Future of Learning with Large Language Models

Applications and Research in Education

Large language models (LLMs), advanced AI systems trained on vast text datasets, are reshaping education. This book explores their role in revolutionizing learning through cognitive reinforcement, personalization, curriculum-wide applications, and teacher training.

The book covers theoretical foundations on how LLMs can enhance learning, cognitive reinforcement, improving learning efficiency, and personalization in learning, applications across the curriculum, teacher training and support for LLM integration, using in assessment and evaluation, and measuring the impact and affordances of LLMs. It acknowledges the challenges that come with integrating LLMs into education and will address the responsible development and deployment strategies to ensure that the models become powerful tools for good in the hands of educators. It explores potential research directions, such as the development of domain-specific models, and the creation of ethical frameworks for LLM use in education. As education enters an era of AI-enablement, this visionary book equips teachers, administrators, technologists, and policymakers with an authoritative guide to harnessing the power of large language models. Readers will discover how these advanced systems can expand access to quality education, tailor learning experiences, and nurture the innovators and critical thinkers of tomorrow, and glimpse into the future of learning and education with LLMs.

Contributor: Myint Swe Khine (Edited by), László Bognár (Edited by), Ernest Afari (Edited by)

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