This book collects papers on education quality assessment based on AI technology and introduces the latest research direction and progress of AI technology in the field of education and teaching, including classroom teaching quality assessment, online education quality assessment, teaching reflection quality assessment, etc. This book promotes the application of artificial intelligence technology in the field of education and teaching, effectively improving the quality of education and teaching. Researchers in artificial intelligence technology, teachers, students, and others benefit from this book.

"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

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 introduction of Artificial Intelligence (AI) has ignited a fervent academic discourse. AI's role is as both a powerful ally and a potential adversary in education. For instance, ChatGPT is a generative AI which mimics human conversation with impressive precision. Its capabilities span the educational spectrum, from answering questions and generating essays to composing music and coding. Yet, as with any innovation, its advent has sparked a spirited academic dialogue. AI in Language Teaching, Learning, and Assessment seeks to address these concerns with rigor and thoughtfulness. It explores the undeniable drawbacks of AI in language education and offers strategic insights into their prevention. It scrutinizes the resources and safeguards required to ensure the ethical and secure integration of AI in academic settings. This book lays out the multifaceted benefits of incorporating AI into language teaching, learning, and assessment. Its chapters dissect the transformative impact of AI on pedagogy, teaching materials, assessment methodologies, applied linguistics, and the broader landscape of language education development. This book is a valuable resource for language learners, educators, researchers, and scholars alike. It beckons to those who are keen on exploring and implementing AI in education, as well as AI developers and experts seeking to bridge the chasm between technology and language education.

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.

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.

First Published in 1994. Routledge is an imprint of Taylor & Francis, an informa company.

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.

Enrich, grow, and sustain AfL in your classroom. Twenty years after the publication of Inside the Black Box, the landmark review of formative classroom assessment, international education experts Christine Harrison and Margaret Heritage tackle assessment for learning (AfL) anew, with fresh insights gained from two decades of research, theory, and classroom practice. Packed with key AfL ideas and supports, vignettes that illustrate AfL in action, and practice-based evidence to enrich understanding of AfL from both the teacher’s and the student’s perspectives, this book is a ‘sounding board’ for educators to explore and reflect on their own AfL practices and beliefs.