Aggarwal, R., & Flynn, M., & Daitzman, S., & Lam, D., & del Rosario, Z. R. (2021, November), A Qualitative Study of Engineering Students' Reasoning About Statistical Variability  Paper presented at 2021 Fall ASEE Middle Atlantic Section Meeting, Virtually Hosted by the section. 10.18260/1-2--38421

\bibitem{asee_peer_38421}
  Aggarwal, R., \& Flynn, M., \& Daitzman, S., \& Lam, D., \& del Rosario, Z. R. (2021, November), \emph{A Qualitative Study of Engineering Students' Reasoning About Statistical Variability}
  Paper presented at 2021 Fall ASEE Middle Atlantic Section Meeting, Virtually Hosted by the section.
  10.18260/1-2--38421

Riya Aggarwal, Mira Flynn, Sam Daitzman, Diane Lam, and Zachary Riggins del Rosario.  "A Qualitative Study of Engineering Students' Reasoning About Statistical Variability".  2021 Fall ASEE Middle Atlantic Section Meeting, Virtually Hosted by the section, 2021, November.  ASEE Conferences, 2021.  https://peer.asee.org/38421 Internet.  21 Jan, 2025

\bibitem{asee_peer_38421}
  Riya Aggarwal, Mira Flynn, Sam Daitzman, Diane Lam, and Zachary Riggins del Rosario.
  "A Qualitative Study of Engineering Students' Reasoning About Statistical Variability".
  \emph{2021 Fall ASEE Middle Atlantic Section Meeting, Virtually Hosted by the section, 2021, November}.
  ASEE Conferences, 2021.
  https://peer.asee.org/38421 Internet.  21 Jan, 2025

@INPROCEEDINGS{asee_peer_38421
author = "Riya Aggarwal, Mira Flynn, Sam Daitzman, Diane Lam, and Zachary Riggins del Rosario"
title = "A Qualitative Study of Engineering Students' Reasoning About Statistical Variability"
booktitle = "2021 Fall ASEE Middle Atlantic Section Meeting"
year = "2021"
month = "November"
address = "Virtually Hosted by the section"
publisher = "ASEE Conferences"
note = {https://peer.asee.org/38421}
number = {10.18260/1-2--38421}
}

TY  - CPAPER
AB  - Every aircraft you have ever flown on has been designed using probabilistically-flawed, potentially dangerous criteria (del Rosario et al. 2021, AIAA-J). That these criteria have been in use for over a half-century---but were only recently identified as dangerous---speaks to the difficulty of teaching such concepts to engineering students. Clearly, improvements to teaching probability and statistics to engineers are needed. Key to statistical thinking is an understanding of and facility with variability (Wild and Pfannkuch, 1999).

This work lays foundations for improved statistical literacy among engineers, enabling a multi-disciplinary approach to engineering statistics. We present a novel theoretical framework for both teaching statistical variability and studying engineers' reasoning under variability. While past frameworks for variability focus on a statistician's perspective (e.g. Peters 2011), our framework centralizes the engineering perspective by explicitly considering physical modeling, and makes use of established insights in manufacturing variability (Shewhart 1931).

Using this framework, we have developed an interview protocol and deductive coding scheme, and deployed these qualitative tools in interviews with engineering students. Results from these interviews support the validity of the coding scheme, agree with documented trends in current aerospace practice, and suggest possible teaching interventions for innovative engineering pedagogy. Implications for future multi-disciplinary teaching of engineering statistics will be discussed.

del Rosario, Fenrich, and Iaccarino, "When are Allowables Conservative?" (2021)
AIAA Journal

Wild and Pfannkuch, "Statistical Thinking in Empirical Enquiry" (1999)
International Statistical Review

Peters "Robust Understanding of Statistical Variation" (2011) Statistics
Education Research Journal

Shewhart, Economic control of quality of manufactured product (1931) Macmillan
And Co. Ltd, London

AU  - Riya Aggarwal
AU  - Mira Flynn
AU  - Sam Daitzman
AU  - Diane Lam
AU  - Zachary Riggins del Rosario
CY  - Virtually Hosted by the section
DA  - 2021/11/12
PB  - ASEE Conferences
TI  - A Qualitative Study of Engineering Students' Reasoning About Statistical Variability
UR  - https://peer.asee.org/38421
DO  - 10.18260/1-2--38421
ER  -