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| Ретроспективно мислене на глас× | NASA-TLX× | |
|---|---|---|
| Област | Взаимодействие човек-компютър | Взаимодействие човек-компютър |
| Семейство | Hypothesis test | Hypothesis test |
| Година на възникване≠ | 1980 | 1988 |
| Създател≠ | K. Anders Ericsson, Herbert Simon, adapted by Gary Olson and colleagues | Sandra Hart and Lowell Staveland |
| Тип≠ | Post-task verbalization method for reflecting on decision-making | Multi-dimensional post-task questionnaire for measuring subjective mental workload |
| Основополагащ източник≠ | Ericsson, K. A., & Simon, H. A. (1980). Verbal reports as data. Psychological Review, 87(3), 215–251. DOI ↗ | Hart, S. G., & Staveland, L. E. (1988). Development of NASA-TLX (Task Load Index): Results of empirical and theoretical research. In P. A. Hancock & N. Meshkati (Eds.), Human Mental Workload (pp. 139–183). Elsevier. DOI ↗ |
| Други названия | Delayed Verbalization, Post-task Thinking Aloud, RTA | Task Load Index, TLX, NASA-TLX |
| Свързани | 4 | 4 |
| Резюме≠ | Retrospective Think-Aloud is a variant of the Think-Aloud Protocol in which participants complete a task without verbalization, then immediately review a video or replay of their task performance and narrate their thoughts, reasoning, and reactions. This method captures post-hoc reflection on decision-making and user experience without disrupting task execution. Particularly valuable for exploring user awareness, emotional reactions, and retrospective sense-making, Retrospective Think-Aloud provides the explanatory richness of concurrent thinking aloud without the disruption. | The NASA Task Load Index (TLX) is a multi-dimensional subjective workload assessment tool developed at NASA Ames Research Center by Sandra Hart and Lowell Staveland in the 1980s. TLX measures perceived mental workload across six dimensions—mental demand, physical demand, temporal demand, performance, effort, and frustration—allowing researchers and practitioners to understand the cognitive and affective burden of tasks and interfaces. The instrument is widely used in human factors, cognitive engineering, and HCI to identify task bottlenecks and evaluate system designs. |
| ScholarGateНабор от данни ↗ |
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