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This is an authoritative introduction to Computing Education research written by over 50 leading researchers from academia and the industry.
The Cambridge Handbook of Engineering Education Research is the critical reference source for the growing field of engineering education research, featuring the work of world luminaries writing to define and inform this emerging field. The Handbook draws extensively on contemporary research in the learning sciences, examining how technology affects learners and learning environments, and the role of social context in learning. Since a landmark issue of the Journal of Engineering Education (2005), in which senior scholars argued for a stronger theoretical and empirically driven agenda, engineering education has quickly emerged as a research-driven field increasing in both theoretical and empirical work drawing on many social science disciplines, disciplinary engineering knowledge, and computing. The Handbook is based on the research agenda from a series of interdisciplinary colloquia funded by the US National Science Foundation and published in the Journal of Engineering Education in October 2006.
This book provides an overview of how to approach computer science education research from a pragmatic perspective. It represents the diversity of traditions and approaches inherent in this interdisciplinary area, while also providing a structure within which to make sense of that diversity. It provides multiple 'entry points'- to literature, to methods, to topics Part One, 'The Field and the Endeavor', frames the nature and conduct of research in computer science education. Part Two, 'Perspectives and Approaches', provides a number of grounded chapters on particular topics or themes, written by experts in each domain. These chapters cover the following topics: * design * novice misconceptions * programming environments for novices * algorithm visualisation * a schema theory view on learning to program * critical theory as a theoretical approach to computer science education research Juxtaposed and taken together, these chapters indicate just how varied the perspectives and research approaches can be. These chapters, too, act as entry points, with illustrations drawn from published work.
Information and Communication Technologies (ICTs) have profoundly changed many aspects of life, including the nature of entertainment, work, communication, education, healthcare, industrial production and business, social relations and conflicts. They have had a radical and widespread impact on our moral lives and hence on contemporary ethical debates. The Cambridge Handbook of Information and Computer Ethics, first published in 2010, provides an ambitious and authoritative introduction to the field, with discussions of a range of topics including privacy, ownership, freedom of speech, responsibility, technological determinism, the digital divide, cyber warfare, and online pornography. It offers an accessible and thoughtful survey of the transformations brought about by ICTs and their implications for the future of human life and society, for the evaluation of behaviour, and for the evolution of moral values and rights. It will be a valuable book for all who are interested in the ethical aspects of the information society in which we live.
Written by leading researchers in educational and social psychology, learning science, and neuroscience, this edited volume is suitable for a wide-academic readership. It gives definitions of key terms related to motivation and learning alongside developed explanations of significant findings in the field. It also presents cohesive descriptions concerning how motivation relates to learning, and produces a novel and insightful combination of issues and findings from studies of motivation and/or learning across the authors' collective range of scientific fields. The authors provide a variety of perspectives on motivational constructs and their measurement, which can be used by multiple and distinct scientific communities, both basic and applied.
The interdisciplinary field of the learning sciences encompasses educational psychology, cognitive science, computer science, and anthropology, among other disciplines. The Cambridge Handbook of the Learning Sciences, first published in 2006, is the definitive introduction to this innovative approach to teaching, learning, and educational technology. In this dramatically revised second edition, leading scholars incorporate the latest research to provide practical advice on a wide range of issues. The authors address the best ways to write textbooks, design educational software, prepare effective teachers, organize classrooms, and use the Internet to enhance student learning. They illustrate the importance of creating productive learning environments both inside and outside school, including after school clubs, libraries, and museums. Accessible and engaging, the Handbook has proven to be an essential resource for graduate students, researchers, teachers, administrators, consultants, software designers, and policy makers on a global scale.
Businesses are rushing to collect personal data to fuel surging demand. Data enthusiasts claim personal information that's obtained from the commercial internet, including mobile platforms, social networks, cloud computing, and connected devices, will unlock path-breaking innovation, including advanced data security. By contrast, regulators and activists contend that corporate data practices too often disempower consumers by creating privacy harms and related problems. As the Internet of Things matures and facial recognition, predictive analytics, big data, and wearable tracking grow in power, scale, and scope, a controversial ecosystem will exacerbate the acrimony over commercial data capture and analysis. The only productive way forward is to get a grip on the key problems right now and change the conversation. That's exactly what Jules Polonetsky, Omer Tene, and Evan Selinger do. They bring together diverse views from leading academics, business leaders, and policymakers to discuss the opportunities and challenges of the new data economy.
This Handbook reviews a wealth of research in cognitive and educational psychology that investigates how to enhance learning and instruction to aid students struggling to learn and to advise teachers on how best to support student learning. The Handbook includes features that inform readers about how to improve instruction and student achievement based on scientific evidence across different domains, including science, mathematics, reading and writing. Each chapter supplies a description of the learning goal, a balanced presentation of the current evidence about the efficacy of various approaches to obtaining that learning goal, and a discussion of important future directions for research in this area. It is the ideal resource for researchers continuing their study of this field or for those only now beginning to explore how to improve student achievement.
Coding teaches our students the essence of logical thinking and problem solving while also preparing them for a world in which computing is becoming increasingly pervasive. While there's excitement and enthusiasm about programming becoming an intrinsic part of K-12 curricula the world over, there's also growing anxiety about preparing teachers to teach effectively at all grade levels.This book strives to be an essential, enduring, practical guide for every K-12 teacher anywhere who is either teaching or planning to teach computer science and programming at any grade level. To this end, readers will discover:? An A-to-Z organization that affords comprehensive insight into teaching introductory programming.? 26 chapters that cover foundational concepts, practices and well-researched pedagogies related to teaching introductory programming as an integral part of K-12 computer science. Cumulatively these chapters address the two salient building blocks of effective teaching of introductory programming-what content to teach (concepts and practices) and how to teach (pedagogy).? Concrete ideas and rich grade-appropriate examples inspired by practice and research for classroom use.? Perspectives and experiences shared by educators and scholars who are actively practicing and/or examiningthe teaching of computer science and programming in K-12 classrooms.
Addresses the impacts of data mining on education and reviews applications in educational research teaching, and learning This 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 four guiding principles— prediction, clustering, rule association, and outlier detection. The next series of chapters showcase the pedagogical applications of Educational Data Mining (EDM) and feature case studies drawn from Business, Humanities, Health Sciences, Linguistics, and Physical Sciences education that serve to highlight the successes and some of the limitations of data mining research applications in educational settings. The remaining chapters focus exclusively on EDM’s emerging role in helping to advance educational research—from identifying at-risk students and closing socioeconomic gaps in achievement to aiding in teacher evaluation and facilitating peer conferencing. This book features contributions from international experts in a variety of fields. Includes case studies where data mining techniques have been effectively applied to advance teaching and learning Addresses applications of data mining in educational research, including: social networking and education; policy and legislation in the classroom; and identification of at-risk students Explores Massive Open Online Courses (MOOCs) to study the effectiveness of online networks in promoting learning and understanding the communication patterns among users and students Features supplementary resources including a primer on foundational aspects of educational mining and learning analytics Data Mining and Learning Analytics: Applications in Educational Research is written for both scientists in EDM and educators interested in using and integrating DM and LA to improve education and advance educational research.
