s input to match inferred intentions) depends on users making good decisions about whether and when to engage or ignore assistive features. However, prior work from economics and psychology shows systematic decision-making biases in which people overreact to low probability events and underreact to high probability events – modelled using a probability weighting function. We examine the theoretical implications of this probability weighting for interaction, including its suggestion that users will overuse inaccurate interface assistance and underuse accurate assistance. We then conduct a new analysis of data from a previously published study, quantifying the degree of bias users exhibited, and demonstrating conformance with these predictions. We discuss implications for design, including strategies that could be used to mitigate the deleterious effects of the observed biases.

The overall pace of interaction combines the user’s pace and the system’s pace, and a pace mismatch could impair user preferences (e.g., animations or timeouts that are too fast or slow for the user). Motivated by studies of speech rate convergence, we conducted an experiment to examine whether user preferences for system pace are correlated with user pace. Subjects first completed a series of trials to determine their user pace. They then completed a series of hierarchical drag-and-drop trials in which folders automatically expanded when the cursor hovered for longer than a controlled timeout. Results showed that preferences for timeout values correlated with user pace – slow-paced users preferred long timeouts, and fast-paced users preferred short timeouts. Results indicate potential benefits in moving away from fixed or customisable settings for system pace. Instead, systems could improve preferences by automatically adapting their pace to converge towards that of the user.