Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Закон Хика-Хаймена× | Когнитивный обход× | |
|---|---|---|
| Область | Человеко-компьютерное взаимодействие | Человеко-компьютерное взаимодействие |
| Семейство | Hypothesis test | Hypothesis test |
| Год появления≠ | 1952 | 1990 |
| Автор метода≠ | William Edmund Hick and Ray Hyman | Clayton Lewis, Peter Polson, Cathleen Wharton, John Rieman |
| Тип≠ | Empirical model of choice reaction time as logarithmic function of number of choices | Evaluative walkthrough examining how users learn to use an interface |
| Основополагающий источник≠ | Hick, W. E. (1952). On the rate of gain of information. Quarterly Journal of Experimental Psychology, 4(1), 11–26. DOI ↗ | Lewis, C., Polson, P. G., Wharton, C., & Rieman, J. (1990). Testing a walkthrough methodology for specifying and evaluating user interface designs. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 387–392). link ↗ |
| Другие названия | Hick's Law, Law of Choice Reaction Time | Cognitive Walkthrough, CW Analysis |
| 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. | Cognitive Walkthrough is an inspection method for evaluating interface designs by simulating and analyzing how users will learn to use a system through exploration and trial. Developed by Clayton Lewis, Peter Polson, Cathleen Wharton, and John Rieman in 1990, this method is grounded in cognitive psychology and focuses specifically on learnability—whether first-time or occasional users can discover how to perform tasks without formal training. Evaluators role-play user actions, answer a set of critical questions about feedback and discovery at each step, and document usability problems. |
| ScholarGateНабор данных ↗ |
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