On the role of individual human abilities in the design of adaptive user interfaces for scientific problem solving environments

Zudilova­-Seinstra, Elena

doi:10.1007/s10115-006-0061-3

Cited by 16 publications

(6 citation statements)

References 27 publications

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“…Another approach in the AUI evaluation has been put forward by Paramythis et al [43] that provide a method to separately evaluate each adaptive system constituents through the decomposition of adaptation "from the perspective of HCI-oriented evaluation": adaptation is no longer considered as a singular process. Other approaches concern the adaptive interface evaluation in terms of cost and benefit [44] user's error [45], cognitive workload predictability and accuracy [46], and accessibility [47].…”

Section: Research Backgroundmentioning

confidence: 99%

Prototyping adaptive systems in smart environments using virtual reality

Gullà

Menghi

Papetti

et al. 2018

Int J Interact Des Manuf

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Smart environment is a key challenge for current ICT research: it is one of the solutions that can enhance people's quality of life and enable users with impairment to live independently. Over the years, scientific research has proposed several solutions to help and improve the capabilities of its occupants, but they are often developed for a specific context (e.g. particular disease or impairment). These systems do not adapt to the real needs of users with different profiles, and neglect that the user's requirements may evolve over time. This research work aims to develop a new adaptive smart system able to support users (with and without disabilities) in performing daily tasks by recognizing their preferences and actions and adapting the system feedback consequently. With the aim to develop an easy, efficient and usable adaptive smart system, the final users have been involved in the whole design and development process. The system was validated through a virtual reality system allowing the user interaction evaluation and helping the usability improvement. Keywords Smart environment • Adaptive and adaptable user interface • Virtual reality system • Bayesian network • ICT • User-centered design B Francesca Gullà

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Section: Research Backgroundmentioning

confidence: 99%

Prototyping adaptive systems in smart environments using virtual reality

Gullà

Menghi

Papetti

et al. 2018

Int J Interact Des Manuf

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“…As a result, the UI design of the e-exam should take into account the capability and character of an individual. According to the researches in [27][28][29], and [30], the user features that might affect the UI design can be categorized into physical, cognitive, psychomotor, demographics, or experiences.…”

Section: User Characteristics and Interface Preferencesmentioning

confidence: 99%

A Robust User Authentication Technique in Online Examination

Karim¹,

Kanaker²,

Almasadeh³

et al. 2021

IJC

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User authentication in the online environment is promoting a hugely challenging issue. This has contributed to the realization of a user authentication where the exams can be performed over the Internet at any time and from any place and by using any digital device. Consequently, further investigations are required to focus on improving user authentication methods to enhance online security mechanisms, especially in the field of e-exams. This research proposes a new user authentication technique based on the user interface (UI). The novel idea is created based on the design preferences of candidates who are taking the e-exams. Several design features are used to design a special user interface for e-exams, for example, the font attributes, back colour, number of questions per page, group categories for questions based on difficulties, and timer setting. The introduced technique can be used to support the user authentication process in the e-exams environment. Furthermore, the proposed technique provides the ability to login to the e-exam without the need to remember the login information, but to select what the student prefers according to his/her personal information. Based on the literature review, a primary evaluation claiming that the students have differences in their preferences and that each user has stable design preferences within different sessions is revealed. In regard to these facts, they become the resource and essence of this research. The security performance of the proposed method is evaluated. The results of the experiments show a false positive (FP) rate of 0.416% and a false negative (FN) rate of 0%.

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“…• Virtual learning environment: This includes availability of learning resources and monitoring of the learner's performance. In some environments, the identification of certain characteristics is proposed to customize the environment according to the learner's needs (Zudilova-Seinstra, 2007).…”

Section: Literature Review 21 Learning In Organizationsmentioning

confidence: 99%

An ontology to support the classification of learning material in an organizational learning environment

Valaski

Reinehr

Malucelli

2017

ITSE

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Purpose The purpose of this research was to evaluate whether ontology integrated in an organizational learning environment may support the automatic learning material classification in a specific knowledge area. Design/methodology/approach An ontology for recommending learning material was integrated in the organizational learning environment based on ontology. An experiment was performed with 15 experts and 84 learners. Experts and learners were asked to classify 30 learning material related to Software Engineering area. The results obtained from experts and learners were compared with the ontology results. Findings Among 30 learning materials evaluated, 24 learning materials got closer to the expert classification using the ontology than using the learners’ manual classification. The learners had difficulties in correctly classifying the learning materials according to the knowledge area applied. Originality/value In an autonomous collaborative environment without a tutor responsible for organizing the learning materials shared by collaborators, an ontology may be an auxiliary mechanism to support automatic learning material classification. The proposed ontology uses recommendations given by the collaborators to get the correct knowledge area classification. The correct classification may support retrieval of appropriate learning materials according to the learners’ needs.

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On the role of individual human abilities in the design of adaptive user interfaces for scientific problem solving environments

Cited by 16 publications

References 27 publications

Prototyping adaptive systems in smart environments using virtual reality

Prototyping adaptive systems in smart environments using virtual reality

A Robust User Authentication Technique in Online Examination

An ontology to support the classification of learning material in an organizational learning environment

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