An Empirical Study of Teaching Methodologies and Learning Outcomes for Online and in-class Networking Course Sections

To enhance student learning, we demonstrate an experimental study to analyze student learning outcomes in online and in-class sections of a core data communications course of the Undergraduate IT program in the Information Sciences and Technology (IST) Department at George Mason University (GMU). In this study, student performance is evaluated based on course assessments. This includes home and lab assignments, skill-based assessment, and traditional midterm exam across all 4 sections of the course. All sections have analogous content, assessment plan and teaching methodologies. Student demographics such as exam type and location preferences that may play an important role in their learning process are considered in our study. We had to collect vast amount of data from the learning management system (LMS), Blackboard (BB) Learn, in order to compare and study the results of several assessment outcomes for all students within their respective section and amongst students of other sections. We then tried to understand whether demographics have any influence on student performance by correlating individual student’s survey response to his/her performance in the class. The numerical results up to mid-semester reveal remarkable insights on student success in the online and face-to-face (F2F) sections.