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Artificial intelligence research connected with learning theory ("deep learning," “machine learning,” analysis of the quality of learning, etc.) has existed for many years; however, there have been few investigations in that area conducted from a robust philosophical methodological basis.
This book represents the experience of successful researchers from four continents on a broad range of intelligent systems, and it hints how to avoid anticipated conflicts and problems during multidisciplinary innovative research from Industry 4.0 and/or Internet of Things through modern machine learning, and software agent applications to open data science big data/advance analytics/visual analytics/text mining/web mining/knowledge discovery/deep data mining issues. The considered intelligent part is essential in most smart/control systems, cyber security, bioinformatics, virtual reality, robotics, mathematical modelling projects, and its significance rapidly increases in other technologies. Theoretical foundations of fuzzy sets, mathematical and non-classical logic also are rapidly developing.
Artificial Intelligence and Scientific Method examines the remarkable advances made in the field of AI over the past twenty years, discussing their profound implications for philosophy. Taking a clear, non-technical approach, Donald Gillies shows how current views on scientific method are challenged by this recent research, and suggests a new framework for the study of logic. Finally, he draws on work by such seminal thinkers as Bacon, Gödel, Popper, Penrose, and Lucas, to address the hotly contested question of whether computers might become intellectually superior to human beings.
The new edition of the authoritative book in the field of adult education — fully revised to reflect the latest research and practice implications. For nearly three decades, Learning in Adulthood has been the definitive guide in the field of adult education. Now in its fourth edition, this comprehensive volume is fully revised to reflect the latest developments in theory, research, and practice. The authors integrate foundational research and current knowledge to present fresh, original perspectives on teaching and learning in adulthood. Written by internationally-recognized experts, this market-leading guide draws from work in sociology, philosophy, critical social theory, psychology, and education to provide an inclusive overview of adult learning. Designed primarily for educators of adults, this book is accessible for readers new to adult education, yet suitably rigorous for those more familiar with the subject. Content is organized into four practical parts, covering topics such as the social context of adult learning, self-directed and transformational learning, postmodern and feminist perspectives, cognitive development in adulthood, and more. Offering the most comprehensive single-volume treatment of adult learning available, this landmark text: Offers a wide-ranging perspective on adult learning Synthesizes the latest thinking and work in the field Includes coverage of the sociocultural perspectives of adult learning Explores the broader social implications of adult education Learning in Adulthood: A Comprehensive Guide, 4th Edition is an indispensable resource for educators and administrators involved in teaching adults, as well as faculty and students in graduate programs in adult education.
Can we make machines that think and act like humans or other natural intelligent agents? The answer to this question depends on how we see ourselves and how we see the machines in question. Classical AI and cognitive science had claimed that cognition is computation, and can thus be reproduced on other computing machines, possibly surpassing the abilities of human intelligence. This consensus has now come under threat and the agenda for the philosophy and theory of AI must be set anew, re-defining the relation between AI and Cognitive Science. We can re-claim the original vision of general AI from the technical AI disciplines; we can reject classical cognitive science and replace it with a new theory (e.g. embodied); or we can try to find new ways to approach AI, for example from neuroscience or from systems theory. To do this, we must go back to the basic questions on computing, cognition and ethics for AI. The 30 papers in this volume provide cutting-edge work from leading researchers that define where we stand and where we should go from here.
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.
Whilst most teachers are skilled in providing opportunities for the progression of children’s learning, it is often without fully understanding the theory behind it. With greater insight into what is currently known about the processes of learning and about individual learning preferences, teachers are better equipped to provide effective experiences and situations which are more likely to lead to lasting attainment. Now fully updated, Ways of Learning seeks to provide an understanding of the ways in which learning takes place, which teachers can make use of in their planning and teaching, including: An overview of learning Behaviourism and the beginning of theory Cognitive and constructivist learning Multiple intelligences Learning styles Difficulties with learning The influence of neuro-psychology Relating theory to practice The third edition of this book includes developments in areas covered in the first and second editions, as well as expanding on certain topics to bring about a wider perspective; most noticeably a newly updated and fully expanded chapter on the influence of neuro-educational research. The book also reflects changes in government policy and is closely related to new developments in practice. Written for trainee teachers, serving teachers, and others interested in learning for various reasons, Ways of Learning serves as a valuable introduction for students setting out on higher degree work who are in need of an introduction to the topic.
As the educational system continues to evolve, it is essential that educators of today devise innovative and strategic approaches to program development and assessment. The Handbook of Research on Program Development and Assessment Methodologies in K-20 Education is an essential reference source for the latest terminology and concepts related to program development. Featuring extensive coverage on a broad range of topics such as cognitive diagnostic assessments, self-directed learning, and digital education, this publication is ideally designed for educators, students, program designers, and librarians seeking current research on inventive strategies and practices to enhance education in the 21st century.
"The landscape for education has been rapidly changing in the last years: demographic changes affecting the makeup of families, multiple school options available to children, wealth disparities, the global economy demanding new skills from workers, and continued breakthroughs in technology are some of the factors impacting education. Given these changes, how can schools continue to prepare students for the future? In a world where information is readily available online, how can schools continue to be relevant? The emergence of Artificial Intelligence (AI) has exacerbated the need to have these conversations. Its impact on education and the multiple possibilities that it offers are putting pressure on educational leaders to reformulate the school curriculum and the channels to deliver it. The book "Artificial Intelligence in Education, Promises and Implications for Teaching and Learning" by the Center for Curriculum Redesign immerses the reader in a discussion on what to teach students in the era of AI and examines how AI is already demanding much needed updates to the school curriculum, including modernizing its content, focusing on core concepts, and embedding interdisciplinary themes and competencies with the end goal of making learning more enjoyable and useful in students' lives. The second part of the book dives into the history of AI in education, its techniques and applications -including the way AI can help teachers be more effective, and finishes on a reflection about the social aspects of AI. This book is a must-read for educators and policy-makers who want to prepare schools to face the uncertainties of the future and keep them relevant." --Amada Torres, VP, Studies, Insights, and Research, National Association of Independent School (NAIS) "The rapid advances in technology in recent decades have already brought about substantial changes in education, opening up new opportunities to teach and learn anywhere anytime and providing new tools and methods to improve learning outcomes and support innovative teaching and learning.Research into artificial intelligence and machine learning in education goes back to the late 1970s. Artificial intelligence methods were generally employed in two ways: to design and facilitate interactive learning environments that would support learning by doing, and to design and implement tutoring systems by adapting instructions with respect to the students' knowledge state.But this is just the beginning. As Artificial Intelligence in Education shows, AI is increasingly used in education and learning contexts. The collision of three areas - data, computation and education - is set to have far-reaching consequences, raising fundamental questions about the nature of education: what is taught and how it is taught. Artificial Intelligence in Education is an important, if at times disturbing, contribution to the debate on AI and provides a detailed analysis on how it may affect the way teachers and students engage in education. The book describes how artificial intelligence may impact on curriculum design, on the individualisation of learning, and on assessment, offering some tantalising glimpses into the future (the end of exams, your very own lifelong learning companion) while not falling victim to tech-hype. The enormous ethical, technical and pedagogical challenges ahead are spelt out, and there is a real risk that the rapid advances in artificial intelligence products and services will outstrip education systems' capacity to understand, manage and integrate them appropriately. As the book concludes: "We can either leave it to others (the computer scientists, AI engineers and big tech companies) to decide how artificial intelligence in education unfolds, or we can engage in productive dialogue."I commend this book to anyone concerned with the future of education in a digital world." --Marc Durando, Executive Director, European Schoolnet
This book seeks to provide new perspectives, to broaden the field of philosophy of science, or to renew themes that have had a great impact on the profession. Thus, after an initial chapter to situate the current trends in philosophy of science and the prospective of the near future, it offers contributions in five thematic blocks: I) Philosophy of Medicine and Climate Change; II) Philosophy of Artificial Intelligence and the Internet; III) New Analyses of Probability and the Use of Mathematics in Practice; IV) Scientific Progress Revisited; and V) Scientific Realism and the Instrumentalist Alternative. Within this framework, the volume addresses such relevant issues as the methodological validity of medical evidence or decision making in situations of uncertainty; recent advances in Artificial Intelligence and the future of the Internet; current forms of empirically based methodological pluralism and new ways of understanding mathematics with scientific practice; and the revision of the approaches to scientific progress based on the experiences accumulated in recent decades.