Author: Longbing Cao
Publisher: Springer
ISBN: 3319950924
Category : Computers
Languages : en
Pages : 404
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Book Description
This book explores answers to the fundamental questions driving the research, innovation and practices of the latest revolution in scientific, technological and economic development: how does data science transform existing science, technology, industry, economy, profession and education? How does one remain competitive in the data science field? What is responsible for shaping the mindset and skillset of data scientists? Data Science Thinking paints a comprehensive picture of data science as a new scientific paradigm from the scientific evolution perspective, as data science thinking from the scientific-thinking perspective, as a trans-disciplinary science from the disciplinary perspective, and as a new profession and economy from the business perspective.
Author: Orit Hazzan
Publisher: Springer Nature
ISBN: 3031247582
Category : Computers
Languages : en
Pages : 330
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Book Description
Data science is a new field that touches on almost every domain of our lives, and thus it is taught in a variety of environments. Accordingly, the book is suitable for teachers and lecturers in all educational frameworks: K-12, academia and industry. This book aims at closing a significant gap in the literature on the pedagogy of data science. While there are many articles and white papers dealing with the curriculum of data science (i.e., what to teach?), the pedagogical aspect of the field (i.e., how to teach?) is almost neglected. At the same time, the importance of the pedagogical aspects of data science increases as more and more programs are currently open to a variety of people. This book provides a variety of pedagogical discussions and specific teaching methods and frameworks, as well as includes exercises, and guidelines related to many data science concepts (e.g., data thinking and the data science workflow), main machine learning algorithms and concepts (e.g., KNN, SVM, Neural Networks, performance metrics, confusion matrix, and biases) and data science professional topics (e.g., ethics, skills and research approach). Professor Orit Hazzan is a faculty member at the Technion’s Department of Education in Science and Technology since October 2000. Her research focuses on computer science, software engineering and data science education. Within this framework, she studies the cognitive and social processes on the individual, the team and the organization levels, in all kinds of organizations. Dr. Koby Mike is a Ph.D. graduate from the Technion's Department of Education in Science and Technology under the supervision of Professor Orit Hazzan. He continued his post-doc research on data science education at the Bar-Ilan University, and obtained a B.Sc. and an M.Sc. in Electrical Engineering from Tel Aviv University.
Author: Christopher Moore
Publisher: Routledge
ISBN: 1315298619
Category : Education
Languages : en
Pages : 180
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Book Description
Teach your students how to think like scientists. This book shows you practical ways to incorporate science thinking in your classroom using simple "Thinking Tasks" that you can insert into any lesson. What is science thinking and how can you possibly teach and assess it? How is science thinking incorporated into the Next Generation Science Standards (NGSS) and how can it be weaved into your curriculum? This book answers these questions. This practical book provides a clear, research-verified framework for helping students develop scientific thinking as required by the NGSS. Your students will not be memorizing content but will become engaged in the real work scientists do, using critical thinking patterns such as: Recognizing patterns, Inventing new hypotheses based on observations, Separating causes from correlations, Determining relevant variables and isolating them, Testing hypotheses, and Thinking about their own thinking and the relative value of evidence. The book includes a variety of sample classroom activities and rubrics, as well as frameworks for creating your own tools. Designed for the busy teacher, this book also shows you quick and simple ways to add deep science thinking to existing lessons.
Author: Anne L. Washington
Publisher: Oxford University Press
ISBN: 0197693024
Category : Data mining
Languages : en
Pages : 185
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Book Description
Can data science truly serve the public interest? Data-driven analysis shapes many interpersonal, consumer, and cultural experiences yet scientific solutions to social problems routinely stumble. All too often, predictions remain solely a technocratic instrument that sets financial interests against service to humanity. Amidst a growing movement to use science for positive change, Anne L. Washington offers a solution-oriented approach to the ethical challenges of data science. Ethical Data Science empowers those striving to create predictive data technologies that benefit more people. As one of the first books on public interest technology, it provides a starting point for anyone who wants human values to counterbalance the institutional incentives that drive computational prediction. It argues that data science prediction embeds administrative preferences that often ignore the disenfranchised. The book introduces the prediction supply chain to highlight moral questions alongside the interlocking legal and commercial interests influencing data science. Structured around a typical data science workflow, the book systematically outlines the potential for more nuanced approaches to transforming data into meaningful patterns. Drawing on arts and humanities methods, it encourages readers to think critically about the full human potential of data science step-by-step. Situating data science within multiple layers of effort exposes dependencies while also pinpointing opportunities for research ethics and policy interventions. This approachable process lays the foundation for broader conversations with a wide range of audiences. Practitioners, academics, students, policy makers, and legislators can all learn how to identify social dynamics in data trends, reflect on ethical questions, and deliberate over solutions. The book proves the limits of predictive technology controlled by the few and calls for more inclusive data science.
Author: Erik Lee Nylen
Publisher: Academic Press
ISBN: 012804098X
Category : Science
Languages : en
Pages : 370
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Book Description
A Primer with MATLAB® and PythonTM present important information on the emergence of the use of Python, a more general purpose option to MATLAB, the preferred computation language for scientific computing and analysis in neuroscience. This book addresses the snake in the room by providing a beginner's introduction to the principles of computation and data analysis in neuroscience, using both Python and MATLAB, giving readers the ability to transcend platform tribalism and enable coding versatility. - Includes discussions of both MATLAB and Python in parallel - Introduces the canonical data analysis cascade, standardizing the data analysis flow - Presents tactics that strategically, tactically, and algorithmically help improve the organization of code
Author: Kohei Arai
Publisher: Springer Nature
ISBN: 3031663292
Category :
Languages : en
Pages : 727
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Book Description
Author: Andrew Gelman
Publisher: Oxford University Press
ISBN: 0198785690
Category : Mathematics
Languages : en
Pages : 421
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Book Description
To help overcome the challenges of teaching statistics across various diciplines, Gelman and Nolan have put together this fascinating and thought-provoking book based on years of teaching experience.
Author: Katharina Toeppe
Publisher: Springer Nature
ISBN: 3030712923
Category : Computers
Languages : en
Pages : 662
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Book Description
This two-volume set LNCS 12645-12646 constitutes the refereed proceedings of the 16th International Conference on Diversity, Divergence, Dialogue, iConference 2021, held in Beijing, China, in March 2021. The 32 full papers and the 59 short papers presented in this volume were carefully reviewed and selected from 225 submissions. They cover topics such as: AI and machine learning; data science; human-computer interaction; social media; digital humanities; education and information literacy; information behavior; information governance and ethics; archives and records; research methods; and institutional management.
Author: Constantine Stephanidis
Publisher: Springer Nature
ISBN: 3030901769
Category : Computers
Languages : en
Pages : 585
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Book Description
This two-volume set CCIS 1498 and CCIS 1499 contains the late breaking posters presented during the 23rd International Conference on Human-Computer Interaction, HCII 2021, which was held virtually in July 2021. The total of 1276 papers and 241 posters included in the 39 HCII 2021 proceedings volumes was carefully reviewed and selected from 5222 submissions. 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 posters presented in these two volumes are organized in topical sections as follows: HCI Theory and Practice; UX Design and Research in Intelligent Environments; Interaction with Robots, Chatbots, and Agents; Virtual, Augmented, and Mixed Reality; Games and Gamification; HCI in Mobility, Transport and Aviation; Design for All and Assistive Technologies; Physiology, Affect and Cognition; HCI for Health and Wellbeing; HCI in Learning, Teaching, and Education; Culture and Computing; Social Computing; Design Case Studies; User Experience Studies.
Author: Fazlay S. Faruque
Publisher: Springer Nature
ISBN: 3030713776
Category : Science
Languages : en
Pages : 422
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Book Description
Over the last thirty years or so, there have been tremendous advancements in the area of geospatial health; however, somehow, two aspects have not received as much attention as they should have received. These are a) limitations of different spatial analytical tools and b) progress in making geospatial environmental exposure data available for advanced health science research and for medical practice. This edited volume addresses those two less explored areas of geospatial health with augmented discussions on the theories, methodologies and limitations of contemporary geospatial technologies in a wide range of applications related to human well-being and health. In 20 chapters, readers are presented with an up-to-date assessment of geospatial technologies with an emphasis on understanding general geospatial principles and methodologies that are often overlooked in the research literature. As a result, this book will be of interest to both newcomers and experts in geospatial analysis and will appeal to students and researchers engaged in studying human well-being and health. Chapters are presenting new concepts, new analytical methods and contemporary applications within the framework of geospatial applications in human well-being and health. The topics addressed by the various chapter authors include analytical approaches, newer areas of geospatial health application, introduction to unique resources, geospatial modeling, and environmental pollution assessments for air, water and soil. Although geospatial experts are expected to be the primary readers, this book is designed in such a way so that the public health professionals, environmental health scientists and clinicians also find it useful with or without any familiarity with geospatial analysis.
