Visual Progression Analysis of Student Records Data

TL;DR

This paper introduces eCamp, a visual knowledge discovery system that integrates diverse student data to analyze and visualize student progression, retention, and curriculum effectiveness at university level.

Contribution

The work presents a novel system that combines disconnected campus datasets to model and visualize student flow patterns and progression in higher education.

Findings

Revealed new insights into student progression patterns

Supported analysis of student retention and curriculum design

Enabled visualization of multi-level relationships in student data

Abstract

University curriculum, both on a campus level and on a per-major level, are affected in a complex way by many decisions of many administrators and faculty over time. As universities across the United States share an urgency to significantly improve student success and success retention, there is a pressing need to better understand how the student population is progressing through the curriculum, and how to provide better supporting infrastructure and refine the curriculum for the purpose of improving student outcomes. This work has developed a visual knowledge discovery system called eCamp that pulls together a variety of populationscale data products, including student grades, major descriptions, and graduation records. These datasets were previously disconnected and only available to and maintained by independent campus offices. The framework models and analyzes the multi-level relationships hidden within these data products, and visualizes the student flow patterns through individual majors as well as through a hierarchy of majors. These results support analytical tasks involving student outcomes, student retention, and curriculum design. It is shown how eCamp has revealed student progression information that was previously unavailable.