Limits of Kansei – Kansei unlimited

This article discusses momentary limitations of the Kansei Engineering methods. There are for example the focus on the evaluation of colour and form factors, as well as the highly time consuming creation of the questionnaires. To overcome these limits we firstly suggest the integration of word lists from related research fields, like sociology and cognitive psychology on product emotions in the Kansei questionnaires. Thereafter we present a study on the wide range of Kansei attributes treated in an industrial setting. Concept words used by designers are being collected through word maps and categorized into attributes. In a third step we introduce a user-product interaction schema in which the Kansei attributes from the study are positioned. This schema unfolds potential expansion points for future applications of Kansei engineering beyond its current limits

Enhancing the Design Process by Embedding HCI Research into Experience Triggers

Over the last decade, User Experience (UX) has become a core concept in the field of Human-Computer Interaction (HCI). Beyond the fact of understanding and assessing the User Experience derived from the use of interactive systems, practitioners and researchers from a wide range of disciplines are now facing the challenges of designing for User Experience. Some authors have pinpointed the existence of a gap between the theoretical knowledge developed in HCI Research and the practical knowledge actually used by designers to create rich experiences with interactive artefacts. A special focus of this paper is to translate theoretical work into experiential objects (or situations) called “Experience Triggers” [1]. Through their materiality, these artefacts bring emotions and sensations to the design process and designers can immerge into and understand the theories on experience. As a consequence of this immersion, the final product designed by the team is assumed to be more experiential. Experience Triggers are introduced here as a new tool for science-based UX design

Right, No Matter Why: AI Fact-checking and AI Authority in Health-related Inquiry Settings

Previous research on expert advice-taking shows that humans exhibit two contradictory behaviors: on the one hand, people tend to overvalue their own opinions undervaluing the expert opinion, and on the other, people often defer to other people's advice even if the advice itself is rather obviously wrong. In our study, we conduct an exploratory evaluation of users' AI-advice accepting behavior when evaluating the truthfulness of a health-related statement in different "advice quality" settings. We find that even feedback that is confined to just stating that "the AI thinks that the statement is false/true" results in more than half of people moving their statement veracity assessment towards the AI suggestion. The different types of advice given influence the acceptance rates, but the sheer effect of getting a suggestion is often bigger than the suggestion-type effect

Ethical Tensions in UX Design Practice: Exploring the Fine Line Between Persuasion and Manipulation in Online Interfaces

peer reviewe

The Perceived Influence of E-Shopping Cues on Customers’ Buying Decisions

peer reviewedE-shopping sites use a variety of design elements that affect the shopping process and lead customers to favorable buying decisions. Such elements also play a significant role as impulse buying behavior triggers. In this exploratory study based on online questionnaires (N = 401), we investigated customers’ perception of the influence of eleven common e-shopping cues on their buying decisions and explored the connection between the perceived influence of the cues and the respondents’ gender, education level, and neuroticism. We found (1) that participants group the e-shopping cues by their influence power; (2) participants’ gender and educational level contribute to a more critical/favorable perception of some shopping cues; (3) a connection between a higher level of neuroticism and greater perceived influence of shopping cues, which results in lower shopping risks. Drawing on our research, we offer several design recommendations for the advancement of e-shopping websites, particularly concerning the implementation of e-shopping cues.10. Reduced inequalitie

User experienced dimensions in product design : a consolidation of what academic researchers know and what design practitioners do

Experience has become the new paradigm of product design. Designers seek to anticipate emotions or associations a user might have when in contact with their design. The factors that influence human product perception are diverse. We firstly show which product dimensions are currently investigated by design researchers. It becomes obvious that besides the usual suspects: form and colour, emotion and associations, there must be many others. We conducted a study to identify these and to estimate their pertinence in actual product conception. Word-based techniques like retrospective verbalization and mind mapping were employed. Semantic descriptors, analogies, and functionalities were highly represented. Sensations and emotions did only appear marginally among the abstract dimensions. The same low occurrence was seen for production procedures among the concrete dimensions. Other interesting dimensions found were interaction gestures, design motifs, and product components. An additional analysis of the participant mind maps on relations between the various dimensions showed many connections between e.g. material and texture or semantics and colour. Yet, these were rarely related to sensations and emotions. The insights widen the perspective on unexploited opportunities for design researchers to develop further conception strategies that allow the anticipation of user experience in product design.ANR COSINU

Running out of time(rs): effects of scarcity cues on perceived task load, perceived benevolence and user experience on e-commerce sites

peer reviewe

Analysing the Influence of Loss-Gain Framing on Data Disclosure Behaviour: A Study on the Use Case of App Permission Requests

peer reviewedThis paper examines the effect of the dark pattern strategy ``loss-gain framing'' on users' data disclosure behaviour in mobile settings. Understanding whether framing influences users' willingness to disclose personal information is important to (i) determine if and how this technique can subvert consent and other privacy decisions, (ii) prevent abuse with appropriate policies and sanctions, and (iii) provide clear evidence-based guidelines for app privacy engineering. We conducted an online user study (N=848), in which we varied the framing of app permission requests (i.e., positive, negative, or neutral framing) and examined its impact on participants' willingness to accept the permission, their evaluation of the trustworthiness of the request and their perception of being informed by it. Our findings reveal effects on disclosure behaviour for request types that users cannot easily understand. In this case, negative framing makes users more likely to disclose personal information. Contrary to our expectations, positive framing reduces disclosure rates, possibly because it raises users' suspicion. We discuss implications for the design of interfaces that aim to facilitate informed, privacy-enhancing decision-making.R-AGR-3974 - C20/IS/14717072/DECEPTICON (01/06/2021 - 31/05/2024) - LENZINI Gabriele16. Peace, justice and strong institution

Dark Patterns: Deception or Simply Bad Design?

Lately, researchers, journalists, and regulators are devoting attention to dark patterns, defined as "design choices that benefit an online service by coercing, steering or deceiving users into making decisions that, if fully informed and capable of selecting alternatives, they would not make". Those patterns that have the purpose" or the "substantial effect of obscuring, subverting, or impairing user autonomy, decision-making, or choice" have also been qualified as dark. These definitions are dense: they contain concepts like coercion, nudging, and deception that all alone would deserve an entire work to be discussed

User Requirement Analysis for a Real-Time NLP-Based Open Information Retrieval Meeting Assistant

Meetings are recurrent organizational tasks intended to drive progress in an interdisciplinary and collaborative manner. They are, however, prone to inefficiency due to factors such as differing knowledge among participants. The research goal of this paper is to design a recommendation-based meeting assistant that can improve the efficiency of meetings by helping to contextualize the information being discussed and reduce distractions for listeners. Following a Wizard-of-Oz setup, we gathered user feedback by thematically analyzing focus group discussions and identifying this kind of system’s key challenges and requirements. The findings point to shortcomings in contextualization and raise concerns about distracting listeners from the main content. Based on the findings, we have developed a set of design recommendations that address context, interactivity and personalization issues. These recommendations could be useful for developing a meeting assistant that is tailored to the needs of meeting participants, thereby helping to optimize the meeting experience