OnDiscuss: An Epistemic Network Analysis Learning Analytics Visualization Tool for Evaluating Asynchronous Online Discussions

TL;DR

OnDiscuss is a visualization tool that uses text mining and Epistemic Network Analysis to help instructors efficiently evaluate asynchronous online discussions, enhancing understanding of student interactions.

Contribution

The paper introduces OnDiscuss, a novel learning analytics tool combining text mining and ENA for visualizing and analyzing online discussion data.

Findings

Effective visualization of discussion networks

Improved instructor understanding of student interactions

Potential to save time in assessment processes

Abstract

Asynchronous online discussions are common assignments in both hybrid and online courses to promote critical thinking and collaboration among students. However, the evaluation of these assignments can require considerable time and effort from instructors. We created OnDiscuss, a learning analytics visualization tool for instructors that utilizes text mining algorithms and Epistemic Network Analysis (ENA) to generate visualizations of student discussion data. Text mining is used to generate an initial codebook for the instructor as well as automatically code the data. This tool allows instructors to edit their codebook and then dynamically view the resulting ENA networks for the entire class and individual students. Through empirical investigation, we assess this tool's effectiveness to help instructors in analyzing asynchronous online discussion assignments.