Pedagogical and Strategic Utility of Large Language Models
This presentation at the NLP Summit 2024 explores the transformative role of Large Language Models (LLMs) in both pedagogy and strategic educational planning. It examines how LLMs like GPT-4 can personalize learning, enhance problem-solving, and streamline educational administration.
The talk will cover successful case studies, demonstrate LLM applications in real-world educational settings, and discuss the integration challenges and ethical considerations involved. Attendees will gain insights into the dual utility of LLMs—not only as innovative educational tools but also as strategic assets in curriculum design and resource management.
This session aims to equip educators, administrators, and technologists with the knowledge to effectively implement LLMs in their strategies, ensuring a balanced approach that supports both immediate educational needs and long-term objectives. The discussion will underscore the importance of strategic foresight in the deployment of AI technologies within educational frameworks.
Michelle Banawan
Academic Program Director at Asian Institute of Management
Dr. Michelle Banawan is a full time faculty of the Aboitiz School of Innovation, Technology, and Entrepreneurship at the Asian Institute of Management. She is the Academic Program Director of AIM’s first undergraduate program offering – the dual degree program on Bachelor of Science in Business Administration and Data Science and University of Houston’s Bachelor of Science in Business Administration Major in Management in Information Systems.
Her postdoctoral research at the Science of Learning and Educational Technology lab in Arizona State University involved the design and development of natural language processing (NLP) and machine learning (ML) models using deep learning in the automated evaluation of student writing within Intelligent Tutoring Systems. She is also doing research in computational linguistics to understand academic and social media discourse.
