Honors Theses
Date of Award
Spring 5-9-2025
Document Type
Undergraduate Thesis
Department
Computer and Information Science
First Advisor
Yixin Chen
Second Advisor
Allan Bellman
Third Advisor
Timothy Holston
Relational Format
Dissertation/Thesis
Abstract
Effective grouping methods enhance classroom collaboration and allow for a student-centered teaching approach; however, traditional grouping methods are time-consuming, subjective, and can create inconsistent group dynamics. This project addresses these challenges by employing a data-driven approach to optimize student groups based on academic performance, behavior, attendance, language barriers, and teacher preferences. The minimum viable product is a web application with an algorithm-driven system to group students and a database storage for group results. During the initiation phase, a problem was defined with a proposed solution. During the planning phase, potential design choices and grouping methods were researched and assessed. During the development phase, the web application with the grouping algorithm was developed. The final phase was the closing phase where the product was delivered with a final report and oral presentation. These phases were completed in conjunction with status report updates to develop a successful minimum viable product.
Recommended Citation
Reardon, Kathryn E., "Optimized Student Grouping for Enhanced Classroom Performance" (2025). Honors Theses. 3208.
https://egrove.olemiss.edu/hon_thesis/3208
Included in
Data Science Commons, Educational Methods Commons, Educational Technology Commons, Theory and Algorithms Commons
