Usability Testing: A Practitioner's Guide to Evaluating the User Experience

Hertzum, Morten

doi:10.2200/s00987ed1v01y202001hci045

Cited by 34 publications

(31 citation statements)

References 154 publications

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“…In [27] the Mobile Application Usability Evaluation Metrics (MAUEM) model is proposed, this model extends the PACMAD by adding two new attributes, interruptability and simplicity, and it indicates the different metrics to measure the considered attributes. In [49], the authors, unlike the models seen so far, present six different aspects of usability; this suggests that approaching usability from multiple points of view can lead to a better understanding. The six proposed aspects are: Universal usability, which embraces the challenge of making products universally usable, despite the different abilities, backgrounds, styles and technological environments of the users; situational usability, which considers that users do not experience products in isolation but contextualizes them in different situations of use and consequently usability must be related to specific situations related to users, tasks and contexts of use; perceived usability, user-centered aspect, concerns the user's subjective experience making him the final arbiter of usability; hedonic usability, is focused exclusively on pleasure and emotions and the joy of using a product rather than its ease of use; organizational usability is associated with groups of people who collaborate in an organizational context; cultural usability refers to the kind of usability and is defined as the extent to which a computer system, especially in contexts of intercultural use, adapts itself to the cultural background of its users in such a way as to support their activities in an efficient and enjoyable way.…”

Section: Usabilitymentioning

confidence: 97%

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CoKnowEMe: An Edge Evaluation Scheme for QoS of IoMT Microservices in 6G Scenario

et al. 2021

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The forthcoming 6G will attempt to rewrite the communication networks’ perspective focusing on a shift in paradigm in the way technologies and services are conceived, integrated and used. In this viewpoint, the Internet of Medical Things (IoMT) represents a merger of medical devices and health applications that are connected through networks, introducing an important change in managing the disease, treatments and diagnosis, reducing costs and faults. In 6G, the edge intelligence moves the innovative abilities from the central cloud to the edge and jointly with the complex systems approach will enable the development of a new category of lightweight applications as microservices. It requires edge intelligence also for the service evaluation in order to introduce the same degree of adaptability. We propose a new evaluation model, called CoKnowEMe (context knowledge evaluation model), by introducing an architectural and analytical scheme, modeled following a complex and dynamical approach, consisting of three inter-operable level and different networked attributes, to quantify the quality of IoMT microservices depending on a changeable context of use. We conduct simulations to display and quantify the structural complex properties and performance statistical estimators. We select and classify suitable attributes through a further detailed procedure in a supplementary information document.

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Section: Usabilitymentioning

confidence: 97%

“…ISO 9241-11:2018 [61], Nielsen [56,57], QUIM [35], PACMAD [26,47], GQM [48], MAUEM [27], Mortem Hertzum [49].…”

Section: Concept Evaluation Model and Toolmentioning

confidence: 99%

CoKnowEMe: An Edge Evaluation Scheme for QoS of IoMT Microservices in 6G Scenario

et al. 2021

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“…The test participants were members of the farmer group consist of 30 people. Usability testing is one of the best methods to systematically evaluate interfaces representative of end users, where participants are asked to perform tasks on the prototype of the Mobile-Based Land Monitoring Visualization Application [54], [55]. Usability testing is carried out as part of the UCD goal, called user preferences and needs.…”

Section: Usability and User Experience Evaluationmentioning

confidence: 99%

User Experience Design on Visualization of Mobile-Based Land Monitoring System Using a User-Centered Design Approach

Setiyawati

Purnomo

Mailoa

2022

Int. J. Interact. Mob. Technol.

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The use of information and communication technology could increase the quantity and quality of agricultural production, including horticulture. This study focuses on the development of a mobile-based interface that makes it easier for farmers to view the data obtained from the results of land monitoring. In designing mobile devices, applications, and user interfaces, it is important to consider the user experience. This paper focuses on UX design which is which is based on User-Centered Design approach that focuses on user needs and prioritizes empathy for users, so as to accommodate the identification of user needs and produce high fidelity pro-totypes. Based on the System Usability Scale and the User Experience Questionnaire testing on the prototype, it was found that the level of acceptance of horticultural farmers was positive with the level of the value of all UX elements above the average

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“…Usability is a key characteristic of every product offering tangible advantages such as faster acceptability, saving of costs and user satisfaction. Although the basic principles remain the same, each application domain needs to be analysed in detail in order to promote enhanced usability and design dedicated usability testing [61]. A recent study [43] stressed the unmet need to consider human factors and employ user-centred design to achieve maximal usability, accelerate AI adoption and achieve the desired paradigm shift based on Radiology AI solutions.…”

Section: Usability -For Effective and Beneficial Ai In Medical Imagingmentioning

confidence: 99%

FUTURE-AI: Guiding Principles and Consensus Recommendations for Trustworthy Artificial Intelligence in Medical Imaging

Lekadir,

Osuala,

Gallin

et al. 2021

Preprint

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The recent advancements in artificial intelligence (AI) combined with the extensive amount of data generated by today's clinical systems, has led to the development of imaging AI solutions across the whole value chain of medical imaging, including image reconstruction, medical image segmentation, image-based diagnosis and treatment planning. Notwithstanding the successes and future potential of AI in medical imaging, many stakeholders are concerned of the potential risks and ethical implications of imaging AI solutions, which are perceived as complex, opaque, and difficult to comprehend, utilise, and trust in critical clinical applications. Despite these concerns and risks, there are currently no concrete guidelines and best practices for guiding future AI developments in medical imaging towards increased trust, safety and adoption. To bridge this gap, this paper introduces a careful selection of guiding principles drawn from the accumulated experiences, consensus, and best practices from five large European projects on AI in Health Imaging. These guiding principles are named FUTURE-AI and its building blocks consist of (i) Fairness, (ii) Universality, (iii) Traceability, (iv) Usability, (v) Robustness and (vi) Explainability. In a step-by-step approach, these guidelines are further translated into a framework of concrete recommendations for specifying, developing, evaluating, and deploying technically, clinically and ethically trustworthy AI solutions into clinical practice.

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Usability Testing: A Practitioner's Guide to Evaluating the User Experience

Cited by 34 publications

References 154 publications

CoKnowEMe: An Edge Evaluation Scheme for QoS of IoMT Microservices in 6G Scenario

CoKnowEMe: An Edge Evaluation Scheme for QoS of IoMT Microservices in 6G Scenario

User Experience Design on Visualization of Mobile-Based Land Monitoring System Using a User-Centered Design Approach

FUTURE-AI: Guiding Principles and Consensus Recommendations for Trustworthy Artificial Intelligence in Medical Imaging

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