2026 ASEE Annual Conference & Exposition

Distance education has gained significant momentum over the past few decades due to its flexibility, accessibility, and cost-effectiveness. Higher education institutions have increasingly adopted this instructional mode by offering hybrid and fully online courses, as well as complete degree programs through learning management systems. The COVID-19 pandemic and resulting public health restrictions accelerated this transition, creating a pivotal moment in the evolution of course delivery and institutional strategies for promoting online education.
Despite its advantages, distance learning presents unique challenges for both faculty and students, particularly in quantitative disciplines. This study conducts a comparative analysis of student performance in distance and in-person formats of an undergraduate business analytics course. Data was collected from 1,153 students across 37 course sections offered between 2016 and 2025, including 20 in-person and 17 online classes. Course topics included data visualization, population sampling, hypothesis testing, time series analysis, regression modeling (simple, multiple, and logistic), and optimization. All sections used identical instructional materials and assessments, consisting of eight quizzes, two exams, and eight group case analyses. Student grades from exams, quizzes, and group assignments were analyzed for this study.
The results indicate that student performance declined during the fully remote instruction period of the COVID-19 campus shutdown, reflecting the challenges of learning analytics online. However, performance in online courses improved after the return to campus, when students could freely choose their preferred learning format. Analysis of group assignments showed no significant differences in teamwork or communication between online and in-person students, suggesting that modern students’ familiarity with digital collaboration tools supports effective engagement in remote learning environments.