SOAR: an architecture for general intelligence
Artificial Intelligence
User interface design
Split menus: effectively using selection frequency to organize menus
ACM Transactions on Computer-Human Interaction (TOCHI)
Supporting command reuse: mechanisms for reuse
International Journal of Man-Machine Studies
The GOMS family of user interface analysis techniques: comparison and contrast
ACM Transactions on Computer-Human Interaction (TOCHI)
Cognitive modeling reveals menu search in both random and systematic
Proceedings of the ACM SIGCHI Conference on Human factors in computing systems
Beyond Fitts' law: models for trajectory-based HCI tasks
Proceedings of the ACM SIGCHI Conference on Human factors in computing systems
Toward a deeper comparison of methods: a reaction to Nielsen & Phillips and new data
CHI '94 Conference Companion on Human Factors in Computing Systems
Comparison of GOMS analysis methods
CHI 98 Cconference Summary on Human Factors in Computing Systems
Selection from alphabetic and numeric menu trees using a touch screen: breadth, depth, and width
CHI '85 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
The keystroke-level model for user performance time with interactive systems
Communications of the ACM
Communications of the ACM
Scale effects in steering law tasks
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Quantitative analysis of scrolling techniques
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Usability Engineering
The Psychology of Human-Computer Interaction
The Psychology of Human-Computer Interaction
Personal and Ubiquitous Computing
BinScroll: a rapid selection technique for alphanumeric lists
CHI '00 Extended Abstracts on Human Factors in Computing Systems
Predictive human performance modeling made easy
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
PERCEPTUAL-MOTOR CONTROL IN HUMAN-COMPUTER INTERACTION
ACM SIGCHI Bulletin
International Journal of Human-Computer Studies - Special issue: Fitts law 50 years later: Applications and contributions from human-computer interaction
"Beating" Fitts' law: virtual enhancements for pointing facilitation
International Journal of Human-Computer Studies - Special issue: Fitts law 50 years later: Applications and contributions from human-computer interaction
A simple movement time model for scrolling
CHI '05 Extended Abstracts on Human Factors in Computing Systems
A predictive model of menu performance
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Press On: Principles of Interaction Programming
Press On: Principles of Interaction Programming
Analysis of the cognition involved in spreadsheet software interaction
Human-Computer Interaction
The growth of cognitive modeling in human-computer interaction since GOMS
Human-Computer Interaction
Predicting the skilled use of hierarchical menus with the keystroke-level model
Human-Computer Interaction
Automating human-performance modeling at the millisecond level
Human-Computer Interaction
Information theoretic models of HCI: a comparison of the Hick-Hyman law and Fitts' law
Human-Computer Interaction
Categorization costs for hierarchical keyboard commands
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
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Many interactive systems require users to navigate through large sets of data and commands using constrained input devices—such as scroll rings, rocker switches, or specialized keypads—that provide less power and flexibility than traditional input devices like mice or touch screens. While performance with more traditional devices has been extensively studied in human-computer interaction, there has been relatively little investigation of human performance with constrained input. As a result, there is little understanding of what factors govern performance in these situations, and how interfaces should be designed to optimize interface actions such as navigation and selection. Since constrained input is now common in a wide variety of interactive systems (such as mobile phones, audio players, in-car navigation systems, and kiosk displays), it is important for designers to understand what factors affect performance. To aid in this understanding, we present the Constrained Input Navigation (CIN) model, a predictive model that allows accurate determination of human navigation and selection performance in constrained-input scenarios. CIN identifies three factors that underlie user efficiency: the performance of the interface type for single-level item selection (where interface type depends on the input and output devices, the interactive behavior, and the data organization), the hierarchical structure of the information space, and the user's experience with the items to be selected. We show through experiments that, after empirical calibration, the model's predictions fit empirical data well, and discuss why and how each of the factors affects performance. Models like CIN can provide valuable theoretical and practical benefits to designers of constrained-input systems, allowing them to explore and compare a much wider variety of alternate interface designs without the need for extensive user studies.