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Kano Model×NASA-TLX×
DziedzinaInterakcja człowiek–komputerInterakcja człowiek–komputer
RodzinaHypothesis testHypothesis test
Rok powstania19841988
TwórcaNoriaki KanoSandra Hart and Lowell Staveland
TypTwo-dimensional model categorizing product/service features by satisfaction impactMulti-dimensional post-task questionnaire for measuring subjective mental workload
Źródło pierwotneKano, N., Seraku, N., Takahashi, F., & Tsjui, S. (1984). Attractive quality and must-be quality. Journal of the Japanese Society for Quality Control, 14(2), 147–156. link ↗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 ↗
Inne nazwyKano Analysis, Attractive-Performance-Basic ModelTask Load Index, TLX, NASA-TLX
Pokrewne34
PodsumowanieThe Kano Model is a framework for categorizing product or service features based on their impact on customer satisfaction. Developed by Noriaki Kano, this model distinguishes three types of features: basic (must-have) features that satisfy minimally but cause significant dissatisfaction if absent; performance features that increase satisfaction proportionally with their level; and attractive (delightful) features that exceed expectations and generate disproportionate satisfaction. By classifying features using the Kano Model, product teams prioritize development efforts, balance risk and innovation, and design experiences that delight rather than merely satisfy.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.
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  3. PUBLISHED

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ScholarGatePorównaj metody: Kano Model · NASA-TLX. Pobrano 2026-06-18 z https://scholargate.app/pl/compare