How to Make Engineering Statistics More Appealing to Millennial Students

Robert G. Batson

Download Paper | Permalink

Conference: 2018 ASEE Annual Conference & Exposition
Location: Salt Lake City, Utah
Publication Date: June 23, 2018
Start Date: June 23, 2018
End Date: July 27, 2018
Conference Session: Mathematics Division Technical Session 3
Tagged Division: Mathematics
Tagged Topic: Diversity
Page Count: 12
DOI: 10.18260/1-2--30585
Permanent URL: https://peer.asee.org/30585
Download Count: 492

Paper Authors

biography

Robert G. Batson P.E. University of Alabama

visit author page

Bob Batson is a professor of construction engineering at The University of Alabama. His Ph.D. training was in operations research, and he has developed expertise in applied statistics over the past thirty years. He currently teaches the required courses in project management, safety engineering, engineering management, and engineering statistics within the undergraduate programs of the Civil, Construction, and Environmental Engineering Department, and graduate courses in operations research and engineering statistics. Batson's research interests include project risk management, quality management, supply chain management, maintenance management, and safety management. Since joining the University in 1984, he has held research contracts and grants worth over $2.4M, with organizations such as Mercedes-Benz, American Cast Iron Pipe Company, BellSouth, NSF, NASA, the Federal Aviation Administration, Army Aviation and Missile Command, and Alabama DOT. He served as Head of the Department of Industrial Engineering during 1994-99 and 2005-2010. He is past president of the ASEE Southeastern Section, and has served as an ABET Program Elevator for IIE the past fifteen years. He is a Fellow of the American Society for Quality, and a PE in quality engineering in the State of California.

visit author page

Download Paper | Permalink

Abstract

How to Make Engineering Statistics More Appealing to Millennial Students

A one-semester calculus-based course in Engineering Statistics is taught in almost all engineering colleges, and is viewed as a “tools” course versus courses focused on engineering concepts and methods. Most current engineering faculty members were undergrads in 1970-2010 and graduate students 1975-2015. We argue that the way many of us learned probability and statistics, even as graduate students, does not support engagement and appeal to millennial students. The purpose of this paper is to recommend adapting new pedagogical methods to the accepted topics in an introductory probability and statistics course for engineering undergraduates—methods that better match the learning characteristics of millennial students in our courses. In a nutshell, those characteristics may be summarized as: (1) They want relevance to their major, and future engineering career; (2) They want rationale (for the textbook selected, and for specific course policies and assignments); (3) They revel in technology (to collect data, compute, communicate, and multi-task); (4) They want a relaxed, hands-on environment; (5) They prefer instructors who rotate among several classroom delivery methods.

Considering the “Five R’s” learning characteristics of millennial students, and recommendations of highly respected engineering statistics educators, we suggest a modification of the introductory probability and statistics course for engineers, adapted as follows: (1) Use textbooks that have a plethora of examples and exercises from the students' major fields; (2) Establish student rapport and respect for experience of the textbook author and the instructor while avoiding authoritarian style; (3) Use a statistical package integrated into the textbook, with in-class tutorials and homework solutions that require use of the package; (4) Use of quincunx and stat-a-pult training devices, for in-class demonstrations; (5) Alternate between lecture, problem solving, software tutorial, and physical demonstration. There is a long history of articles similar to this one attempting to identify best practices in teaching probability and statistics to engineering students, who are often mixed together in sections with more than one major. Sixteen articles or books from the past 40 years are referenced to provide the foundation to support the course concept we recommend. Through review of the well-documented learning characteristics of today’s Millennial students, the observations of well-known engineering educators, and our own experiences teaching engineering statistics courses the past 30 years, we have recommended a multi-faceted approach to modernize the introductory engineering statistics course. Hopefully other instructors, whether new or seasoned, can benefit from these recommendations.

Citation
Format

Batson, R. G. (2018, June), How to Make Engineering Statistics More Appealing to Millennial Students Paper presented at 2018 ASEE Annual Conference & Exposition , Salt Lake City, Utah. 10.18260/1-2--30585

TY  - CPAPER
AB  - How to Make Engineering Statistics More Appealing to Millennial Students

A one-semester calculus-based course in Engineering Statistics is taught in almost all engineering colleges, and is viewed as a “tools” course versus courses focused on engineering concepts and methods. Most current engineering faculty members were undergrads in 1970-2010 and graduate students 1975-2015. We argue that the way many of us learned probability and statistics, even as graduate students, does not support engagement and appeal to millennial students. The purpose of this paper is to recommend adapting new pedagogical methods to the accepted topics in an introductory probability and statistics course for engineering undergraduates—methods that better match the learning characteristics of millennial students in our courses. In a nutshell, those characteristics may be summarized as: (1) They want relevance to their major, and future engineering career; (2) They want rationale (for the textbook selected, and for specific course policies and assignments); (3) They revel in technology (to collect data, compute, communicate, and multi-task); (4) They want a relaxed, hands-on environment; (5) They prefer instructors who rotate among several classroom delivery methods.

Considering the “Five R’s” learning characteristics of millennial students, and recommendations of  highly respected engineering statistics educators, we suggest a modification of the introductory probability and statistics course for engineers, adapted as follows: (1) Use textbooks that have a plethora of examples and exercises from the students&#39; major fields; (2) Establish student rapport and respect for experience of the textbook author and the instructor while avoiding authoritarian style; (3) Use a statistical package integrated into the textbook, with in-class tutorials and homework solutions that require use of the package; (4) Use of quincunx and stat-a-pult training devices, for in-class demonstrations; (5) Alternate between lecture, problem solving, software tutorial, and physical demonstration. 
There is a long history of articles similar to this one attempting to identify best practices in teaching probability and statistics to engineering students, who are often mixed together in sections with more than one major. Sixteen articles or books from the past 40 years are referenced to provide the foundation to support the course concept we recommend. Through review of the well-documented learning characteristics of today’s Millennial students, the observations of well-known engineering educators, and our own experiences teaching engineering statistics courses the past 30 years, we have recommended a multi-faceted approach to modernize the introductory engineering statistics course. Hopefully other instructors, whether new or seasoned, can benefit from these recommendations. 

AU  - Robert G. Batson P.E.
CY  - Salt Lake City, Utah
DA  - 2018/06/23
PB  - ASEE Conferences
TI  - How to Make Engineering Statistics More Appealing to Millennial Students
UR  - https://peer.asee.org/30585
DO  - 10.18260/1-2--30585
ER  -