Algorithms And Ai In Education
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Algorithms of Education
Author: Kalervo N. Gulson
language: en
Publisher: U of Minnesota Press
Release Date: 2022-05-17
A critique of what lies behind the use of data in contemporary education policy While the science fiction tales of artificial intelligence eclipsing humanity are still very much fantasies, in Algorithms of Education the authors tell real stories of how algorithms and machines are transforming education governance, providing a fascinating discussion and critique of data and its role in education policy. Algorithms of Education explores how, for policy makers, today’s ever-growing amount of data creates the illusion of greater control over the educational futures of students and the work of school leaders and teachers. In fact, the increased datafication of education, the authors argue, offers less and less control, as algorithms and artificial intelligence further abstract the educational experience and distance policy makers from teaching and learning. Focusing on the changing conditions for education policy and governance, Algorithms of Education proposes that schools and governments are increasingly turning to “synthetic governance”—a governance where what is human and machine becomes less clear—as a strategy for optimizing education. Exploring case studies of data infrastructures, facial recognition, and the growing use of data science in education, Algorithms of Education draws on a wide variety of fields—from critical theory and media studies to science and technology studies and education policy studies—mapping the political and methodological directions for engaging with datafication and artificial intelligence in education governance. According to the authors, we must go beyond the debates that separate humans and machines in order to develop new strategies for, and a new politics of, education.
Foundations and Frameworks for AI in Education
The integration of artificial intelligence (AI) into education reshapes how teaching, learning, and assessment are approached. AI in education uses foundational concepts from computer science, cognitive psychology, and pedagogy, personalizing learning experiences, automating administrative tasks, and providing real-time feedback. Frameworks guiding AI implementation enhance educational outcomes by making instruction more responsive and data driven. However, these frameworks must also account for ethical considerations, such as data privacy, algorithmic bias, and equitable access. By grounding AI technologies in educational theory and responsible design principles, organizations can create systems that support learners and educators in meaningful, inclusive ways. Foundations and Frameworks for AI in Education explores the transformative potential of AI in reshaping educational practices across all levels of learning. It provides a comprehensive examination of AI-driven tools and methodologies, including adaptive learning platforms, intelligent tutoring systems, and data-driven decision-making processes in education. This book covers topics such as data privacy, digital technology, and special education, and is a useful resource for educators, computer engineers, sociologists, academicians, researchers, and scientists.
Artificial Intelligence in Education
The book "AI in Education: Transforming Learning for the Future" aims to provide an in-depth exploration of the applications, advantages, challenges, and ethical considerations of integrating artificial intelligence in educational settings. The book focuses on how AI can revolutionize teaching and learning processes, empower educators, and enhance student outcomes while being mindful of potential concerns. Through case studies and best practices, readers will gain insights into successful AI implementation and learn how to navigate the dynamic landscape of AI-driven education. The book emphasizes the importance of ethical AI development, fostering a balanced approach that combines technological advancement with human values for a brighter future in education.