Abstract
This study focused on learning equity in colleges and universities where teaching and learning depends heavily on computer technologies. The study used the Structural Equation Modeling (SEM) to investigate gender and racial/ethnic heterogeneity in the use of a computer based course management system (CMS). Two latent variables (CMS usage and scholastic aptitudes)—with two moderation covariates (gender and ethnicity)—were used to explore their associational relationships with students’ final grades. More than 990 students’ CMS data were collected from courses at a Midwest public university in the United States. The final model indicated that there was gender and racial/ethnic invariance in the use of the CMS. Additionally, CMS use was significantly positively associated with students’ academic achievement. These findings have policy and practical implications for understanding the correlation between technology use and academic achievement in colleges and universities. This study also pointed out future research directions for technology use in higher education.
Highlights
The traditional higher education institution has been transformed by the convergence of powerful new information and instructional technologies
This study provided an initial examination of the different behaviors of females and males, and among Caucasian, Asian American, African American, and Hispanic students in terms of using course management systems in higher education
The finding resonates with recent studies that the digital divide still remains [67], but the divide has already shifted from the quantity of technology use to the quality of technology use
Summary
The traditional higher education institution has been transformed by the convergence of powerful new information and instructional technologies. The different levels of exposure to computers in childhood may cause students to have different attitudes towards computer use and, result in varying effectiveness for computer use. Those who have a great deal of experience with computers are more likely to incorporate new technology into their work and study habits. Those who have few or unpleasant experiences or who hold negative attitudes towards the new technologies may not believe that computer use can enhance their work efficiency [8] Such inequalities regarding computer use in higher education may result in differences in students’
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