A Logistic Approach To Predicting Student Success In Online Database Courses

Abstract

This paper examines the affects of reading comprehension on the performance of online students in a beginning database management class. Reading comprehension is measured by the results of a Cloze Test administered online to the students during the first week of classes. Using data collected from 2002 through 2008, the significance of the Cloze Test score is analyzed with respect to the three different assessment methods used in the class as well as to the overall average score of the students in the class. The data are tested using a binary logistic model that analyzes the data on a success (improvement) or failure (no improvement) basis. The analysis finds that reading comprehension has a significant impact on the scores students earn on examinations and on the final class average. However, the reading comprehension score has no significant impact on assessments that are more under the control of the student such as online open-book quizzes and projects.