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The effect of deductive and inductive teaching methods in an introductory programming course

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2019 ASEE PNW Section Conference


Corvallis, Oregon

Publication Date

March 20, 2019

Start Date

March 20, 2019

End Date

March 22, 2019

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Jen Symons University of Portland

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Jen Symons is an Assistant Professor in Biomedical and Mechanical Engineering in the Shiley School of Engineering at the University of Portland. She is most passionate about teaching biomechanics and statistics for engineers. Her research focuses on understanding the causes of musculoskeletal injury and developing noninvasive mechanisms that prevent injuries and/or enhance performance in equine athletes.

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Heather Dillon University of Portland Orcid 16x16

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Dr. Heather Dillon is an Associate Professor in Mechanical Engineering at the University of Portland. Her teaching focuses on thermodynamics, heat transfer, renewable energy, and optimization of energy systems. She currently leads a research team working on energy efficiency, renewable energy, and fundamental heat transfer. Before joining the university, Heather Dillon worked for the Pacific Northwest National Laboratory (PNNL) as a senior research engineer.

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Joseph P Hoffbeck University of Portland

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Joseph P. Hoffbeck is a Professor of Electrical Engineering at the University of Portland in Portland, Oregon. He has a Ph.D. from Purdue University, West Lafayette, Indiana. He previously worked with digital cell phone systems at Lucent Technologies (formerly AT&T Bell Labs) in Whippany, New Jersey. His technical interests include communication systems, digital signal processing, and remote sensing.

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Many first and second year engineering students are required to complete an introductory programming course as part of their program. Typically, class time within these courses is divided into traditional instructor lecture and student work time interacting with the software. This study aimed to determine the effect of different instructor teaching methods on student quiz performance as it related to challenging concepts (i.e. functions, loops, and conditional statements). A Latin square design was used to assess 3 different teaching methods across 3 course sections of students, all taught by the same instructor. Teaching methods included: a single deductive lecture explaining the concept (control), a similar deductive approach that divided content into two smaller lectures within one session, and an inductive approach that presented code within an applied context. After the teaching methods were delivered, points from quizzes completed by students were divided into categories based on the three course concepts. The effect of teaching method on percentage of points earned by students for each concept was assessed by ANOVA. Teaching method showed a trend, but failed to achieve statistical significance (p=0.11). However, post-hoc tests indicated a significant difference between the control teaching method and the inductive teaching method (p=0.04). The control teaching method yielded the best student quiz scores, whereas the inductive teaching method yielded the worst scores. These results support a deductive approach when teaching first and second year students introductory programming skills, as opposed to an inductive approach that may be more well suited outside foundational engineering courses.

Symons, J., & Dillon, H., & Hoffbeck, J. P. (2019, March), The effect of deductive and inductive teaching methods in an introductory programming course Paper presented at 2019 ASEE PNW Section Conference, Corvallis, Oregon. 10.18260/1-2--31897

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