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As the outcome of the Dagstuhl Seminar 15481 on Crowdsourcing and Human-Centered Experiments, this book is a primer for computer science researchers who intend to use crowdsourcing technology for human centered experiments. The focus of this Dagstuhl seminar, held in Dagstuhl Castle in November 2015, was to discuss experiences and methodological considerations when using crowdsourcing platforms to run human-centered experiments to test the effectiveness of visual representations. The inspiring Dagstuhl atmosphere fostered discussions and brought together researchers from different research directions. The papers provide information on crowdsourcing technology and experimental methodologies, comparisons between crowdsourcing and lab experiments, the use of crowdsourcing for visualisation, psychology, QoE and HCI empirical studies, and finally the nature of crowdworkers and their work, their motivation and demographic background, as well as the relationships among people forming the crowdsourcing community.
This book evaluates the impact of relevant factors affecting the results of speech quality assessment studies carried out in crowdsourcing. The author describes how these factors relate to the test structure, the effect of environmental background noise, and the influence of language differences. He details multiple user-centered studies that have been conducted to derive guidelines for reliable collection of speech quality scores in crowdsourcing. Specifically, different questions are addressed such as the optimal number of speech samples to include in a listening task, the influence of the environmental background noise in the speech quality ratings, as well as methods for classifying background noise from web audio recordings, or the impact of language proficiency in the user perception of speech quality. Ultimately, the results of these studies contributed to the definition of the ITU-T Recommendation P.808 that defines the guidelines to conduct speech quality studies in crowdsourcing.
This book constitutes late breaking papers from the 23rd International Conference on Human-Computer Interaction, HCII 2021, which was held in July 2021. The conference was planned to take place in Washington DC, USA but had to change to a virtual conference mode due to the COVID-19 pandemic. A total of 5222 individuals from academia, research institutes, industry, and governmental agencies from 81 countries submitted contributions, and 1276 papers and 241 posters were included in the volumes of the proceedings that were published before the start of the conference. Additionally, 174 papers and 146 posters are included in the volumes of the proceedings published after the conference, as “Late Breaking Work” (papers and posters). The contributions thoroughly cover the entire field of HCI, addressing major advances in knowledge and effective use of computers in a variety of application areas.
This expanded and revised version of the best-selling Universal Methods of Design is a comprehensive reference that provides a thorough and critical presentation of 125 research methods, synthesis/analysis techniques, and research deliverables for human-centered design. The text and accompanying photos and graphics of this classic resource are delivered in a concise and accessible format perfect for designers, educators, and students. Information can be easily referenced and utilized by cross-disciplinary teams in nearly any design project. This new, expanded edition includes a comprehensive index for referencing. Earlier chapters have been updated to include new information on digital design and software for A/B testing, content analysis, and territory maps. The addition of 25 chapters brings fresh relevance to the text with new and innovative design methods, such as subtraction and position maps, that have emerged since the first edition. Universal Methods of Design distills each method down to its essence, in a format that helps design teams select and implement the most credible research methods suited to their design culture.
This comprehensive reference provides a thorough and critical presentation of 100 research methods, synthesis/analysis techniques, and research deliverables for human centered design, delivered in a concise and accessible format perfect for designers, educators, and students. Universal Methods of Design serves as an invaluable compendium of methods that can be easily referenced and used by cross-disciplinary teams in nearly any design project. Methods and techniques are organized alphabetically for ongoing, quick reference. Each method is presented in a two-page format. The left-hand page contains a concise description of the method, accompanied by references for further reading. On the right-hand page, images and cases studies for each method are presented visually. The relevant phases for design application are highlighted as numbered icons along the right side of the page, from phases 1 (planning) through 5 (launch and monitor). Build more meaningful products with these methods and more: A/B Testing, Affinity Diagramming, Behavioral Mapping, Bodystorming, Contextual Design, Critical Incident Technique, Directed Storytelling, Flexible Modeling, Image Boards, Graffiti Walls, Heuristic Evaluation, Parallel Prototyping, Simulation Exercises, Touchstone Tours, and Weighted Matrix. This essential guide: Dismantles the myth that user research methods are complicated, expensive, and time-consuming Creates a shared meaning for cross-disciplinary design teams Illustrates methods with compelling visualizations and case studies Characterizes each method at a glance Indicates when methods are best employed to help prioritize appropriate design research strategies Universal Methods of Design is an essential resource for designers of all levels and specializations.
The five-volume set LNCS 12932-12936 constitutes the proceedings of the 18th IFIP TC 13 International Conference on Human-Computer Interaction, INTERACT 2021, held in Bari, Italy, in August/September 2021. The total of 105 full papers presented together with 72 short papers and 70 other papers in these books was carefully reviewed and selected from 680 submissions. The contributions are organized in topical sections named: Part I: affective computing; assistive technology for cognition and neurodevelopment disorders; assistive technology for mobility and rehabilitation; assistive technology for visually impaired; augmented reality; computer supported cooperative work. Part II: COVID-19 & HCI; croudsourcing methods in HCI; design for automotive interfaces; design methods; designing for smart devices & IoT; designing for the elderly and accessibility; education and HCI; experiencing sound and music technologies; explainable AI. Part III: games and gamification; gesture interaction; human-centered AI; human-centered development of sustainable technology; human-robot interaction; information visualization; interactive design and cultural development. Part IV: interaction techniques; interaction with conversational agents; interaction with mobile devices; methods for user studies; personalization and recommender systems; social networks and social media; tangible interaction; usable security. Part V: user studies; virtual reality; courses; industrial experiences; interactive demos; panels; posters; workshops. The chapter ‘Stress Out: Translating Real-World Stressors into Audio-Visual Stress Cues in VR for Police Training’ is open access under a CC BY 4.0 license at link.springer.com. The chapter ‘WhatsApp in Politics?! Collaborative Tools Shifting Boundaries’ is open access under a CC BY 4.0 license at link.springer.com.
Crowdsourcing is a means by which public interest is sought and leveraged to achieve specific goals, and this fascinating study highlights how the model has been used to challenge the effects of the COVID-19 pandemic. The book investigates what factors have encouraged the use of crowdsourcing during the pandemic, as well as those issues which have restricted its use. It is illustrated with four detailed case studies, covering the fields of education and health, demonstrating how crowdsourcing as a means of crisis management has, ultimately, been used to influence and develop public policy. A timely analysis of this emerging concept, the book will appeal to researchers and practitioners across health and social care, public policy and management, and the voluntary sector more generally.
Visualization and visual analytics are powerful concepts for exploring data from various application domains. The endless number of possible parameters and the many ways to combine visual variables as well as algorithms and interaction techniques create lots of possibilities for building such techniques and tools. The major goal of those tools is to include the human users with their tasks at hand, their hypotheses, and research questions to provide ways to find solutions to their problems or at least to hint them in a certain direction to come closer to a problem solution. However, due to the sheer number of design variations, it is unclear which technique is suitable for those tasks at hand, requiring some kind of user evaluation to figure out how the human users perform while solving their tasks. The technology of eye tracking has existed for a long time; however, it has only recently been applied to visualization and visual analytics as a means to provide insights to the users’ visual attention behavior. This generates another kind of dataset that has a spatio-temporal nature and hence demands for advanced data science and visual analytics concepts to find insights into the recorded eye movement data, either as a post process or even in real-time. This book describes aspects from the interdisciplinary field of visual analytics, but also discusses more general approaches from the field of visualization as well as algorithms and data handling. A major part of the book covers research on those aspects under the light and perspective of eye tracking, building synergy effects between both fields – eye tracking and visual analytics – in both directions, i.e. eye tracking applied to visual analytics and visual analytics applied to eye tracking data. Technical topics discussed in the book include: • Visualization; • Visual Analytics; • User Evaluation; • Eye Tracking; • Eye Tracking Data Analytics; Eye Tracking and Visual Analytics includes more than 500 references from the fields of visualization, visual analytics, user evaluation, eye tracking, and data science, all fields which have their roots in computer science. Eye Tracking and Visual Analytics is written for researchers in both academia and industry, particularly newcomers starting their PhD, but also for PostDocs and professionals with a longer research history in one or more of the covered research fields. Moreover, it can be used to get an overview about one or more of the involved fields and to understand the interface and synergy effects between all of those fields. The book might even be used for teaching lectures in the fields of information visualization, visual analytics, and/or eye tracking.
This book studies the motivation of crowdworkers to find out how to attract more people and reach a higher quality of outcomes. The book first proposes a taxonomy for studying the motivation of crowdworkers including the potential influencing factors, different types of motivation, and possible consequences and outcomes related to the motivation. Next, the CWMS questionnaire, an instrument for measuring the underlying motivation of crowdworkers is developed. It considers different dimensions of motivation suggested by the Self-Determination Theory of motivation which is a well-established and empirically validated psychological theory used in various domains. This instrument can be used to study the effect of platform and user characteristics on the general motivation of crowdworkers. Later, the task-specific motivation of crowdworkers is studied in detail: Influencing factors are investigated, subjective methods for measuring them are evaluated, a model for predicting worker’s decision on taking a task is proposed, the relative importance of different factors for two populations of crowdworkers is studied, and finally, a model for predicting the expected workload (as one of the major influencing factors) given the task design is proposed.