Learning, Forgetting, and Relearning for Keystroke- and Mouse-Driven Tasks: Relearning Is Important

Abstract

We investigate performance change arising through learning, forgetting, and relearning. Participants learned a spreadsheet task with either keystrokedriven (keyboard, n D 30) or mouse-based menu-driven (mouse, n D 30) commands. Their performance confirmed the power law of practice. The keyboard users learned to complete the task faster than the mouse users on the last learning session (Day 4). At a 6-day retention interval, the mouse users were observed to forget more-they took more time to complete the task than the keyboard users. Of interest, the participants in the two modality groups showed no reliable differences in their forgetting under the retention of 12 and 18 days. With additional practice, the mouse group users with the 6-day retention relearned more-they reliably reduced the time to complete the task in comparison to the paired keyboard group. These results help understand why people may choose to use a mouse-driven graphical user interface rather than a keystroke-driven interface: People choosing to use a mouse-based menu-driven interface may not need to use a knowledge-in-the-head strategy but knowledge-in-the-world, and may be doing so because this strategy provides better relearning, rather than because it is faster or easier initially or because it is better for learning or forgetting. These results provide a richer explanation of why menu-driven interfaces (knowledge-in-the-world) are more ubiquitous and suggests when they can be replaced, for example, where use is infrequent but often enough that forgetting does not substantially occur. Our results provide preliminary suggestions for choosing optimal training strategies and supporting these strategies in terms of the three stages of learning and forgetting. ) is a cognitive scientist with an interest in human-computer interaction and cognitive modeling; he is a Research Scientist at the University of Central Florida. Frank E. Ritter (frank.ritter@psu.edu) is a cognitive scientist with an interest in human-computer interaction and cognitive modeling; he is a Professor in the College of Information Sciences and Technology, and in CSE and Psychology at the Pennsylvania State University.Color versions of one or more of the figures in the article can be found online at www.tandfonline. com/hhci.

Supporting Novice to Expert Transitions in User Interfaces

“…A recent study by Kim and Ritter [2013] investigated learning, forgetting, and re-learning a spreadsheet task when using mouse-and-menu interaction methods in comparison to keyboard-command interaction. Their findings suggest a tendency for mouse-and-menu users to forget methods sooner than the keyboard-command group.…”

Effect of Human Learning on Performance of Cloud Applications

“…A graph like this is popularly referred to as the learning curve. Figure 1 elucidates the three level hypothesis of learning postulated by Fitts [11], Anderson [1] and, Kim and Ritter [15]. The hypothesis posits that a learning curve is roughly divided into three levels of user expertise.…”

Novel application of a predictive skill retention model to technical VLE content production skills among Higher Education teachers: a case study

“…In order to support Setting up a quiz shorter refresher training intervals, or the provision of further support tools (e.g., video tutorials) would be required to extend skill retention periods. In addition, VLE design could support Setting up a quiz if functions are set up such that the number of steps which have to be performed in a particular order are reduced (West et al, 1991;Wilson, 2002;Kim & Ritter, 2015).…”

“…Despite this, there are often high expectations of staff technical abilities with respect to implementing technology within their teaching provision (Attwell & Hughes, 2010). Support, training, and ongoing development are needed to address this as are the development of systems designed to reduce cognitive load resulting from having to retrieve too many procedural steps from memory (Kim & Ritter, 2015;Kim, Ritter, & Koubek, 2013;West, Farmer, & Wolff, 1991;Wilson, 2002). Where system complexity in terms of the number of procedural steps cannot be minimised, job aids can provide an appropriate level of support.…”