The Design of Everyday Things: Revised and Expanded Edition

By D. Norman. 2013

2,193 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/d61435d38e02bdc35fdae7afd60f99eefd472306

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Citations in the corpus

Human-Centered Explainable AI (XAI): From Algorithms to User Experiences (2021, background): “In interactions with computing technologies, an appropriate understanding of how the system works, often referred to as users’ “mental model” [78], is the foundation for users to correctly anticipate system behaviors and interact effectively.”
I Think I Get Your Point, AI! The Illusion of Explanatory Depth in Explainable AI (2021, background): “The respective mental model is adjusted with every interaction (e.g., exposure to an XAI explanation) and helps the person to reflect on their belief about the system (e.g., the ML model behavior) [39].”
Principles of Explanatory Debugging to Personalize Interactive Machine Learning (2015, background): “Thus, continued user interaction may depend upon users being able to see incremental changes to the learning system’s reasoning after each interaction (i.e., overcoming the gulf of evaluation that exists between a user’s mental model and a system’s actual state [33]).”
The Rise of Consumer Health Wearables: Promises and Barriers (2016, background): “Poor implementation of user experience principles [16] alongside the ad hoc design of user interfaces stems in part from the rapid nature of development, which may also explain the lack of randomised trials.”
Measuring user competence in using artificial intelligence: validity and reliability of artificial intelligence literacy scale (2022, background): “of a product can shape one’s mental model of it (Brandt 2001; Grassian and Kaplowitz 2001; Rosling and Littlemore 2011); this is important as mental models play a vital role in interaction processes (Norman 2013).”
Trends and Trajectories for Explainable, Accountable and Intelligible Systems: An HCI Research Agenda (2018, background): “a core concepts within HCI [138], that we can see as part of our vocabulary to discuss challenges in the use of interactive technology (i.”
Cognitive Offloading. (2016, background): “This could reflect a desire to increase usability [91,92] or automate tasks entirely [93–95].”
Framing Creative Work: Helping Novices Frame Better Problems through Interactive Scaffolding (2021, background): “Additionally, despite the the course’s emphasis on human-centered design, where a clearly defined stakeholder is required to develop effective solutions [10, 39, 46], students who did not use the template were less likely to include a stakeholder.”
Nudges for Privacy and Security (2017, unknown): “Absent nudging efforts, the design process involves complex, often interrelated choices [Norman 2013].”
A psychological ownership approach to designing object attachment (2015, background): “Affordances are possible interactions with, and use of, an object given the properties of the object and capabilities of the user (Norman 2013).”
Survey on human–robot collaboration in industrial settings: Safety, intuitive interfaces and applications (2018, background): “These general design recommendations are addressed by the branch of literature referring to concept of usability in human–computer interaction, whose pioneering reference works are [88,89] and which is out of the scope of this survey.”
Do Neural Language Representations Learn Physical Commonsense? (2019, unknown): “Coined by Gibson (1966), this term initially described animal-perceived uses for an object, but has since come to mean the perceived uses of an object in a given environment (Norman, 1988; Gaver, 1991).”
Network oscillations imply the highest cognitive workload and lowest cognitive control during idea generation in open-ended creation tasks (2021, background): “Therefore, one could expect: (1) idea generation would be associated with more decreases in delta, theta, alpha, and beta power17; (2) EEG microstate class C would be more prevalent during idea generation, since EEG microstate class C reflects activities in the default mode network48,49 and is assoc”