Investigating the Combination of Adaptive UIs and Adaptable UIs for Improving Usability and User Performance of Complex UIs

Zhang, Le; Qu, Qing-Xing; Chao, Wen-Yu; Duffy, Vincent G.

doi:10.1080/10447318.2019.1606975

Cited by 11 publications

(4 citation statements)

References 43 publications

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“…The symbiotic relationship between UX and UI ensures that products meet users' functional demands and expectations and provide comprehensive, intuitive, and satisfying experiences [11][12][13][14]. This approach is supported by several studies [11,12,15,16] that demonstrate the direct correlation between the success of an application, specific aspects of UX/UI, and metrics such as user retention, speed of learning, ease of use, conversion rate, user satisfaction, accessibility, performance and load time, as well as direct user feedback, and highlight the importance of practical design and constant monitoring through metrics to ensure continued user adoption and satisfaction [17,18].…”

Section: Introductionmentioning

confidence: 89%

“…It is essential to note that, depending on the nature of the application to be evaluated, different usability measurement attributes are considered relevant; in this case, special attention will be paid to the mobile application environment, as shown in Table 1. The importance of this distinction lies in recognizing that, although certain aspects can be objectively quantified, the interpretation of the results may have subjective nuances, thus underlining the relevance of considering both factors in usability evaluations [15,29].…”

Section: Theorical Contextmentioning

confidence: 99%

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Improving Usability in Mobile Apps for Residential Energy Management: A Hybrid Approach Using Fuzzy Logic

Nuñez,

Cano,

Cruz

et al. 2024

Applied Sciences

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This paper presents a study that evaluates the usability and user experience of a mobile application interface for residential energy management, adopting a hybrid approach that integrates quantitative and qualitative methods within a user-centered design framework. For the evaluation, metrics and tools such as the User Experience Questionnaire Short (UEQ-S) and the System Usability Scale (SUS) were used, in addition to the implementation of a fuzzy logic model to interpret and contrast the data obtained through these metrics, allowing a more accurate assessment of usability and user experience, reflecting the variability and trends in the responses. Three aspects evaluated stand out: satisfaction with the interface, ease of use, and efficiency. These are fundamental to understanding how users perceive the system. The results indicate a high likelihood of user recommendation of the system and a high overall quality of user experience. This study significantly contributes to mobile application usability, especially in residential energy management, offering valuable insights for designing more intuitive and effective user interfaces on mobile devices.

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Section: Introductionmentioning

confidence: 89%

Section: Theorical Contextmentioning

confidence: 99%

Improving Usability in Mobile Apps for Residential Energy Management: A Hybrid Approach Using Fuzzy Logic

Nuñez,

Cano,

Cruz

et al. 2024

Applied Sciences

View full text Add to dashboard Cite

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“…However, multimodal interactions can introduce complexity and increase the learning curve for users. To mitigate these challenges, we recommend implementing intelligent, context-aware transitions between interaction modalities that seamlessly accommodate users' current tasks and facilitate fluid interaction and analysis of situated visualizations [131]. Moreover, when implementing transition methods, maintaining consistency from activating the visualization to performing analytical operations is crucial for a cohesive user experience.…”

Section: Flexibility and Complexity Of Multimodal Interleavedmentioning

confidence: 99%

Make Interaction Situated: Designing User Acceptable Interaction for Situated Visualization in Public Environments

Zhu,

Wang,

Zeng

et al. 2024

Proceedings of the CHI Conference on Human Factors in Computing Systems

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Situated visualization blends data into the real world to fulfill individuals' contextual information needs. However, interacting with situated visualization in public environments faces challenges posed by users' acceptance and contextual constraints. To explore appropriate interaction design, we first conduct a formative study to identify users' needs for data and interaction. Informed by the findings, we summarize appropriate interaction modalities with eye-based, hand-based and spatially-aware object interaction for situated visualization in public environments. Then, through an iterative design process with six users, we explore and implement interactive techniques for activating and analyzing with situated visualization. To assess the effectiveness and acceptance of these interactions, we integrate them into an AR prototype and conduct a within-subjects study in public scenarios using conventional hand-only interactions as the baseline. The results show that participants preferred our prototype over the baseline, attributing their preference to the interactions being more acceptable, flexible, and practical in public. CCS CONCEPTS• Human-centered computing → Visualization techniques.

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“…Additionally, Mourtzis and Vlachou [13] presented an adaptive Cyber Physical System (CPS) to improve factory performance by assisting operators in decision-making through adaptive scheduling. Finally, AUIs were found to facilitate users in complex tasks in Zhang et al [26]. Several of these approaches are modelbased and do not consider in particular user interactions.…”

Section: Introductionmentioning

confidence: 99%

Exploring the transformation of user interactions to Adaptive Human-Machine Interfaces

Carrera-Rivera,

Reguera-Bakhache,

Larrinaga

et al. 2023

XXIII International Conference on Human Computer Interaction

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Human-machine interfaces (HMI) facilitate communication between humans and machines, and their importance has increased in modern technology. However, traditional HMIs are often static and do not adapt to individual user preferences or behavior. Adaptive User Interfaces (AUIs) have become increasingly important in providing personalized user experiences. Machine learning techniques have gained traction in User Experience (UX) research to provide smart adaptations that can reduce user cognitive load. This paper presents an ongoing exploration of a method for generating adaptive user interfaces by analyzing user interactions and contextual data. It also provides an illustrative example using Markov chains to predict the next step for users interacting with an app for an industrial mixing machine. Furthermore, the paper conducts an offline evaluation of the approach, focusing on the precision of the recommendations. The study emphasizes the importance of incorporating user interactions and contextual data into the design of adaptive HMIs, while acknowledging the existing challenges and potential benefits.

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Investigating the Combination of Adaptive UIs and Adaptable UIs for Improving Usability and User Performance of Complex UIs

Cited by 11 publications

References 43 publications

Improving Usability in Mobile Apps for Residential Energy Management: A Hybrid Approach Using Fuzzy Logic

Improving Usability in Mobile Apps for Residential Energy Management: A Hybrid Approach Using Fuzzy Logic

Make Interaction Situated: Designing User Acceptable Interaction for Situated Visualization in Public Environments

Exploring the transformation of user interactions to Adaptive Human-Machine Interfaces

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