Date of Award

Spring 2024

Document Type

Thesis

Terms of Use

© 2024 Lys Kang. This work is freely available courtesy of the author. It may be used under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) license. For all other uses, please contact the copyright holder.

Degree Name

Bachelor of Arts

Department

Engineering Department

First Advisor

Allan R. Moser

Abstract

This report details the development of a personalized quiz feature for the Alby learning management platform, designed to enhance student learning by generating quizzes tailored to individual performance data. The project involved creating an algorithm to analyze dynamic student data and identify areas for improvement and then using OpenAI's GPT-4 to generate the multiple choice quizzes with elaborative feedback. Developed as a serverless application with AWS tools, the feature operates independently from the main platform. Despite the absence of applicable professional standards and constraints like limited data availability, the project met its functional requirements, demonstrating the potential to improve educational outcomes through customized, adaptive quizzes. Future work will aim to optimize quiz generation times and explore the development of a custom AI model.

Included in

Engineering Commons

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