E-Learning Paradigms and Applications
E-Learning Paradigms and Applications

Author: Mirjana Ivanović

Publisher: Springer

Published: 2013-12-05

Total Pages: 281

ISBN-13: 3642419658

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Teaching and learning paradigms have attracted increased attention especially in the last decade. Immense developments of different ICT technologies and services have paved the way for alternative but effective approaches in educational processes. Many concepts of the agent technology, such as intelligence, autonomy and cooperation, have had a direct positive impact on many of the requests imposed on modern e-learning systems and educational processes. This book presents the state-of-the-art of e-learning and tutoring systems and discusses their capabilities and benefits that stem from integrating software agents. We hope that the presented work will be of a great use to our colleagues and researchers interested in the e-learning and agent technology.

Sequence Learning
Sequence Learning

Author: Ron Sun

Publisher: Springer

Published: 2003-06-29

Total Pages: 400

ISBN-13: 354044565X

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Sequential behavior is essential to intelligence in general and a fundamental part of human activities, ranging from reasoning to language, and from everyday skills to complex problem solving. Sequence learning is an important component of learning in many tasks and application fields: planning, reasoning, robotics natural language processing, speech recognition, adaptive control, time series prediction, financial engineering, DNA sequencing, and so on. This book presents coherently integrated chapters by leading authorities and assesses the state of the art in sequence learning by introducing essential models and algorithms and by examining a variety of applications. The book offers topical sections on sequence clustering and learning with Markov models, sequence prediction and recognition with neural networks, sequence discovery with symbolic methods, sequential decision making, biologically inspired sequence learning models.

Machine Learning Paradigms
Machine Learning Paradigms

Author: Maria Virvou

Publisher: Springer

Published: 2019-03-16

Total Pages: 230

ISBN-13: 3030137430

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This book presents recent machine learning paradigms and advances in learning analytics, an emerging research discipline concerned with the collection, advanced processing, and extraction of useful information from both educators’ and learners’ data with the goal of improving education and learning systems. In this context, internationally respected researchers present various aspects of learning analytics and selected application areas, including: • Using learning analytics to measure student engagement, to quantify the learning experience and to facilitate self-regulation; • Using learning analytics to predict student performance; • Using learning analytics to create learning materials and educational courses; and • Using learning analytics as a tool to support learners and educators in synchronous and asynchronous eLearning. The book offers a valuable asset for professors, researchers, scientists, engineers and students of all disciplines. Extensive bibliographies at the end of each chapter guide readers to probe further into their application areas of interest.

Machine Learning Paradigms: Theory and Application
Machine Learning Paradigms: Theory and Application

Author: Aboul Ella Hassanien

Publisher: Springer

Published: 2018-12-08

Total Pages: 472

ISBN-13: 3030023575

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The book focuses on machine learning. Divided into three parts, the first part discusses the feature selection problem. The second part then describes the application of machine learning in the classification problem, while the third part presents an overview of real-world applications of swarm-based optimization algorithms. The concept of machine learning (ML) is not new in the field of computing. However, due to the ever-changing nature of requirements in today’s world it has emerged in the form of completely new avatars. Now everyone is talking about ML-based solution strategies for a given problem set. The book includes research articles and expository papers on the theory and algorithms of machine learning and bio-inspiring optimization, as well as papers on numerical experiments and real-world applications.

Machine Learning and Big Data Analytics Paradigms: Analysis, Applications and Challenges
Machine Learning and Big Data Analytics Paradigms: Analysis, Applications and Challenges

Author: Aboul Ella Hassanien

Publisher: Springer Nature

Published: 2020-12-14

Total Pages: 648

ISBN-13: 303059338X

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This book is intended to present the state of the art in research on machine learning and big data analytics. The accepted chapters covered many themes including artificial intelligence and data mining applications, machine learning and applications, deep learning technology for big data analytics, and modeling, simulation, and security with big data. It is a valuable resource for researchers in the area of big data analytics and its applications.

Understanding Machine Learning
Understanding Machine Learning

Author: Shai Shalev-Shwartz

Publisher: Cambridge University Press

Published: 2014-05-19

Total Pages: 415

ISBN-13: 1107057132

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Introduces machine learning and its algorithmic paradigms, explaining the principles behind automated learning approaches and the considerations underlying their usage.

Emerging Methods and Paradigms in Scholarship and Education Research
Emerging Methods and Paradigms in Scholarship and Education Research

Author: Ling, Lorraine

Publisher: IGI Global

Published: 2019-08-30

Total Pages: 351

ISBN-13: 1799810038

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There is a renaissance in the use of the term “scholarship,” as it is being used to define areas of academic endeavour, describe academic work and achievements, and measure the quality of higher education. Although all academicians are required to engage in scholarship, it is difficult to navigate as there is a misunderstanding of this concept as new methods and approaches emerge. Emerging Methods and Paradigms in Scholarship and Education Research is an essential academic book that is designed to explain the areas of scholarship and their contemporary relationship to key components of academic work: research, teaching, service, and engagement. The chapter authors explore conceptions of scholarship, paradigms, and methods that fit a variety of contexts and needs. Highlighting a wide range of approaches from scientific realism and neo-positivism to interpretative, transformative, and pragmatic educational strategies and policy, this book is ideal for researchers, teachers, educational leaders, academicians, educational policymakers, and quality assurance agencies.

E-Learning
E-Learning

Author: Boyka Gradinarova

Publisher: BoD – Books on Demand

Published: 2015-10-21

Total Pages: 512

ISBN-13: 953512188X

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In this book, we can read about new technologies that enhance training and performance; discover new, exciting ways to design and deliver content; and have access to proven strategies, practices and solutions shared by experts. The authors of this book come from all over the world; their ideas, studies, findings and experiences are beneficial contributions to enhance our knowledge in the field of e-learning. The book is divided into three sections, and their respective chapters refer to three macro areas. The first section of the book covers Instructional Design of E-learning, considering methodology and tools for designing e-learning environments and courseware. Also, there are examples of effective ways of gaming and educating. The second section is about Organizational Strategy and Management. The last section deals with the new Developments in E-learning Technology, emphasizing subjects like knowledge building by mobile e-learning systems, cloud computing and new proposals for virtual learning environments/platforms.

Intelligent Agents for Data Mining and Information Retrieval
Intelligent Agents for Data Mining and Information Retrieval

Author: Masoud Mohammadian

Publisher: IGI Global

Published: 2004-01-01

Total Pages: 327

ISBN-13: 1591402778

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There is a large increase in the amount of information available on World Wide Web and also in number of online databases. This information abundance increases the complexity of locating relevant information. Such a complexity drives the need for improved and intelligent systems for search and information retrieval. Intelligent Agents are currently used to improve the search and retrieval information on World Wide Web. The use of existing search and retrieval engines with the addition of intelligent agents allows a more comprehensive search with a performance that can be measured. Intelligent Agents for Mining and Information Retrieval discusses the foundation as well as the pratical side of intelligent agents and their theory and applications for web data mining and information retrieval. The book can used for researchers at the undergraduate and post-graduate levels as well as a reference of the state-of-art for cutting edge researchers.