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]
"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
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.
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.
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.
Why—contrary to much expert and popular opinion—more education may not be the answer to skyrocketing inequality. For generations, Americans have looked to education as the solution to economic disadvantage. Yet, although more people are earning degrees, the gap between rich and poor is widening. Cristina Groeger delves into the history of this seeming contradiction, explaining how education came to be seen as a panacea even as it paved the way for deepening inequality. The Education Trap returns to the first decades of the twentieth century, when Americans were grappling with the unprecedented inequities of the Gilded Age. Groeger’s test case is the city of Boston, which spent heavily on public schools. She examines how workplaces came to depend on an army of white-collar staff, largely women and second-generation immigrants, trained in secondary schools. But Groeger finds that the shift to more educated labor had negative consequences—both intended and unintended—for many workers. Employers supported training in schools in order to undermine the influence of craft unions, and so shift workplace power toward management. And advanced educational credentials became a means of controlling access to high-paying professional and business jobs, concentrating power and wealth. Formal education thus became a central force in maintaining inequality. The idea that more education should be the primary means of reducing inequality may be appealing to politicians and voters, but Groeger warns that it may be a dangerous policy trap. If we want a more equitable society, we should not just prescribe more time in the classroom, but fight for justice in the workplace.
This book explores the exciting potential of generative AI to transform education. It argues that AI can personalize learning, create engaging experiences, and make education more accessible for all students. Here are the key takeaways: Generative AI for Personalized Learning: AI can analyze student data and learning styles to create customized learning paths, suggest relevant resources, and provide targeted feedback. This ensures students are challenged appropriately and can progress at their own pace. Engaging Learning Experiences: Generative AI can power interactive simulations, immersive virtual reality environments, and gamified learning experiences. These engaging formats capture student attention, make learning more enjoyable, and reinforce understanding. AI-powered Support for Educators: AI can automate tasks like grading and record-keeping, freeing up educators' time for more strategic activities like lesson planning and providing personalized support to students. Ethical Considerations: The book emphasizes the importance of using AI responsibly. Educators need to be aware of potential biases in AI models and ensure student data privacy is protected. The Human Touch Remains Crucial: AI cannot replace the irreplaceable role of educators. Educators bring empathy, critical thinking skills, and the ability to build relationships with students, all crucial for a well-rounded education. The Future is a Human-AI Partnership: The book envisions a future where educators leverage AI tools to create personalized and engaging learning experiences, while still fostering social-emotional development and critical thinking skills in students. This future holds immense promise for creating a more equitable and effective education system for all learners.
A roadmap for how we can rebuild America's working class by transforming workforce education and training. The American dream promised that if you worked hard, you could move up, with well-paying working-class jobs providing a gateway to an ever-growing middle class. Today, however, we have increasing inequality, not economic convergence. Technological advances are putting quality jobs out of reach for workers who lack the proper skills and training. In Workforce Education, William Bonvillian and Sanjay Sarma offer a roadmap for rebuilding America's working class. They argue that we need to train more workers more quickly, and they describe innovative methods of workforce education that are being developed across the country.
Big data has the power to transform education and educational research. Governments, researchers and commercial companies are only beginning to understand the potential that big data offers in informing policy ideas, contributing to the development of new educational tools and innovative ways of conducting research. This cutting-edge overview explores the current state-of-play, looking at big data and the related topic of computer code to examine the implications for education and schooling for today and the near future. Key topics include: · The role of learning analytics and educational data science in schools · A critical appreciation of code, algorithms and infrastructures · The rise of ‘cognitive classrooms’, and the practical application of computational algorithms to learning environments · Important digital research methods issues for researchers This is essential reading for anyone studying or working in today′s education environment!
