Large Language Model Applications in Education

Catalog description

Large Language Model (LLM) Applications in Education is designed for graduate students, offering an overview and introduction to both the theoretical foundations and practical applications of LLMs in education. The course focuses on leveraging LLMs, particularly through the OpenAI API, to address real-world challenges in education, such as personalized learning, content generation, automated grading, and learning analytics. Students will gain hands-on experience in using LLMs to develop tools and solutions that enhance teaching and learning processes. The course is divided into three parts: Introduction to LLMs: Covers the history, evolution, and ethical considerations of LLMs, along with hands-on experience in setting up and using the OpenAI API. LLMs in Education: Explores applications of LLMs in education, including content generation, personalized learning, automated grading, and chatbots. Concerns and Future Directions: Discusses ethical challenges, bias, and future trends in LLMs, with a focus on their implications for learning analytics and AI in education. Prerequisite: Python required; EDUC 6190 Feature Engineering (or Equivalent) and EDUC 6191 Core Methods in Educational Data Mining (or Equivalent) are recommended