방법 비교

	AttrakDiff/UEQ	사고 구술법 (Think-Aloud Protocol)
분야	인간-컴퓨터 상호작용	인간-컴퓨터 상호작용
계열	Hypothesis test	Hypothesis test
기원 연도	2003	1980
창시자	Marc Hassenzahl (AttrakDiff), Martin Schrepp (UEQ)	K. Anders Ericsson and Herbert A. Simon, adapted to HCI by Clayton Lewis
유형	Questionnaire measuring pragmatic and hedonic quality dimensions	Protocol for capturing user cognition and decision-making during task execution
원전	Hassenzahl, M. (2003). The thing and I: Understanding the relationship between user and product. In M. A. Blythe, K. Overbeeke, A. F. Monk, & P. C. Wright (Eds.), Funology (pp. 31–42). Kluwer Academic Publishers.	Ericsson, K. A., & Simon, H. A. (1980). Verbal reports as data. Psychological Review, 87(3), 215–251.
별칭	Hedonic Quality Assessment, Pragmatic vs. Hedonic, UEQ	Talk-Aloud Protocol, Concurrent Thinking Aloud, TA
관련	4	4
요약	AttrakDiff and the User Experience Questionnaire (UEQ) are assessment instruments for measuring user experience across multiple dimensions. AttrakDiff, developed by Marc Hassenzahl, evaluates the tension between pragmatic quality (functionality, usability, does the system do what I need?) and hedonic quality (beauty, emotional engagement, does it delight me?). The UEQ, developed by Schrepp and colleagues, extends this framework with additional dimensions including efficiency, perspicuity, stimulation, and novelty. Both instruments provide quantitative post-use assessment, complementing task-based usability testing with holistic experience evaluation.	The Think-Aloud Protocol is a usability testing method in which participants verbalize their thoughts while completing tasks on a system. As users navigate an interface, they continuously narrate their observations, interpretations, and reasoning, allowing researchers to understand their mental models, decision-making, and frustration points. Originating from cognitive psychology research by Ericsson and Simon (1980), this method was adapted for HCI by Clayton Lewis and has become one of the most widely used techniques for identifying usability problems and understanding user behavior.