User technology has an agreeable impact on consumer decisions; yet the way such impact takes place may be little known. This study attempts to examine the impact of augmented reality (AR) on retail ...user experience (UX) and its subsequent influence on user satisfaction and user's willingness to buy. Five hypotheses are tested using a lab experiment. The results show that AR significantly shapes UX, by impinging on various characteristics of product quality, and that UX subsequently influences user satisfaction and user's willingness to buy. UX is captured as a third-order formative construct derived from four user experience characteristics: pragmatic quality, aesthetic quality, hedonic quality by stimulation and hedonic quality by identification. Except for the latter, these characteristics are second-order constructs. Important implications for researchers and managers follow.
A recommender system is a Web technology that proactively suggests items of interest to users based on their objective behavior or explicitly stated preferences. Evaluations of recommender systems ...(RS) have traditionally focused on the performance of algorithms. However, many researchers have recently started investigating system effectiveness and evaluation criteria from users’ perspectives. In this paper, we survey the state of the art of user experience research in RS by examining how researchers have evaluated design methods that augment RS’s ability to help users find the information or product that they truly prefer, interact with ease with the system, and form trust with RS through system transparency, control and privacy preserving mechanisms finally, we examine how these system design features influence users’ adoption of the technology. We summarize existing work concerning three crucial interaction activities between the user and the system: the initial preference elicitation process, the preference refinement process, and the presentation of the system’s recommendation results. Additionally, we will also cover recent evaluation frameworks that measure a recommender system’s overall perceptive qualities and how these qualities influence users’ behavioral intentions. The key results are summarized in a set of design guidelines that can provide useful suggestions to scholars and practitioners concerning the design and development of effective recommender systems. The survey also lays groundwork for researchers to pursue future topics that have not been covered by existing methods.
We present a novel visual exploration method based on small multiples and large singles for effective and efficient data analysis. Users are enabled to explore the state space by offering multiple ...alternatives from the current state. Users can then select the alternative of choice and continue the analysis. Furthermore, the intermediate steps in the exploration process are preserved and can be revisited and adapted using an intuitive navigation mechanism based on the well‐known undo‐redo stack and filmstrip metaphor. As proof of concept the exploration method is implemented in a prototype. The effectiveness of the exploration method is tested using a formal user study comparing four different interaction methods. By using Small Multiples as data exploration method users need fewer steps in answering questions and also explore a significantly larger part of the state space in the same amount of time, providing them with a broader perspective on the data, hence lowering the chance of missing important features. Also, users prefer visual exploration with small multiples over non‐small multiple variants.
We present ManuKnowVis, the result of a design study, in which we contextualize data from multiple knowledge repositories of a manufacturing process for battery modules used in electric vehicles. In ...data-driven analyses of manufacturing data, we observed a discrepancy between two stakeholder groups involved in serial manufacturing processes: Knowledge providers (e.g., engineers) have domain knowledge about the manufacturing process but have difficulties in implementing data-driven analyses. Knowledge consumers (e.g., data scientists) have no first-hand domain knowledge but are highly skilled in performing data-driven analyses. ManuKnowVis bridges the gap between providers and consumers and enables the creation and completion of manufacturing knowledge. We contribute a multi-stakeholder design study, where we developed ManuKnowVis in three main iterations with consumers and providers from an automotive company. The iterative development led us to a multiple linked view tool, in which, on the one hand, providers can describe and connect individual entities (e.g., stations or produced parts) of the manufacturing process based on their domain knowledge. On the other hand, consumers can leverage this enhanced data to better understand complex domain problems, thus, performing data analyses more efficiently. As such, our approach directly impacts the success of data-driven analyses from manufacturing data. To demonstrate the usefulness of our approach, we carried out a case study with seven domain experts, which demonstrates how providers can externalize their knowledge and consumers can implement data-driven analyses more efficiently.
Abstract The aim of this paper is to review some work conducted in the field of user testing that aims at specifying or clarifying the test procedures and at defining and developing tools to help ...conduct user tests. The topics that have been selected were considered relevant for evaluating applications in the field of medical and health care informatics. These topics are: the number of participants that should take part in a user test, the test procedure, remote usability evaluation, usability testing tools, and evaluating mobile applications.
The graphical user interface (GUI) has become the prime means for interacting with computing systems. It leverages human perceptual and motor capabilities for elementary tasks such as command ...exploration and invocation, information search, and multitasking. For designing a GUI, numerous interconnected decisions must be made such that the outcome strikes a balance between human factors and technical objectives. Normally, design choices are specified manually and coded within the software by professional designers and developers. This article surveys combinatorial optimization as a flexible and powerful tool for computational generation and adaptation of GUIs. As recently as 15 years ago, applications were limited to keyboards and widget layouts. The obstacle has been the mathematical definition of design tasks, on the one hand, and the lack of objective functions that capture essential aspects of human behavior, on the other. This article presents definitions of layout design problems as integer programming tasks, a coherent formalism that permits identification of problem types, analysis of their complexity, and exploitation of known algorithmic solutions. It then surveys advances in formulating evaluative functions for common design-goal foci such as user performance and experience. The convergence of these two advances has expanded the range of solvable problems. Approaches to practical deployment are outlined with a wide spectrum of applications. This article concludes by discussing the position of this application area within optimization and human-computer interaction research and outlines challenges for future work.
Although Voice Assistants are ubiquitously available for some years now, the interaction is still monotonous and utilitarian. Sound design offers conceptual and methodological research to design ...auditive interfaces. Our work aims to complement and supplement voice interaction with
sonic overlays
to enrich the user experience. Therefore, we followed a user-centered design process to develop a sound library for weather forecasts based on empirical results from a user survey of associative mapping. After analyzing the data, we created audio clips for seven weather conditions and evaluated the perceived combination of sound and speech with 15 participants in an interview study. Our findings show that supplementing speech with soundscapes is a promising concept that communicates information and induces emotions with a positive affect for the user experience of Voice Assistants. Besides a novel design approach and a collection of sound overlays, we provide four design implications to support voice interaction designers.
•End-user oriented approaches for artifact creation and modification are considered.•A systematic mapping study in the fields of EUD, EUP and EUSE is presented.•Trends and gaps emerged from the study ...are discussed.
End-User Development (EUD), End-Programming (EUP) and End-User Software Engineering (EUSE) are three related research fields that study methods and techniques for empowering end users to modify and create digital artifacts. This paper presents a systematic mapping study aimed at identifying and classifying scientific literature about EUD, EUP and EUSE in the time range January 2000–May 2017. We selected 165 papers found through a manual selection of papers from specific conferences, journal special issues, and books, integrated with an automatic search on the most important digital libraries. The answer to our research question was built through a classification of the selected papers on seven dimensions: type of approach, interaction technique, phase in which the approach is adopted, application domain, target use, class of users, and type of evaluation. Our findings suggest that EUD, EUP and EUSE are active research topics not only in Human–Computer Interaction, but also in other research communities. However, little cross-fertilization exists among the three themes, as well as unifying frameworks and approaches for guiding novice designers and practitioners. Other findings highlight trends and gaps related to the analysis’ dimensions, which have implications on the design of future tools and suggest open issues for further investigations.
PDF
