Advanced Intelligent Systems for Sustainable Development (AI2SD’2019)

Advanced Intelligent Systems for Sustainable Development (AI2SD’2019) PDF

Author: Mostafa Ezziyyani

Publisher: Springer

Published: 2020-01-04

Total Pages: 240

ISBN-13: 9783030366520

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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.

Intelligent and Adaptive Educational-Learning Systems

Intelligent and Adaptive Educational-Learning Systems PDF

Author: Alejandro Peña-Ayala

Publisher: Springer Science & Business Media

Published: 2012-08-10

Total Pages: 522

ISBN-13: 3642301711

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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.

Data Analytics and Adaptive Learning

Data Analytics and Adaptive Learning PDF

Author: Patsy D. Moskal

Publisher: Taylor & Francis

Published: 2023-08-25

Total Pages: 364

ISBN-13: 100092923X

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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.

Deep Learning Manual

Deep Learning Manual PDF

Author: Paul Stephen Prueitt

Publisher: Independently Published

Published: 2020-06-10

Total Pages: 316

ISBN-13:

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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.

Learning for Adaptive and Reactive Robot Control

Learning for Adaptive and Reactive Robot Control PDF

Author: Aude Billard

Publisher: MIT Press

Published: 2022-02-08

Total Pages: 425

ISBN-13: 0262367017

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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.

Innovative Learning Environments in STEM Higher Education

Innovative Learning Environments in STEM Higher Education PDF

Author: Jungwoo Ryoo

Publisher: Springer Nature

Published: 2021-03-11

Total Pages: 148

ISBN-13: 303058948X

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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.