The Handbook of Computational Social Science is a comprehensive reference source for scholars across multiple disciplines. It outlines key debates in the field, showcasing novel statistical modeling and machine learning methods, and draws from specific case studies to demonstrate the opportunities and challenges in CSS approaches.The Handbook is divided into two volumes written by outstanding, internationally renowned scholars in the field. This first volume focuses on the scope of...

Offers a clear view of the utility and place for survey data within the broader Big Data ecosystemThis book presents a collection of snapshots from two sides of the Big Data perspective. It assembles an array of tangible tools, methods, and approaches that illustrate how Big Data sources and methods are being used in the survey and social sciences to improve official statistics and estimates for human populations. It also provides examples of how survey data are be...

An in-depth look at current issues, new research findings, andinterdisciplinary exchange in survey methodology andprocessingSurvey Measurement and Process Quality extends the marriage oftraditional survey issues and continuous quality improvementfurther than any other contemporary volume. It documents thecurrent state of the field, reports new research findings, andpromotes interdisciplinary exchange in questionnaire design, datacollection, data processing, quality assessment, and ...

Featuring a timely presentation of total survey error (TSE), this edited volume introduces valuable tools for understanding and improving survey data quality in the context of evolving large-scale data setsThis book provides an overview of the TSE framework and current TSE research as related to survey design, data collection, estimation, and analysis. It recognizes that survey data affects many public policy and business decisions and thus focuses on the framework...

The Handbook of Computational Social Science is a comprehensive reference source for scholars across multiple disciplines. It outlines key debates in the field, showcasing novel statistical modeling and machine learning methods, and draws from specific case studies to demonstrate the opportunities and challenges in CSS approaches.The Handbook is divided into two volumes written by outstanding, internationally renowned scholars in the field. This second volume focuses on fo...

This Handbook describes the extent and shape of computing education research today. Over fifty leading researchers from academia and industry (including Google and Microsoft) have contributed chapters that together define and expand the evidence base. The foundational chapters set the field in context, articulate expertise from key disciplines, and form a practical guide for new researchers. They address what can be learned empirically, methodologically and theoretically from each area. Th...

Addresses the impacts of data mining on education and reviews applications in educational research teaching, and learningThis book discusses the insights, challenges, issues, expectations, and practical implementation of data mining (DM) within educational mandates. Initial series of chapters offer a general overview of DM, Learning Analytics (LA), and data collection models in the context of educational research, while also defining and discussing data mining’s fo...

Drawing together the most up-to-date research from experts all across the world, the second edition of Computer Science Education offers the most up-to-date coverage available on this developing subject, ideal for building confidence of new pre-service and in-service educators teaching a new discipline. It provides an international overview of key concepts, pedagogical approaches and assessment practices.Highlights of the second edition include:- New sections on mac...

This book is about the ways in which experiments can be employed in the context of research on learning technologies and child–computer interaction (CCI). It is directed at researchers, supporting them to employ experimental studies while increasing their quality and rigor. The book provides a complete and comprehensive description on how to design, implement, and report experiments, with a focus on and examples from CCI and learning technology research. The topics covered include an intro...

A guide for using computational text analysis to learn about the social worldFrom social media posts and text messages to digital government documents and archives, researchers are bombarded with a deluge of text reflecting the social world. This textual data gives unprecedented insights into fundamental questions in the social sciences, humanities, and industry. Meanwhile new machine learning tools are rapidly transforming the way science and business are conducte...

Computer engineering refers generally to the field that integrates hardware design, production, and implementation, and it combines the expertise of practitioners in electrical, software, and hardware engineering. Computer Engineering: Concepts, Methodologies, Tools, and Applications is a broad, multi-volume collection of the best recent works published under the umbrella of computer engineering. It includes perspectives on the fundamental aspects, tools and technologies, methods and desig...

Winner of the 2019 McGuffey Longevity Award from the Textbook & Academic Authors Association (TAA)Recognized as one of the most cited methodology books in the social sciences, the Sixth Edition of Robert K. Yin′s bestselling text provides a complete portal to the world of case study research. With the integration of 11 applications in this edition, the book gives readers access to exemplary case studies drawn from a wide variety of academi...