User-Centered Design (IX): A "User Experience 3.0" Paradigm Framework in
  the Intelligence Era
        - URL: http://arxiv.org/abs/2302.06681v6
 - Date: Fri, 24 Mar 2023 03:52:50 GMT
 - Title: User-Centered Design (IX): A "User Experience 3.0" Paradigm Framework in
  the Intelligence Era
 - Authors: Wei Xu
 - Abstract summary: This paper proposes a "UX 3.0" paradigm framework and the corresponding UX methodology system in the intelligence era.
The "UX 3.0" paradigm includes five categories of UX methods: ecological experience, innovation-enabled experience, AI-enabled experience, human-AI interaction-based experience, and human-AI collaboration-based experience.
The proposal of the "UX 3.0" paradigm helps improve the existing UX methods and provides methodological support for the research and applications of UX in developing intelligent systems.
 - Score: 11.297065069875625
 - License: http://creativecommons.org/licenses/by/4.0/
 - Abstract:   The field of user experience (UX) based on the design philosophy of
"user-centered design" is moving towards the intelligence era. Still, the
existing UX paradigm mainly aims at non-intelligent systems and lacks a
systematic approach to UX for intelligent systems. Throughout the development
of UX, the UX paradigm shows the evolution characteristics of the
cross-technology era. At present, the intelligence era has put forward new
demands on the UX paradigm. For this reason, this paper proposes a "UX 3.0"
paradigm framework and the corresponding UX methodology system in the
intelligence era. The "UX 3.0" paradigm framework includes five categories of
UX methods: ecological experience, innovation-enabled experience, AI-enabled
experience, human-AI interaction-based experience, and human-AI
collaboration-based experience methods, each providing corresponding multiple
UX paradigmatic orientations. The proposal of the "UX 3.0" paradigm helps
improve the existing UX methods and provides methodological support for the
research and applications of UX in developing intelligent systems. Finally,
this paper looks forward to future research and applications of the "UX 3.0"
paradigm.
 
       
      
        Related papers
        - User Experience Estimation in Human-Robot Interaction Via Multi-Instance   Learning of Multimodal Social Signals [2.7138092972120766]
This study proposes a UX estimation method for human-robot interaction (HRI) by leveraging multimodal social signals.<n>Unlike conventional models that rely on momentary observations, our approach captures both short- and long-term interaction patterns.<n> Experimental results demonstrate that our method outperforms third-party human evaluators in UX estimation.
arXiv  Detail & Related papers  (2025-07-31T13:34:15Z) - Do MLLMs Capture How Interfaces Guide User Behavior? A Benchmark for   Multimodal UI/UX Design Understanding [45.81445929920235]
We introduce WiserUI-Bench, a novel benchmark for assessing models' multimodal understanding of UI/UX design.<n>It includes 300 diverse real-world UI image pairs, each consisting of two design variants A/B-tested at scale by actual companies.<n>Our benchmark supports two core tasks: (1) selecting the more effective UI/UX design by predicting the A/B test verified winner and (2) assessing how well a model, given the winner, can explain its effectiveness in alignment with expert reasoning.
arXiv  Detail & Related papers  (2025-05-08T08:00:32Z) - Integrating UX Design in Astronomical Software Development: A Case Study [0.0]
In 2023, ASTRON took the step of incorporating a dedicated User Experience (UX) designer into its software development process.
This decision aimed to enhance the accessibility and usability of services providing access to the data holdings from the telescopes we are developing.
We discuss how we integrate the UX designer at the start of our software development lifecycle.
arXiv  Detail & Related papers  (2025-03-11T18:00:00Z) - XEQ Scale for Evaluating XAI Experience Quality Grounded in Psychometric   Theory [0.7576000093755312]
Explainable Artificial Intelligence (XAI) aims to improve the transparency of autonomous decision-making through explanations.
Recent literature has emphasised users' need for holistic "multi-shot" explanations and the ability to personalise their engagement with XAI systems.
We introduce the XAI Experience Quality (XEQ) Scale, for evaluating the user-centred quality of XAI experiences.
arXiv  Detail & Related papers  (2024-07-15T12:25:49Z) - Generating User Experience Based on Personas with AI Assistants [0.0]
My research introduces a novel approach of combining Large Language Models and personas.
The research is structured around three areas: (1) a critical review of existing adaptive UX practices and the potential for their automation; (2) an investigation into the role and effectiveness of personas in enhancing UX adaptability; and (3) the proposal of a theoretical framework that leverages LLM capabilities to create more dynamic and responsive UX designs and guidelines.
arXiv  Detail & Related papers  (2024-05-02T07:03:16Z) - How Human-Centered Explainable AI Interface Are Designed and Evaluated:   A Systematic Survey [48.97104365617498]
The emerging area of em Explainable Interfaces (EIs) focuses on the user interface and user experience design aspects of XAI.
This paper presents a systematic survey of 53 publications to identify current trends in human-XAI interaction and promising directions for EI design and development.
arXiv  Detail & Related papers  (2024-03-21T15:44:56Z) - Systematic Mapping Protocol -- UX Design role in software development
  process [55.2480439325792]
We present a systematic mapping protocol for investigating the role of the UX designer in the software development process.
We define the research questions, scope, sources, search strategy, selection criteria, data extraction, and analysis methods that we will use to conduct the mapping study.
arXiv  Detail & Related papers  (2024-02-20T16:56:46Z) - Toward 6G Native-AI Network: Foundation Model based Cloud-Edge-End   Collaboration Framework [55.73948386625618]
We analyze the challenges of achieving 6G native AI from perspectives of data, AI models, and operational paradigm.
We propose a 6G native AI framework based on foundation models, provide an integration method for the expert knowledge, present the customization for two kinds of PFM, and outline a novel operational paradigm for the native AI framework.
arXiv  Detail & Related papers  (2023-10-26T15:19:40Z) - Generative User-Experience Research for Developing Domain-specific   Natural Language Processing Applications [4.139846693958609]
This paper proposes a new methodology for integrating generative UX research into developing domain NLP applications.
Generative UX research employs domain users at the initial stages of prototype development, i.e., ideation and concept evaluation, and the last stage for evaluating system usefulness and user utility.
arXiv  Detail & Related papers  (2023-06-28T12:17:45Z) - Towards Human Cognition Level-based Experiment Design for Counterfactual
  Explanations (XAI) [68.8204255655161]
The emphasis of XAI research appears to have turned to a more pragmatic explanation approach for better understanding.
An extensive area where cognitive science research may substantially influence XAI advancements is evaluating user knowledge and feedback.
We propose a framework to experiment with generating and evaluating the explanations on the grounds of different cognitive levels of understanding.
arXiv  Detail & Related papers  (2022-10-31T19:20:22Z) - Connecting Algorithmic Research and Usage Contexts: A Perspective of
  Contextualized Evaluation for Explainable AI [65.44737844681256]
A lack of consensus on how to evaluate explainable AI (XAI) hinders the advancement of the field.
We argue that one way to close the gap is to develop evaluation methods that account for different user requirements.
arXiv  Detail & Related papers  (2022-06-22T05:17:33Z) - A User-Centred Framework for Explainable Artificial Intelligence in
  Human-Robot Interaction [70.11080854486953]
We propose a user-centred framework for XAI that focuses on its social-interactive aspect.
The framework aims to provide a structure for interactive XAI solutions thought for non-expert users.
arXiv  Detail & Related papers  (2021-09-27T09:56:23Z) - FaceX-Zoo: A PyTorch Toolbox for Face Recognition [62.038018324643325]
We introduce a novel open-source framework, named FaceX-Zoo, which is oriented to the research-development community of face recognition.
FaceX-Zoo provides a training module with various supervisory heads and backbones towards state-of-the-art face recognition.
A simple yet fully functional face SDK is provided for the validation and primary application of the trained models.
arXiv  Detail & Related papers  (2021-01-12T11:06:50Z) - Seq2Seq and Joint Learning Based Unix Command Line Prediction System [13.416277446363775]
UNIX based platforms have not been able to garner an overwhelming reception from amateur end users.
One of the rationales for under popularity of UNIX based systems is the steep learning curve corresponding to them.
This work describes an assistive, adaptive and dynamic way of enhancing UNIX command line prediction systems.
arXiv  Detail & Related papers  (2020-06-20T11:57:01Z) 
        This list is automatically generated from the titles and abstracts of the papers in this site.
       
     
           This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.