Virtual
August 9, 2021
August 9, 2021
August 21, 2021
2
10.18260/1-2--38389
https://peer.asee.org/38389
368
A Senior Engineering Education student at Ohio northern University, Will participates in Robotics, serves as the president of his schools ASEE chapter, and is a member of Tau Beta Pi, IEEE and ACM. His engineering interests lie mainly in the fields of electrical and computer engineering. Upon graduation, he hopes to begin teaching engineering to high school students and to serve as both a role model and advocate for pursuing STEM, and specifically engineering as a field of study and career.
Todd France is the director of Ohio Northern University's Engineering Education program, which strives to prepare engineering educators for grades 7-12. Dr. France also helps coordinate the first-year engineering experience at ONU. He earned his PhD from the University of Colorado Boulder in Architectural Engineering, and conducted research in K-12 engineering education and project-based learning.
Dr. Hylton is an Assistant Professor of Mechanical Engineering and Coordinator of the First-Year Engineering experience for the T.J. Smull College of Engineering at Ohio Northern University. He previously completed his graduate studies in Mechanical Engineering at Purdue University, where he conducted research in both the School of Mechanical Engineering and the School of Engineering Education. Prior to Purdue, he completed his undergraduate work at the University of Tulsa, also in Mechanical Engineering. He currently teaches first-year engineering courses as well as various courses in Mechanical Engineering, primarily in the mechanics area. His pedagogical research areas include standards-based assessment and curriculum design, including the incorporation of entrepreneurial thinking into the engineering curriculum and especially as pertains to First-Year Engineering.
Modeling with mathematics is an integral part of engineering, and therefore early exposure is ideal for engineering students. Hands on math modeling allows students to see why it is valuable. Additionally, immediate implementation of the model allows students to get instant feedback and success. To meet this demand, an activity was designed for students to build, model, program and test an LED display. These displays consisted of PCBs which contained 7 different colored LEDs and a resistor in series with each. Students were taught how to solder and constructed their circuits. Then students learned basic aspect of the Arduino programming language and made their light strip respond to simple situations such as button presses using if-else statements or timed intervals using loops. In order to be able to display dynamic data, students learned how to use an Arduino with an analog sensor, in this case a potentiometer, by having if-else statements create threshold values at which certain lights would turn on. Students are then tasked with writing a function to take in analog values and map them using an equation onto the LEDs. This task has students creating a system to monitor light levels. Students collect data using both a photometer and a photoresistor. Using the collected data, they are scaffolded through modeling by having them map specific values onto the data they have collected. They used linear regression and function transformation to accomplish this. Using this modeling skill, they also learn how to use Arduino libraries to interact with sensors that need them, such as ultrasonic sensors and create intelligent displays using these. Additionally, they experiment with other analog sensors, such as a hall effect and thermistor. This activity is designed to give students a practical introduction to the uses of math modeling in intelligent design practices and gives them the tools to implement sensor-based decision making into semester projects.
Sierzputowski, W., & France, T., & Hylton, J. B. (2021, August), Hands on Math Modeling through Building and Programing Intelligent, Adaptable Display Systems with LEDs and Arduinos Paper presented at 2021 First-Year Engineering Experience, Virtual . 10.18260/1-2--38389
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