A Pilot Study of Predicting Failing Grades Using Data from UCLA's Learning Management System

Kang, Elliot Minkiu (2017) A Pilot Study of Predicting Failing Grades Using Data from UCLA's Learning Management System. Masters thesis, University of California, Los Angeles.

Full text not available from this repository.
Official URL: http://escholarship.org/uc/item/9fz536hn

Abstract

UCLA develops and uses a learning management system to provide an online environment for students to access and interact with course content. The data collected by the learning management system is a direct measure of student activity, and provides information that augments known information about the student, such as assignment grades and demographics. This paper assesses UCLA's learning management system data for its usefulness in creating an early warning system that will advise instructors and students of whether a student is likely to receive a failing grade. The data are used in two analyses: an exploratory analysis of how students use the learning management system, and a predictive model to forecast end-of-term grades based on partial-term information. Recommendations on how to generalize the results across the UCLA undergraduate population are drawn from the findings of the analyses.

Item Type: Thesis (Masters)
Subjects: Educational technology > Early warning systems
Educational technology > Learning analytics
Education (General) > Higher education
Divisions: Higher education, Universities, Vocational training, Colleges
Depositing User: Elizabeth Dalton
Date Deposited: 05 Jul 2017 22:06
Last Modified: 05 Jul 2017 22:06
URI: http://research.moodle.net/id/eprint/196

Actions (login required)

View Item View Item