  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 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.
