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Deep Learning In Adaptive Learning Educational Behavior And Strategy
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Book Synopsis Deep Learning in Adaptive Learning: Educational Behavior and Strategy by : Chia-Chen Chen
Download or read book Deep Learning in Adaptive Learning: Educational Behavior and Strategy written by Chia-Chen Chen and published by Frontiers Media SA. This book was released on 2022-09-14 with total page 652 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Advanced Intelligent Systems for Sustainable Development (AI2SD’2019) by : Mostafa Ezziyyani
Download or read book Advanced Intelligent Systems for Sustainable Development (AI2SD’2019) written by Mostafa Ezziyyani and published by Springer Nature. This book was released on 2020-01-03 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains the latest researches on advanced intelligent systems applied in the field of education presented during the second edition of the International Conference on Advanced Intelligent Systems for Sustainable Development (AI2SD’2019) held on July 08–11, 2019, in Marrakech, Morocco. The book proposes new approaches and innovative strategies for the manipulation of data and big data collected from the educational environment, exploiting the analysis tools, algorithms of artificial intelligence, and machine learning techniques, in order to extract results, which allow improving the performance and effectiveness of the education field, which is a strategic lever for sustainable development. The book deals with concepts, strategies, and approaches developed on various current axes of scientific research in the field of education, such as smart e-learning, smart education (smart classroom, smart assessment and smart teaching and learning technologies), massive open online courses (MOOC), courseware design, and development for smart learning, cloud learning, and mobile learning. The book is intended for all actors in the educational sector, namely students, professors, academic researchers, and stakeholders. It constitutes a large-scale forum for the exchange of ideas, approaches, and innovative techniques between these actors on the development and innovation of the field of education with the revolution 4.0. The authors of each chapter report the state of the art of the various topics addressed and present results of their own research, laboratory experiments, and successful applications. The purpose of this session is to share the idea of advanced intelligent systems with appropriate tools and techniques for modeling, management, and decision support in the field of education.
Book Synopsis Anticipatory Behavior in Adaptive Learning Systems by : Martin V. Butz
Download or read book Anticipatory Behavior in Adaptive Learning Systems written by Martin V. Butz and published by Springer. This book was released on 2007-09-19 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the refereed post-proceedings of the Third International Workshop on Anticipatory Behavior in Adaptive Learning Systems. Twenty full papers were chosen from among the many submissions. Papers are organized into sections covering anticipatory aspects in brains, language, and cognition; individual anticipatory frameworks; learning predictions and anticipations; anticipatory individual behavior; and anticipatory social behavior.
Book Synopsis Adaptive Learning Environments by : Marlene Jones
Download or read book Adaptive Learning Environments written by Marlene Jones and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: Adaptive Learning Environments (ALEs) can be viewed as the intersection of two traditionally distinct areas of research: instructional science and computer science. They encompass intelligent tutoring systems, interactive learning environments, and situated learning environments. There is increasing interest in effective instructional systems from education, industry, military and government sectors. Given recent advances in hardware architecture and reduction of hardware costs, the time is right to define the next steps in research and development of ALEs. This book is an outgrowth of the presentations and discussions that took place at the NATO Advanced Study Institute held at the University of Calgary in July 1990. It contains chapters from both researchers in instructional science and researchers in computer science on the following topics: - Systems and architectures for instruction - Representing curriculum and designing instructional tasks - Environments to support learning - Diagnosing students' learning and adjusting plans for instruction - Models of students' metacognition, motivation and learning strategies - Student-system interactions. The book containsintroductions/critiques of each pair of chapters, and a final chapter discusses the synthesis of instructional science and computer science.
Book Synopsis Innovative Learning Environments in STEM Higher Education by : Jungwoo Ryoo
Download or read book Innovative Learning Environments in STEM Higher Education written by Jungwoo Ryoo and published by Springer Nature. This book was released on 2021-03-11 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt: As explored in this open access book, higher education in STEM fields is influenced by many factors, including education research, government and school policies, financial considerations, technology limitations, and acceptance of innovations by faculty and students. In 2018, Drs. Ryoo and Winkelmann explored the opportunities, challenges, and future research initiatives of innovative learning environments (ILEs) in higher education STEM disciplines in their pioneering project: eXploring the Future of Innovative Learning Environments (X-FILEs). Workshop participants evaluated four main ILE categories: personalized and adaptive learning, multimodal learning formats, cross/extended reality (XR), and artificial intelligence (AI) and machine learning (ML). This open access book gathers the perspectives expressed during the X-FILEs workshop and its follow-up activities. It is designed to help inform education policy makers, researchers, developers, and practitioners about the adoption and implementation of ILEs in higher education.
Book Synopsis Multi-Strategy Learning Environment by : Vrince Vimal
Download or read book Multi-Strategy Learning Environment written by Vrince Vimal and published by Springer Nature. This book was released on with total page 710 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Educational equity in the age of artificial intelligence by : Dr. Mara Fischer
Download or read book Educational equity in the age of artificial intelligence written by Dr. Mara Fischer and published by epubli. This book was released on 2024-02-25 with total page 99 pages. Available in PDF, EPUB and Kindle. Book excerpt: In "Educational Equity in the Age of Artificial Intelligence," Dr. Mara Fischer takes readers on a profound journey into the heart of modern education's greatest challenge and opportunity: the integration of AI technologies. The book opens with a compelling examination of the current educational landscape, highlighting the disparities that threaten to widen in the wake of technological advancement. Fischer expertly navigates through the complexities of AI, demystifying its principles for non-technical readers while underscoring its potential to transform learning environments for the better. The narrative progresses to explore innovative case studies and theoretical frameworks that propose equitable solutions for integrating AI into education. Fischer's analysis is both critical and hopeful, offering a balanced view on how artificial intelligence can be leveraged to democratize education, personalize learning experiences, and equip students with the skills needed for a digital future. With a keen eye on policy implications and ethical considerations, this section not only enlightens but also inspires action among stakeholders. Concluding with a visionary outlook, "Educational Equity in the Age of Artificial Intelligence" calls for a collaborative effort between educators, policymakers, and technologists to create an inclusive educational system. Dr. Fischer emphasizes the urgency of this task, presenting a roadmap for harnessing the power of AI to ensure that every student, regardless of background, has access to the tools and opportunities necessary to thrive in the 21st century. This book is an indispensable resource for anyone committed to the cause of educational equity, offering practical insights and strategies to navigate the challenges and seize the opportunities presented by AI in education.
Book Synopsis Anticipatory Behavior in Adaptive Learning Systems by : Martin V. Butz
Download or read book Anticipatory Behavior in Adaptive Learning Systems written by Martin V. Butz and published by Springer. This book was released on 2004-01-21 with total page 305 pages. Available in PDF, EPUB and Kindle. Book excerpt: The interdisciplinary topic of anticipation, attracting attention fromnbsp;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.
Book Synopsis Learning for Adaptive and Reactive Robot Control by : Aude Billard
Download or read book Learning for Adaptive and Reactive Robot Control written by Aude Billard and published by MIT Press. This book was released on 2022-02-08 with total page 425 pages. Available in PDF, EPUB and Kindle. Book excerpt: Methods by which robots can learn control laws that enable real-time reactivity using dynamical systems; with applications and exercises. This book presents a wealth of machine learning techniques to make the control of robots more flexible and safe when interacting with humans. It introduces a set of control laws that enable reactivity using dynamical systems, a widely used method for solving motion-planning problems in robotics. These control approaches can replan in milliseconds to adapt to new environmental constraints and offer safe and compliant control of forces in contact. The techniques offer theoretical advantages, including convergence to a goal, non-penetration of obstacles, and passivity. The coverage of learning begins with low-level control parameters and progresses to higher-level competencies composed of combinations of skills. Learning for Adaptive and Reactive Robot Control is designed for graduate-level courses in robotics, with chapters that proceed from fundamentals to more advanced content. Techniques covered include learning from demonstration, optimization, and reinforcement learning, and using dynamical systems in learning control laws, trajectory planning, and methods for compliant and force control . Features for teaching in each chapter: applications, which range from arm manipulators to whole-body control of humanoid robots; pencil-and-paper and programming exercises; lecture videos, slides, and MATLAB code examples available on the author’s website . an eTextbook platform website offering protected material[EPS2] for instructors including solutions.
Book Synopsis Strategies for Deep Learning with Digital Technology by : Robert Zheng
Download or read book Strategies for Deep Learning with Digital Technology written by Robert Zheng and published by . This book was released on 2018 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Anticipatory Behavior in Adaptive Learning Systems by : Giovanni Pezzulo
Download or read book Anticipatory Behavior in Adaptive Learning Systems written by Giovanni Pezzulo and published by Springer Science & Business Media. This book was released on 2009-06-15 with total page 345 pages. Available in PDF, EPUB and Kindle. Book excerpt: Anticipatory behavior in adaptive learning systems continues attracting attention of researchers in many areas, including cognitive systems, neuroscience, psychology, and machine learning. This book constitutes the thoroughly refereed post-workshop proceedings of the 4th International Workshop on Anticipatory Behavior in Adaptive Learning Systems, ABiALS 2008, held in Munich, Germany, in June 2008, in collaboration with the six-monthly Meeting of euCognition 'The Role of Anticipation in Cognition'. The 18 revised full papers presented were carefully selected during two rounds of reviewing and improvement for inclusion in the book. The introductory chapter of this state-of-the-art survey not only provides an overview of the contributions included in this volume but also revisits the current available terminology on anticipatory behavior and relates it to the available system approaches. The papers are organized in topical sections on anticipation in psychology with focus on the ideomotor view, conceptualizations, anticipation and dynamical systems, computational modeling of psychological processes in the individual and social domains, behavioral and cognitive capabilities based on anticipation, and computational frameworks and algorithms for anticipation, and their evaluation.
Book Synopsis Deep Learning Illustrated by : Jon Krohn
Download or read book Deep Learning Illustrated written by Jon Krohn and published by Addison-Wesley Professional. This book was released on 2019-08-05 with total page 725 pages. Available in PDF, EPUB and Kindle. Book excerpt: "The authors’ clear visual style provides a comprehensive look at what’s currently possible with artificial neural networks as well as a glimpse of the magic that’s to come." – Tim Urban, author of Wait But Why Fully Practical, Insightful Guide to Modern Deep Learning Deep learning is transforming software, facilitating powerful new artificial intelligence capabilities, and driving unprecedented algorithm performance. Deep Learning Illustrated is uniquely intuitive and offers a complete introduction to the discipline’s techniques. Packed with full-color figures and easy-to-follow code, it sweeps away the complexity of building deep learning models, making the subject approachable and fun to learn. World-class instructor and practitioner Jon Krohn–with visionary content from Grant Beyleveld and beautiful illustrations by Aglaé Bassens–presents straightforward analogies to explain what deep learning is, why it has become so popular, and how it relates to other machine learning approaches. Krohn has created a practical reference and tutorial for developers, data scientists, researchers, analysts, and students who want to start applying it. He illuminates theory with hands-on Python code in accompanying Jupyter notebooks. To help you progress quickly, he focuses on the versatile deep learning library Keras to nimbly construct efficient TensorFlow models; PyTorch, the leading alternative library, is also covered. You’ll gain a pragmatic understanding of all major deep learning approaches and their uses in applications ranging from machine vision and natural language processing to image generation and game-playing algorithms. Discover what makes deep learning systems unique, and the implications for practitioners Explore new tools that make deep learning models easier to build, use, and improve Master essential theory: artificial neurons, training, optimization, convolutional nets, recurrent nets, generative adversarial networks (GANs), deep reinforcement learning, and more Walk through building interactive deep learning applications, and move forward with your own artificial intelligence projects Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.
Book Synopsis Computational Psychometrics: New Methodologies for a New Generation of Digital Learning and Assessment by : Alina A. von Davier
Download or read book Computational Psychometrics: New Methodologies for a New Generation of Digital Learning and Assessment written by Alina A. von Davier and published by Springer Nature. This book was released on 2022-01-01 with total page 265 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book defines and describes a new discipline, named “computational psychometrics,” from the perspective of new methodologies for handling complex data from digital learning and assessment. The editors and the contributing authors discuss how new technology drastically increases the possibilities for the design and administration of learning and assessment systems, and how doing so significantly increases the variety, velocity, and volume of the resulting data. Then they introduce methods and strategies to address the new challenges, ranging from evidence identification and data modeling to the assessment and prediction of learners’ performance in complex settings, as in collaborative tasks, game/simulation-based tasks, and multimodal learning and assessment tasks. Computational psychometrics has thus been defined as a blend of theory-based psychometrics and data-driven approaches from machine learning, artificial intelligence, and data science. All these together provide a better methodological framework for analysing complex data from digital learning and assessments. The term “computational” has been widely adopted by many other areas, as with computational statistics, computational linguistics, and computational economics. In those contexts, “computational” has a meaning similar to the one proposed in this book: a data-driven and algorithm-focused perspective on foundations and theoretical approaches established previously, now extended and, when necessary, reconceived. This interdisciplinarity is already a proven success in many disciplines, from personalized medicine that uses computational statistics to personalized learning that uses, well, computational psychometrics. We expect that this volume will be of interest not just within but beyond the psychometric community. In this volume, experts in psychometrics, machine learning, artificial intelligence, data science and natural language processing illustrate their work, showing how the interdisciplinary expertise of each researcher blends into a coherent methodological framework to deal with complex data from complex virtual interfaces. In the chapters focusing on methodologies, the authors use real data examples to demonstrate how to implement the new methods in practice. The corresponding programming codes in R and Python have been included as snippets in the book and are also available in fuller form in the GitHub code repository that accompanies the book.
Download or read book Deep Learning written by Ian Goodfellow and published by MIT Press. This book was released on 2016-11-10 with total page 801 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives. “Written by three experts in the field, Deep Learning is the only comprehensive book on the subject.” —Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models. Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.
Book Synopsis AI in Education by : StoryBuddiesPlay
Download or read book AI in Education written by StoryBuddiesPlay and published by StoryBuddiesPlay. This book was released on 2024-04-03 with total page 39 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unveiling the Transformative Potential of AI in Education: A Comprehensive Guide to Personalized Learning Are you ready to personalize learning for every student? This comprehensive guide explores the exciting possibilities of Artificial Intelligence (AI) in education. Discover how AI can revolutionize the classroom by tailoring instruction and curriculum to the unique needs, learning styles, and goals of each student. Move beyond the limitations of the traditional one-size-fits-all model. Learn about powerful AI-powered tools like adaptive learning platforms, intelligent tutoring systems, and virtual learning environments. See how these tools can personalize the "what" and "how" of learning, offering students targeted practice exercises, alternative explanations, and engaging learning resources. This guide doesn't shy away from the challenges. We explore ethical considerations surrounding data privacy, algorithmic bias, and the importance of human oversight. We delve into the irreplaceable role of educators in fostering social and emotional learning, while highlighting how AI can empower teachers by automating administrative tasks and providing data-driven insights. Here's what you'll find inside: The benefits of personalized learning for students and educators How AI can identify and cater to different learning styles Unveiling the power of AI-powered learning tools (adaptive platforms, intelligent tutors, virtual environments) Strategies for personalized learning beyond content (targeted practice, alternative explanations, goal setting) The evolving role of educators in the AI age (empowerment through automation, data-driven instruction) Exploring immersive learning experiences with VR and AR powered by AI Addressing equity and accessibility concerns in AI-powered education Ethical considerations: data privacy, algorithmic bias, human-AI collaboration A glimpse into the future of personalized learning: human-AI collaboration for a more engaging and effective education Whether you're an educator, parent, or student, this guide offers a roadmap for understanding and navigating the exciting new frontier of AI-powered education. Embrace the potential of AI to personalize learning and empower every student to reach their full potential!
Book Synopsis Adaptive Learning and the Human Condition by : Jeffrey C. Levy
Download or read book Adaptive Learning and the Human Condition written by Jeffrey C. Levy and published by Routledge. This book was released on 2021-09-30 with total page 405 pages. Available in PDF, EPUB and Kindle. Book excerpt: Adaptive Learning and the Human Condition provides a coherent and comprehensive introduction to the basic principles of classical (Pavlovian) and instrumental (Skinnerian) conditioning. When combined with observational learning and language, they are responsible for human accomplishment from the Stone Age to the digital age. This edition has been thoroughly updated throughout, relating adaptive learning principles to clinical applications as well as non-traditional topics such as parenting, moral development, and the helping professions. Defining learning as an adaptive process enables students to understand the need to review the basic animal research literature in classical and operant conditioning and consider how it applies to human beings in our everyday lives. Divided into four parts, this book covers historical research into psychology and adaptive learning, principles of adaptive learning (prediction and control), adaptive learning and the human condition, and behavior modification and the helping professions. The book showcases how an adaptive learning strategy can be practical, diagnostic, and prescriptive, making this an essential companion for psychology students and those enrolled in programs in professional schools and helping professions including psychiatry, special education, health psychology, and physical therapy.
Book Synopsis Learning Strategies by : Harold F. O'Neil
Download or read book Learning Strategies written by Harold F. O'Neil and published by Academic Press. This book was released on 2014-05-10 with total page 245 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learning Strategies describes a program of research in learning strategies initiated by the Defense Advanced Research Projects Agency (DARPA) in 1976. The goal of the program is to improve learning, decrease training time, and reduce training costs by developing and evaluating instructional materials designed to teach basic intellectual and affective skills. This book records the program's progress and suggests further avenues for research. Comprised of eight chapters, this book begins with an overview of the theoretical underpinnings of the teaching and learning approaches to the improvement of education, followed by a discussion on DARPA's preliminary work on an empirically based learning-strategy training program as well as its efforts to expand and modify the program. In order to provide an intellectual foundation for this program, several fields are surveyed for potential learning strategies, namely, cognitive psychology, artificial intelligence, behavioral modification, and motor learning. An instructional systems development approach for learning strategies is also proposed. The final chapter deals with models of evaluation extant in education and training and discusses the specific application of transactional evaluation to the DARPA Learning Strategies Research Program. This monograph should be of interest to students, teachers, and educational psychologists.
