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This book is devoted to the emerging field of integrated visual knowledge discovery that combines advances in artificial intelligence/machine learning and visualization/visual analytic. A long-standing challenge of artificial intelligence (AI) and machine learning (ML) is explaining models to humans, especially for live-critical applications like health care. A model explanation is fundamentally human activity, not only an algorithmic one. As current deep learning studies demonstrate, it makes the paradigm based on the visual methods critically important to address this challenge. In general, visual approaches are critical for discovering explainable high-dimensional patterns in all types in high-dimensional data offering "n-D glasses," where preserving high-dimensional data properties and relations in visualizations is a major challenge. The current progress opens a fantastic opportunity in this domain. This book is a collection of 25 extended works of over 70 scholars presented at AI and visual analytics related symposia at the recent International Information Visualization Conferences with the goal of moving this integration to the next level. The sections of this book cover integrated systems, supervised learning, unsupervised learning, optimization, and evaluation of visualizations. The intended audience for this collection includes those developing and using emerging AI/machine learning and visualization methods. Scientists, practitioners, and students can find multiple examples of the current integration of AI/machine learning and visualization for visual knowledge discovery. The book provides a vision of future directions in this domain. New researchers will find here an inspiration to join the profession and to be involved for further development. Instructors in AI/ML and visualization classes can use it as a supplementary source in their undergraduate and graduate classes.
Education in today's technologically advanced environments makes complex cognitive demands on students pre-learning, during, and post-learning. Not surprisingly, these analytical learning processes--metacognitive processes--have become an important focus of study as new learning technologies are assessed for effectiveness in this area.Rich in theoretical models and empirical data, the International Handbook of Metacognition and Learning Technologies synthesizes current research on this critical topic. This interdisciplinary reference delves deeply into component processes of self-regulated learning (SRL), examining theories and models of metacognition, empirical issues in the study of SRL, and the expanding role of educational technologies in helping students learn. Innovations in multimedia, hypermedia, microworlds, and other platforms are detailed across the domains, so that readers in diverse fields can evaluate the theories, data collection methods, and conclusions. And for the frontline instructor, contributors offer proven strategies for using technologies to benefit students at all levels. For each technology covered, the Handbook: Explains how the technology fosters students' metacognitive or self-regulated learning.Identifies features designed to study or support metacognitve/SRL behaviors.Reviews how its specific theory or model addresses learners' metacognitive/SRL processes.Provides detailed findings on its effectiveness toward learning.Discusses its implications for the design of metacognitive tools.Examines any theoretical, instructional, or other challenges.These leading-edge perspectives make the International Handbook of Metacognition and Learning Technologies a resource of great interest to professionals and researchers in science and math education, classroom teachers, human resource researchers, and industrial and other instructors.
This open access book tackles the design of 3D spatial interactions in an audio-centered and audio-first perspective, providing the fundamental notions related to the creation and evaluation of immersive sonic experiences. The key elements that enhance the sensation of place in a virtual environment (VE) are: Immersive audio: the computational aspects of the acoustical-space properties of Virutal Reality (VR) technologies Sonic interaction: the human-computer interplay through auditory feedback in VE VR systems: naturally support multimodal integration, impacting different application domains Sonic Interactions in Virtual Environments will feature state-of-the-art research on real-time auralization, sonic interaction design in VR, quality of the experience in multimodal scenarios, and applications. Contributors and editors include interdisciplinary experts from the fields of computer science, engineering, acoustics, psychology, design, humanities, and beyond. Their mission is to shape an emerging new field of study at the intersection of sonic interaction design and immersive media, embracing an archipelago of existing research spread in different audio communities and to increase among the VR communities, researchers, and practitioners, the awareness of the importance of sonic elements when designing immersive environments.
Provides a unique and timely re-examination of key issues such as strategies in context, strategy instruction, and strategy research methods by numerous experts in the field. Offers an invaluable overview of what is known from empirical research about listening, reading, speaking, writing, vocabulary, and grammar strategies. Proposes a clear and focused research agenda for the next decades. Research into language learner strategies has the fundamental goal of improving the teaching and learning of second languages. This book explores the notion that the reason some learners of second languages excel and others struggle lies in what the learners themselves do-the strategies they bring to language learning and to language use.
This book introduces a novel approach for intelligent visualizations that adapts the different visual variables and data processing to human’s behavior and given tasks. Thereby a number of new algorithms and methods are introduced to satisfy the human need of information and knowledge and enable a usable and attractive way of information acquisition. Each method and algorithm is illustrated in a replicable way to enable the reproduction of the entire “SemaVis” system or parts of it. The introduced evaluation is scientifically well-designed and performed with more than enough participants to validate the benefits of the methods. Beside the introduced new approaches and algorithms, readers may find a sophisticated literature review in Information Visualization and Visual Analytics, Semantics and information extraction, and intelligent and adaptive systems. This book is based on an awarded and distinguished doctoral thesis in computer science.
Automated System for the Generation of Document Indexes to Volume Visualization
This book brings together the latest research in this new and exciting area of visualization, looking at classifying and modelling cognitive biases, together with user studies which reveal their undesirable impact on human judgement, and demonstrating how visual analytic techniques can provide effective support for mitigating key biases. A comprehensive coverage of this very relevant topic is provided though this collection of extended papers from the successful DECISIVe workshop at IEEE VIS, together with an introduction to cognitive biases and an invited chapter from a leading expert in intelligence analysis. Cognitive Biases in Visualizations will be of interest to a wide audience from those studying cognitive biases to visualization designers and practitioners. It offers a choice of research frameworks, help with the design of user studies, and proposals for the effective measurement of biases. The impact of human visualization literacy, competence and human cognition on cognitive biases are also examined, as well as the notion of system-induced biases. The well referenced chapters provide an excellent starting point for gaining an awareness of the detrimental effect that some cognitive biases can have on users’ decision-making. Human behavior is complex and we are only just starting to unravel the processes involved and investigate ways in which the computer can assist, however the final section supports the prospect that visual analytics, in particular, can counter some of the more common cognitive errors, which have been proven to be so costly.
This volume constitutes the refereed proceedings of the Second International Conference on Human Centered Design, HCD 2011, held as Part of HCI International 2011, in Orlando, FL, USA, in July 2011, jointly with 9 other thematically similar conferences. The 66 revised papers presented were carefully reviewed and selected from numerous submissions. The papers are organized in topical parts on human centered design methods and tools, mobile and ubiquitous interaction, human centered design in health and rehabilitation, human centered design in work, business and education, and applications of human centered design.
This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.
This book offers a thorough exploration of interaction design by examining various technologies, interaction techniques, styles, and devices. This book • Assists readers in acquiring a deep understanding of diverse ways humans interact with computer technologies and in selecting the most suitable approach for various interactive scenarios. • Introduces cutting‐edge interaction techniques, including multimodal and gesture‐based interaction, wearables, haptic, speech and sound‐based interaction, embodied interaction, and more. • Advances beyond traditional interfaces to large and multiscreen interactions, proxemics, brain‐computer interfaces, affective computing and Extended Reality. This book will appeal to individuals interested in Human-Computer Interaction research and applications.