AI Usage and Student Performance

Authors

• Isabella J. Anderson, University of Central FloridaFollow
• Jenny Tran, University of Central Florida
• Mia Bukritsky, University of Central Florida
• Kaito Powell, University of Central Florida
• Madison Renda, University of Central FloridaFollow

Streaming Media

Files

Course Code

STA

Course Number

4164

Faculty/Instructor

Nathaniel Simone

Faculty/Instructor Email

nathaniel.simone@ucf.edu

About the Author

Isabella Anderson, Mia Bukritsky, Kaito Powell, Madison Renda, and Jenny Tran are undergraduate students at the University of Central Florida. We extend our gratitude to Dr. Simone in Statistical Methods III for his guidance on this project.

Abstract, Summary, or Creative Statement

The purpose of our project is to research whether a student's AI usage intensity can predict their exam scores, or if their academic ability holds more importance. We obtained data for our research from an online source called Hugging Face. Our variables were the average number of back-and-forth messages between the student and the AI, and AI usage depth. We also looked at students based on grade category. Through graphing and collinearity examination, we decided on a final model that would best predict the exam scores of a student. We found that AI usage does not significantly impact the exam score of a student. Rather, exam scores are more accurately determined by assignment completion consistency

The project can be viewed at https://drive.google.com/file/d/1SCL_VEdjqb71KwF87K7OEIh0jJYMajP8/view?usp=sharing

Keywords

AI; Education; Exam Scores

Recommended Citation

Anderson, Isabella J.; Tran, Jenny; Bukritsky, Mia; Powell, Kaito; and Renda, Madison, "AI Usage and Student Performance" (2026). High Impact Practices Student Showcase Spring 2026. 32.
https://stars.library.ucf.edu/hip-2026spring/32