Brian Faulkner, Ph.D.

Assistant Professor

  • Milwaukee WI UNITED STATES
  • Allen Bradley Hall of Science S347
  • Electrical Engineering and Computer Science

Dr. Brian Faulkner is an assistant professor of electrical engineering.

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Education, Licensure and Certification

Ph.D.

Electrical and Computer Engineering

University of Illinois Urbana-Champaign

2018

M.S.

Electrical and Computer Engineering

University of Illinois Urbana-Champaign

2015

B.S.

Physics and Mathematics

University of Idaho

2010

Biography

Dr. Brian Faulkner is an assistant professor in MSOE's Electrical Engineering and Computer Science Department. He joined the MSOE faculty in 2019 and teaches courses in digital signal processing, linear circuits, signals and systems, and electrical engineering.

Affiliations

  • American Society for Engineering Education: Mathematics Division: Secretary/Treasurer

Selected Publications

When am I ever going to use this? An Investigation of the Calculus Content of Core Engineering Courses

Journal of Engineering Education

Faulkner, B., Johnson-Glauch, N., Choi, D.S., Herman, G. L.

2020

Many engineering students fail to proceed through required prerequisite mathematics courses. Since these courses strongly influence engineering student attrition, we should examine to what degree these courses truly serve as prerequisites for following engineering coursework. We examined two research questions: Which concepts and skills learned in calculus are applied in engineering statics and circuits homework assignments? How are calculus skills applied in engineering statics and circuits homework assignments?

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Mathematical Maturity for Engineering Students

International Journal of Research in Undergraduate Mathematics Education

Faulkner, B., Earl, K. and Herman, G.

2019

Facing increased pressure to improve retention and graduation rates, engineering departments are increasingly scrutinizing whether they are getting their desired outcomes from core mathematics coursework. Since mathematics courses are a significant source of attrition and many engineering faculty are unhappy with students’ mathematical abilities, more engineering departments are increasingly looking at drastic options of taking students out of mathematics courses and teaching students mathematics themselves. To mitigate this trend, it may be valuable to better understand what engineering faculty hope students learn from their mathematics coursework. When engineering faculty explain why they require these high-failure prerequisites, many claim that “mathematical maturity”, not calculus skill, is the desired outcome of completing the core math sequence of courses. To better understand what engineering faculty mean by “mathematical maturity”, we conducted a qualitative thematic analysis of how 27 engineering faculty members define “mathematical maturity”. We found that these engineering faculty believed that the mathematically mature student would have strong mathematical modeling skills supported by the ability to extract meaning from symbols and the ability to use computational tools as needed. Faculty frequently lamented that students had underdeveloped epistemic beliefs that undermined their modeling skills, thinking that mathematics is unrelated to the real world and has little practical value. They attributed these dysfunctional epistemic beliefs to their perception that mathematics is too often taught without genuine physical context and realistic examples. We suggest potential avenues for reform that will allow mathematics departments to better serve their client departments in engineering and thus retain control of their courses.

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Understanding Bernoulli's Principle Through Simulations

American Journal of Physics

Faulkner, B.E. and Ytreberg, F.M.

2011

Computer simulations are used to develop a deeper understanding of Bernoulli’s principle. Hard disks undergoing elastic collisions are injected into a Venturi nozzle and the pressure in the narrow throat of the nozzle is compared to the pressure in the wider section of the pipe. This model system is an ideal student project because the theory and programming are straightforward, and the computational cost is low.

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