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Modeling Student Satisfaction and Implementation of the I-C-D Method to Improve the Industrial Engineering Undergraduate Course Experience

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2016 ASEE Annual Conference & Exposition


New Orleans, Louisiana

Publication Date

June 26, 2016

Start Date

June 26, 2016

End Date

June 29, 2016





Conference Session

Industrial Engineering Division Technical Session 2

Tagged Division

Industrial Engineering

Tagged Topic


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Paper Authors


Paul C. Lynch Penn State University - Erie

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Paul C. Lynch received his Ph.D., M.S., and B.S. degrees in Industrial Engineering from the Pennsylvania State University. Dr. Lynch is a member of AFS, SME, IIE, and ASEE. Dr. Lynch’s primary research interests are in metal casting, manufacturing systems, and engineering education. Dr. Lynch has been recognized by Alpha Pi Mu, IIE, and the Pennsylvania State University for his scholarship, teaching, and advising. He received the Outstanding Industrial Engineering Faculty Award in 2011, 2013, and 2015, the Penn State Industrial & Manufacturing Engineering Alumni Faculty Appreciation Award in 2013, and the Outstanding Advising Award in the College of Engineering in 2014 for his work in undergraduate education at Penn State. Dr. Lynch worked as a regional production engineer for Universal Forest Products prior to pursuing his graduate degrees. He is currently an Assistant Professor of Industrial Engineering in the School of Engineering at Penn State Erie, The Behrend College.

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Cynthia Bober Penn State University

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Cynthia Bober is a 2015 graduate of the Penn State University with a M.S. and B.S. Degree in Industrial Engineering and a minor in Six Sigma Methodology. As a former Schreyer Honors College scholar, she wrote her thesis in Engineering Education, specifically from a Learning Styles perspective. In the summer of 2013, Cyndy interned with the Walt Disney Company in the Workforce Management Department. As an intern, she was able to create a Variance Analysis Tool to monitor workload forecasting for the Walt Disney World resort. She returned to the Walt Disney World Resort during the summer of 2014 as a Staffing Strategies Intern. Cyndy is now working in the Washington, D.C. Metro area with Accenture Federal Services.

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Joseph Wilck United States Air Force Academy

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Dr. Joe Wilck is an Assistant Professor of Operations Research at the United States Air Force Academy. He is a registered Professional Engineer. He is a volunteer leader with the Institute of Industrial Engineers (IIE) and the American Society for Engineering Education (ASEE). He is also an active member of INFORMS, MORS, INCOSE, and TRB. His research is in the areas of applied optimization and engineering education, and he has been funded by the National Science Foundation, the Department of Energy, DARPA, and the North Carolina Department of Transportation; among others. He primarily teaches courses in analytics, operations research, supply chain, and logistics.

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As the need for industrial engineers across all sectors of the national economy grows, it is of vital importance for universities and colleges to retain students in these programs and provide a satisfying academic experience. This paper discusses the results of a study performed at a large public university to identify and implement the significant factors and predictors of student satisfaction and motivation within the industrial engineering undergraduate classroom. Building on a previous study performed at this major public university, the three overarching factors influencing student satisfaction and motivation were found to be: Instructor Interaction and Feedback, Classroom Environment, and Modes of Instruction. This study defined the specific factors that feed into each of the aforementioned areas of Instructor Interaction and Feedback, Classroom Environment, and Modes of Instruction.

After creating multiple ordinal logistic regression models, built from the responses of 107 randomly selected junior Industrial Engineering students who were selected to participate in a survey, the significant factors were chosen by comparing p-values - a measure of statistical significance - against a chosen significance level. The three main classroom factors of Instructor Interaction and Feedback, Classroom Environment, and Modes of Instruction were regressed using ordinal logistic regression for survey data, as well as an overall model of those factors related to overall student satisfaction in the classroom. Eleven significant factors influencing student satisfaction and motivation were identified across the three main classroom regression models.

Once the factors that most significantly influence student motivation and satisfaction were identified, an implementation model was created and tested. As a result of the work mentioned, the pedagogical method to be presented is known as the “Interact, Cultivate, and Deliver” method, also known as the “I-C-D” method. The method is a simple way to implement the eleven significant factors found across the three ordinal logistic regression models in a succinct manner for instructors. Industrial engineering instructors can increase student satisfaction and motivation by adopting this methodology in the classroom which “interacts, cultivates, and delivers” according to the eleven significant factors presented.

When this model is implemented into the industrial engineering classroom, student satisfaction and motivation are predicted to significantly increase. Instructors should strive to be a “coach” in the classroom - allowing students to feel that the instructor is on their “team” toward the goal of student learning. With both instructors and students aiming toward the same goal of increased self-learning, student motivation and satisfaction will naturally increase within the classroom.

Three undergraduate industrial engineering courses were piloted for a student satisfaction study at this large public university. The quantitative and qualitative data collected from the pilot implementation study between the three industrial engineering courses at this public university will be discussed. Through this study, it was found that when the significant factors were implemented into the classroom, the satisfaction and motivation levels (as rated by students) were statistically significantly better than predicted values for both metrics. In fact, when student satisfaction data was collected for the course in which the I-C-D method was fully implemented, 98.61% (71 out of 72) students rated both the overall quality of the instructor and the overall quality of the course as a 6 or a 7 (highest rating) on a 7 point Likert scale. In fact, the mean of the overall quality of the course rating was 6.78 while the mean of the overall quality of the instructor rating was 6.88.

With the knowledge gained from the implementation of this model, the author’s encourage implementation and testing of this model in other large public universities in an effort to increase student satisfaction and motivation in the industrial engineering classroom.

Lynch, P. C., & Bober, C., & Wilck, J. (2016, June), Modeling Student Satisfaction and Implementation of the I-C-D Method to Improve the Industrial Engineering Undergraduate Course Experience Paper presented at 2016 ASEE Annual Conference & Exposition, New Orleans, Louisiana. 10.18260/p.25743

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