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Board 198: A Mixed-Methods Investigation of Engineers Targeting the Consequences of Variability

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Conference

2023 ASEE Annual Conference & Exposition

Location

Baltimore , Maryland

Publication Date

June 25, 2023

Start Date

June 25, 2023

End Date

June 28, 2023

Conference Session

NSF Grantees Poster Session

Tagged Topic

NSF Grantees Poster Session

Page Count

31

DOI

10.18260/1-2--42595

Permanent URL

https://peer.asee.org/42595

Download Count

77

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Paper Authors

biography

Zachary Riggins del Rosario Olin College Orcid 16x16 orcid.org/0000-0003-4676-1692

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Zachary del Rosario is an Assistant Professor of Engineering and Applied Statistics at Olin College. His goal is to help scientists and engineers reason under uncertainty. Zach uses a toolkit from data science and uncertainty quantification to address a diverse set of problems, including reliable aircraft design and AI-assisted discovery of novel materials.

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Abstract

Variability is an unavoidable reality. Physical phenomena such as loading conditions, material properties, and human behavior all exhibit variability. Engineers must deal with this variability when designing solutions. Unfortunately, an extensive body of human subjects research suggests that people---including engineers---consistently fail to understand variability. This deficit view of working with data is focused on statistical inference; identifying stable patterns in data.

However, engineering concerns are not identical to statistical concerns! Through a human subjects study using grounded theory methods, we have identified a novel cognitive resource that engineers use to analyze variability. Engineers can recognize the consequences of variability, and make data analysis choices that target those consequences. Targeting the consequences of variability is key to safe engineering design, but is not presently taught to engineering students.

In this poster I will describe the process of targeting variability, highlight factors that affect an engineer's proclivity to target (or not), and discuss implications for engineering education.

This work was funded by the NSF EEC under award number #2138463.

del Rosario, Z. R. (2023, June), Board 198: A Mixed-Methods Investigation of Engineers Targeting the Consequences of Variability Paper presented at 2023 ASEE Annual Conference & Exposition, Baltimore , Maryland. 10.18260/1-2--42595

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