Adaptive user interfaces and universal usability through plasticity of user interface design

A review of research on universal usability, plasticity of user interface design and facilitation of interface development with universal usability is presented. The survey was based on 165 research papers spanning over fifty-five years. The foundations of adaptive or intelligent user interfaces (AU...

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Vydáno v:Computer science review Ročník 40; s. 100363
Hlavní autoři: Miraz, Mahdi H., Ali, Maaruf, Excell, Peter S.
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier Inc 01.05.2021
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ISSN:1574-0137, 1876-7745
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Abstract A review of research on universal usability, plasticity of user interface design and facilitation of interface development with universal usability is presented. The survey was based on 165 research papers spanning over fifty-five years. The foundations of adaptive or intelligent user interfaces (AUI or IUI) are presented, three core domains being focused upon: Artificial Intelligence (AI), User Modelling (UM) and Human–Computer Interaction (HCI). For comparison of the various AUIs, a proposed taxonomy is given. One conclusion is that an efficient training vector for fast optimal convergence of the machine-learning algorithm is a necessity, but key to this is the bounding of the dataset, the goal being to achieve an accurate user preference model, which has to be built from a limited number of datasets obtained from the human interaction. More research also needs to be conducted to ascertain the usefulness and effectiveness of IUIs compared against AUIs. With the global mobility of users, interface design must take account of the abilities and cultures of users, derived from actual user behaviour and not on their feedback. A key question is whether the interface should be adaptive under system control or be made adaptable under user control. A need is identified for an “afferential component” that stores a priori information about the end user, an “inferential component” that determines to what extent the user interface actually needs to be adapted, and the “efferential component” that actually determines how the adaptivity is applied seamlessly to the system. Application to e-learning is a priority: the use of machine intelligence to achieve appropriate learnability, ideally enhanced by “Playful interaction”, was found to be desirable. Universal application of adaptation lies in the future, but AUI properties cannot be ascertained while disregarding the other parameters of the system in which it will be used. A more complete understanding of the human mental model is necessary, requiring a highly multidisciplinary approach and cooperation between diverse researchers. Finally, a performance evaluation of plasticity of user interface was conducted: it is concluded that the use of dynamic techniques can enhance the user experience to a much greater extent than more basic approaches, although optimisation of usability parameter trade-offs needs further attention. It is noted that most of the work reviewed originated from a limited range of cultural perspectives. To make an interface simultaneously usable for users from a diverse range of cultural backgrounds will require a very large amount of adaptation, but the powerful principles of plasticity of user interface design hold the future promise of an optimum tool to achieve cross-cultural usability.
AbstractList A review of research on universal usability, plasticity of user interface design and facilitation of interface development with universal usability is presented. The survey was based on 165 research papers spanning over fifty-five years. The foundations of adaptive or intelligent user interfaces (AUI or IUI) are presented, three core domains being focused upon: Artificial Intelligence (AI), User Modelling (UM) and Human–Computer Interaction (HCI). For comparison of the various AUIs, a proposed taxonomy is given. One conclusion is that an efficient training vector for fast optimal convergence of the machine-learning algorithm is a necessity, but key to this is the bounding of the dataset, the goal being to achieve an accurate user preference model, which has to be built from a limited number of datasets obtained from the human interaction. More research also needs to be conducted to ascertain the usefulness and effectiveness of IUIs compared against AUIs. With the global mobility of users, interface design must take account of the abilities and cultures of users, derived from actual user behaviour and not on their feedback. A key question is whether the interface should be adaptive under system control or be made adaptable under user control. A need is identified for an “afferential component” that stores a priori information about the end user, an “inferential component” that determines to what extent the user interface actually needs to be adapted, and the “efferential component” that actually determines how the adaptivity is applied seamlessly to the system. Application to e-learning is a priority: the use of machine intelligence to achieve appropriate learnability, ideally enhanced by “Playful interaction”, was found to be desirable. Universal application of adaptation lies in the future, but AUI properties cannot be ascertained while disregarding the other parameters of the system in which it will be used. A more complete understanding of the human mental model is necessary, requiring a highly multidisciplinary approach and cooperation between diverse researchers. Finally, a performance evaluation of plasticity of user interface was conducted: it is concluded that the use of dynamic techniques can enhance the user experience to a much greater extent than more basic approaches, although optimisation of usability parameter trade-offs needs further attention. It is noted that most of the work reviewed originated from a limited range of cultural perspectives. To make an interface simultaneously usable for users from a diverse range of cultural backgrounds will require a very large amount of adaptation, but the powerful principles of plasticity of user interface design hold the future promise of an optimum tool to achieve cross-cultural usability.
ArticleNumber 100363
Author Excell, Peter S.
Miraz, Mahdi H.
Ali, Maaruf
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  givenname: Mahdi H.
  orcidid: 0000-0002-6795-7048
  surname: Miraz
  fullname: Miraz, Mahdi H.
  email: m.miraz@ieee.org
  organization: School of Electrical and Computer Engineering, Xiamen University Malaysia, Malaysia
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  givenname: Maaruf
  surname: Ali
  fullname: Ali, Maaruf
  organization: Department of Computer Engineering, Epoka University, Rruga Tiranë-Rinas, Km 12, 1032, Vorë, Tiranë, Albania
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  givenname: Peter S.
  surname: Excell
  fullname: Excell, Peter S.
  organization: Faculty of Arts, Science and Technology, Wrexham Glyndŵr University, UK
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Keywords Design for All
Universal usability
Dynamic UI Design
Plasticity
Interaction design
User interface (UI)
Adaptive user interface (AUI)
Inclusive Design
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Snippet A review of research on universal usability, plasticity of user interface design and facilitation of interface development with universal usability is...
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StartPage 100363
SubjectTerms Adaptive user interface (AUI)
Design for All
Dynamic UI Design
Inclusive Design
Interaction design
Plasticity
Universal usability
User interface (UI)
Title Adaptive user interfaces and universal usability through plasticity of user interface design
URI https://dx.doi.org/10.1016/j.cosrev.2021.100363
Volume 40
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