Incorporating ChatGPT for teaching and learning statistical concepts - a devil or an angel?

This presentation will share my experience of using ChatGPT for teaching and learning statistical concepts. AI is revitalizing education in personalized learning, automating the repetitive and time-consuming tasks for teachers and allowing 24/7 availability for learning. The recent hype of ChatGPT has generated great interest and concerns on how it can do in every aspect of human activities, including education. Among some unique features, the fact that ChatGPT is capable of providing human-like conversations raises a particular attention. A major negative impact to education is to make assessment of student learning difficult. Statistical concepts are unique to other disciplines due to the fact that various concepts are subtle and confusing. Some examples include independent Vs. conditional events, correlation Vs. causation, standard deviation Vs. standard error and Central Limit Theorem. (1) "Is the current ChatGPT capable of explaining these unique statistical concepts?" Numerical computation is an integral process of learning statistical concepts. Hands-on activities and projects are critical for statistical thinking. (2) "Is ChatGPT capable of performing proper computations, suggesting hands-on activities and projects for teaching and learning statistics?" Misuse of statistics in practical analysis has been a critical concern. (3) "Can ChatGPT identify different misuses of statistical techniques?". ChatGPT uses data-driven approach, not causality-driven. It provides a most likely answer based on the available data. However, it is not able to validate the answer. Some pros and cons will be discussed. The fast development of AI will continue to evolve and become more and more sophisticate. Educators, including statistics profession, will need to embrace and take the advantage of AI technology in their teaching and finding creative approaches to facilitate learning.

Artificial Intelligence

Data-driven Vs. Causality-driven

Misuse of Statistics

Numerical computation

Personalized learning 

Beginner

Education

Symposium on Data Science and Statistics (SDSS) 2023