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Active Learning in Electrical Engineering: Measuring the Difference

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2019 ASEE Annual Conference & Exposition


Tampa, Florida

Publication Date

June 15, 2019

Start Date

June 15, 2019

End Date

October 19, 2019

Conference Session

Active & Cooperative Learning in ECE

Tagged Division

Electrical and Computer

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Paper Authors


C. Richard Compeau Jr Texas State University

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C. Richard Compeau Jr. is the Electrical Engineering Program Coordinator and a Professor of Practice in the Ingram School of Engineering. He is interested in teaching and curriculum development. His research is typically project-specific for the EE Capstone courses, with an emphasis on applied electromagnetics.

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Austin Talley P.E. Texas State University

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Dr. Austin Talley a Founding Research Fellow with LBJ Institute for STEM Education & Research and Senior Lecturer in the Ingram School of Engineering at Texas State University. Prior to joining the faculty at Texas State University, Dr. Austin Talley worked as a manufacturing quality engineer for a test and measurement company, National Instruments, in Austin, TX. Dr. Austin Talley is a licensed by state of Texas as a Professional Engineer. Both of Dr. Austin Talley’s graduate degrees, a doctorate and masters in Mechanical Engineering, manufacturing and design area, are from the University of Texas at Austin. Additionally, Dr. Austin Talley holds an undergraduate degree from Texas A&M University in Mechanical Engineering. His research is in engineering design theory and engineering education. He has published over 25 papers in engineering education journals and conference proceedings. He has worked to implement multiple National Science Foundation (NSF) grants focused on engineering education. He has been an instructor in more than ten week long summer K-12 teach Professional Development Institutes (PDI). He has received multiple teaching awards. He has developed design based curriculum for multiple K-12 teach PDIs and student summer camps.

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Phillip Q. Tran Texas State University

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Engineering Electromagnetics is a challenging junior-level course containing many concepts and formulae, and is a core course in many Electrical Engineering programs. A traditional way to teach this class is via didactic instruction, i.e., lecture mode. The instructor often introduces the concepts and then works examples for the students. While the process of working examples may be helpful to some students, the question arose as to whether or not actively engaging the students would improve their understanding of the material. To address this hypothesis, raw exam scores were examined for a total of six semesters. In the first three semesters, only direct instruction was used, whereas the next three semesters used direct instruction for the first half of the class period, working no examples, and then having students collaboratively solve examples and problems for the second half of the class, while being mentored by the faculty as needed. Students were strongly encouraged to work together in teams and to discuss the material while the instructor circulated to give guided practice. Solutions became visible 20 minutes before the end of the class period via the learning management system so that students could check their level of understanding. These in-class exercises, in the form of written problem sets, were worth one and one-half letter grades. Pre and post student knowledge was measured by comparing raw scores on four exams for each semester: three exams and a final. Each exam covered the same topics, for example, the first exam was concerned with transmission lines, the second exam tested for knowledge of electrostatics and magnetostatics, and so forth. While the exams differed from semester to semester by changing values, boundary conditions, or solving for a particular variable, the exams were substantially similar in content, number of questions, and number of concepts tested. While student grades were determined by scaling the exam scores, the extent of their content mastery was performed by comparing raw scores. Subsequent analysis revealed that there was an improvement both in average raw score and in standard deviation of score. For example, the average raw score in Spring of 2017 (pre active engagement) was 53.5% with a standard deviation of 17% but in Spring of 2018 (post active engagement) the average raw score improved to 60.1% and the standard deviation decreased to 7.9%.

Compeau, C. R., & Talley, A., & Tran, P. Q. (2019, June), Active Learning in Electrical Engineering: Measuring the Difference Paper presented at 2019 ASEE Annual Conference & Exposition , Tampa, Florida. 10.18260/1-2--32030

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