Artificial Intelligence and Student Usage in Online Learning: A Longitudinal Analysis of Usage Patterns, Achievement, and Perceptions in K-12 Virtual Education

Citation

McGehee, N. (2025). Artificial Intelligence and Student Usage in Online Learning: A Longitudinal Analysis of Usage Patterns, Achievement, and Perceptions in K-12 Virtual Education. Michigan Virtual. https://michiganvirtual.org/research/publications/artificial-intelligence-and-student-usage-in-online-learning-a-longitudinal-analysis-of-usage-patterns-achievement-and-perceptions-in-k-12-virtual-education/

Abstract

This study follows more than 26,000 Michigan students over two years to see how they actually use AI in their online courses—and what happens to their grades when they do. AI adoption nearly doubled, with sophisticated “tool + tutor” use growing fastest, especially among high-achieving students. Early achievement gaps between AI users and non-users almost disappeared, yet teacher responsiveness and course design still mattered far more than any AI tool. The findings offer a grounded look at how AI is reshaping K–12 learning right now, without replacing the humans at the heart of it.

Authors

  • McGehee, Nikolas

Reference Type

Report

Keywords

  • Artificial Intelligence
Select this as a favorite