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Comprises of 8 books for grade 1 to 8
This edited volume fills the gaps in existing literature on visualization and dashboard design for learning analytics. To do so, it presents critical tips to stakeholders and acts as guide to efficient implementation. The book covers the following topics: visualization and dashboard design for learning analytics, visualization and dashboard preferences of stakeholders, learners’ patterns on the dashboard, usability of visualization techniques and the dashboard, dashboard and intervention design, learning and instructional design for learning analytics, privacy and security issues about the dashboard, and future directions of visualization and dashboard design. This book will be of interest to researchers with interest in learning analytics and data analytics, teachers and students in higher education institutions and instructional designers, as it includes contributions from a wide variety of educational and psychological researchers, engineers, instructional designers, learning scientists, and computer scientists interested in learning analytics.
An encyclopedia designed especially to meet the needs of elementary, junior high, and senior high school students.
Over the last decades, the interior of cars has been constantly changing. A promising, yet unexplored, modality are large stereoscopic 3D (S3D) dashboards. Replacing the traditional car dashboard with a large display and applying binocular depth cues, such a user interface (UI) could provide novel possibilities for research and industry. In this book, the author introduces a development environment for such a user interface. With it, he performed several driving simulator experiments and shows that S3D can be used across the dashboard to support menu navigation and to highlight elements without impairing driving performance. The author demonstrates that S3D has the potential to promote safe driving when used in combination with virtual agents during conditional automated driving. Further, he present results indicating that S3D navigational cues improve take-over maneuvers in conditional automated vehicles. Finally, investigating the domain of highly automated driving, he studied how users would interact with and manipulate S3D content on such dashboards and present a user-defined gesture set.
Welcome to the exciting world of Computer Science Success, our comprehensive computer series, which is tailored for the learners from classes 1 to 8. In today's fast-paced digital landscape, computers have seamlessly integrated into nearly every aspect of our daily lives, from our homes to our workplaces. Proficiency in computer knowledge has become a fundamental requirement for success in a wide range of careers. Moreover, the boundless realm of the Internet serves as an invaluable repository of knowledge. Our series is meticulously crafted to equip students with not just computer skills but also creativity and diligence needed to excel in the ever-evolving world of technology. Drawing inspiration from the National Education Policy (NEP) 2020, we have seamlessly integrated key NEP elements and essential 21st Century Skills into practical activities throughout our chapters. Our chapters are aligned with the six phases of logical understanding outlined in the latest National Curriculum Framework (NCF) 2023, fostering cognitive abilities in Perception, Inference, Comparison, Postulation, Non-Apprehension and Verbal Testimony. Our books are a treasure trove of relevant topics and engaging features that make learning a truly enjoyable journey. Features of the Series - Course Book Learning Objectives: Goals aimed at achieving by the end of the chapter Do and Learn: Engaging activities fostering practical learning experiences Know More: Nuggets of knowledge, sparking curiosity and encouraging further exploration Facts: Historical or relevant facts enriching the understanding of the topic Think About It: Provocative questions prompting critical thinking and active engagement Summary: Summarise chapter for a quick grasp of key concepts Exercises: A variety of questions for self-assessment Activity Zone: Hands-on activities connecting students to key concepts, including Life Skills and Problem-Solving challenges Teacher's Notes: Valuable suggestions for educators to enhance the teaching-learning experience Test Papers: Comprehensive assessments covering all chapters for thorough evaluation Project Work: Problem-solving projects designed to test practical application skills Annexure: Supplementary knowledge to enrich both computer and life skills Features of the Series - Other Components Teacher's Resource Book: Contains lesson plans and detailed solutions to questions Online Support: E-books and animated videos of the text to enhance the learning process We hope that our series Computer Science Success caters to the requirements of the teachers and the learners. Suggestions to enhance our books are welcomed, as we collectively shape the future of education. -Authors
Interactive visualization and visual analytics tools have been designed and developed in the past and will be developed in the future as well. In each application domain in which data is measured, generated, and recorded we see a potential candidate for an interactive visualization tool with the goal to find insights and knowledge in the data. This knowledge can be found either visually by humans’ interventions or algorithmically by the machine, in the best case by applying both concepts in combination as in visual analytics. One of the easiest ways to get an interactive visualization tool running is by means of dashboards, typically implemented as webpages that can run in a web browser and are accessible online, creating some kind of web-based solution. This book describes ways to design and implement dashboards based on the programming language Python, the graphics library Plotly, and Dash. The readers can use the provided dashboard codes as a starting point and extend the functionality and features on their desire. Technical topics discussed in the book include: Design in visualization Interaction principles in information visualization User interface design Linking Python, Dash, and Plotly Coding in Python Dashboard examples with Python code.
The definitive reference book with real-world solutions you won't find anywhere else The Big Book of Dashboards presents a comprehensive reference for those tasked with building or overseeing the development of business dashboards. Comprising dozens of examples that address different industries and departments (healthcare, transportation, finance, human resources, marketing, customer service, sports, etc.) and different platforms (print, desktop, tablet, smartphone, and conference room display) The Big Book of Dashboards is the only book that matches great dashboards with real-world business scenarios. By organizing the book based on these scenarios and offering practical and effective visualization examples, The Big Book of Dashboards will be the trusted resource that you open when you need to build an effective business dashboard. In addition to the scenarios there's an entire section of the book that is devoted to addressing many practical and psychological factors you will encounter in your work. It's great to have theory and evidenced-based research at your disposal, but what will you do when somebody asks you to make your dashboard 'cooler' by adding packed bubbles and donut charts? The expert authors have a combined 30-plus years of hands-on experience helping people in hundreds of organizations build effective visualizations. They have fought many 'best practices' battles and having endured bring an uncommon empathy to help you, the reader of this book, survive and thrive in the data visualization world. A well-designed dashboard can point out risks, opportunities, and more; but common challenges and misconceptions can make your dashboard useless at best, and misleading at worst. The Big Book of Dashboards gives you the tools, guidance, and models you need to produce great dashboards that inform, enlighten, and engage.
This book constitutes the proceedings of the 11th International Congress on Telematics and Computing, WITCOM 2022, held in Cancún, México, in November 2022. The 30 full papers presented in this volume were carefully reviewed and selected from 73 submissions. The papers are focused on the topics of artificial intelligence techniques, Data Science, Blockchain, environment Monitoring, Cybersecurity, Education, and software for communications protocols.
The term 'learning analytics' is defined as the measurement, collection, analysis, and reporting of information about learners and their contexts for the purposes of understanding and optimizing learning. In recent years learning analytics has emerged as a promising area of research that trails the digital footprint of the learners and extracts useful knowledge from educational databases to understand students’ progress and success. With the availability of an increased amount of data, potential benefits of learning analytics can be far-reaching to all stakeholders in education including students, teachers, leaders, and policymakers. Educators firmly believe that, if properly harnessed, learning analytics will be an indispensable tool to enhance the teaching-learning process, narrow the achievement gap, and improve the quality of education. Many investigations have been carried out and disseminated in the literature and studies related to learning analytics are growing exponentially. This book documents recent attempts to conduct systematic, prodigious and multidisciplinary research in learning analytics and present their findings and identify areas for further research and development. The book also unveils the distinguished and exemplary works by educators and researchers in the field highlighting the current trends, privacy and ethical issues, creative and unique approaches, innovative methods, frameworks, and theoretical and practical aspects of learning analytics. Contributors are: Arif Altun, Alexander Amigud, Dongwook An, Mirella Atherton, Robert Carpenter, Martin Ebner, John Fritz, Yoshiko Goda, Yasemin Gulbahar, Junko Handa, Dirk Ifenthaler, Yumi Ishige, Il-Hyun Jo, Kosuke Kaneko, Selcan Kilis, Daniel Klasen, Mehmet Kokoç, Shin'ichi Konomi, Philipp Leitner, ChengLu Li, Min Liu, Karin Maier, Misato Oi, Fumiya Okubo, Xin Pan, Zilong Pan, Clara Schumacher, Yi Shi, Atsushi Shimada, Yuta Taniguchi, Masanori Yamada, and Wenting Zou.
In the Guide to the Software Engineering Body of Knowledge (SWEBOK(R) Guide), the IEEE Computer Society establishes a baseline for the body of knowledge for the field of software engineering, and the work supports the Society's responsibility to promote the advancement of both theory and practice in this field. It should be noted that the Guide does not purport to define the body of knowledge but rather to serve as a compendium and guide to the knowledge that has been developing and evolving over the past four decades. Now in Version 3.0, the Guide's 15 knowledge areas summarize generally accepted topics and list references for detailed information. The editors for Version 3.0 of the SWEBOK(R) Guide are Pierre Bourque (Ecole de technologie superieure (ETS), Universite du Quebec) and Richard E. (Dick) Fairley (Software and Systems Engineering Associates (S2EA)).