Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Закон Хика-Хаймена× | KLM-GOMS× | |
|---|---|---|
| Область | Человеко-компьютерное взаимодействие | Человеко-компьютерное взаимодействие |
| Семейство | Hypothesis test | Hypothesis test |
| Год появления≠ | 1952 | 1983 |
| Автор метода≠ | William Edmund Hick and Ray Hyman | Stuart Card, Thomas Moran, Allen Newell |
| Тип≠ | Empirical model of choice reaction time as logarithmic function of number of choices | Computational cognitive model for task execution time prediction |
| Основополагающий источник≠ | Hick, W. E. (1952). On the rate of gain of information. Quarterly Journal of Experimental Psychology, 4(1), 11–26. DOI ↗ | Card, S. K., Moran, T. P., & Newell, A. (1983). The Psychology of Human-Computer Interaction. Lawrence Erlbaum Associates. ISBN: 0898592437 |
| Другие названия | Hick's Law, Law of Choice Reaction Time | GOMS Model, KLM |
| Связанные | 4 | 4 |
| Сводка≠ | The Hick-Hyman Law predicts that human decision time increases logarithmically with the number of equally likely choices. Independently formulated by William Edmund Hick and Ray Hyman in the early 1950s, this law describes how long it takes a person to make a choice among alternatives. In human-computer interaction, the law is widely applied to menu design, navigation hierarchies, and command selection, showing that users take longer to select from larger sets of options, but the relationship is logarithmic, not linear. | The Keystroke-Level Model (KLM), part of the Goals-Operators-Methods-Selection rules (GOMS) framework, is a computational method for predicting how long a user will take to accomplish a routine task using an interactive system. Developed by Card, Moran, and Newell in 1983, KLM decomposes user actions into primitive operators (keystrokes, mouse clicks, mental preparation, system response waits) with empirically derived execution times, enabling designers to estimate task performance without running user studies. |
| ScholarGateНабор данных ↗ |
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