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Full Description
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.
Contents
PART I: FOUNDATIONS, FRAMEWORKS, AND ETHICAL CONSIDERATIONS. Responsible, Ethical, and Effective Use of LLMs in Higher Education. Prompting Learning: The EPICC Framework for Effective Prompt Engineering in Education. Improving Large Foundation Models in Education for Multi-cultural Understanding. Engagement Dynamics in AI-Augmented Classrooms: Factors and Evolution. Engagement Diversity in AI-Enhanced Learning: Demographic and Disciplinary Perspectives. PART II: PRACTICAL TOOLS AND APPLICATIONS FOR EDUCATORS. vTA: How an Instructor Leverages Large Language Models for Superior Student Learning. A Step Towards Adaptive Online Learning: Exploring the Role of GPT as Virtual Teaching Assistants in Online Education. Leverage LLMs on Knowledge Tagging for Math Questions in Education. The Educator's Co-Pilot: Leveraging Generative AI and OERs for Learning Path Design. PART III: STUDENT-CENTERED LEARNING AND EMERGING TRENDS WITH AI. CHAPTER 10: Examining Graduate Students' Experiences in Using Generative AI for Academic Writing: Insights from Cambodian Higher Education. Generating Feedback for Programming Exercises with OpenAI's o1-preview. From Algorithms to Classrooms: The Future of Education with Large Language Models.
