Optimizing the Curriculum in an Engineering Statistics Course with Realistic Problems to Enhance Learning

Kyle Frederick Larsen; Nm A Hossain; Hani Serhal Saad; Abolfazl Amin; Heechang Bae

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Conference: 2018 ASEE Zone IV Conference
Location: Boulder, Colorado
Publication Date: March 25, 2018
Start Date: March 25, 2018
End Date: March 27, 2018
Page Count: 12
DOI: 10.18260/1-2--29623
Permanent URL: https://peer.asee.org/29623
Download Count: 409

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Paper Authors

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Kyle Frederick Larsen P.E. Eastern Washington University

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Dr. Larsen currently teaches mechanical engineering at Eastern Washington University. He received his B.S. and M.S. degrees in mechanical engineering from California State University Sacramento and his Ph.D. in mechanical engineering from Brigham Young University.

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Nm A Hossain Eastern Washington University

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Dr. Hossain is Professor in the Department of Engineering and Design at Eastern Washington University, Cheney, WA. His research interests involve the computational and experimental analysis of lightweight space structures and composite materials. Dr. Hossain received M.S. and Ph.D. degrees in Materials Engineering and Science from South Dakota School of Mines and Technology, Rapid City, South Dakota.

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Hani Serhal Saad Eastern Washington University

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B.S. and M.S. in Mechanical Engineering, Marquette University
PhD. in Mechanical Engineering, Washington State University

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Abolfazl Amin Utah Valley University

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Ph.D. in Mechanical Engineering, Brigham Young University
M.S. in Mechanical Engineering, Brigham Young University
B.S. in Mechanical Engineering, Brigham Young University

Engineering Professor at Utah Valley University since 1990.
Instructed Mathematics and Physics as an adjunct at University of Utah and Westminster College.

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Heechang Bae Eastern Washington University

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Abstract

The primary objective of an engineering statistics course is to provide the fundamental knowledge necessary to understand both descriptive and inferential statistics and how to apply it to real life engineering situations. This is important in nearly all engineering applications and especially in quality control used in all manufacturing processes. Having a thorough understanding of probability as it pertains to uncertainty is critical for all engineering students. In addition, teaching students how to apply and use statistics in real life settings is just as or more important.

Nearly all Universities require some type of engineering statistics class in order for students to graduate. How effective these courses are in teaching the students how to use and apply statistics in a real world engineering setting is unclear. Most of these schools teach the basics such as general probability, probability distributions, confidence intervals, hypothesis testing, regression, analysis of variance, nonparametric statistics, and statistical quality control. However, most of this learning is in the class room and not applied to engineering projects so the students don’t know how to use it in real applications. In our institution we don’t have students take a typical engineering statistics class rather we require a one-quarter long Laboratory Analysis and Reports course. In this class, among other things, we have the students study several engineering problems analyzing the data including error analysis and data interpretation. By teaching the class in this manner the students not only learn statistics but they also learn how to use it in solving real engineering problems.

Solving these realistic problems helps our students to also enhance their conceptual understanding, and motivate them to further pursue their learning in the use of statistics. This paper will present in detail several interesting problems related to different uses of statistics and how they are linked to convey the message of targeted course objectives. The paper will also present how different topics taught in this class fulfill the targeted course objectives, which are mapped with ABET Engineering criteria. Furthermore, this paper will explain the details of this teaching methodology and discuss the educational outcomes obtained in our lab analysis course. This paper will discuss a series of problems that are currently used at our institution to best help the students apply what they are learning in the course. Furthermore, this paper will address how to properly integrate this in the curriculum to optimize the students learning. In addition, a study will be conducted of several other colleges to find the best possible problems. From this study, the best applications along with their optimal integration in the classroom setting with interesting and realistic problems, will be surveyed, explored, and implementation recommendations will be given.

Citation
Format

Larsen, K. F., & Hossain, N. A., & Saad, H. S., & Amin, A., & Bae, H. (2018, March), Optimizing the Curriculum in an Engineering Statistics Course with Realistic Problems to Enhance Learning Paper presented at 2018 ASEE Zone IV Conference, Boulder, Colorado. 10.18260/1-2--29623

TY  - CPAPER
AB  - The primary objective of an engineering statistics course is to provide the fundamental knowledge necessary to understand both descriptive and inferential statistics and how to apply it to real life engineering situations.  This is important in nearly all engineering applications and especially in quality control used in all manufacturing processes. Having a thorough understanding of probability as it pertains to uncertainty is critical for all engineering students. In addition, teaching students how to apply and use statistics in real life settings is just as or more important.

Nearly all Universities require some type of engineering statistics class in order for students to graduate.  How effective these courses are in teaching the students how to use and apply statistics in a real world engineering setting is unclear. Most of these schools teach the basics such as general probability, probability distributions, confidence intervals, hypothesis testing, regression, analysis of variance, nonparametric statistics, and statistical quality control.
However, most of this learning is in the class room and not applied to engineering projects so the students don’t know how to use it in real applications.  
	
In our institution we don’t have students take a typical engineering statistics class rather we require a one-quarter long Laboratory Analysis and Reports course.  In this class, among other things, we have the students study several engineering problems analyzing the data including error analysis and data interpretation. By teaching the class in this manner the students not only learn statistics but they also learn how to use it in solving real engineering problems.  

 Solving these realistic problems helps our students to also enhance their conceptual understanding, and motivate them to further pursue their learning in the use of statistics. This paper will present in detail several interesting problems related to different uses of statistics and how they are linked to convey the message of targeted course objectives. The paper will also present how different topics taught in this class fulfill the targeted course objectives, which are mapped with ABET Engineering criteria. Furthermore, this paper will explain the details of this teaching methodology and discuss the educational outcomes obtained in our lab analysis course. This paper will discuss a series of problems that are currently used at our institution to best help the students apply what they are learning in the course. Furthermore, this paper will address how to properly integrate this in the curriculum to optimize the students learning. In addition, a study will be conducted of several other colleges to find the best possible problems. From this study, the best applications along with their optimal integration in the classroom setting with interesting and realistic problems, will be surveyed, explored, and implementation recommendations will be given.  

AU  - Kyle Frederick Larsen P.E.
AU  - Nm A Hossain
AU  - Hani Serhal Saad
AU  - Abolfazl Amin
AU  - Heechang Bae
CY  - Boulder, Colorado
DA  - 2018/03/25
PB  - ASEE Conferences
TI  - Optimizing the Curriculum in an Engineering Statistics Course with Realistic Problems to Enhance Learning 
UR  - https://peer.asee.org/29623
DO  - 10.18260/1-2--29623
ER  -