Teaching LLM literacy for more effective AI-aided learning in a statistics and data science course

Music City Center 

Large Language Model (LLM) tools (e.g., ChatGPT) are increasingly helping statistics/data science (DS) courses foster self-efficacy, personalize learning, and make data science accessible to students with less coding training. However, students with inadequate understanding of how LLM tools work may use them counterproductively, thus hindering their learning and problem-solving abilities. To address this, we developed an interactive LLM Literacy curriculum to help students (1) learn LLM fundamentals and then (2) develop best practices for using LLM tools as statistics/DS aids. The modules focus on debugging and statistical design, integrating literature on best practices in these fields with best practices for the use of LLMs as learning aids. The curriculum is tool-agnostic and adaptable to evolving LLM tools. We incorporated the curriculum into a graduate statistics/DS course for biomedical students and found significant improvements in students' LLM prompt-writing practices, ability to solve statistics/DS problems, and confidence in their skills. These findings underscore the importance of LLM literacy training as a necessary part of modern statistics/DS education.

large language model

statistics education

data science education

generative AI

statistical literacy

computing 

Section on Statistics and Data Science Education