Learning Gap Diagnostic and Support System: Analyzing Student Performance and Educator Input to Personalize Online Education

Researcher(s)

  • Taylor Jenkins, Computer Science, University of Delaware

Faculty Mentor(s)

  • Matthew Mauriello, Computer and Information Sciences, University of Delaware

Abstract

Since the COVID-19 pandemic, many students have fallen behind in school because they missed important lessons or failed to grasp concepts during online learning. This has made it harder for them to keep up in class. At the same time, teachers often find it difficult to know exactly where students are struggling or how to help them catch up in online settings. The goal of this project is to design, build, and test a computer program that can find these learning gaps by looking at both student test scores and the lessons teachers are using. This tool will give students and teachers helpful suggestions for how to get back on track. To guide the design of the program, we will ask teachers across Delaware to share their experiences with online learning, including the challenges they’ve faced and what has worked well. In the early stages, the first phase of this project will focus on surveys and interviews with teachers to understand what causes students to fall behind and how online learning has affected teaching. Later, we will use what we learn to build a prototype of the program (phase 2), which will help identify areas where students need support and give personalized feedback. This tool aims to make learning easier for students and give teachers better ways to help their students succeed. Through this research, we also hope to answer questions like: What are the key factors contributing to learning gaps in online education? How do teachers currently find and fix these gaps? What kinds of tools would help them do this better? And how can we use data to support students in a fair and respectful way?