Courses & Teaching

Teaching Philosophy

The current engineering educational ecosystem is built on the philosophy of survival of the fittest.  We use practices such as rigorous admissions standards, the calculus sequence as a filter,  strict prerequisite structure in the degree requirement,  little or no freedom of choice in the curriculum, and many other age-old practices which effectively keeps many talented students out of the profession.   Then we lament that the number of women and under-represented minoroties in engineering is not improving.    I reject these exclusionary practices.   I believe that the engineering degree program should be a enjoyable, growth-minded, and a friendly ecosystem.   Cooperation rather than competition should be the guiding principle.   The system needs to be flexible enough so that  motivated individuals should be able to easily navigate and finish the program at the pace that is most suitable for them.   Colleges should be "student ready" and meet the students where they are rather than expect students to be "college ready".   The profession cannot afford to exclude anyone who is motivated to want to get in.  We should learn how to "weave-in" students rather than perpetuate the current practice of "weeding-out."

In my courses, in order to achieve these changes, I have implemented practices such as mastery-based grading, reducing the importance of high-stakes exams and laying more emphasis on projects and other alternative ways to demonstrate mastery.    My goal is to work towards changing the students' mind-set from a state where they think of the course as an obstacle race full of trickery to a state where they can focus on learning and earning grades solely based on  what they learn.  The type of courses I typically teach are engineering science courses with significant applications of mathematical concepts as well as applications of mathematical modeling tools.  One particular aspect that I try to emphasize is how mathematical representations link to the concrete.  In all my courses I strive to help students make this connection of the relative abstract world of mathematics with the concrete physical world, so that the students can make similar connections themselves and understand that mathematics is a powerful tool for problem solving in the hands of engineers.  

A change in the engineering education ecosystem cannot just happen by individuals making changes in their own course.  A system wide change is necessary as well.   For the last several years my colleagues and I have researched and written about the need for this large-scale change of the system (references can be found in the Educational research section of this site).   Currently, I am part of a nationwide group of faculty members that are participating in a NSF-ASEE-NAE project to develop a roadmap for this change that we are seeking.   This work has been a very rewarding experinece.  

Currently, these are the courses I teach at University of Detroit Mercy during each academic year:

ENGR1234: Introductory Mathematics for Engineering Applications (FALL)

ENGR3260: Mechanics of Materials (FALL)

ENGR3120: Statics (WINTER)

ENGR 4420/5420: Finite Element Method (FALL)

ENGR 4790/5790: Mechatronics Modeling and Simulation (WINTER)

ENGR 4070/5070: Introduction to Electric Vehicle Modeling (WINTER)

ENGR1234: Introductory Mathematics for Engineering Applications (FALL)

This is a unique course designed after the "Wright State Model" of Introductory Mathematics for Engineers course.  It covers topics that range from Linear Equations to Differential Equations but all taught in the context of engineering problems.   The math topics covered in this class are only those needed in early engineering classes and nothing more.   As an engineering faculty teaching this class I am able to emphasize a few essential aspects of math that engineers need to understand: (a) the importance of viewing math as a powerful tool for solving engineering problems, (b) the importance of understanding  the difference between a correct answer and an useful answer, (c) the engineering context that makes a math problem/concept useful, (d) true meaning and importance of significant figures, (e) trade-off between a good and useful result vs. an accurate result, etc.   Students finish this class with a genuine understanding and appreciation for the need for math in engineering.    Also, a C or better grade in this class lets students take Physics I, Statics and other follow-up classes while they can finish the Calculus sequence at a comfortable pace. 

ENGR3260: Mechanics of Materials (FALL)

This is a typical Mechanics of Materials class that covers the concepts of stresses and strains that arise from axial, torsional, bending and combined loading.   Other topics that are dealt with in detail are stress transformation and buckling.   The unique feature of this class is that I use mastery based grading.  This means that students need to show mastery on twenty topics to earn the grade in the class.  The mastery is determined by students solving problems on the topics in exam-type settings where no partial grade is given.  They get 100% or 0% on the problem but they have unlimited number of opportunities during a semester to demonstrate their mastery.   This grading method has been very well received by the students as they can focus on doing the problems correctly without the pressure or stress associated with the thought  of doing poorly in tests.  

ENGR3120: Statics (WINTER)

This is a typical Statics class that covers the concepts of equilibrium of loads acting at a point and on rigid bodies, trusses, frames, beams, etc.  The unique feature of this class is that I use mastery based grading.  This means that students need to show mastery on the syllabus topics to earn the grade in the class.  The mastery is determined by students solving problems on the topics in exam-type settings where no partial grade is given.  They get 100% or 0% on the problem but they have unlimited number of opportunities to do that.   This grading method has been very well received by the students as they can focus on doing the problems right without the pressure or stress associated with the thought  of doing poorly in tests. 

ENGR 4420/5420: Finite Element Method (FALL)

The Finite Element Method has become a powerful and ubiquitous tool in the hands of today’s engineers.   We often come across the term CAE (Computer Aided Engineering), a methodology used extensively in product development, design and analysis engineering, and in numerous other engineering applications.   FEA or Finite Element Analysis is a core component of CAE.  Many reliable FEA software tools are presently available for engineers to use in solving all classes of engineering problems.   User-friendly graphical user interfaces have made these tools very easy to use, so much so that engineers can set-up, analyze and use the results without a clear understanding of the process.   This can lead to inability to obtain correct results and may lead to flawed decision making.   In the past FEA courses were designed to teach all the mathematics behind the method, the fundamental understanding of all aspects of the process with detailed mathematical models.   Those courses were designed to train students to become developers of FEA codes.   Today, a typical engineer or user is often caught between the world of commercial tools that are easy to use and dense coursework that are hard to understand.   This course is an attempt to help the user who is interested in learning the method through hands-on means.  There is enough discussion of some of the very basic theory so that the user can get a broad understanding of the process.  Also, there are many opportunities with step-by-step instructions for the user to quickly develop some proficiency in using FEA.  We use Matlab and its PDE toolbox as well as ABAQUS, a commercial FEA tool.  The syntax and the modeling process in both cases are easy to understand and a new user can become productive very quickly.   

ENGR 4790/5790: Mechatronics Modeling and Simulation (WINTER)

Engineering systems of today are complex and multidisciplinary.  Synergistic combination of mechanical components with electronics and control software have made engineering systems a lot more efficient than they were before.  New innovations in all fields of engineering, but especially in artificial intelligence and machine learning will make engineering systems even better in future years.  Traditional engineering courses place a lot of emphasis on component design and analysis, and comparatively less on system design.   It is necessary to change that.  Engineers should be much more comfortable in systems thinking and be adept at system design.   System modeling is a powerful tool to develop user expertise in system analysis, system identification, and system synthesis, three aspects of system design.  In this course attempt is made to introduce students to mechatronic system modeling and simulation as a tool to do multi-disciplinary system design.  We have used 20-SIM and Simscape, two software tools which take slightly different approaches to model mechatronic systems.   Simscape uses the physical network approach which is very intuitive and 20Sim uses bond graphs which is a method that uses generalized variables to bridge the traditional divisions between different disciplines.  In both cases the models track the flow of power through the system.  A special feature of this course is an end-of-term project where student teams choose their own systems and model and simulate their behavior using the two tools and present their work in poster sessions in the college.