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Tensions and Trade-offs in Instructional Goals for Physics Courses Aimed at Engineers

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Conference

2015 ASEE Annual Conference & Exposition

Location

Seattle, Washington

Publication Date

June 14, 2015

Start Date

June 14, 2015

End Date

June 17, 2015

ISBN

978-0-692-50180-1

ISSN

2153-5965

Conference Session

Engineering Physics & Physics Division Technical Session 3

Tagged Division

Engineering Physics & Physics

Tagged Topic

Diversity

Page Count

24

Page Numbers

26.1499.1 - 26.1499.24

DOI

10.18260/p.24836

Permanent URL

https://peer.asee.org/24836

Download Count

47

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Paper Authors

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Andrew Elby University of Maryland, College Park

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My work focuses on student and teacher epistemologies and how they couple to other cognitive machinery and help to drive behavior in learning environments. My academic training was in Physics and Philosophy before I turned to science (particularly physics) education research. More recently, I have started exploring engineering students' entangled identities and epistemologies.

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Eric Kuo Stanford University

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Ayush Gupta University of Maryland, College Park

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Ayush Gupta is Research Assistant Professor in Physics and Keystone Instructor in the A. J. Clark School of Engineering at the University of Maryland. Broadly speaking he is interested in modeling learning and reasoning processes. In particular, he is attracted to fine-grained analysis of video data both from a micro-genetic learning analysis methodology (drawing on knowledge in pieces) as well as interaction analysis methodology. He has been working on how learners' emotions are coupled with their conceptual and epistemological reasoning. He is also interested in developing models of the dynamics of categorizations (ontological) underlying students' reasoning in physics. Lately, he has been interested in engineering design thinking, how engineering students come to understand and practice design.

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Michael M. Hull Wayne State College

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Assistant Professor of Physical Sciences

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Abstract

Tensions and trade-offs in instructional goals for physics courses aimed at engineersWhat instructional objectives in physics courses most help engineering students succeed in theirsubsequent engineering courses and careers? Faculty often talk vaguely of “problem solvingskills” and “conceptual understanding”; but decades of physics and engineering educationresearch have barely addressed this question empirically (McDermott & Redish, 1999; Meltzer& Thornton, 2012; Prince, 2004).As part of a study that does address this issue, we did an experiment involving the first-semesterphysics course taken by almost all engineering majors at Big State University. One section,taught by a novice instructor, emphasized mathematical sense-making—translating and seekingcoherence between mathematical formalism and physical reasoning (often intuitive), usingmathematics flexibly as part of sense-making about the physical world. Another section, taughtby an experienced, well-regarded professor, emphasized “traditional” quantitative problemsolving of the type emphasized by popular physics textbooks.Some engineering educators argue that traditional problem-solving is important to emphasizebecause it develops important skills that students can build on, skills they apply in laterengineering classes. Others argue that mathematical sense-making is closer to what practicingengineers actually do (Gainsburg, 2006). This paper will not present evidence bearing on thisdebate, in order to focus on a crucial related issue: the trade-off between emphasizingmathematical sense-making and emphasizing traditional problem-solving. Our evidence showsthat they do not automatically reinforce each other. Both sections of the physics course took thesame final exam, and we coded both sets. Students of the novice professor who emphasizedmathematical sense-making exhibited much higher performance on items demanding non-routinemathematical sense-making; but the students expertly instructed in standard quantitative problemsolving performed slightly but statistically-significantly better on traditional quantitativeproblems. We use these results to argue that, at least initially, physics courses can’t “have it all”;tough choices must be made between different instructional goals.ReferencesGainsburg, J. (2006). The mathematical modeling of structural engineers. MathematicalThinking and Learning, 8(1), 3-36.McDermott, L. C., & Redish, E. F. (1999). Resource letter: PER-1: Physics education research.American journal of physics, 67(9), 755-767.Meltzer, D. E., & Thornton, R. K. (2012). Resource letter ALIP–1: active-learning instruction inphysics. American journal of physics, 80(6), 478-496.Prince, M. (2004). Does active learning work? A review of the research. Journal of engineeringeducation, 93(3), 223-231.

Elby, A., & Kuo, E., & Gupta, A., & Hull, M. M. (2015, June), Tensions and Trade-offs in Instructional Goals for Physics Courses Aimed at Engineers Paper presented at 2015 ASEE Annual Conference & Exposition, Seattle, Washington. 10.18260/p.24836

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