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| examples of ai in education: AI and education Miao, Fengchun, Holmes, Wayne, Ronghuai Huang, Hui Zhang, UNESCO, 2021-04-08 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] |
| examples of ai in education: Artificial Intelligence in Education Wayne Holmes, Maya Bialik, Charles Fadel, 2019-02-28 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 |
| examples of ai in education: AI for School Teachers Rose Luckin, Karine George, Mutlu Cukurova, 2022-04-07 What is artificial intelligence? Can I realistically use it in my school? What’s best done by human intelligence vs. artificial intelligence, and how do I bring these strengths together? What would it look like for me, and my school, to be AI Ready? AI for School Teachers will help teachers and headteachers understand enough about AI to build a strategy for how it can be used in their school. Examining the needs of schools to ensure they are ready to leverage the power of AI and drawing examples from early years to high school students, this book outlines the educational implications and benefits that AI brings to school education in practical ways. It develops an understanding of what AI is and isn't and how we define and measure what we value and provides a framework which supports a step-by-step approach to developing an AI mindset, focusing on ways to improve educational opportunities for students with evidence-informed interventions. |
| examples of ai in education: Business Trends in Practice Bernard Marr, 2021-11-15 WINNER OF THE BUSINESS BOOK OF THE YEAR AWARD 2022! Stay one step ahead of the competition with this expert review of the most impactful and disruptive business trends coming down the pike Far from slowing down, change and transformation in business seems to come only at a more and more furious rate. The last ten years alone have seen the introduction of groundbreaking new trends that pose new opportunities and challenges for leaders in all industries. In Business Trends in Practice: The 25+ Trends That Are Redefining Organizations, best-selling business author and strategist Bernard Marr breaks down the social and technological forces underlying these rapidly advancing changes and the impact of those changes on key industries. Critical consumer trends just emerging today—or poised to emerge tomorrow—are discussed, as are strategies for rethinking your organisation’s product and service delivery. The book also explores: Crucial business operations trends that are changing the way companies conduct themselves in the 21st century The practical insights and takeaways you can glean from technological and social innovation when you cut through the hype Disruptive new technologies, including AI, robotic and business process automation, remote work, as well as social and environmental sustainability trends Business Trends in Practice: The 25+ Trends That Are Redefining Organizations is a must-read resource for executives, business leaders and managers, and business development and innovation leads trying to get – and stay – on top of changes and disruptions that are right around the corner. |
| examples of ai in education: OECD Digital Education Outlook 2021 Pushing the Frontiers with Artificial Intelligence, Blockchain and Robots OECD, 2021-06-08 How might digital technology and notably smart technologies based on artificial intelligence (AI), learning analytics, robotics, and others transform education? This book explores such question. It focuses on how smart technologies currently change education in the classroom and the management of educational organisations and systems. |
| examples of ai in education: Teaching AI Michelle Zimmerman, 2018-12-15 Get the tools, resources and insights you need to explore artificial intelligence in the classroom and explore what students need to know about living in a world with AI. For many, artificial intelligence, or AI, may seem like science fiction, or inherently overwhelming. The reality is that AI is already being applied in industry and, for many of us, in our daily lives as well. A better understanding of AI can help you make informed decisions in the classroom that will impact the future of your students. Drawing from a broad variety of expert voices from countries including Australia, Japan, and South Africa, as well as educators from around the world and underrepresented student voices, this book explores some of the ways AI can improve education. These include educating learners about AI, teaching them about living in a world where they will be surrounded by AI and helping educators understand how they can use AI to augment human ability. Each chapter offers activities and questions to help you deepen your understanding, try out new concepts and reflect on the information presented. Links to media artifacts from trusted sources will help make your learning experience more dynamic while also providing additional resources to use in your classroom. This book: • Offers a unique approach to the topic, with chapter opening scenes, case studies, and featured student voices. • Discusses a variety of ways to teach students about AI, through design thinking, project-based learning and STEM connections. • Includes lesson ideas, activities and tools for exploring AI with your students. • Includes references to films and other media you can use in class to start discussions on AI or inspire design thinking and STEM projects. In Teaching AI, you’ll learn what AI is, how it works and how to use it to better prepare students in a world with increased human-computer interaction. |
| examples of ai in education: Artificial Intelligence and Inclusive Education Jeremy Knox, Yuchen Wang, Michael Gallagher, 2019-06-13 This book brings together the fields of artificial intelligence (often known as A.I.) and inclusive education in order to speculate on the future of teaching and learning in increasingly diverse social, cultural, emotional, and linguistic educational contexts. This book addresses a pressing need to understand how future educational practices can promote equity and equality, while at the same time adopting A.I. systems that are oriented towards automation, standardisation and efficiency. The contributions in this edited volume appeal to scholars and students with an interest in forming a critical understanding of the development of A.I. for education, as well as an interest in how the processes of inclusive education might be shaped by future technologies. Grounded in theoretical engagement, establishing key challenges for future practice, and outlining the latest research, this book offers a comprehensive overview of the complex issues arising from the convergence of A.I. technologies and the necessity of developing inclusive teaching and learning. To date, there has been little in the way of direct association between research and practice in these domains: A.I. has been a predominantly technical field of research and development, and while intelligent computer systems and ‘smart’ software are being increasingly applied in many areas of industry, economics, social life, and education itself, a specific engagement with the agenda of inclusion appears lacking. Although such technology offers exciting possibilities for education, including software that is designed to ‘personalise’ learning or adapt to learner behaviours, these developments are accompanied by growing concerns about the in-built biases involved in machine learning techniques driven by ‘big data’. |
| examples of ai in education: Rewiring Education John D. Couch, 2023-01-03 What if we could unlock the potential in every child? As it turns out, we can. Apple's iconic cofounder Steve Jobs had a powerful vision for education: employing technology to make an enormous impact on the lives of millions of students. To realize this vision, Jobs tapped John D. Couch, a trusted engineer and executive with a passion for education. Couch believed the real purpose of education was to help children discover their unique potential and empower them to reach beyond their perceived limitations. Today, technology is increasingly integrated into every aspect of our lives, rewiring our homes, our jobs, and even our brains. Most important, it presents an opportunity to rewire education to enrich and strengthen our schools, children, and society In Rewiring Education, Couch shares the professional lessons he's learned during his 50-plus years in education and technology. He takes us behind Apple's major research study, Apple Classrooms of Tomorrow (ACOT), and its follow-up (ACOT 2), highlighting the powerful effects of the Challenge-Based Learning framework. Going beyond Apple's walls, he also introduces us to some of the most extraordinary parents, educators, and entrepreneurs from around the world who have ignored the failed promises of memorization and, instead, utilize new science-backed methods and technologies that benefit all children, from those who struggle to honor students. Rewiring Education presents a bold vision for the future of education, looking at promising emerging technologies and how we—as parents, teachers, and voters—can ensure children are provided with opportunities and access to the relevant, creative, collaborative, and challenging learning environments they need to succeed. |
| examples of ai in education: Artificial Intelligence in Education Matthew N.O. Sadiku, Sarhan M. Musa, Uwakwe C. Chukwu, 2022-01-27 The quest for building an artificial brain developed in the fields of computer science and psychology. Artificial intelligence (AI), sometimes called machine intelligence, refers to intelligence demonstrated by machines, while the natural intelligence is the intelligence displayed by humans and animals. Typically, AI systems demonstrate at least some of the following human behaviors: planning, learning, reasoning, problem solving, knowledge representation, perception, speech recognition, decision-making, language translation, motion, manipulation, intelligence, and creativity. Artificial intelligence is an emerging technology which the educational sector can benefit from. In this book, we consider the applications of AI in key areas of education. Artificial intelligence in education (AIED) refers to the application of AI technologies in educational settings to facilitate teaching, learning, or decision making. AI will impact the education field in the areas of administration, instruction, and personalized, and individualized learning applications. In this book, AI is specifically applied in the following key educational sectors: education, natural sciences, social sciences, computer science, engineering, business, and medicine. |
| examples of ai in education: Artificial Intelligence in Practice Bernard Marr, 2019-04-15 Cyber-solutions to real-world business problems Artificial Intelligence in Practice is a fascinating look into how companies use AI and machine learning to solve problems. Presenting 50 case studies of actual situations, this book demonstrates practical applications to issues faced by businesses around the globe. The rapidly evolving field of artificial intelligence has expanded beyond research labs and computer science departments and made its way into the mainstream business environment. Artificial intelligence and machine learning are cited as the most important modern business trends to drive success. It is used in areas ranging from banking and finance to social media and marketing. This technology continues to provide innovative solutions to businesses of all sizes, sectors and industries. This engaging and topical book explores a wide range of cases illustrating how businesses use AI to boost performance, drive efficiency, analyse market preferences and many others. Best-selling author and renowned AI expert Bernard Marr reveals how machine learning technology is transforming the way companies conduct business. This detailed examination provides an overview of each company, describes the specific problem and explains how AI facilitates resolution. Each case study provides a comprehensive overview, including some technical details as well as key learning summaries: Understand how specific business problems are addressed by innovative machine learning methods Explore how current artificial intelligence applications improve performance and increase efficiency in various situations Expand your knowledge of recent AI advancements in technology Gain insight on the future of AI and its increasing role in business and industry Artificial Intelligence in Practice: How 50 Successful Companies Used Artificial Intelligence to Solve Problems is an insightful and informative exploration of the transformative power of technology in 21st century commerce. |
| examples of ai in education: Educational Design Research Jan Van den Akker, Koeno Gravemeijer, Susan McKenney, Nienke Nieveen, 2006-11-22 The field of design research has been gaining momentum over the last five years, particularly in educational studies. As papers and articles have grown in number, definition of the domain is now beginning to standardise. This book fulfils a growing need by providing a synthesised assessment of the use of development research in education. It looks at four main elements: background information including origins, definitions of development research, description of applications and benefits and risks associated with studies of this kind how the approach can serve the design of learning environments and educational technology quality assurance - how to safeguard academic rigor while conducting design and development studies a synthesis and overview of the topic along with relevant reflections. |
| examples of ai in education: AI in Education: A step-by-step Guide for Teachers and Students Mr. Jawahar Sri Prakash Thiyagarajan, (Neuroscience, UK), Dr. Jeyashree Swaminathan, M.A., M.Ed., MLIS, M.Phil., Ph.D.,, Dr. Thiyagarajan Sivaprakasam, M.Sc., Ph.D.,, 2024-10-15 AI in Education: A Step-by-Step Guide for Teachers and Students is an essential resource for educators and students seeking to understand and implement artificial intelligence (AI) in modern educational settings. This book provides a comprehensive exploration of AI concepts, including machine learning, neural networks, and deep learning, and their practical applications in the classroom. Designed with both teachers and learners in mind, the guide covers a wide range of topics: Fundamentals of AI: An introduction to AI, its subfields, and real-world applications that enhance educational experiences. AI-Powered Tools: Step-by-step guidance on using AI tools such as generative AI, image recognition, and personalized learning platforms. Ethical Considerations: A thoughtful examination of the ethical implications of AI in education, focusing on fairness, transparency, and privacy. Hands-on Exercises: Practical activities and scenario-based examples that help educators and students apply AI in teaching and learning environments. Future Trends: Insights into the future of AI in education, from AI-driven lesson planning to adaptive learning technologies. Whether you're an educator looking to enrich your teaching methods or a student eager to explore AI’s potential, this book offers the tools, techniques, and knowledge needed to navigate the evolving landscape of AI in education. |
| examples of ai in education: Robot-Proof, revised and updated edition Joseph E. Aoun, 2024-10-15 A fresh look at a “robot-proof” education in the new age of generative AI. In 2017, Robot-Proof, the first edition, foresaw the advent of the AI economy and called for a new model of higher education designed to help human beings flourish alongside smart machines. That economy has arrived. Creative tasks that, seven years ago, seemed resistant to automation can now be performed with a simple prompt. As a result, we must now learn not only to be conversant with these technologies, but also to comprehend and deploy their outputs. In this revised and updated edition, Joseph Aoun rethinks the university’s mission for a world transformed by AI, advocating for the lifelong endeavor of a “robot-proof” education. Aoun puts forth a framework for a new curriculum, humanics, which integrates technological, data, and human literacies in an experiential setting, and he renews the call for universities to embrace lifelong learning through a social compact with government, employers, and learners themselves. Drawing on the latest developments and debates around generative AI, Robot-Proof is a blueprint for the university as a force for human reinvention in an era of technological change—an era in which we must constantly renegotiate the shifting boundaries between artificial intelligence and the capacities that remain uniquely human. |
| examples of ai in education: Deep Learning for Coders with fastai and PyTorch Jeremy Howard, Sylvain Gugger, 2020-06-29 Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala |
| examples of ai in education: The ABCs of How We Learn: 26 Scientifically Proven Approaches, How They Work, and When to Use Them Daniel L. Schwartz, Jessica M. Tsang, Kristen P. Blair, 2016-07-26 Selected as one of NPR's Best Books of 2016, this book offers superior learning tools for teachers and students, from A to Z. An explosive growth in research on how people learn has revealed many ways to improve teaching and catalyze learning at all ages. The purpose of this book is to present this new science of learning so that educators can creatively translate the science into exceptional practice. The book is highly appropriate for the preparation and professional development of teachers and college faculty, but also parents, trainers, instructional designers, psychology students, and simply curious folks interested in improving their own learning. Based on a popular Stanford University course, The ABCs of How We Learn uses a novel format that is suitable as both a textbook and a popular read. With everyday language, engaging examples, a sense of humor, and solid evidence, it describes 26 unique ways that students learn. Each chapter offers a concise and approachable breakdown of one way people learn, how it works, how we know it works, how and when to use it, and what mistakes to avoid. The book presents learning research in a way that educators can creatively translate into exceptional lessons and classroom practice. The book covers field-defining learning theories ranging from behaviorism (R is for Reward) to cognitive psychology (S is for Self-Explanation) to social psychology (O is for Observation). The chapters also introduce lesser-known theories exceptionally relevant to practice, such as arousal theory (X is for eXcitement). Together the theories, evidence, and strategies from each chapter can be combined endlessly to create original and effective learning plans and the means to know if they succeed. |
| examples of ai in education: Application of Artificial Intelligence to Assessment Hong Jiao, Robert W. Lissitz, 2020-03-01 The general theme of this book is to present the applications of artificial intelligence (AI) in test development. In particular, this book includes research and successful examples of using AI technology in automated item generation, automated test assembly, automated scoring, and computerized adaptive testing. By utilizing artificial intelligence, the efficiency of item development, test form construction, test delivery, and scoring could be dramatically increased. Chapters on automated item generation offer different perspectives related to generating a large number of items with controlled psychometric properties including the latest development of using machine learning methods. Automated scoring is illustrated for different types of assessments such as speaking and writing from both methodological aspects and practical considerations. Further, automated test assembly is elaborated for the conventional linear tests from both classical test theory and item response theory perspectives. Item pool design and assembly for the linear-on-the-fly tests elaborates more complications in practice when test security is a big concern. Finally, several chapters focus on computerized adaptive testing (CAT) at either item or module levels. CAT is further illustrated as an effective approach to increasing test-takers’ engagement in testing. In summary, the book includes both theoretical, methodological, and applied research and practices that serve as the foundation for future development. These chapters provide illustrations of efforts to automate the process of test development. While some of these automation processes have become common practices such as automated test assembly, automated scoring, and computerized adaptive testing, some others such as automated item generation calls for more research and exploration. When new AI methods are emerging and evolving, it is expected that researchers can expand and improve the methods for automating different steps in test development to enhance the automation features and practitioners can adopt quality automation procedures to improve assessment practices. |
| examples of ai in education: Human-Centered AI Ben Shneiderman, 2022 The remarkable progress in algorithms for machine and deep learning have opened the doors to new opportunities, and some dark possibilities. However, a bright future awaits those who build on their working methods by including HCAI strategies of design and testing. As many technology companies and thought leaders have argued, the goal is not to replace people, but to empower them by making design choices that give humans control over technology. In Human-Centered AI, Professor Ben Shneiderman offers an optimistic realist's guide to how artificial intelligence can be used to augment and enhance humans' lives. This project bridges the gap between ethical considerations and practical realities to offer a road map for successful, reliable systems. Digital cameras, communications services, and navigation apps are just the beginning. Shneiderman shows how future applications will support health and wellness, improve education, accelerate business, and connect people in reliable, safe, and trustworthy ways that respect human values, rights, justice, and dignity. |
| examples of ai in education: Robots for Kids Allison Druin, James A. Hendler, 2000 This work brings together the insights of ten designers, researchers, and educators, each invited to contribute a chapter that relates his or her experience develping or using a children's robotic learning device. This growing area of endeavour is expected to have prodound and long-lasting effets on the ways children learn and develop, and its participants come from a wide range of backgrounds. |
| examples of ai in education: Handbook of Research on Learning in the Age of Transhumanism Sisman-Ugur, Serap, Kurubacak, Gulsun, 2019-05-03 As a movement, transhumanism aims to upgrade the human body through science, constantly pushing back the limits of a person by using cutting-edge technologies to fix the human body and upgrade it beyond its natural abilities. Transhumanism can not only change human habits, but it can also change learning practices. By improving human learning, it improves the human organism beyond natural and biological limits. The Handbook of Research on Learning in the Age of Transhumanism is an essential research publication that discusses global values, norms, and ethics that relate to the diverse needs of learners in the digital world and addresses future priorities and needs for transhumanism. The book will identify and scrutinize the needs of learners in the age of transhumanism and examine best practices for transhumanist leaders in learning. Featuring topics such as cybernetics, pedagogy, and sociology, this book is ideal for educators, trainers, instructional designers, curriculum developers, professionals, researchers, academicians, policymakers, and librarians. |
| examples of ai in education: Self-Determined Learning Stewart Hase, Chris Kenyon, 2013-09-26 Heutagogy, or self-determined learning, redefines how we understand learning and provides some exciting opportunities for educators. It is a novel approach to educational practice, drawing on familiar concepts such as constructivism, capability, andragogy and complexity theory. Heutagogy is also supported by a substantial and growing body of neuroscience research. Self-Determined Learning explores how heutagogy was derived, and what this approach to learning involves, drawing on recent research and practical applications. The editors draw together contributions from educators and practitioners in different fields, illustrating how the approach can been used and the benefits its use has produced. The subjects discussed include: the nature of learning, heutagogy in the classroom, flexible curriculum, assessment, e-learning, reflective learning, action learning and research, and heutagogy in professional practice settings. |
| examples of ai in education: Artificial Intelligence in Healthcare Adam Bohr, Kaveh Memarzadeh, 2020-06-21 Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data |
| examples of ai in education: AI 2041 Kai-Fu Lee, Chen Qiufan, 2024-03-05 How will AI change our world within twenty years? A pioneering technologist and acclaimed writer team up for a “dazzling” (The New York Times) look at the future that “brims with intriguing insights” (Financial Times). This edition includes a new foreword by Kai-Fu Lee. A BEST BOOK OF THE YEAR: The Wall Street Journal, The Washington Post, Financial Times Long before the advent of ChatGPT, Kai-Fu Lee and Chen Qiufan understood the enormous potential of artificial intelligence to transform our daily lives. But even as the world wakes up to the power of AI, many of us still fail to grasp the big picture. Chatbots and large language models are only the beginning. In this “inspired collaboration” (The Wall Street Journal), Lee and Chen join forces to imagine our world in 2041 and how it will be shaped by AI. In ten gripping, globe-spanning short stories and accompanying commentary, their book introduces readers to an array of eye-opening settings and characters grappling with the new abundance and potential harms of AI technologies like deep learning, mixed reality, robotics, artificial general intelligence, and autonomous weapons. |
| examples of ai in education: MOOCs and Open Education in the Global South Ke Zhang, Curtis J. Bonk, Thomas C. Reeves, Thomas H. Reynolds, 2019-11-05 With e-learning technologies evolving and expanding at high rates, organizations and institutions around the world are integrating massive open online courses (MOOCs) and other open educational resources (OERs). MOOCs and Open Education in the Global South explores the initiatives that are leveraging these flexible systems to educate, train, and empower populations previously denied access to such opportunities. Featuring contributors leading efforts in rapidly changing nations and regions, this wide-ranging collection grapples with accreditation, credentialing, quality standards, innovative assessment, learner motivation and attrition, and numerous other issues. The provocative narratives curated in this volume demonstrate how MOOCs and OER can be effectively designed and implemented in vastly different ways in particular settings, as detailed by experts from Asia, Latin America, the Middle East, Africa, the Pacific/Oceania, and the Caribbean. This comprehensive text is an essential resource for policy makers, instructional designers, practitioners, administrators, and other MOOC and OER community stakeholders. |
| examples of ai in education: The Chromebook Infused Classroom Holly Clark, 2020-06-15 Do you have Chromebooks in the classroom? Then this book is for you! Conquer remote learning and digital leaning experiences like a pro! Whether Chromebooks are a new addition to your school, you've recently gone 1:1 in the classroom, or you've been using them for years and you want to make the most of technology for your learners... The Chromebook Infused Classroom is a resource you will want to refer to again and again.You'll learn how to: Amplify student voice in the classroom Create opportunities to promote a global perspective and cultural empathy Use technology to assess understanding and craft personalized learning experiences Help students develop critical skills for success in school, work, and life |
| examples of ai in education: Embracing AI in Education: A Guide for Teachers KHRITISH SWARGIARY, 2024-08-01 The advent of Artificial Intelligence (AI) marks a transformative era in education. As educators, we stand at the threshold of a new landscape where AI has the potential to revolutionize how we teach, learn, and interact within the classroom. This book, Embracing AI in Education: A Guide for Teachers, is crafted to serve as a comprehensive resource for educators seeking to harness the power of AI in their teaching practices. In recent years, AI technologies have permeated various aspects of our lives, reshaping industries and redefining possibilities. The field of education is no exception. From personalized learning platforms to AI-driven administrative tools, the integration of AI offers unprecedented opportunities to enhance the educational experience. However, with these opportunities come challenges and responsibilities that educators must navigate. This book is designed to guide you through this evolving landscape. It aims to demystify AI, offering practical insights and actionable strategies for effectively incorporating AI tools into your teaching. Whether you are a seasoned educator or just beginning your journey, this guide provides valuable perspectives on how to utilize AI to support student learning, streamline administrative tasks, and foster an engaging and inclusive classroom environment. |
| examples of ai in education: Machine Learning for Kids Dale Lane, 2021-01-19 A hands-on, application-based introduction to machine learning and artificial intelligence (AI) that guides young readers through creating compelling AI-powered games and applications using the Scratch programming language. Machine learning (also known as ML) is one of the building blocks of AI, or artificial intelligence. AI is based on the idea that computers can learn on their own, with your help. Machine Learning for Kids will introduce you to machine learning, painlessly. With this book and its free, Scratch-based, award-winning companion website, you'll see how easy it is to add machine learning to your own projects. You don't even need to know how to code! As you work through the book you'll discover how machine learning systems can be taught to recognize text, images, numbers, and sounds, and how to train your models to improve their accuracy. You'll turn your models into fun computer games and apps, and see what happens when they get confused by bad data. You'll build 13 projects step-by-step from the ground up, including: • Rock, Paper, Scissors game that recognizes your hand shapes • An app that recommends movies based on other movies that you like • A computer character that reacts to insults and compliments • An interactive virtual assistant (like Siri or Alexa) that obeys commands • An AI version of Pac-Man, with a smart character that knows how to avoid ghosts NOTE: This book includes a Scratch tutorial for beginners, and step-by-step instructions for every project. Ages 12+ |
| examples of ai in education: Understanding the impact of artificial intelligence on skills development UNESCO International Centre for Technical and Vocational Education and Training, 2021-04-02 |
| examples of ai in education: Application of Artificial Intelligence in Government Practices and Processes José Ramón Saura, Felipe Debasa, 2022 This book identifies the main uses that governments make of artificial intelligence and outlines define citizens' concerns about their privacy, covering topics that are essential to understanding how governments should use artificial intelligence in their practices and processes-- |
| examples of ai in education: Machine Learning and Human Intelligence Rosemary Luckin, 2018 Intelligence is at the heart of what makes us human, but the methods we use for identifying, talking about and valuing human intelligence are impoverished. We invest artificial intelligence (AI) with qualities it does not have and, in so doing, risk losing the capacity for education to pass on the emotional, collaborative, sensory and self-effective aspects of human intelligence that define us. To address this, Rosemary Luckin--leading expert in the application of AI in education - proposes a framework for understanding the complexity of human intelligence. She identifies the comparative limitation of AI when analyzed using the same framework, and offers clear-sighted recommendations for how educators can draw on what AI does best to nurture and expand our human capabilities. |
| examples of ai in education: International Perspectives on the Role of Technology in Humanizing Higher Education Enakshi Sengupta, Patrick Blessinger, Mandla Makhanya, 2020-11-12 By highlighting the use of emerging technologies in pedagogy and drawing on real-life case studies, the authors in this volume address the ongoing debate that technology brings a positive effect on education and beyond. They demonstrate how technology continues to fulfil the challenges of creating a more democratic educational environment. |
| examples of ai in education: Artificial Intelligence Stuart Russell, Peter Norvig, 2016-09-10 Artificial Intelligence: A Modern Approach offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence. Number one in its field, this textbook is ideal for one or two-semester, undergraduate or graduate-level courses in Artificial Intelligence. |
| examples of ai in education: Conducting Educational Design Research Susan McKenney, Thomas Reeves, 2018-09-03 Educational design research blends scientific investigation with the systematic development and implementation of solutions to educational challenges. Empirical inquiry is conducted in real learning settings – not laboratories – to craft effective solutions to the complex challenges facing educational practitioners. At the same time, the research is carefully structured to produce theoretical understanding that can serve the work of others. Conducting Educational Design Research, 2nd Edition has been written to support graduate students as well as experienced researchers who are new to this approach. Part I describes the origins, outcomes, and generic approach. Part II discusses the core processes of the generic approach in detail. Part III recommends how to propose, report, and advance educational design research. In addition to expanded treatment of research goals and practicalities, more examples, and attention to design-based implementation research, this new edition features enhanced guidance. For each of the four core processes, this volume offers: assessment tools detailed, behind-the-scenes descriptions of actual project work examples of how specific theories have been used to enrich the work For decades, policies for educational research worldwide have swung back and forth between demanding rigor above all other concerns, and increasing emphasis on impact. These two qualities, rigor and impact, need not be mutually exclusive. This volume supports readers in grasping and realizing the potential of educational design research. It demonstrates how rigorous and relevant investigation can yield both theoretical understanding and solutions to urgent educational challenges. |
| examples of ai in education: Embedding STEAM in Early Childhood Education and Care Caroline Cohrssen, Susanne Garvis, 2021-05-28 This book approaches STEAM (Science, Technology, Engineering, the Arts and Mathematics) in early childhood education from multiple angles. It focuses on the teaching and learning of children from two years of age to the early years of school. Proponents of STEAM describe how it can create opportunities for children to learn creatively, and various chapter authors make strong connections between discipline areas within the context of an informal curriculum. Others advocate for an integrated STEM, rather than STEAM, approach. With a light touch on theory and a focus on how to embed STE(A)M in an integrated early childhood curriculum, the editors and contributors examine the STEAM versus STEM question from multiple angles. The chapters provide helpful frameworks for parents, teachers and higher education institutions, and make practical suggestions of ways to support young children’s inquiry learning. Drawing on pedagogy and research from around the world, this book will be of interest to scholars of STEAM education, early childhood educators, students of early childhood education and parents of young children. |
| examples of ai in education: Spurious Correlations Tyler Vigen, 2015-05-12 Spurious Correlations ... is the most fun you'll ever have with graphs. -- Bustle Military intelligence analyst and Harvard Law student Tyler Vigen illustrates the golden rule that correlation does not equal causation through hilarious graphs inspired by his viral website. Is there a correlation between Nic Cage films and swimming pool accidents? What about beef consumption and people getting struck by lightning? Absolutely not. But that hasn't stopped millions of people from going to tylervigen.com and asking, Wait, what? Vigen has designed software that scours enormous data sets to find unlikely statistical correlations. He began pulling the funniest ones for his website and has since gained millions of views, hundreds of thousands of likes, and tons of media coverage. Subversive and clever, Spurious Correlations is geek humor at its finest, nailing our obsession with data and conspiracy theory. |
| examples of ai in education: The Datafication of Education Juliane Jarke, Andreas Breiter, 2020-05-21 This book attends to the transformation of processes and practices in education, relating to its increasing digitisation and datafication. The introduction of new means to measure, capture, describe and represent social life in numbers has not only transformed the ways in which teaching and learning are organised, but also the ways in which future generations (will) construct reality with and through data. Contributions consider data practices that span across different countries, educational fields and governance levels, ranging from early childhood education, to schools, universities, educational technology providers, to educational policy making and governance. The book demonstrates how digital data not only support decision making, but also fundamentally change the organisation of learning and teaching, and how these transformation processes can have partly ambivalent consequences, such as new possibilities for participation, but also the monitoring and emergence/manifestation of inequalities. Focusing on how data can drive decision making in education and learning, this book will be of interest to those studying both educational technology and educational policy making. The chapters in this book were originally published in Learning, Media and Technology. Chapter 4 of this book is freely available as a downloadable Open Access PDF at http://www.taylorfrancis.com under a Creative Commons Attribution-Non Commercial-No Derivatives (CC-BY-NC-ND) 4.0 license. |
| examples of ai in education: Teaching in the Post COVID-19 Era Ismail Fayed, Jill Cummings, 2022-01-03 This handbook showcases extraordinary educational responses in exceptional times. The scholarly text discusses valuable innovations for teaching and learning in times of COVID-19 and beyond. It examines effective teaching models and methods, technology innovations and enhancements, strategies for engagement of learners, unique approaches to teacher education and leadership, and important mental health and counseling models and supports. The unique solutions here implement and adapt effective digital technologies to support learners and teachers in critical times – for example, to name but a few: Florida State University’s Innovation Hub and interdisciplinary project-based approach; remote synchronous delivery (RSD) and blended learning approaches used in Yorkville University’s Bachelor of Interior Design, General Studies, and Business programs; University of California’s strategies for making resources affordable to students; resilient online assessment measures recommended from Qatar University; strategies in teacher education from the University of Toronto/OISE to develop equity in the classroom; simulation use in health care education; gamification strategies; innovations in online second language learning and software for new Canadian immigrants and refugees; effective RSD and online delivery of directing and acting courses by the Toronto Film School, Canada; academic literacy teaching in Colombia; inventive international programs between Japan and Taiwan, Japan and the USA, and Italy and the USA; and, imaginative teaching and assessment methods developed for online Kindergarten – Post-Secondary learners and teachers. Authors share unique global perspectives from a network of educators and researchers from more than thirty locations, schools, and post-secondary institutions worldwide. Educators, administrators, policymakers, and instructional designers will draw insights and guidelines from this text to sustain education during and beyond the COVID-19 era. |
| examples of ai in education: Artificial Intelligence Harvard Business Review, 2019 Companies that don't use AI to their advantage will soon be left behind. Artificial intelligence and machine learning will drive a massive reshaping of the economy and society. What should you and your company be doing right now to ensure that your business is poised for success? These articles by AI experts and consultants will help you understand today's essential thinking on what AI is capable of now, how to adopt it in your organization, and how the technology is likely to evolve in the near future. Artificial Intelligence: The Insights You Need from Harvard Business Review will help you spearhead important conversations, get going on the right AI initiatives for your company, and capitalize on the opportunity of the machine intelligence revolution. Catch up on current topics and deepen your understanding of them with the Insights You Need series from Harvard Business Review. Featuring some of HBR's best and most recent thinking, Insights You Need titles are both a primer on today's most pressing issues and an extension of the conversation, with interesting research, interviews, case studies, and practical ideas to help you explore how a particular issue will impact your company and what it will mean for you and your business. |
| examples of ai in education: How to Personalize Learning Barbara Bray, Kathleen McClaskey, 2016-09-29 HOW to Personalize Learning This practical follow-up to Bray and McClaskey’s first book, Make Learning Personal: The What, Who, Wow, Where, and Whybrings theory to practice. Teachers will find the tools, skills, and strategies needed to personalize learning and develop self-directed, independent learners with agency. Discover how to get started and go deeper by building a shared vision that supports personalized learning using the Universal Design for Learning (UDL) framework. Also included are: Tools and templates such as the Learner Profile, Personal Learning Backpack, Personal Learning Plan, as well as tips for lesson design and PBL Lesson and project examples that show how teachers can change instructional practice by encouraging learner voice and choice QR codes and links to the authors’ website for electronic versions of tools, templates, activities, and checklists Create a powerful shift in education by building a culture of learning so every learner is valued. If you are looking for a step-by-step guide on what personalized learning is and how to implement it, while being inspired and gaining ideas to implement immediately, this is definitely the book to read! Diana Petschauer, Assistive Technology Professional, CEO AT for Education & Access4Employment, Wolfeboro Falls, NH Barbara and Kathleen present well-tested strategies for personalization within a coherent framework. This highly practical book forms a reliable foundation for empowering a community striving to make schools work for all learners. John H. Clarke, Professor Emeritus, University of Vermont |
| examples of ai in education: Artificial Intelligence in Society OECD, 2019-06-11 The artificial intelligence (AI) landscape has evolved significantly from 1950 when Alan Turing first posed the question of whether machines can think. Today, AI is transforming societies and economies. It promises to generate productivity gains, improve well-being and help address global challenges, such as climate change, resource scarcity and health crises. |
| examples of ai in education: Integrating Generative AI in Education to Achieve Sustainable Development Goals Doshi, Ruchi, Dadhich, Manish, Poddar, Sandeep, Hiran, Kamal Kant, 2024-06-03 A new challenge has become present in the field of generative artificial intelligence (AI). The fundamental nature of education, a vital element for advancing the United Nations' Sustainable Development Goals (SDGs), now grapples with the transformative impact of AI technologies. As we stand at this intersection of progress and pedagogy, critical questions surface about the future roles of educators and the integrity of assessment processes. AIs rapid progression prompts an exploration of the competencies our education systems must cultivate in a world where human and machine intelligence are becoming increasingly interconnected. Against this backdrop of transformative uncertainty, Integrating Generative AI in Education to Achieve Sustainable Development Goals addresses profound challenges and offers promising solutions at the crossroads of AI and education. This book assembles distinguished academics, researchers, and practitioners, forming a collective voice on the intersection of Generative AI and education. The three-part structure dissects the technical aspects of AI-powered innovations in educational design, explores multidisciplinary applications enhancing educational content, and highlights AI-driven solutions to address equality and inclusion concerns within educational systems. The book also underscores the importance of ethical considerations of generative AI to ensure a future where technology serves the broader goals of sustainability and equitable education. |
Examples - Apache ECharts
Apache ECharts，一款基于JavaScript的数据可视化图表库，提供直观，生动，可交互，可个性化定制的数据可视化图表。
Examples - Apache ECharts
Examples; Resources. Spread Sheet Tool; Theme Builder; Cheat Sheet; More Resources; Community. Events; Committers; Mailing List; How to Contribute; Dependencies; Code …
Examples - Apache ECharts
Examples; Resources. Spread Sheet Tool; Theme Builder; Cheat Sheet; More Resources; Community. Events; Committers; Mailing List; How to Contribute; Dependencies; Code …
Apache ECharts
ECharts: A Declarative Framework for Rapid Construction of Web-based Visualization. 如果您在科研项目、产品、学术论文、技术报告、新闻报告、教育、专利以及其他相关活动中使用了 …
Events - Apache ECharts
Examples; Resources. Spread Sheet Tool; Theme Builder; Cheat Sheet; More Resources; Community. Events; Committers; Mailing List; How to Contribute; Dependencies; Code …
Examples - Apache ECharts
Apache ECharts，一款基于JavaScript的数据可视化图表库，提供直观，生动，可交互，可个性化定制的数据可视化图表。
Examples - Apache ECharts
Examples; Resources. Spread Sheet Tool; Theme Builder; Cheat Sheet; More Resources; Community. Events; Committers; Mailing List; How to Contribute; Dependencies; Code …
Examples - Apache ECharts
Examples; Resources. Spread Sheet Tool; Theme Builder; Cheat Sheet; More Resources; Community. Events; Committers; Mailing List; How to Contribute; Dependencies; Code …
Apache ECharts
ECharts: A Declarative Framework for Rapid Construction of Web-based Visualization. 如果您在科研项目、产品、学术论文、技术报告、新闻报告、教育、专利以及其他相关活动中使用了 …
Events - Apache ECharts
Examples; Resources. Spread Sheet Tool; Theme Builder; Cheat Sheet; More Resources; Community. Events; Committers; Mailing List; How to Contribute; Dependencies; Code …
