1,148 research outputs found

    Usability Textual Data Analysis: A Formulaic Coding Think-Aloud Protocol Method for Usability Evaluation

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    Think-aloud protocols are among the most standard methods for usability evaluation, which help to discover usability problems and to examine improvements because they provide direct information on a user's thinking and cognitive processes; however, it is often difficult to determine how to analyze the data to identify usability problems because there is no formulaic analysis procedure for textual data. Therefore, the analysis is time-consuming, and the quality of the results varies depending on an analyst's skills. In the present study, the author proposes a formulaic analysis think-aloud protocol method that specifies the procedure for analyzing participants' verbal responses during usability tests. The aim of the proposed think-aloud protocol method was to deliver an explicit procedure using step coding (SCAT) and 70 design items for textual data analysis, and then, the method was applied to a case study of usability evaluation to confirm that the method could extract the target system's problems. By using step coding and 70 design items, the process of extracting usability problems from textual data was made explicit, and the problems were extracted analytically. In other words, the proposed method was less ambiguous. Once a formulaic analysis procedure was established, textual data analysis could be performed easily and efficiently. The analysis could be performed without hesitation after data acquisition, and there were fewer omissions. In addition, it is expected that the procedure would be easy to use, even for novice designers

    Exoskeleton for the Mind: Exploring Strategies Against Misinformation with a Metacognitive Agent

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    Misinformation is a global problem in modern social media platforms with few solutions known to be effective. Social media platforms have offered tools to raise awareness of information, but these are closed systems that have not been empirically evaluated. Others have developed novel tools and strategies, but most have been studied out of context using static stimuli, researcher prompts, or low fidelity prototypes. We offer a new anti-misinformation agent grounded in theories of metacognition that was evaluated within Twitter. We report on a pilot study (n=17) and multi-part experimental study (n=57, n=49) where participants experienced three versions of the agent, each deploying a different strategy. We found that no single strategy was superior over the control. We also confirmed the necessity of transparency and clarity about the agent's underlying logic, as well as concerns about repeated exposure to misinformation and lack of user engagement.Comment: Pages 209-22

    Design and Implementation of a Usability-Framework for Smartwatches

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    Due to technological developments in the last decade, the class of wearable computers arose which offers innovative access to human-computer interaction. Especially smartwatches attracted attention and are established as a permanently worn computer device on many wrists nowadays. In particular, for new technologies usability is an important success factor. Although usability is a well-known domain with a long research history, unique characteristics of smartwatch applications complicate the utilization of recent usability analysis methods. Therefore, we survey recent techniques for the usability analysis, outline and respectively adapt suited approaches based on the requirements induced by the special characteristics of smartwatches. In addition, we design and implement a usability framework which facilitates the automated usability analysis for smartwatch applications in a design science research approach. Furthermore, we demonstrate the applicability of the developed framework and show the results of a usability analysis for an exemplary case study

    User Experience in Virtual Reality, conducting an evaluation on multiple characteristics of a Virtual Reality Experience

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    Virtual Reality applications are today numerous and cover a wide range of interests and tastes. As popularity of Virtual Reality increases, developers in industry are trying to create engrossing and exciting experiences that captivate the interest of users. User-Experience, a term used in the field of Human-Computer Interaction and Interaction Design, describes multiple characteristics of the experience of a person interacting with a product or a system. Evaluating User-Experience can provide valuable insight to developers and researchers on the thoughts and impressions of the end users in relation to a system. However, little information exists regarding on how to conduct User-Experience evaluations in the context of Virtual Reality. Consecutively, due to the numerous parameters that influence User-Experience in Virtual Reality, conducting and organizing evaluations can be overwhelming and challenging. The author of this thesis investigated how to conduct a User-Experience evaluation on multiple aspects of a Virtual Reality headset by identifying characteristics of the experience, and the methods that can be used to measure and evaluate them. The data collected was both qualitative and quantitative to cover a wide range of characteristics of the experience. Furthermore, the author applied usability testing, think-aloud protocol, questionnaires and semi-structured interview as methods to observe user behavior and collect information regarding the aspects of the Virtual Reality headset. The testing session described in this study included 14 participants. Data from this study showed that the combination of chosen methods were able to provide adequate information regarding the experience of the users despite encountered difficulties. Additionally, this thesis showcases which methods were used to evaluate specific aspects of the experience and the performance of each method as findings of the study

    A Study of Fidelity Level and Task/Non-Task Based Testing Scenarios on the Effectiveness of Usability Testing

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    Advances in usability are directing developers towards creating a better and all around friendlier environment for users. Unlike when buying a physical product where you purchase it first and then experience its usability, web site usability is immediately present. So, if a site doesn\u27t meet our needs, we as users, are quick to look elsewhere. Some research has suggested that fidelity makes no significant impact on users\u27 ability to locate errors or problems in a web site. This paper is intends to investigate the interaction between fidelity and task vs. non-task user testing with regards to the types of problems experienced by users. The goal is to identify the most efficient types of user testing. User testing is conventionally designed to emulate typical user situations and tasks. However the goal of testing is to find all possible problems with the interface\u27s design and correct or improve them. Asking users to perform typical tasks may not uncover all of these problems. Asking users to perform a non-task or browse the interface may provide additional information. And the interaction between fidelity and task should suggest that both types of tasks are needed at varying degrees of fidelity to ensure a quality user interface

    Anchorage: Visual Analysis of Satisfaction in Customer Service Videos via Anchor Events

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    Delivering customer services through video communications has brought new opportunities to analyze customer satisfaction for quality management. However, due to the lack of reliable self-reported responses, service providers are troubled by the inadequate estimation of customer services and the tedious investigation into multimodal video recordings. We introduce Anchorage, a visual analytics system to evaluate customer satisfaction by summarizing multimodal behavioral features in customer service videos and revealing abnormal operations in the service process. We leverage the semantically meaningful operations to introduce structured event understanding into videos which help service providers quickly navigate to events of their interest. Anchorage supports a comprehensive evaluation of customer satisfaction from the service and operation levels and efficient analysis of customer behavioral dynamics via multifaceted visualization views. We extensively evaluate Anchorage through a case study and a carefully-designed user study. The results demonstrate its effectiveness and usability in assessing customer satisfaction using customer service videos. We found that introducing event contexts in assessing customer satisfaction can enhance its performance without compromising annotation precision. Our approach can be adapted in situations where unlabelled and unstructured videos are collected along with sequential records.Comment: 13 pages. A preprint version of a publication at IEEE Transactions on Visualization and Computer Graphics (TVCG), 202

    Understanding the cognitive aspects of human error will increase the usability of user interfaces.

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    Understanding the cognitive aspects of human error will increase the usability of user interfaces. It is important to study the cognitive aspects of human error because many disasters have been attributed to operator errors. Creating usable interfaces that reduce the likelihood of error will save industries a great deal of money and may even save human lives. A greater understanding of human errors can be obtained by examining the psychological basis of errors, the methods used to study errors, some of the problems associated with studying errors and different types of errors. Next, the current research findings can then be applied to user interfaces to reduce the probability of user errors. Then, a web survey system, phpESP, will be analyzed based on the guidelines for reducing human error in user interfaces. The analysis of the survey system can server as a guide to help designers reduce potential user errors
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