Longitudinal trends in sentiment polarity and readability of an online masters of computer science course

Abstract

In four years, the Georgia Tech Online MS in CS (OMSCS) program has grown from 200 students to over 6000. Despite early evidence of success, there is a need to evaluate the program's effectiveness. In this paper, we focus on trends from Fall 2014 to Fall 2017 in the on-campus and online sections of one OMSCS course, Knowledge-Based Artificial-Intelligence (KBAI). We leverage sentiment analysis and readability assessments to quantify the evolving quality of discourse on the online forum discussions of the various sections. The research was conducted as a longitudinal study, and aims to evaluate the success of the KBAI course by comparing trends between residential and online sections. Despite slight downward trends in online discourse quality and sentiment polarity, our results suggest that the growing OMSCS program has been successful in replicating the quality of learning experienced by on-campus students in the KBAI course.