AN INTEGRATED PROJECT-BASED COURSE IN MATHEMATICS AND ENGINEERING WITH ENTREPRENEURSHIP Dr. Shinemin Lin Savannah State University

Abstract  Engineering Technology faculty regularly encounter undergraduates taking courses in their professional field of study who lack adequate preparation in mathematics. Additionally, students facing difficulty in applying mathematical concepts may be due to the fact that examples from engineering technology disciplines are not widely used in mathematics courses. Also, a recent report by a select group of engineering technology educators and industry leaders calls for substantive changes in the ways we recruit and educate engineers for the 21st century. The report suggests developing curricula which are relevant to the careers of students, attractive to a more diverse student population, and connected to the needs of society.

 In response to these issues and the growing demand to retain minority students in engineering and technology programs, we developed a problem-solving based mathematics course. The goals for creating this course were to: 1) increase retention rates of minority students enrolled in engineering and technology programs, 2) introduce engineering problem- solving methodologies in mathematics courses, and 3) promote team work among students. This paper describes our course structure, course activities, E-Team projects and initial evaluation of the effectiveness of this course.

 We taught Math 1113 Precalculus using this approaches in summer Most students enjoyed problem-solving based instructions. They were not fear about Trigonometry any more. Their final performance is no less than the other Precalculus classes. Furthermore, female students performed better than male students. Although we don’t see significant difference from the other classes, students’ attitude toward mathematics course is totally different. Since the sample is very small, 12 students in the class, we need to get bigger sample to test our hypothesis. We also need to get follow up research to check if those students are ready for calculus I, or engineering technology courses  This project was sponsored by NCIIA award grant #

Course Structures  This is a entrance level project based course in engineering and mathematics which leads to an entrepreneurship. Using an application- oriented, hand-on-approach this course will address only the salient math topics actually used in a variety of core engineering and technology courses. In addition to Trigonometry, the course will cover vectors, complex numbers in polar form, matrix algebra and introduction to differential and integral calculus.  The class will use Matlab to explore mathematics concepts.  Dr. Lin will cover math concepts and Dr. Asda will be in charge in Engineering applications  Dr. Lin and Dr. Asda will assign 50% grades respectively

Contents  Unit 1. Course Introduction ; Application of Algebra in Engineering Technology – Linear Equations; Application of Algebra in Engineering – Quadratic Equations  Lab: Introduction to MATLAB  Unit 2: Trigonometry – One link Planar Robot; Trigonometry – Two link Planar robots.  Lab: Application of Algebra in Engineering Technology: The One-loop Circuit  Unit 3: 2-D Vectors in Engineering Technology; Complex number in Engineering Technology  Lab: Measurement of trigonometric relationships in One and Two-link Planar Robots; Application of Vectors in Statics.  Unit 4: Sinusoids and Harmonic signals in Engineering Technology; Systems of Equations in Engineering Technology  Lab: Measurement and Analysis of Harmonic Signals  Unit 5: Matrix algebra and Vectors in Engineering Technology  Lab: System of Equations in Engineering Technology: The two loop circuit  Unit 6: Entrepreneurship and E-Team Projects.  Lab: E-team project.

Students Grades  Dr. Asada Dr. Asada  Dr. Lin Dr. Lin

Grade Distribution Grades 2008 Summer 2007 Summer 2009 Summer A18%529%15% B650%741%420% C542%00%1050% D00%16%15% F00%424%420%

Pretest VS Final Grades

Final Grade VS Lab Average

Grade VS Labs and Tests SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations12 ANOVA dfSSMSF Significance F Regression Residual Total CoefficientsStandard Errort StatP-valueLower 95%Upper 95%Lower 95.0% Intercept Lab Average Test AVG Final Grade = 0.43 test average lab average

Conclusions  Because the data is very small. It does not show statistical significant differences. However, because of labs there are more interactions between students and professors. As the result, the failure rate is lower.  Students are mostly from business school, usually they are more motivated.  Final grades are more affected by lab grades than tests grade.

Reflections  Administrators like interdisciplinary classes. But don’t want to deal with teaching load problem of team teaching.  Different instructors give different standard of grades. It is hard to say lab grades contribute more toward final grades.  This class should exclude business major students.