Predictive Identification of At-Risk Students: Using Learning Management System Data

Predictive Identification of At-Risk Students: Using Learning Management System Data

This paper describes a neural network model that can be used to detect at-risk students failing a particular course using only grade book data from a learning management system. By analyzing data extracted from the learning management system at the end of week 5, the model can predict with an accur...

Full description

Bibliographic Details
Main Authors: J Bryan Osborne, Andrew S.I.D. Lang
Format: Article
Language:English
Published: Florida State Open Publishing 2023-07-01
Series:Journal of Postsecondary Student Success
Subjects:
at-risk students
early detection
LMS data
machine learning
student retention
student success
Online Access:https://journals.flvc.org/jpss/article/view/132082

Internet

https://journals.flvc.org/jpss/article/view/132082

Similar Items