An Application-Oriented Course to Improve Student Performance in Mathematics Courses

Jaskirat Sodhi; Ashish Borgaonkar; Edwin Hou; Moshe Kam

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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: First-Year Programs Division - Visualization and Mathematics
Tagged Divisions: First-Year Programs and Mathematics
Page Count: 11
DOI: 10.18260/1-2--29772
Permanent URL: https://peer.asee.org/29772
Download Count: 490

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Paper Authors

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Jaskirat Sodhi New Jersey Institute of Technology

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Dr. Jaskirat Sodhi is a University Lecturer in the department of Mechanical and Industrial Engineering at New Jersey Institute of Technology.

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Ashish Borgaonkar New Jersey Institute of Technology

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Dr. Ashish Borgaonkar works as Asst. Dean in the Office of the Dean, Newark College of Engineering, NJIT, Newark, NJ. He has taught several engineering courses primarily in the first year engineering, civil engineering, and mechanical engineering departments and won multiple awards for excellence in instruction. He also has worked on several programs and initiatives to help students bridge the gap between high school and college as well as preparing students for the rigors of mathematics. His research interests include engineering education, excellence in instruction, water and wastewater treatment, civil engineering infrastructure, and transportation engineering.

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Edwin Hou New Jersey Institute of Technology

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Dr. Edwin Hou is a professor in the Helen and John C. Hartmann Department of Electrical and Computer Engineering at New Jersey Institute of Technology. His research interests include embedded systems, autonomous vehicles, nonlinear optimization, and engineering education.

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Moshe Kam P.E. New Jersey Institute of Technology

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Moshe Kam serves at present as Dean of the Newark College of Engineering at the New Jersey Institute
of Technology (NJIT). Earlier he served as the Robert Quinn Professor and Department Head of Electrical
and Computer Engineering at Drexel University. His education is in Electrical Engineering (B.S., Tel Aviv
University (1976); M.S.(1985) and Ph.D. (1987), Drexel University). Kam's professional interests are in
detection and estimation, multi-sensor systems, data and decision fusion, robotics, and engineering
education. He served as President and CEO of IEEE, and on the Boards of Directors of IEEE (2003-2007,
2010-2012)and ABET (2009-2014). During his tenure as IEEE's Vice President for Educational Activities
(2005-2007) IEEE launched tryengineering.org and expanded greatly its pre-university engineering
programs, including EPICS-in-IEEE. Kam is a Fellow of IEEE "for contributions to the theory of decision
fusion and distributed detection." He received the IEEE Third Millennium Medal and the C. Holmes
MacDonald Award "for the Outstanding Young Electrical Engineering Educator."

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Abstract

This is an evidence-based practice paper. Performance in pre-calculus and calculus courses has a strong impact on student success, retention, and graduation in any engineering school. One of the important reasons why students perform poorly in these courses is their failure to make the connection between concepts of mathematics, and engineering problems and applications. Without making this connection, students lose interest in their mathematics courses, resulting in high failure rates. This also strongly affects students’ chances to make satisfactory academic progress within their degree, as mathematics and science courses are usually pre-requisites or co-requisites to their core engineering courses. This is a serious problem and must be addressed if students’ retention and graduation rates are to be improved. Starting Fall 2016, New Jersey Institute of Technology (NJIT) is offering a new course: Analytical Methods for Engineering Applications (ENGR101). This is an application-oriented course based on the Wright State University model adopted by over 40 colleges and universities. ENGR101 specifically targets students that are ill-prepared in mathematics based on the performance of a mandatory placement exam that all incoming first-time full-time first-year students take. All students placed in either of the two pre-calculus courses would take ENGR 101 in their first or second semester. Throughout the course, students are introduced to engineering problems and applications that rely on concepts of mathematics. Although this course has only been offered three times thus far, preliminary results are very encouraging. We found that students taking ENGR101 mostly did better in their pre-calculus courses than students who did not take ENGR101. An improvement in performance was also seen in their subsequent-semester mathematics courses. We are committed to offer this course for at least three consecutive years to assess the short-term and long-term effect on students’ academic progress, performance in mathematics courses, and retention and graduation rates. This paper includes information about setting up such a course and the challenges that needed to be met. It also presents the results of our analysis thus far, including a comparison of the performance in mathematics courses of the participants against a control group.

Citation
Format

Sodhi, J., & Borgaonkar, A., & Hou, E., & Kam, M. (2018, June), An Application-Oriented Course to Improve Student Performance in Mathematics Courses Paper presented at 2018 ASEE Annual Conference & Exposition , Salt Lake City, Utah. 10.18260/1-2--29772

TY - CPAPER
AB - This is an evidence-based practice paper. Performance in pre-calculus and calculus courses has a strong impact on student success, retention, and graduation in any engineering school. One of the important reasons why students perform poorly in these courses is their failure to make the connection between concepts of mathematics, and engineering problems and applications. Without making this connection, students lose interest in their mathematics courses, resulting in high failure rates. This also strongly affects students’ chances to make satisfactory academic progress within their degree, as mathematics and science courses are usually pre-requisites or co-requisites to their core engineering courses. This is a serious problem and must be addressed if students’ retention and graduation rates are to be improved. Starting Fall 2016, New Jersey Institute of Technology (NJIT) is offering a new course: Analytical Methods for Engineering Applications (ENGR101). This is an application-oriented course based on the Wright State University model adopted by over 40 colleges and universities. ENGR101 specifically targets students that are ill-prepared in mathematics based on the performance of a mandatory placement exam that all incoming first-time full-time first-year students take. All students placed in either of the two pre-calculus courses would take ENGR 101 in their first or second semester. Throughout the course, students are introduced to engineering problems and applications that rely on concepts of mathematics. Although this course has only been offered three times thus far, preliminary results are very encouraging. We found that students taking ENGR101 mostly did better in their pre-calculus courses than students who did not take ENGR101. An improvement in performance was also seen in their subsequent-semester mathematics courses. We are committed to offer this course for at least three consecutive years to assess the short-term and long-term effect on students’ academic progress, performance in mathematics courses, and retention and graduation rates. This paper includes information about setting up such a course and the challenges that needed to be met. It also presents the results of our analysis thus far, including a comparison of the performance in mathematics courses of the participants against a control group.
AU - Jaskirat Sodhi
AU - Ashish Borgaonkar
AU - Edwin Hou
AU - Moshe Kam P.E.
CY - Salt Lake City, Utah
DA - 2018/06/23
PB - ASEE Conferences
TI - An Application-Oriented Course to Improve Student Performance in Mathematics Courses
UR - https://peer.asee.org/29772
DO - 10.18260/1-2--29772
ER -