Streamlining Personalized Learning with Generative AI: Building a Tool for Diagnostic-Based Study Guides in 5th Grade Math

Alissa Mitelman

Co-Presenters: Individual Presentation

College: The Dorothy and George Hennings College of Science, Mathematics and Technology

Major: Mathematics - STEM Teacher Education 5 Year

Faculty Research Mentor: Brian Baldwin

Abstract:

In recent years, the use of artificial intelligence (AI) has grown in popularity amongst students in school and university alike. Additionally, educational technology has made significant advances in helping increase student learning in the K-12 classroom. Programs like IXL and Khanmigo offer students the ability to ask mathematical questions and gain practice problems, but there is a need for a tool that allows students to prepare for specific exams. This tool was built from scratch to offer students a personalized study guide based on a diagnostic assessment. The tool uses a combination of Google Forms, Google Sheets, Gemini, Google Apps Script and the AI Assist and Autocrat plugins. As soon as students press submit on a diagnostic Google Form, the tool will grade and track their responses, flag topics the student is struggling with, ask Gemini to create a personalized study guide for the student, and send it to the student. With this tool, teachers can tailor learning to each individual student, focusing their energy on helping students understand concepts rather than picking problems for each student. This tool will allow students to get the help that they need and teachers to spend more time with the student rather than behind their desk.