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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 Intelligent and Adaptive Educational-Learning Systems by : Alejandro Peña-Ayala
Download or read book Intelligent and Adaptive Educational-Learning Systems written by Alejandro Peña-Ayala and published by Springer Science & Business Media. This book was released on 2012-08-10 with total page 522 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Addressing Maladaptive Behaviors from AI Integration in Learning by : KHRITISH SWARGIARY
Download or read book Addressing Maladaptive Behaviors from AI Integration in Learning written by KHRITISH SWARGIARY and published by EdTech Research Association, US. This book was released on 2024-08-01 with total page 110 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years, the integration of Artificial Intelligence (AI) into educational systems has marked a transformative shift in how learning is delivered and experienced. AI technologies, ranging from intelligent tutoring systems to adaptive learning platforms, offer unprecedented opportunities for personalized and efficient education. However, this rapid evolution also brings new challenges, particularly concerning students' behavioral and emotional well-being. The purpose of this book is to explore the complex interplay between AI and maladaptive behaviors in educational settings. While AI has the potential to revolutionize education by tailoring learning experiences to individual needs, it also has the capacity to influence student behavior in ways that may be detrimental to their overall development. As educators, policymakers, and researchers, it is crucial to understand and address these potential impacts to create a more supportive and balanced learning environment.
Book Synopsis The Deep Learning AI Playbook by : Carlos Perez
Download or read book The Deep Learning AI Playbook written by Carlos Perez and published by Lulu.com. This book was released on 2017-10-11 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: Just like any new technology, what perplexes many is the question of how to apply Deep Learning in a business context. Technology that is disruptive does not automatically imply that the development of valuable use cases are apparent. For years, many people could not figure out how to monetize the World Wide Web. We are in that same situation with Deep Learning AI. The developments are mind-boggling but the monetization is far from being obvious.Deep Learning Artificial Intelligence involves the interplay of Computer Science, Physics, Biology, Linguistics and Psychology. In addition to that, it is technology that can be extremely disruptive. Furthermore, the ramifications to society and even our own humanity can be immense. There are few subjects that are as captivating and as consequential as this. Surprisingly, there is very little that is written about this new technology in a more comprehensive and cohesive way. This book is an opinionated take on the developments of Deep Learning AI.
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. This book was released on 2020-01-04 with total page 240 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 AI Algorithms and ChatGPT for Student Engagement in Online Learning by : Bansal, Rohit
Download or read book AI Algorithms and ChatGPT for Student Engagement in Online Learning written by Bansal, Rohit and published by IGI Global. This book was released on 2024-05-28 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: The shift to virtual education has presented numerous challenges, including maintaining student focus and participation. Traditional methods of instruction often need to catch up in capturing the attention of digital learners, leading to disengagement and reduced learning outcomes. However, there is a solution at hand. AI Algorithms and ChatGPT for Student Engagement in Online Learning offers a comprehensive approach to leveraging artificial intelligence (AI) algorithms and ChatGPT to enhance student engagement in digital classrooms. This book addresses the pressing need for innovative strategies to keep students actively involved in their online learning journey. By harnessing the power of AI algorithms, educators can personalize learning paths to suit individual student needs, ensuring that content is relevant and engaging. Additionally, ChatGPT serves as a virtual assistant, providing students with instant feedback and support, fostering a sense of connection to the learning process.
Book Synopsis Data Analytics and Adaptive Learning by : Patsy D. Moskal
Download or read book Data Analytics and Adaptive Learning written by Patsy D. Moskal and published by Taylor & Francis. This book was released on 2023-08-25 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Analytics and Adaptive Learning offers new insights into the use of emerging data analysis and adaptive techniques in multiple learning settings. In recent years, both analytics and adaptive learning have helped educators become more responsive to learners in virtual, blended, and personalized environments. This set of rich, illuminating, international studies spans quantitative, qualitative, and mixed-methods research in higher education, K–12, and adult/continuing education contexts. By exploring the issues of definition and pedagogical practice that permeate teaching and learning and concluding with recommendations for the future research and practice necessary to support educators at all levels, this book will prepare researchers, developers, and graduate students of instructional technology to produce evidence for the benefits and challenges of data-driven learning.
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 Deep Learning Manual by : Paul Stephen Prueitt
Download or read book Deep Learning Manual written by Paul Stephen Prueitt and published by Independently Published. This book was released on 2020-06-10 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: This latest volume in the Deep Learning Manual series presents an architecture and roadmap for implementing, on a nationwide basis, a deep learning-based education platform. The proposed platform combines adaptive learning software and behavioral neuroscience in a unique and powerful way. The author's motivation for this approach comes from decades of observing classroom behaviors that limit rather than advance our individual and collective capacity for self-discovery. Many of these behaviors reinforce longstanding inequalities. Education need not be difficult in our current age, regardless of a person's socio-economic background. Much of the basis for students' struggles, especially in college-level mathematics, is the over-emphasis on rote memorization at the expense of understanding the topics in ways that make sense to the individual student. For this reason, sense-making tools and practices form a key aspect of the proposed platform. Prueitt's approach is based on the premise of having a "sense of location" as a student navigates a "knowledge space" of topics, moving from those that are "comfortable" to those that are "uncomfortable." This book paints both a vision and a roadmap to the future, where first principles of science and mathematics are communicated through a "learning medium" that builds upon traditional books and research publications. The goal is to create a national and even global network of knowledge media that improves an average citizen's capacity for lifelong learning. Design Principles is richly illustrated with anonymized images of real handwritten narratives from freshman college mathematics students who have gone from struggling with and disdain toward the subject to feeling knowledgeable and empowered to apply the learned principles in future classes, work, and life.
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 Proceedings of TEEM 2023 by : José Alexandre de Carvalho Gonçalves
Download or read book Proceedings of TEEM 2023 written by José Alexandre de Carvalho Gonçalves and published by Springer Nature. This book was released on with total page 1513 pages. Available in PDF, EPUB and Kindle. Book excerpt:
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 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 AI and education by : Miao, Fengchun
Download or read book AI and education written by Miao, Fengchun and published by UNESCO Publishing. This book was released on 2021-04-08 with total page 50 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence (AI) has the potential to address some of the biggest challenges in education today, innovate teaching and learning practices, and ultimately accelerate the progress towards SDG 4. However, these rapid technological developments inevitably bring multiple risks and challenges, which have so far outpaced policy debates and regulatory frameworks. This publication offers guidance for policy-makers on how best to leverage the opportunities and address the risks, presented by the growing connection between AI and education. It starts with the essentials of AI: definitions, techniques and technologies. It continues with a detailed analysis of the emerging trends and implications of AI for teaching and learning, including how we can ensure the ethical, inclusive and equitable use of AI in education, how education can prepare humans to live and work with AI, and how AI can be applied to enhance education. It finally introduces the challenges of harnessing AI to achieve SDG 4 and offers concrete actionable recommendations for policy-makers to plan policies and programmes for local contexts. [Publisher summary, ed]
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 Deep Learning, Reinforcement Learning, and the Rise of Intelligent Systems by : Uddin, M. Irfan
Download or read book Deep Learning, Reinforcement Learning, and the Rise of Intelligent Systems written by Uddin, M. Irfan and published by IGI Global. This book was released on 2024-02-26 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: The applications of rapidly advancing intelligent systems are so varied that many are still yet to be discovered. There is often a disconnect between experts in computer science, artificial intelligence, machine learning, robotics, and other specialties, which inhibits the potential for the expansion of this technology and its many benefits. A resource that encourages interdisciplinary collaboration is needed to bridge the gap between these respected leaders of their own fields. Deep Learning, Reinforcement Learning, and the Rise of Intelligent Systems represents an exploration of the forefront of artificial intelligence, navigating the complexities of this field and its many applications. This guide expertly navigates through the intricate domains of deep learning and reinforcement learning, offering an in-depth journey through foundational principles, advanced methodologies, and cutting-edge algorithms shaping the trajectory of intelligent systems. The book covers an introduction to artificial intelligence and its subfields, foundational aspects of deep learning, a demystification of the architecture of neural networks, the mechanics of backpropagation, and the intricacies of critical elements such as activation and loss functions. The book serves as a valuable educational resource for professionals. Its structured approach makes it an ideal reference for students, researchers, and industry professionals.
Book Synopsis Grokking Deep Reinforcement Learning by : Miguel Morales
Download or read book Grokking Deep Reinforcement Learning written by Miguel Morales and published by Manning Publications. This book was released on 2020-11-10 with total page 470 pages. Available in PDF, EPUB and Kindle. Book excerpt: Grokking Deep Reinforcement Learning uses engaging exercises to teach you how to build deep learning systems. This book combines annotated Python code with intuitive explanations to explore DRL techniques. You’ll see how algorithms function and learn to develop your own DRL agents using evaluative feedback. Summary We all learn through trial and error. We avoid the things that cause us to experience pain and failure. We embrace and build on the things that give us reward and success. This common pattern is the foundation of deep reinforcement learning: building machine learning systems that explore and learn based on the responses of the environment. Grokking Deep Reinforcement Learning introduces this powerful machine learning approach, using examples, illustrations, exercises, and crystal-clear teaching. You'll love the perfectly paced teaching and the clever, engaging writing style as you dig into this awesome exploration of reinforcement learning fundamentals, effective deep learning techniques, and practical applications in this emerging field. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology We learn by interacting with our environment, and the rewards or punishments we experience guide our future behavior. Deep reinforcement learning brings that same natural process to artificial intelligence, analyzing results to uncover the most efficient ways forward. DRL agents can improve marketing campaigns, predict stock performance, and beat grand masters in Go and chess. About the book Grokking Deep Reinforcement Learning uses engaging exercises to teach you how to build deep learning systems. This book combines annotated Python code with intuitive explanations to explore DRL techniques. You’ll see how algorithms function and learn to develop your own DRL agents using evaluative feedback. What's inside An introduction to reinforcement learning DRL agents with human-like behaviors Applying DRL to complex situations About the reader For developers with basic deep learning experience. About the author Miguel Morales works on reinforcement learning at Lockheed Martin and is an instructor for the Georgia Institute of Technology’s Reinforcement Learning and Decision Making course. Table of Contents 1 Introduction to deep reinforcement learning 2 Mathematical foundations of reinforcement learning 3 Balancing immediate and long-term goals 4 Balancing the gathering and use of information 5 Evaluating agents’ behaviors 6 Improving agents’ behaviors 7 Achieving goals more effectively and efficiently 8 Introduction to value-based deep reinforcement learning 9 More stable value-based methods 10 Sample-efficient value-based methods 11 Policy-gradient and actor-critic methods 12 Advanced actor-critic methods 13 Toward artificial general intelligence
