Intelligent Adaptation and Personalization Techniques in Computer-supported Collaborative Learning

Adaptation and personalization have been extensively studied in CSCL research community aiming to design intelligent systems that adaptively support eLearning processes and collaboration. Yet, with th

This book proposes and validates an information flow approach to analyzing knowledge co-construction and predicting group performance in the context of collaborative learning. In addition, it highligh

This book proposes and validates an information flow approach to analyzing knowledge co-construction and predicting group performance in the context of collaborative learning. In addition, it highligh

Edited by an industrial-organizational psychologist (Orvis) and a professor of industrial/organizational psychology at Minnesota State U. (Lassiter), this examination of computer-supported collaborati

Theoretically, the term "script" appears to be rather ill-defined.This book clarifies the use of the term "script" in education. It approaches the term from at least three perspectives: cognitive psyc

Provides information on scripting computer-supported collaborative learning.

This book discusses the significance of flexible scripting to structure CSCL against the framework of “Script theory of guidance” and reports on findings from two empirical studies on the effects of f

Ertl (University of Bundeswehr-Munich, Germany) gathers perspectives and scenarios on e-collaborative knowledge construction. Material is in sections on environments for e-collaborative knowledge cons

Contributors from information and communication technology, computer science, and education sample recent developments in intelligent distance education technologies from perspectives of socially inte

Online Collaborative Learning: Theory and Practice provides a resource for researchers and practitioners in the area of online collaborative learning (also known as CSCL, computer-supported collaborat

This book reveals how advances in computer science and human-computer interaction impact Computer-Supported Collaborative Learning (CSCL) environments. The underlying theme of the contributions is the

International contributors in education, psychology, technology, and telecommunications engineering describe recent theory and applications in the field of computer supported collaborative learning (C

The field of Computer-Supported Collaborative Learning (CSCL) has traditionally focused on virtual learning environments and has somewhat neglected the physical environments in which students interac

This book is an edited volume of case studies exploring the uptake and use of computer supported collaborative learning in work settings. This book fills a significant gap in the literature. A numbe

With the advent and increasing popularity of Computer Supported Collaborative Learning (CSCL) and e-learning technologies, the need of automatic assessment and of teacher/tutor support for the two tig

This book will help readers understand fundamental and advanced statistical models and deep learning models for robust speaker recognition and domain adaptation. This useful toolkit enables readers to apply machine learning techniques to address practical issues, such as robustness under adverse acoustic environments and domain mismatch, when deploying speaker recognition systems. Presenting state-of-the-art machine learning techniques for speaker recognition and featuring a range of probabilistic models, learning algorithms, case studies, and new trends and directions for speaker recognition based on modern machine learning and deep learning, this is the perfect resource for graduates, researchers, practitioners and engineers in electrical engineering, computer science and applied mathematics.

Intelligent Collaborative e-Learning Systems and Applications is a major research theme in CSCL and CSCW research community. It comprises a variety of research topics that focus on developing systems

Nowadays, intelligent techniques are more and more used in Computer Graphics in order to optimise the processing time, to find more accurate solutions for a lot of Computer Graphics problems, than wit

Rational thinking as exemplified in mathematical cognition is immensely important in the modern world. This book documents how a group of three eighth-grade girls developed specific group practices typical of such thinking in an online educational experience. A longitudinal case study tracks the team through eight hour-long sessions, following the students' meaning-making processes through their mutual chat responses preserved in computer logs coordinated with their geometric actions. The examination of data focuses on key areas of the team's development: its effective team collaboration, its productive mathematical discourse, its enacted use of dynamic-geometry tools, and its ability to identify and construct dynamic-geometry dependencies. This detailed study of group cognition serves as a paradigmatic example of computer-supported collaborative learning, incorporating a unique model of human-computer interaction analysis applied to the use of innovative educational technology. A valu

Technology-enhanced systems and computer-aided tools that support scaffolding in collaborative learning are key goals in the education research sector. This book covers a number of approaches to foste

THE SERIES: INTELLIGENT BIOMEDICAL DATA ANALYSISBy focusing on the methods and tools for intelligent data analysis, this series aims to narrow the increasing gap between data gathering and data comprehension. Emphasis is also given to the problems resulting from automated data collection in modern hospitals, such as analysis of computer-based patient records, data warehousing tools, intelligent alarming, effective and efficient monitoring. In medicine, overcoming this gap is crucial since medical decision making needs to be supported by arguments based on existing medical knowledge as well as information, regularities and trends extracted from big data sets.

This book provides the first comprehensive overview of theoretical issues, historical developments and current trends in ICALL (Intelligent Computer-Assisted Language Learning). It assumes a basic fam

This SpringerBrief reveals the latest techniques in computer vision and machine learning on robots that are designed as accurate and efficient military snipers. Militaries around the world are investi

An introduction to neurorobotics that presents approaches and design principles for developing intelligent autonomous systems grounded in biology and neuroscience.Neurorobotics is an interdisciplinary field that draws on artificial intelligence, cognitive sciences, computer science, engineering, psychology, neuroscience, and robotics. Because the brain is closely coupled to the body and situated in the environment, neurorobots―autonomous systems modeled after some aspect of the brain―offer a powerful tool for studying neural function and may also be a means for developing autonomous systems with intelligence that rivals that of biological organisms. This textbook introduces approaches and design principles for developing intelligent autonomous systems grounded in biology and neuroscience. It is written for anyone interested in learning about this topic and can be used in cognitive robotics courses for students in psychology, cognitive science, and computer science.Neurorobotics covers

Assembled in this volume is a collection of some of the state-of-the-art methods that are using computer vision and machine learning techniques as applied in robotic applications. Currently there is a

This book is for anyone who has biomedical data and needs to identify variables that predict an outcome, for two-group outcomes such as tumor/not-tumor, survival/death, or response from treatment. Statistical learning machines are ideally suited to these types of prediction problems, especially if the variables being studied may not meet the assumptions of traditional techniques. Learning machines come from the world of probability and computer science but are not yet widely used in biomedical research. This introduction brings learning machine techniques to the biomedical world in an accessible way, explaining the underlying principles in nontechnical language and using extensive examples and figures. The authors connect these new methods to familiar techniques by showing how to use the learning machine models to generate smaller, more easily interpretable traditional models. Coverage includes single decision trees, multiple-tree techniques such as Random Forests™, neural nets, suppor

This book is for anyone who has biomedical data and needs to identify variables that predict an outcome, for two-group outcomes such as tumor/not-tumor, survival/death, or response from treatment. Statistical learning machines are ideally suited to these types of prediction problems, especially if the variables being studied may not meet the assumptions of traditional techniques. Learning machines come from the world of probability and computer science but are not yet widely used in biomedical research. This introduction brings learning machine techniques to the biomedical world in an accessible way, explaining the underlying principles in nontechnical language and using extensive examples and figures. The authors connect these new methods to familiar techniques by showing how to use the learning machine models to generate smaller, more easily interpretable traditional models. Coverage includes single decision trees, multiple-tree techniques such as Random Forests™, neural nets, suppor

In Deep Learning with Python, Second Edition, updated from the original bestseller with over 50% new content, you'll explore challenging concepts and practice applications in computer vision, natural-language processing, and generative models. The bestseller revised Deep Learning with Python, Second Edition is a comprehensive introduction to the field of deep learning using Python and the powerful Keras library, written by the creator of Keras himself. This revised edition has been updated with new chapters, new tools, and cutting-edge techniques drawn from the latest research. In Deep Learning with Python, Second Edition, updated from the original bestseller with over 50% new content, you'll explore challenging concepts and practice applications in computer vision, natural-language processing, and generative models, building your understanding through practical examples and intuitive explanations that make the complexities of deep learning easily accessible. Purchase of the print book

This comprehensive textbook teaches the fundamentals of database design, modeling, systems, data storage, and the evolving world of data warehousing, governance and more. Written by experienced educators and experts in big data, analytics, data quality, and data integration, it provides an up-to-date approach to database management. This full-color, illustrated text has a balanced theory-practice focus, covering essential topics, from established database technologies to recent trends, like Big Data, NoSQL, and more. Fundamental concepts are supported by real-world examples, query and code walkthroughs, and figures, making it perfect for introductory courses for advanced undergraduates and graduate students in information systems or computer science. These examples are further supported by an online playground with multiple learning environments, including MySQL, MongoDB, Neo4j Cypher, and tree structure visualization. This combined learning approach connects key concepts throughout th

With this comprehensive and accessible introduction to the field, you will gain all the skills and knowledge needed to work with current and future audio, speech, and hearing processing technologies. Topics covered include mobile telephony, human-computer interfacing through speech, medical applications of speech and hearing technology, electronic music, audio compression and reproduction, big data audio systems and the analysis of sounds in the environment. All of this is supported by numerous practical illustrations, exercises, and hands-on MATLAB® examples on topics as diverse as psychoacoustics (including some auditory illusions), voice changers, speech compression, signal analysis and visualisation, stereo processing, low-frequency ultrasonic scanning, and machine learning techniques for big data. With its pragmatic and application driven focus, and concise explanations, this is an essential resource for anyone who wants to rapidly gain a practical understanding of speech and audi

This book examines one of the thorniest problems of ancient American archaeology: the origins and domestication of maize. Using a variety of scientific techniques, Duccio Bonavia explores the development of maize, its adaptation to varying climates and its fundamental role in ancient American cultures. An appendix (by Alexander Grobman) provides the first-ever comprehensive compilation of maize genetic data, correlating this data with the archaeological evidence presented throughout the book. This book provides a unique interpretation of questions of dating and evolution, supported by extensive data, following the spread of maize from South to North America and eventually to Europe and beyond.

"Learning professionals are finding success applying game-based sensibilities to the development of instruction. This is the first book to show how to design online instruction that leverages the best elements of online games to increase learning, retention, and application. It explains how to match different game strategies to types of learning content for the right learning outcome and discusses how gamification techniques can be used in a variety of settings to improve learning, retention and application of knowledge. Supported by peer-reviewed studies and examples from corporations who have adopted game-based learning successfully, the book illustrates how combining instructional design thinking with game concepts can create engaged and interactive learning experiences across a variety of media, from online to face-to-face"--