A Hybrid Mastery-Conventional Assessment in Engineering Economy

Omar Ashour; Faisal Aqlan; Paul C. Lynch

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Conference: 2017 ASEE Annual Conference & Exposition
Location: Columbus, Ohio
Publication Date: June 24, 2017
Start Date: June 24, 2017
End Date: June 28, 2017
Conference Session: Engineering Economy Division Technical Session 2
Tagged Division: Engineering Economy
Page Count: 14
DOI: 10.18260/1-2--27469
Permanent URL: https://peer.asee.org/27469
Download Count: 598

Paper Authors

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Omar Ashour The Pennsylvania State University, The Behrend College orcid.org/0000-0003-3775-6445

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Dr. Omar Ashour is an Assistant Professor of Industrial Engineering at Pennsylvania State University, The Behrend College, Erie, PA. He earned his MEng in Industrial Engineering/Ergonomics and Human Factors and PhD in Industrial Engineering and Operations Research from Pennsylvania State University in 2010 and 2012, respectively. He earned his B.S. in Industrial Engineering/Design and Manufacturing and M.S. in Industrial Engineering from Jordan University of Science and Technology in 2005 and 2007, respectively. Dr. Ashour is the first recipient of William and Wendy Korb Early Career Professorships in Industrial Engineering at Penn State Behrend. His research interest mainly includes process improvement, modeling and simulation, and decision making modeling of manufacturing and healthcare systems. He is a member of the Institute of Industrial and Systems Engineers (IISE), Jordanian Engineering Association (JEA), and Society of Industrial Engineering and Operations Management (IEOM). Currently, Dr. Ashour serves as a co-Chair for the Modeling and Simulation track in the 2017 IISE Annual Conference and Expo, a chair for the Sustainable Manufacturing track in the 2016 Detroit IEOM conference, a Director of the IISE Logistic and Supply Chain division, and a Director of the IISE Engineering Economy division.

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Faisal Aqlan Penn State Behrend orcid.org/0000-0002-0695-5364

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Dr. Faisal Aqlan is an assistant professor of industrial engineering at Penn State Behrend. He earned the B.S. and M.S. in industrial engineering from Jordan University of Science and Technology in 2007 and 2010, respectively and the Ph.D. in Industrial and Systems Engineering from the State University of New York at Binghamton in 2013. Prior to joining the faculty at Behrend, Dr. Aqlan was a faculty member in industrial and system engineering at the University of New Haven where he taught undergraduate and graduate courses. Dr. Aqlan has also worked on industry projects with Innovation Associates Company and IBM Corporation. His work has resulted in both business value and intellectual property. He has published several papers in reputed journals and conferences. Dr. Aqlan is a senior member of the Institute of Industrial and Systems Engineers (IISE) and has received numerous awards and honors including the IBM Vice President award for innovation excellence.

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Paul C. Lynch Penn State Erie, The Behrend College

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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, IISE, 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, IISE, 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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Abstract

Mastery learning and assessment is an approach that has existed in education for decades. There are two main approaches for mastery learning: Bloom’s Learning for Mastery and Keller’s Personalized System of Instruction. Both approaches hinge on the idea of dividing the course material into basic modules. The students have to master each module before moving to the next module. Student’s mastery is assessed via set of tests where each test is focused on a certain concept. Mastery learning and assessment have been implemented for a number of years at this University within the School of Engineering. The implementation of mastery learning was solely focused on fundamental engineering courses (i.e. Statics, Strength of Materials, and Thermodynamics). The use of mastery approach in these fundamental courses showed clear evidence that students who passed these courses with at least a C could solve engineering problems successfully and were better prepared for advanced courses in engineering when compared to the conventional learning and assessment approach. Mastery learning was not utilized in the engineering economy course until this semester (Fall 2016). In this study, a variation of the mastery learning approach is implemented in an engineering economy course at this large U.S. public University. The engineering economy course is a hybrid in the sense that the first third of the course is mastery learning where the students are required to successfully solve problems before receiving credit for their work. The pace of the course is led by the instructor. The remaining two thirds of the course is a traditional learning and assessment approach where grades are based on partial credit. The mastery portion of the course may require students to take assessments multiple times prior to receiving credit for their work. Two assessment tests are delivered in the mastery portion of the course. Each test involves a first attempt, a retake attempt, and a final attempt. The retake and final attempts include new questions that have similar difficulty levels to the first attempt questions while also testing the same concepts. The student will not receive grade points for these tests until he/she successfully solves the test questions. Successfully solving the test is defined as achieving at least a B grade for the tested concepts. After the initial attempt, students are awarded reduced credit for successive retakes. The complete detail of the credit breakdown is displayed in the paper. In this paper, mastery learning and concept assessment practices are applied to the engineering economy course. The initial set of concepts in this course. i.e., time value of money and money management, are fundamental to understanding the remainder of the engineering economy concepts. The main hypothesis in this study is that mastery learning and assessment motivates students to learn the fundamental concepts in engineering economy better than the conventional approach. Data has been collected and analyzed to test the effectiveness of the implementation of mastery learning in the engineering economy course. The initial data analysis has shown that the implementation of the mastery learning practice led to a statistically significant increase in student knowledge of the time value of money and money management concepts in the engineering economy course when compared to the traditional teaching approach. A two sample t-test was performed. The two samples tested are statistically different. The average of grades on the first midterm exam were 87.89% and 75.95% for the mastery approach cohort and traditional approach cohort, respectively. This paper will discuss in detail the background of mastery approach that was implemented in the engineering economy course, and the quantitative data analysis that was carried out on student performance for both the traditional and mastery approaches. Future research should focus on collecting additional data to confirm the results in the engineering economy course.

Citation
Format

Ashour, O., & Aqlan, F., & Lynch, P. C. (2017, June), A Hybrid Mastery-Conventional Assessment in Engineering Economy Paper presented at 2017 ASEE Annual Conference & Exposition, Columbus, Ohio. 10.18260/1-2--27469

TY - CPAPER
AB - Mastery learning and assessment is an approach that has existed in education for decades. There are two main approaches for mastery learning: Bloom’s Learning for Mastery and Keller’s Personalized System of Instruction. Both approaches hinge on the idea of dividing the course material into basic modules. The students have to master each module before moving to the next module. Student’s mastery is assessed via set of tests where each test is focused on a certain concept.
Mastery learning and assessment have been implemented for a number of years at this University within the School of Engineering. The implementation of mastery learning was solely focused on fundamental engineering courses (i.e. Statics, Strength of Materials, and Thermodynamics). The use of mastery approach in these fundamental courses showed clear evidence that students who passed these courses with at least a C could solve engineering problems successfully and were better prepared for advanced courses in engineering when compared to the conventional learning and assessment approach.
Mastery learning was not utilized in the engineering economy course until this semester (Fall 2016). In this study, a variation of the mastery learning approach is implemented in an engineering economy course at this large U.S. public University. The engineering economy course is a hybrid in the sense that the first third of the course is mastery learning where the students are required to successfully solve problems before receiving credit for their work. The pace of the course is led by the instructor. The remaining two thirds of the course is a traditional learning and assessment approach where grades are based on partial credit. The mastery portion of the course may require students to take assessments multiple times prior to receiving credit for their work. Two assessment tests are delivered in the mastery portion of the course. Each test involves a first attempt, a retake attempt, and a final attempt. The retake and final attempts include new questions that have similar difficulty levels to the first attempt questions while also testing the same concepts. The student will not receive grade points for these tests until he/she successfully solves the test questions. Successfully solving the test is defined as achieving at least a B grade for the tested concepts. After the initial attempt, students are awarded reduced credit for successive retakes. The complete detail of the credit breakdown is displayed in the paper.
In this paper, mastery learning and concept assessment practices are applied to the engineering economy course. The initial set of concepts in this course. i.e., time value of money and money management, are fundamental to understanding the remainder of the engineering economy concepts. The main hypothesis in this study is that mastery learning and assessment motivates students to learn the fundamental concepts in engineering economy better than the conventional approach. Data has been collected and analyzed to test the effectiveness of the implementation of mastery learning in the engineering economy course. The initial data analysis has shown that the implementation of the mastery learning practice led to a statistically significant increase in student knowledge of the time value of money and money management concepts in the engineering economy course when compared to the traditional teaching approach. A two sample t-test was performed. The two samples tested are statistically different. The average of grades on the first midterm exam were 87.89% and 75.95% for the mastery approach cohort and traditional approach cohort, respectively. This paper will discuss in detail the background of mastery approach that was implemented in the engineering economy course, and the quantitative data analysis that was carried out on student performance for both the traditional and mastery approaches. Future research should focus on collecting additional data to confirm the results in the engineering economy course.
AU - Omar Ashour
AU - Faisal Aqlan
AU - Paul C. Lynch
CY - Columbus, Ohio
DA - 2017/06/24
PB - ASEE Conferences
TI - A Hybrid Mastery-Conventional Assessment in Engineering Economy
UR - https://peer.asee.org/27469
DO - 10.18260/1-2--27469
ER -