Model-based adaptive user interface based on context and user experience evaluation

2018 ◽  
Vol 12 (1) ◽  
pp. 1-16 ◽  
Author(s):  
Jamil Hussain ◽  
Anees Ul Hassan ◽  
Hafiz Syed Muhammad Bilal ◽  
Rahman Ali ◽  
Muhammad Afzal ◽  
...  
Keyword(s):  
User Interface ◽  
User Experience ◽  
Model Based ◽  
Adaptive User Interface

scholarly journals Model-based intelligent user interface adaptation: challenges and future directions

2021 ◽  
Author(s):  
Silvia Abrahão ◽  
Emilio Insfran ◽  
Arthur Sluÿters ◽  
Jean Vanderdonckt
Keyword(s):  
User Interface ◽  
User Experience ◽  
Relevant Literature ◽  
Machine Learning Techniques ◽  
Future Directions ◽  
Model Based ◽  
Intelligent User Interface ◽  
Learning Techniques ◽  
New Ideas ◽  
Interface Adaptation

AbstractAdapting the user interface of a software system to the requirements of the context of use continues to be a major challenge, particularly when users become more demanding in terms of adaptation quality. A considerable number of methods have, over the past three decades, provided some form of modelling with which to support user interface adaptation. There is, however, a crucial issue as regards in analysing the concepts, the underlying knowledge, and the user experience afforded by these methods as regards comparing their benefits and shortcomings. These methods are so numerous that positioning a new method in the state of the art is challenging. This paper, therefore, defines a conceptual reference framework for intelligent user interface adaptation containing a set of conceptual adaptation properties that are useful for model-based user interface adaptation. The objective of this set of properties is to understand any method, to compare various methods and to generate new ideas for adaptation. We also analyse the opportunities that machine learning techniques could provide for data processing and analysis in this context, and identify some open challenges in order to guarantee an appropriate user experience for end-users. The relevant literature and our experience in research and industrial collaboration have been used as the basis on which to propose future directions in which these challenges can be addressed.

An Adaptive User Interface Model Based on Experience Awareness

2011 ◽  
Vol 34 (11) ◽  
pp. 2211-2223 ◽  
Author(s):  
Yin-Ting FAN ◽  
Dong-Xing TENG ◽  
Hai-Yan YANG ◽  
Cui-Xia MA ◽  
Guo-Zhong DAI ◽  
...  
Keyword(s):  
User Interface ◽  
Interface Model ◽  
Model Based ◽  
Adaptive User Interface

A Model-Based Framework for an Adaptive User Interface in Supervisory Control

2013 ◽  
Vol 46 (15) ◽  
pp. 37-43 ◽  
Author(s):  
D. Evans ◽  
Vignesh A. Arasu ◽  
M. Fendley
Keyword(s):  
User Interface ◽  
Supervisory Control ◽  
Model Based ◽  
Adaptive User Interface

scholarly journals BlindSense: An Accessibility-inclusive Universal User Interface for Blind People

2018 ◽  
Vol 8 (2) ◽  
pp. 2775-2784 ◽  
Author(s):  
A. Khan ◽  
S. Khusro ◽  
I. Alam
Keyword(s):  
User Interface ◽  
Empirical Study ◽  
Assistive Technology ◽  
User Experience ◽  
Blind People ◽  
Interface Model ◽  
Adaptive User Interface

A large number of blind people use smartphone-based assistive technology to perform their common activities. In order to provide a better user experience the existing user interface paradigm needs to be revisited. A new user interface model has been proposed in this paper. A simplified, semantically consistent, and blind-friendly adaptive user interface is provided. The proposed solution is evaluated through an empirical study on 63 blind people leveraging an improved user experience in performing common activities on a smartphone.

Intelligent Systems

2019 ◽  
pp. 131-150
Author(s):  
William B. Rouse
Keyword(s):  
User Interface ◽  
User Experience ◽  
Statistical Models ◽  
Intelligent Systems ◽  
Human Performance ◽  
Human Intelligence ◽  
Symbolic Logic ◽  
Model Based ◽  
Enabling Technologies ◽  
Intelligent Systems Technology

This chapter addresses the ways in which human intelligence in routine and partly routine jobs can be augmented rather than replaced. The design of aids should begin with defining the user experience, proceed to designing the user interface to support this experience, and then focus on the enabling technologies. Intelligent aids should be considered for enhancing human performance; the extent of success will depend on the domain of application and the potential performance of the aid. Intelligent aids are inherently model based, drawing upon symbolic logic, mathematical paradigms, and/or statistical models; understanding the underlying modeling assumptions is key to establishing confidence in and trust of such aids. Intelligent systems technology has much promise but also many perils that warrant attention; its prospects depend on well-reasoned strategies for development and adoption.

scholarly journals A DATA-DRIVEN APPROACH TO USER-EXPERIENCE-FOCUSED MODEL-BASED ROADMAPPING FOR NEW PRODUCT PLANNING

2021 ◽  
Vol 1 ◽  
pp. 61-70
Author(s):  
Ilia Iuskevich ◽  
Andreas-Makoto Hein ◽  
Kahina Amokrane-Ferka ◽  
Abdelkrim Doufene ◽  
Marija Jankovic
Keyword(s):  
New Product Development ◽  
User Experience ◽  
Planning Process ◽  
New Product ◽  
Data Driven ◽  
User Needs ◽  
User Testing ◽  
Model Based ◽  
Data Driven Approach ◽  
To Receive

AbstractUser experience (UX) focused business needs to survive and plan its new product development (NPD) activities in a highly turbulent environment. The latter is a function of volatile UX and technology trends, competition, unpredictable events, and user needs uncertainty. To address this problem, the concept of design roadmapping has been proposed in the literature. It was argued that tools built on the idea of design roadmapping have to be very flexible and data-driven (i.e., be able to receive feedback from users in an iterative manner). At the same time, a model-based approach to roadmapping has emerged, promising to achieve such flexibility. In this work, we propose to incorporate design roadmapping to model-based roadmapping and integrate it with various user testing approaches into a single tool to support a flexible data-driven NPD planning process.

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