The technical enablers for mobile augmented reality (MAR) are becoming robust enough to allow the development of MAR services that are truly valuable for consumers. Such services would provide a ...novel interface to the ubiquitous digital information in the physical world, hence serving in great variety of contexts and everyday human activities. To ensure the acceptance and success of future MAR services, their development should be based on knowledge about potential end users’ expectations and requirements. We conducted 16 semi-structured interview sessions with 28 participants in shopping centres, which can be considered as a fruitful context for MAR services. We aimed to elicit new knowledge about (1) the characteristics of the expected user experience and (2) central user requirements related to MAR in such a context. From a pragmatic viewpoint, the participants expected MAR services to catalyse their sense of efficiency, empower them with novel context-sensitive and proactive functionalities and raise their awareness of the information related to their surroundings with an intuitive interface. Emotionally, MAR services were expected to offer stimulating and pleasant experiences, such as playfulness, inspiration, liveliness, collectivity and surprise. The user experience categories and user requirements that were identified can serve as targets for the design of user experience of future MAR services.
Graphical User Interface (GUI) provides a visual bridge between a software application and end users, through which they can interact with each other. With the upgrading of mobile devices and the ...development of aesthetics, the visual effects of the GUI are more and more attracting, and users pay more attention to the accessibility and usability of applications. However, such GUI complexity posts a great challenge to the GUI implementation. According to our pilot study of crowdtesting bug reports, display issues such as text overlap, component occlusion, missing image always occur during GUI rendering on different devices due to the software or hardware compatibility. They negatively influence the app usability, resulting in poor user experience. To detect these issues, we propose a fully automated approach, Nighthawk , based on deep learning for modelling visual information of the GUI screenshot. Nighthawk can detect GUIs with display issues and also locate the detailed region of the issue in the given GUI for guiding developers to fix the bug. At the same time, training the model needs a large amount of labeled buggy screenshots, which requires considerable manual effort to prepare them. We therefore propose a heuristic-based training data auto-generation method to automatically generate the labeled training data. The evaluation demonstrates that our Nighthawk can achieve average 0.84 precision and 0.84 recall in detecting UI display issues, average 0.59 AP and 0.60 AR in localizing these issues. We also evaluate Nighthawk with popular Android apps on Google Play and F-Droid, and successfully uncover 151 previously-undetected UI display issues with 75 of them being confirmed or fixed so far.
This study presents a new machine learning (support vector machine (SVM))-based cooperative spectrum sensing (CSS) model, which utilises the methods of user grouping, to reduce cooperation overhead ...and effectively improve detection performance. Cognitive radio users were properly grouped before the cooperative sensing process using energy data samples and an SVM model. The resulting user group which participates in cooperative sensing procedures is safe, less redundant, or the optimised user group. Three grouping algorithms are presented in this study. The first grouping algorithm divides normal and abnormal users (malicious and severely fading users) into two groups. The second grouping algorithm distinguishes redundant and non-redundant users. The third grouping algorithm establishes an optimisation model with the objective of minimising average correlation within subsets. All users are then divided into a specific number of optimised groups, only one of which is required for cooperative sensing in each time. The performances of the three algorithms were quantified in terms of the average training time, classification speed and classification accuracy. Experimental results showed the proposed algorithms achieved their intended function and outperformed a conventional machine learning-based CSS model (proposed by Karaputugala et al.) in terms of security, energy consumption, and sensing efficiency.
Most programs today are written not by professional software developers, but by people with expertise in other domains working towards goals for which they need computational support. For example, a ...teacher might write a grading spreadsheet to save time grading, or an interaction designer might use an interface builder to test some user interface design ideas. Although these end-user programmers may not have the same goals as professional developers, they do face many of the same software engineering challenges, including understanding their requirements, as well as making decisions about design, reuse, integration, testing, and debugging. This article summarizes and classifies research on these activities, defining the area of End-User Software Engineering (EUSE) and related terminology. The article then discusses empirical research about end-user software engineering activities and the technologies designed to support them. The article also addresses several crosscutting issues in the design of EUSE tools, including the roles of risk, reward, and domain complexity, and self-efficacy in the design of EUSE tools and the potential of educating users about software engineering principles.
Organizational use of information and communications technologies (ICT) is increasingly resulting in negative cognitions in individuals, such as information overload and interruptions. Recent ...literature has encapsulated these cognitions in the concept of technostress, which is stress caused by an inability to cope with the demands of organizational computer usage. Given the critical role of the user in organizational information processing and accomplishing application-enabled workflows, understanding how these cognitions affect users' satisfaction with ICT and their performance in ICT-mediated tasks is an important step in appropriating benefits from current computing environments. The objective of this paper is to (1) understand the negative effects of technostress on the extent to which end users perceive the applications they use to be satisfactory and can utilize them to improve their performance at work and (2) identify mechanisms that can mitigate these effects. Specifically, we draw from the end-user computing and technostress literature to develop and validate a model that analyzes the effects of factors that create technostress on the individual's satisfaction with, and task performance using, ICT. The model also examines how user involvement in ICT development and support mechanisms for innovation can be used to weaken technostress-creating factors and their outcomes. The results, based on survey data analysis from 233 ICT users from two organizations, show that factors that create technostress reduce the satisfaction of individuals with the ICT they use and the extent to which they can utilize ICT for productivity and innovation in their tasks. Mechanisms that facilitate involvement of users, and encourage them to take risks, learn, explore new ideas, and experiment in the context of ICT use, diminish the factors that create technostress and increase satisfaction with the ICT they use. These mechanisms also have a positive effect on users' appropriation of ICT for productivity and innovation in their tasks. The paper contributes to emerging literature on negative outcomes of ICT use by (1) highlighting the influence of technostress on users' satisfaction and performance (i.e., productivity and innovation in ICT-mediated tasks) with ICT, (2) extending the literature on technostress, which has so far looked largely at the general behavioral and psychological domains, to include the domain of end-user computing, and (3) demonstrating the importance of user involvement and innovation support mechanisms in reducing technostress-creating conditions and their ICT use-related outcomes.
City dashboard websites are a common modality for bringing open-government philosophies into the public domain. Yet, there has been little research concerning the optimum design for city dashboards ...that takes account of users' expectations and skills. Indeed, there has been minimal exploration of user-centered design (UCD) to improve the usability and utility of smart city technologies in general. This study sought to conduct a user evaluation analysis to inform a UCD approach to city dashboards. Interviews with different types of users were conducted that applied a protocol analysis to gain insight into user perspectives and experiences of city dashboards. Along with critical incident technique procedures, interaction data of critical significance to the user was collected and a content analysis was conducted. These qualitative data were used to determine representations of users, as identified through observed behaviors, attitudes, needs, and goals. Targeted-scope user experience personas for the design process were then constructed to represent and build empathy towards three potential users of city dashboard systems: novices, end-users, and advanced users. The collected user requirements and the personas formulated are underpinning the re-design of an existing city dashboard.
Obesity is a chronic condition that influences the quality of life of patients and families while increasing the economic burden for the world population. Multidisciplinary prevention programs are ...crucial to address it, allowing an early introduction of healthy behaviors into daily habits. Mobile health interventions provide adequate support for these programs, especially considering the gamification techniques used to promote users' engagement. TeenPower is a multidisciplinary mHealth intervention program conducted in Portugal during 2018 to empower adolescents, promoting healthy behaviors while preventing obesity. An agile software development process was applied to the development of the digital platform that holds a web-based application and a mobile application. We also propose a model for future developments based on the user-centered design approach adopted for this development and the assessment conducted in each phase. The user-centered design approach model proposed has three distinct phases: (1) design study; (2) pre-production usability tests; and (3) post-production data. Phase 1 allowed us to obtain the high-fidelity version of the graphical user interfaces (
= 5). Phase 2 showed a task completion success rate of 100% (
= 5). Phase 3 was derived from statistical analysis of the usage of the platform by real end users (
= 90). We achieved an average retention rate of 35% (31 out of 90 participants). Each technique has provided input for the continuous design and improvement of the platform. This allowed the creation of a tailored platform that could meet users' expectations. Nevertheless, the retention rate decreased significantly over a short period of time, revealing the need for further work in the improvement of the gamification experience.
Dramatic success in machine learning has led to a new wave of AI applications (for example, transportation, security, medicine, finance, defense) that offer tremendous benefits but cannot explain ...their decisions and actions to human users. DARPA's explainable artificial intelligence (XAI) program endeavors to create AI systems whose learned models and decisions can be understood and appropriately trusted by end users. Realizing this goal requires methods for learning more explainable models, designing effective explanation interfaces, and understanding the psychologic requirements for effective explanations. The XAI developer teams are addressing the first two challenges by creating ML techniques and developing principles, strategies, and human‐computer interaction techniques for generating effective explanations. Another XAI team is addressing the third challenge by summarizing, extending, and applying psychologic theories of explanation to help the XAI evaluator define a suitable evaluation framework, which the developer teams will use to test their systems. The XAI teams completed the first of this 4‐year program in May 2018. In a series of ongoing evaluations, the developer teams are assessing how well their XAM systems' explanations improve user understanding, user trust, and user task performance.
User comments allow 'annotative reporting' by embedding users' viewpoints within an article's context, providing readers with additional information to form opinions, which can potentially enhance ...deliberative processes. But are these the only reasons why people comment on online news and read these comments? This study examines factors that motivate, or demotivate and constrict, such participation by surveying nearly 650 commenters, lurkers, and non-users in Germany. From a normative perspective, the results are ambivalent. The results show that commenters are driven by social-interactive motives to participate in journalism, and to discuss with other users. However, the data suggest that commenters do not obtain cognitive gratifications to the desired extent. Presumably, their exchange is socially and not deliberatively motivated. Reading comments is fuelled by both cognitive and entertainment motives, but regression analyses show that the entertainment dimension − a dimension that is not usually considered to be linked to deliberation processes − is the more stable one. A low standard of discussions not only increases the frequency at which comments are read, but also reduces lurkers' satisfaction. Similarly, non-users are even more frustrated by the low quality of discussions. They consider such participation activities to be a waste of time, and are not willing to register.
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