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A Study on the Effectiveness of the CLICK Approach in an Operations Research Course

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Conference

2021 ASEE Virtual Annual Conference Content Access

Location

Virtual Conference

Publication Date

July 26, 2021

Start Date

July 26, 2021

End Date

July 19, 2022

Conference Session

Computers in Education 10 - Technology 2

Tagged Division

Computers in Education

Page Count

17

DOI

10.18260/1-2--36616

Permanent URL

https://peer.asee.org/36616

Download Count

43

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Paper Authors

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Christian E. Lopez Lafayette College Orcid 16x16 orcid.org/0000-0003-2801-4618

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I am an Assistant Professor of Computer Science with an affiliation in Mechanical Engineering at Lafayette College.

I completed my Ph.D. from the Harold and Inge Marcus Department of Industrial and Manufacturing Engineering at the Pennsylvania State University, and a Master of Science in Industrial and Systems Engineering from the Rochester Institute of Technology, NY. I worked in the Service and Manufacturing sectors before pursuing m yPh.D.

I am interested in the design and optimization of intelligent decision support systems and persuasive technologies to augment human proficiencies. My research over the last few years has focused on the development of machine learning methods that personalize the human learning process and enhance the efficiency of task completion and decision making.

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Omar Ashour Pennsylvania State University Orcid 16x16 orcid.org/0000-0003-3775-6445

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Dr. Omar Ashour is an Associate Professor of Industrial Engineering at Pennsylvania State University,
The Behrend College. Dr. Ashour received the B.S. degree in Industrial Engineering/Manufacturing Engineering
and the M.S. degree in Industrial Engineering from Jordan University of Science and Technology
(JUST) in 2005 and 2007, respectively. He received his M.Eng. degree in Industrial Engineering/Human
Factors and Ergonomics and the Ph.D. degree in Industrial Engineering and Operations Research from
Pennsylvania State University (PSU) in 2010 and 2012, respectively. Dr. Ashour was the inaugural recipient
of William and Wendy Korb Early Career Professorship in Industrial Engineering in 2016. Dr.
Ashour’s research areas include applied decision making, modeling and simulation, virtual reality, and
process improvement. He contributed to research directed to improve engineering education.

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James Devin Cunningham Carnegie Mellon University

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PhD student in Mechanical Engineering at Carnegie Mellon University, with research interests in machine learning and reinforcement learning.

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Conrad Tucker Carnegie Mellon University

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Conrad Tucker is a professor of mechanical engineering. He focuses on the design and optimization of systems through the acquisition, integration, and mining of large scale, disparate data.

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Abstract

This paper presents an investigation of the effectiveness of the connected learning and integrated course knowledge (CLICK) approach. The CLICK approach aims to integrate the knowledge across the industrial engineering (IE) curriculum by leveraging immersive technology, i.e., 3D simulation and virtual reality (VR). The effectiveness of the CLICK approach is measured by its impact on students’ motivation, engineering identity, and learning outcomes. In this work, a virtual system that simulates a manufacturing assembly system was developed and used in an operations research (OR) course. The virtual system includes data collection tasks and exercises to calculate statistics that are taught in a probability and statistics course, and inventory and queueing theories concepts that are taught in an operations research course. The virtual system (CLICK learning module) is used to teach inventory and queueing theory concepts. Due to COVID-19 and the sudden shift to remote learning, the research team faced challenges including limitations in performing in-person experiments on campus as well as the potential risk of spreading the disease when VR headsets are used by several people. To alleviate some of the challenges, the researchers built the virtual system in simulation software, i.e., Simio, to provide more flexibility and scalability. The virtual system can be run on a regular personal computer without the need for a VR-ready computer and VR headsets. Yet, the virtual system can be run on an Oculus VR headset if the student prefers to do so. The study involves two groups: Control and intervention groups. The control group is represented by the students who are taught traditionally while the intervention group is represented by the students who are taught with the aid of the CLICK learning module. The results of this study compared the groups in terms of students’ motivation, and engineering identity. The learning outcomes were assessed using a self-assessment instrument and the student's grades in the learning module. The data of the control and intervention groups were collected at Penn State Behrend in Fall 2019, and Fall 2020 semesters, respectively. The groups were not statistically significantly different for motivation and Engineering Identity, however, the resulted motivation and Engineering Identity scores for the intervention group were not worse than the control group considering the shift to remote learning setting. The students showed good learning outcomes when the CLICK learning module was used. The grades were positively correlated to the motivation and Engineering Identity scores.

Lopez, C. E., & Ashour, O., & Cunningham, J. D., & Tucker, C. (2021, July), A Study on the Effectiveness of the CLICK Approach in an Operations Research Course Paper presented at 2021 ASEE Virtual Annual Conference Content Access, Virtual Conference. 10.18260/1-2--36616

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