Search results for: intelligent-and-adaptive-learning-systems

Intelligent and Adaptive Learning Systems

Author : Sabine Graf
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"This book focuses on how intelligent support and adaptive features can be integrated in currently used learning systems and discusses how intelligent and adaptive learning systems can be improved in order to provide a better learning environment for learners"--Provided by publisher.

Intelligent and Adaptive Educational Learning Systems

Author : Alejandro Peña-Ayala
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The Smart Innovation, Systems and Technologies book series encompasses the topics of knowledge, intelligence, innovation and sustainability. The aim of the series is to make available a platform for the publication of books on all aspects of single and multi-disciplinary research on these themes in order to make the latest results available in a readily-accessible form. This book is devoted to the “Intelligent and Adaptive Educational-Learning Systems”. It privileges works that highlight key achievements and outline trends to inspire future research. After a rigorous revision process twenty manuscripts were accepted and organized into four parts: Modeling, Content, Virtuality and Applications. This volume is of interest to researchers, practitioners, professors and postgraduate students aimed to update their knowledge and find out targets for future work in the field of artificial intelligence on education.

Innovative Trends in Personalized Software Engineering and Information Systems

Author : C. Troussas
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This book, Innovative Trends in Personalized Software Engineering and Information Systems – The Case of Intelligent and Adaptive E-learning Systems, studies the development of personalized and knowledge-based systems with the purpose of developing fully-automated adaptive software, mainly focusing on enhancing digital learning. The authors cover several integral phases of software engineering and their application in the effective implementation of sophisticated learning technology systems. Systems development and systems evaluation, tailored to adaptive e-learning, are examined in depth. More specifically, intelligent and knowledge-based techniques, such as artificial neural networks, fuzzy logic, genetic algorithms, pattern recognition, learning analytics and data mining, as well as evaluation frameworks adapted to digital learning software are presented. This publication will be of interest to scientists from various disciplines, including computer science, artificial intelligence, education and psychology, and will help researchers working in computer science and engineering to build intelligent and adaptive learning technology systems by employing personalization techniques while following the basic concepts of software engineering and information systems. It will also serve as a valuable tool for junior and senior scientists, supporting their research activities in the field of personalized and knowledge-based software engineering, and instructors will be able to use the book as a guide to the effective design and development of intelligent systems in education.

Adaptive Instructional Systems

Author : Robert A. Sottilare
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This book constitutes the refereed proceedings of the First International Conference on Adaptive Instructional Systems, AIS 2019, held in July 2019 as part of HCI International 2019 in Orlando, FL, USA. HCII 2019 received a total of 5029 submissions, of which 1275 papers and 209 posters were accepted for publication after a careful reviewing process. The 50 papers presented in this volume are organized in topical sections named: Adaptive Instruction Design and Authoring, Interoperability and Standardization in Adaptive Instructional Systems, Instructional Theories in Adaptive Instruction, Learner Assessment and Modelling, AI in Adaptive Instructional Systems, Conversational Tutors.

Expanding the Self

Author : Alex Bennet
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We live in unprecedented times; indeed, turbulent times that can arguably be defined as ushering humanity into a new Golden Age, offering the opportunity to embrace new ways of learning and living in a globally and collaboratively entangled connectedness. In this shifting and dynamic environment, life demands accelerated cycles of learning experiences. Fortunately, we as a humanity have begun to look within ourselves to better understand the way our mind/brain operates, the amazing qualities of the body that power our thoughts and feelings, and the reciprocal loops as those thoughts and feelings change our physical structure. This emerging knowledge begs us to relook and rethink what we know about learning, providing a new starting point to expand toward the future. This book is a treasure for those interested in how recent findings in neuroscience impact learning. The result of this work is an expanded experiential learning model, the Intelligent Complex Adaptive Learning System, which adds a fifth mode of Social Engagement to Kolb's concrete experience, reflective observation, abstract conceptualization and active experimentation, with the five modes undergirded by the power of Self in an ever-shifting environment. A significant conclusion is that, should they desire, adults have much more control over their learning than they may realize.

Intelligent Learning Systems and Advancements in Computer Aided Instruction Emerging Studies

Author : Jin, Qun
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"This book reviews computational models and technologies for distance education, focusing on systems, infrastructures, and frameworks for delivering quality education"--Provided by publisher.

Intelligent Adaptation and Personalization Techniques in Computer Supported Collaborative Learning

Author : Thanasis Daradoumis
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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 the fast development in Internet technologies, especially with the emergence of new data technologies and the mobile technologies, new opportunities and perspectives are opened for advanced adaptive and personalized systems. Adaptation and personalization are posing new research and development challenges to nowadays CSCL systems. In particular, adaptation should be focused in a multi-dimensional way (cognitive, technological, context-aware and personal). Moreover, it should address the particularities of both individual learners and group collaboration. As a consequence, the aim of this book is twofold. On the one hand, it discusses the latest advances and findings in the area of intelligent adaptive and personalized learning systems. On the other hand it analyzes the new implementation perspectives for intelligent adaptive learning and collaborative systems that are brought by the advances in scripting languages, IMS LD, educational modeling languages and learning activity management systems. Given the variety of learning needs as well as the existence of different technological solutions, the book exemplifies the methodologies and best practices through several case studies and adaptive real-world collaborative learning scenarios, which show the advancement in the field of analysis, design and implementation of intelligent adaptive and personalized systems.

Web based Educational Systems and Learning Styles

Author : Abdulrahman Alghamdi
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Adaptive Technologies for Training and Education

Author : Paula J. Durlach
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"This volume provides an overview of the latest advancements in computer-based education training that use student performance data to provide adaptive and hence more efficient individualized learning opportunities"--

Computational Intelligence for Technology Enhanced Learning

Author : Fatos Xhafa
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E-Learning has become one of the most wide spread ways of distance teaching and learning. Technologies such as Web, Grid, and Mobile and Wireless networks are pushing teaching and learning communities to find new and intelligent ways of using these technologies to enhance teaching and learning activities. Indeed, these new technologies can play an important role in increasing the support to teachers and learners, to shorten the time to learning and teaching; yet, it is necessary to use intelligent techniques to take advantage of these new technologies to achieve the desired support to teachers and learners and enhance learners’ performance in distributed learning environments. The chapters of this volume bring advances in using intelligent techniques for technology enhanced learning as well as development of e-Learning applications based on such techniques and supported by technology. Such intelligent techniques include clustering and classification for personalization of learning, intelligent context-aware techniques, adaptive learning, data mining techniques and ontologies in e-Learning systems, among others. Academics, scientists, software developers, teachers and tutors and students interested in e-Learning will find this book useful for their academic, research and practice activity.

Anticipatory Behavior in Adaptive Learning Systems

Author : Martin V. Butz
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The interdisciplinary topic of anticipation, attracting attention from computer scientists, psychologists, philosophers, neuroscientists, and biologists is a rather new and often misunderstood matter of research. This book attempts to establish anticipation as a research topic and encourage further research and development work. First, the book presents philosophical thoughts and concepts to stimulate the reader's concern about the topic. Fundamental cognitive psychology experiments then confirm the existence of anticipatory behavior in animals and humans and outline a first framework of anticipatory learning and behavior. Next, several distinctions and frameworks of anticipatory processes are discussed, including first implementations of these concepts. Finally, several anticipatory systems and studies on anticipatory behavior are presented.

Artificial Intelligence in Education

Author : Ulrich Hoppe
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This work reports on research into intelligent systems, models, and architectures for educational computing applications. It covers a wide range of advanced information and communication and computational methods applied to education and training.

Knowledge Based Virtual Education

Author : Claude Ghaoui
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This monograph provides a wide range of innovative approaches of virtual education with a special emphasis on inter-disciplinary approaches. The book covers a wide range of important issues on the subject of "Innovations in Knowledge-Based Virtual Education ", aiming at researchers and practitioners from academia, industry, and government. The carefully selected contributions report on research, development and real-world experiences of virtual education such as intelligent virtual teaching, web-based adaptive learning systems, intelligent agents or using multiagent intelligence. TOC:Just-in-Time Approach to Learning: Arguing the Case for Cost-Effective Knowledge Dissemination.- P-Dinamet: A Web-Based Adaptive Learning System to Assist Learners and Teachers.- Intelligent Agents that Learn to Deliver Online Materials to Students Better: Agent Design, Simulation and Assumptions.- Intelligent Web-Based Computer-Supported Collaborative Learning.- Using Multiagent Intelligence to Support Synchronous and Asynchronous Learning.- Intelligent Agents to Improve Adaptivity in A Web-Based Learning Environment.- Intelligent Virtual Teaching.- Developing a User Centered Model for Creating a Virtual Learning Portfolio.- A Didactics Aware Approach to Knowledge Transfer in Web-based Education

Building Intelligent Interactive Tutors

Author : Beverly Park Woolf
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Building Intelligent Interactive Tutors discusses educational systems that assess a student's knowledge and are adaptive to a student's learning needs. The impact of computers has not been generally felt in education due to lack of hardware, teacher training, and sophisticated software. and because current instructional software is neither truly responsive to student needs nor flexible enough to emulate teaching. Dr. Woolf taps into 20 years of research on intelligent tutors to bring designers and developers a broad range of issues and methods that produce the best intelligent learning environments possible, whether for classroom or life-long learning. The book describes multidisciplinary approaches to using computers for teaching, reports on research, development, and real-world experiences, and discusses intelligent tutors, web-based learning systems, adaptive learning systems, intelligent agents and intelligent multimedia. It is recommended for professionals, graduate students, and others in computer science and educational technology who are developing online tutoring systems to support e-learning, and who want to build intelligence into the system. Combines both theory and practice to offer most in-depth and up-to-date treatment of intelligent tutoring systems available Presents powerful drivers of virtual teaching systems, including cognitive science, artificial intelligence, and the Internet Features algorithmic material that enables programmers and researchers to design building components and intelligent systems

Adaptive Learning Methods for Nonlinear System Modeling

Author : Danilo Comminiello
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Adaptive Learning Methods for Nonlinear System Modeling presents some of the recent advances on adaptive algorithms and machine learning methods designed for nonlinear system modeling and identification. Real-life problems always entail a certain degree of nonlinearity, which makes linear models a non-optimal choice. This book mainly focuses on those methodologies for nonlinear modeling that involve any adaptive learning approaches to process data coming from an unknown nonlinear system. By learning from available data, such methods aim at estimating the nonlinearity introduced by the unknown system. In particular, the methods presented in this book are based on online learning approaches, which process the data example-by-example and allow to model even complex nonlinearities, e.g., showing time-varying and dynamic behaviors. Possible fields of applications of such algorithms includes distributed sensor networks, wireless communications, channel identification, predictive maintenance, wind prediction, network security, vehicular networks, active noise control, information forensics and security, tracking control in mobile robots, power systems, and nonlinear modeling in big data, among many others. This book serves as a crucial resource for researchers, PhD and post-graduate students working in the areas of machine learning, signal processing, adaptive filtering, nonlinear control, system identification, cooperative systems, computational intelligence. This book may be also of interest to the industry market and practitioners working with a wide variety of nonlinear systems. Presents the key trends and future perspectives in the field of nonlinear signal processing and adaptive learning. Introduces novel solutions and improvements over the state-of-the-art methods in the very exciting area of online and adaptive nonlinear identification. Helps readers understand important methods that are effective in nonlinear system modelling, suggesting the right methodology to address particular issues.

Intelligent Tutoring Systems

Author : Beverly Woolf
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The9thInternationalConferenceonIntelligentTutoringSystems(ITS2008)was heldJune 23–27,2008inMontreal. Thisyearwecelebratedthe 20thanniversary ofthe conferencefounded in 1988in Montreal. We havehadbiennial conferences for most of the past 10 years around the world, including in Brazil, Taiwan, France, Canada, and the USA. These ITS conferences provide a forum for the interchange of ideas in all areas of computer science and human learning, a unique environment to exchange ideas and support new developments relevant for the future. The 2008 conference was a symbolic milestone that enabled us to look back at what has been achieved and what is currently being done, in order to face the challenges of tomorrow. Much has changed in the last 20 years in terms of hardware, software, p- grammers,and education stakeholders. Technology is now networked, pervasive, and availableanyplace and anytime. The potential exists to provide customized, ubiquitous guidance andinstruction. However,much has remainedthe same and the need is just as great to model the learner, teaching strategies and domain knowledge. This year we saw an increase in research into student a?ect (mo- vation, boredom, and frustration), speci?cally attempts to detect student a?ect, while feedback studies consideredwhich responses to provide given both student cognition and a?ect. Studies also looked at the impact on learning of positive feedbackandpolitenessinfeedback. Newresearchwasseenindataminingbased on larger studies that use data from real students to diagnose e?ective learning and teaching. So much interest has been generated in this area that the ?rst International Conference on Educational Data Mining was co-located with ITS 2008.

Future Directions for Intelligent Systems and Information Sciences

Author : Nikola Kasabov
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This edited volume comprises invited chapters that cover five areas of the current and the future development of intelligent systems and information sciences. Half of the chapters were presented as invited talks at the Workshop "Future Directions for Intelligent Systems and Information Sciences" held in Dunedin, New Zealand, 22-23 November 1999 after the International Conference on Neuro-Information Processing (lCONIPI ANZIISI ANNES '99) held in Perth, Australia. In order to make this volume useful for researchers and academics in the broad area of information sciences I invited prominent researchers to submit materials and present their view about future paradigms, future trends and directions. Part I contains chapters on adaptive, evolving, learning systems. These are systems that learn in a life-long, on-line mode and in a changing environment. The first chapter, written by the editor, presents briefly the paradigm of Evolving Connectionist Systems (ECOS) and some of their applications. The chapter by Sung-Bae Cho presents the paradigms of artificial life and evolutionary programming in the context of several applications (mobile robots, adaptive agents of the WWW). The following three chapters written by R.Duro, J.Santos and J.A.Becerra (chapter 3), GCoghill . (chapter 4), Y.Maeda (chapter 5) introduce new techniques for building adaptive, learning robots.

An Intelligent Learning System Using Cognitive Science Theory and Artificial Intelligence Methods

Author : Dean Lee Christensen
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Adaptive and Learning Systems II

Author : Firooz A. Sadjadi
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Principles of Adaptive Filters and Self learning Systems

Author : Anthony Zaknich
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Teaches students about classical and nonclassical adaptive systems within one pair of covers Helps tutors with time-saving course plans, ready-made practical assignments and examination guidance The recently developed "practical sub-space adaptive filter" allows the reader to combine any set of classical and/or non-classical adaptive systems to form a powerful technology for solving complex nonlinear problems