Supporting Novice to Expert Transitions in User Interfaces

Abstract

Interface design guidelines encourage designers to provide high-performance mechanisms for expert users. However, research shows that many expert interface components are seldom used and that there is a tendency for users to persistently fail to adopt faster methods for completing their work. This article summarizes and organizes research relevant to supporting users in making successful transitions to expert levels of performance. First, we provide a brief introduction to the underlying human factors of skill acquisition relevant to interaction with computer systems. We then present our focus, which is a review of the state of the art in user interfaces that promote expertise development. The review of interface research is based around four domains of performance improvement: intramodal improvement that occurs as a factor of repetition and practice with a single method of interaction; intermodal improvement that occurs when users switch from one method to another that has a higher performance ceiling; vocabulary extension, in which the user broadens his or her knowledge of the range of functions available; and task mapping, which examines the ways in which users perform their tasks. The review emphasizes the relationship between interface techniques and the human factors that explain their relative success.

Is Two Enough?

“…Similar approaches have been proposed as multi-layered user interfaces [50] in the context of information visualization for gradually teaching users about the benefits of multiple coordinated views. Other strategies include to support intermodal improvement and vocabulary extensions [11], e.g., by improving the learnability of mobile devices [26] or executable context-specific action suggestions [13].…”

Plateaus, Dips, and Leaps: Where to Look for Inventions and Discoveries During Skilled Performance

“…Carroll and Rosson, who at that time worked for the IBM Watson Research Center, shared the HCI's community's concern that the expected productivity gains of the computer revolution were not occurring (e.g., Cockburn, Gutwin, Scarr, & Malacria, 2014;Doane, Pellegrino, & Klatzky, 1990;Nilsen, Jong, Olson, Biolsi, Rueter, & Mutter, 1993). 5 Ericsson came to his conclusions from years of study of exceptional performers.…”

Effects of Frequency Distribution on Linear Menu Performance

“…Indeed, analyses of software containing many commands such as AudoCad show that users only use a subset of the available commands [19]. This implies that users' performance is often impaired by not using the appropriate functions, possibly due to the lack of awareness of the menu content [7,14].…”