Asfaw, A. F., & Randolph, S., & Siaumau, V., & Aguilar, Y. R., & Flores, E., & Lehr, J. L., & Danowitz, A. (2021, July), Statistical Analysis of the CAR (Confront, Address, Replace) Strategy and Its Efficacy when Applied to Master-slave Terminology  Paper presented at 2021 ASEE Virtual Annual Conference Content Access, Virtual Conference. 10.18260/1-2--37724

\bibitem{asee_peer_37724}
  Asfaw, A. F., \& Randolph, S., \& Siaumau, V., \& Aguilar, Y. R., \& Flores, E., \& Lehr, J. L., \& Danowitz, A. (2021, July), \emph{Statistical Analysis of the CAR (Confront, Address, Replace) Strategy and Its Efficacy when Applied to Master-slave Terminology}
  Paper presented at 2021 ASEE Virtual Annual Conference Content Access, Virtual Conference.
  10.18260/1-2--37724

Amman Fasil Asfaw, Storm Randolph, Victoria Siaumau, Yumi Rosa Aguilar, Emily Flores, Jane L. Lehr, and Andrew Danowitz.  "Statistical Analysis of the CAR (Confront, Address, Replace) Strategy and Its Efficacy when Applied to Master-slave Terminology".  2021 ASEE Virtual Annual Conference Content Access, Virtual Conference, 2021, July.  ASEE Conferences, 2021.  https://peer.asee.org/37724 Internet.  12 May, 2025

\bibitem{asee_peer_37724}
  Amman Fasil Asfaw, Storm Randolph, Victoria Siaumau, Yumi Rosa Aguilar, Emily Flores, Jane L. Lehr, and Andrew Danowitz.
  "Statistical Analysis of the CAR (Confront, Address, Replace) Strategy and Its Efficacy when Applied to Master-slave Terminology".
  \emph{2021 ASEE Virtual Annual Conference Content Access, Virtual Conference, 2021, July}.
  ASEE Conferences, 2021.
  https://peer.asee.org/37724 Internet.  12 May, 2025

@INPROCEEDINGS{asee_peer_37724
author = "Amman Fasil Asfaw, Storm Randolph, Victoria Siaumau, Yumi Rosa Aguilar, Emily Flores, Jane L. Lehr, and Andrew Danowitz"
title = "Statistical Analysis of the CAR (Confront, Address, Replace) Strategy and Its Efficacy when Applied to Master-slave Terminology"
booktitle = "2021 ASEE Virtual Annual Conference Content Access"
year = "2021"
month = "July"
address = "Virtual Conference"
publisher = "ASEE Conferences"
note = {https://peer.asee.org/37724}
number = {10.18260/1-2--37724}
}

TY  - CPAPER
AB  - “Master-slave” terminology is still commonplace in engineering education and industry, however, questions have been raised about negative impacts of such language. Usage of iniquitous terminology such as“master-slave” in academia can make students—especially those who identify as women and/or Black/African-American—feel uncomfortable, potentially evoking Stereotype Threat and/or Curriculum Trauma [1], [2]. Indeed, prior research shows that students from a number of backgrounds find non-inclusive terminologies such as “master-slave” to be a major problem [1]. Currently, women-identifying and gender nonbinary students are underrepresented in the engineering industry while Black/African-American students are underrepresented in the entire higher education system, including engineering fields [3], [4].

The CAR Strategy, introduced here, stands for: 1) confront; 2) address; 3) replace and aims to provide a framework for driving out exclusionary terminologies in engineering education such as “master-slave.” The first step is to confront the historical significance of “master-slave” terminology. The second step is to address the technical inaccuracies of “master-slave”. Lastly, replace “master-slave” with an optional but recommended replacement terminology.

This study reports specifically on student perceptions and the effectiveness of The CAR Strategy piloted as a teaching framework in the computer engineering department of a Predominantly White Institution (PWI) in California. Of 64 students surveyed: 70% either agree or strongly agree that The CAR Strategy is an effective framework for driving out iniquitous terminologies such as “master-slave” in engineering education; and 67% either agree or strongly agree they would like to see all professors use The CAR Strategy when applicable in their classes. 

Combining the statistical analysis with qualitative data points, we find The CAR Strategy to be an overall effective framework for driving out non-inclusive terminologies in engineering education. Further research is warranted on The CAR Strategy’s efficacy on other potentially problematic terminologies in engineering education such as “female-male” (connectors), “blacklist-whitelist” (element selection), and “blackhat-whitehat” (hackers).
AU  - Amman Fasil Asfaw
AU  - Storm Randolph
AU  - Victoria Siaumau
AU  - Yumi Rosa Aguilar
AU  - Emily Flores
AU  - Jane L. Lehr
AU  - Andrew Danowitz
CY  - Virtual Conference
DA  - 2021/07/26
PB  - ASEE Conferences
TI  - Statistical Analysis of the CAR (Confront, Address, Replace) Strategy and Its Efficacy when Applied to Master-slave Terminology
UR  - https://peer.asee.org/37724
DO  - 10.18260/1-2--37724
ER  -