2025 ASEE Annual Conference & Exposition

A comparative analysis of student performance outcomes in online and in-person classes

Presented at Engineering Management Pedagogy: Teaching for Real-World Impact

The COVID-19 pandemic energized a wave for online education that had started a couple of decades earlier [1] which has persisted beyond the pandemic. Seventy one percent of students surveyed in 2021 reported they would continue at least some form of online learning even post-pandemic [2]. The popularity of online degree programs promises to continue in the future and many universities are experimenting in the fully online space. However online teaching, particularly teaching quantitative subjects, can be challenging. Ultimately, academic programs and faculty must ensure students enrolled in online courses have the same learning outcomes as in-person students. The question examined in this study is whether online education impacts learning outcomes in a quantitative introductory statistics course. This is an extension of a previous study [3] that examined performance outcomes of students in asynchronous online sections of a required introductory statistics course to that of sections where the students attended class in person and compared overall performance of online v. in-person sections on homework, take-home midterm exam, and proctored final exam. The study also compared overall performance in take-home midterm vs. proctored final exams.

This is an important topic for engineering management programs and faculty because knowledge of probability and statistics is required for managing quality management systems, which is a domain in the Engineering Management Body of Knowledge (EMBoK) published by the American Society for Engineering Management. This paper presents a summary of those findings but extends the analysis to a more granular level. It compares the performance of online and in-person sections for homework in four major course topics: Descriptive Statistics, Inferential Statistics, Simple and Multiple Regression, and fundamentals of Project Management. Findings will help determine whether instruction mode is a factor that impacts effectiveness of student learning for various content and topics. We will use parametric and nonparametric tests of mean and validate their assumptions using tests for normality and homogeneity of variance as our tools for analysis to capture findings.

Authors

Dr. Majid Nabavi University of Nebraska - Lincoln [biography]

Dr. Majid Nabavi is an associate professor of practice in department of Supply Chain Management and Analytics in the College of Business at the University of Nebraska-Lincoln. His research and teaching interests include analytical methods, database systems, and application of analytical models for business problem solving. He has developed and taught online and in-class courses in operations and logistics management, business analytics, database systems, and programming. He has published in Quality Management Journal, and a textbook in Business Analytics.
Majid received his MBA and Ph. D. in Operations Management from University of Nebraska-Lincoln, and B.E. and M.E. degrees in Mining Engineering from University of Tehran. Prior to the University of Nebraska-Lincoln, Majid was an associate professor of Supply Chain Management and Decision Sciences at Bellevue University.
Dr. Jena Shafai Asgarpoor University of Nebraska - Lincoln [biography]

Dr. Jena Asgarpoor is a Professor of Practice at the University of Nebraska – Lincoln and the Director for the Master of Engineering Management Program in the College of Engineering. She received her Ph. D. and M.S. in Industrial Engineering, specializing in Engineering Management, from Texas A&M University in College Station where she had previously earned a B.A. in Political Science (Summa Cum Laude). Prior to UNL, she was a professor at Bellevue University for 26 years, where in 1994 as part of her teaching portfolio she developed and taught the first fully online asynchronous web-based course offered by that institution. Her interests lie in engineering management, quality management, pedagogy, and assessment of teaching and learning, particularly in the online space. She is active in the American Society for Engineering Management (ASEM) and the American Society for Engineering Education (ASEE). In recent years she has President of the Council of Engineering Management Academic Leaders (CEMAL) and Program Chair and Chair of the Engineering Management Division (EMD) of ASEE. Dr. Asgarpoor is currently serving as President of the American Society for Engineering Management (ASEM).

Note

The full paper will be available to logged in and registered conference attendees once the conference starts on June 22, 2025, and to all visitors after the conference ends on June 25, 2025

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