AI and Cognitive Modelling for Education
Title | AI and Cognitive Modelling for Education PDF eBook |
Author | Boris Aberšek |
Publisher | Springer Nature |
Total Pages | 236 |
Release | 2023-07-30 |
Genre | Education |
ISBN | 3031353315 |
This book offers a groundbreaking approach to bridging the gap between various disciplines involved in cognitive modeling in education. By drawing on the fields of learning, neuro science, cognitive science, neurobiology, and computer science, it provides a new perspective on how we can integrate these disciplines with education to create more effective learning environments. The main objective of this book is to delve into the ethical, sociological, and technological questions surrounding the introduction of intelligent and smart learning environments in education. By analyzing these issues, this book aims to bridge the gap between the various disciplines involved in cognitive modeling and education, while highlighting the benefits and risks associated with these advancements. With the emergence of AI-based tutors, coaches, and learning environments, students now have access to a new type of self-learning and self-training that was previously unavailable. Distance learning has become increasingly popular in recent years, and the use of computer-assisted learning tools has revolutionized the way we think about education. The goal of education must be to instill in students a desire to learn for themselves, and this can only be achieved through active, self-directed, and reflective learning. With intelligent tutoring systems, students are empowered to take an active role in their own education, rather than simply being passive recipients of information. This book offers practical strategies for teachers to facilitate this transition, enabling them to act as facilitators and guides rather than one-way communicators. By embracing this new approach to education, we can help students become lifelong learners who are equipped with the skills they need to succeed in the 21st century. As we cannot predict the future with certainty, the true effects of education may only be revealed in the long run, making it critical to understand the potential consequences of introducing these new learning tools. By exploring these complex topics, this book offers valuable insights for educators, policymakers, and anyone interested in the future of education.
AI and education
Title | AI and education PDF eBook |
Author | Miao, Fengchun |
Publisher | UNESCO Publishing |
Total Pages | 50 |
Release | 2021-04-08 |
Genre | Political Science |
ISBN | 9231004476 |
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]
Artificial Intelligence in Education
Title | Artificial Intelligence in Education PDF eBook |
Author | Vania Dimitrova |
Publisher | IOS Press |
Total Pages | 852 |
Release | 2009 |
Genre | Computers |
ISBN | 1607500280 |
Artificial Intelligence in Education conference 2009 (AIED) is part of a series of biennial international conferences for top quality research in intelligent systems and cognitive science for educational computing applications. This title covers papers presented at the Artificial Intelligence in Education conference 2009 (AIED).
Applied Biomedical Engineering Using Artificial Intelligence and Cognitive Models
Title | Applied Biomedical Engineering Using Artificial Intelligence and Cognitive Models PDF eBook |
Author | Jorge Garza Ulloa |
Publisher | Elsevier |
Total Pages | 705 |
Release | 2021-11-30 |
Genre | Science |
ISBN | 0128209348 |
Applied Biomedical Engineering Using Artificial Intelligence and Cognitive Models focuses on the relationship between three different multidisciplinary branches of engineering: Biomedical Engineering, Cognitive Science and Computer Science through Artificial Intelligence models. These models will be used to study how the nervous system and musculoskeletal system obey movement orders from the brain, as well as the mental processes of the information during cognition when injuries and neurologic diseases are present in the human body. The interaction between these three areas are studied in this book with the objective of obtaining AI models on injuries and neurologic diseases of the human body, studying diseases of the brain, spine and the nerves that connect them with the musculoskeletal system. There are more than 600 diseases of the nervous system, including brain tumors, epilepsy, Parkinson's disease, stroke, and many others. These diseases affect the human cognitive system that sends orders from the central nervous system (CNS) through the peripheral nervous systems (PNS) to do tasks using the musculoskeletal system. These actions can be detected by many Bioinstruments (Biomedical Instruments) and cognitive device data, allowing us to apply AI using Machine Learning-Deep Learning-Cognitive Computing models through algorithms to analyze, detect, classify, and forecast the process of various illnesses, diseases, and injuries of the human body. Applied Biomedical Engineering Using Artificial Intelligence and Cognitive Models provides readers with the study of injuries, illness, and neurological diseases of the human body through Artificial Intelligence using Machine Learning (ML), Deep Learning (DL) and Cognitive Computing (CC) models based on algorithms developed with MATLAB® and IBM Watson®. Provides an introduction to Cognitive science, cognitive computing and human cognitive relation to help in the solution of AI Biomedical engineering problems Explain different Artificial Intelligence (AI) including evolutionary algorithms to emulate natural evolution, reinforced learning, Artificial Neural Network (ANN) type and cognitive learning and to obtain many AI models for Biomedical Engineering problems Includes coverage of the evolution Artificial Intelligence through Machine Learning (ML), Deep Learning (DL), Cognitive Computing (CC) using MATLAB® as a programming language with many add-on MATLAB® toolboxes, and AI based commercial products cloud services as: IBM (Cognitive Computing, IBM Watson®, IBM Watson Studio®, IBM Watson Studio Visual Recognition®), and others Provides the necessary tools to accelerate obtaining results for the analysis of injuries, illness, and neurologic diseases that can be detected through the static, kinetics and kinematics, and natural body language data and medical imaging techniques applying AI using ML-DL-CC algorithms with the objective of obtaining appropriate conclusions to create solutions that improve the quality of life of patients
Artificial Intelligence in Education
Title | Artificial Intelligence in Education PDF eBook |
Author | Wayne Holmes |
Publisher | |
Total Pages | 244 |
Release | 2019-02-28 |
Genre | Computers |
ISBN | 9781794293700 |
"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
Computers As Cognitive Tools
Title | Computers As Cognitive Tools PDF eBook |
Author | Susanne P. Lajoie |
Publisher | Routledge |
Total Pages | 413 |
Release | 2013-05-13 |
Genre | Education |
ISBN | 1136475478 |
Highlighting and illustrating several important and interesting theoretical trends that have emerged in the continuing development of instructional technology, this book's organizational framework is based on the notion of two opposing camps. One evolves out of the intelligent tutoring movement, which employs artificial-intelligence technologies in the service of student modeling and precision diagnosis, and the other emerges from a constructivist/developmental perspective that promotes exploration and social interaction, but tends to reject the methods and goals of the student modelers. While the notion of opposing camps tends to create an artificial rift between groups of researchers, it represents a conceptual distinction that is inherently more interesting and informative than the relatively meaningless divide often drawn between "intelligent" and "unintelligent" instructional systems. An evident trend is that researchers in both "camps" view their computer learning environments as "cognitive tools" that can enhance learning, performance, and understanding. Cognitive tools are objects provided by the instructional environment that allow students to incorporate new auxiliary methods or symbols into their social problem solving which otherwise would be unavailable. A final section of the book represents researchers who are assimilating and accommodating the wisdom and creativity of their neighbors from both camps, perhaps forming the look of technology for the future. When the idea of model tracing in a computer-based environment is combined with appreciation for creative mind-extension cognitive tools and for how a community of learners can facilitate learning, a camp is created where AI technologists and social constructivist learning theorists can feel equally at home.
In Order to Learn
Title | In Order to Learn PDF eBook |
Author | Frank E. Ritter |
Publisher | Oxford University Press |
Total Pages | 255 |
Release | 2007-07-30 |
Genre | Computers |
ISBN | 019517884X |
In Order to Learn shows how order effects are crucial in human learning, instructional design, machine learning, and both symbolic and connectionist cognitive models. Each chapter explains a different aspect of how the order in which material is presented can strongly influence what is learned by humans and theoretical models of learning in a variety of domains. In addition to data, models are provided that predict and describe order effects and analyze how and when they will occur.