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Coding for Culture, Diversity, Gender, and Identity: the Potential for Automation in Research

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Conference

2018 ASEE Annual Conference & Exposition

Location

Salt Lake City, Utah

Publication Date

June 23, 2018

Start Date

June 23, 2018

End Date

July 27, 2018

Conference Session

Women in Engineering Division Technical Session 6

Tagged Division

Women in Engineering

Tagged Topic

Diversity

Page Count

14

Permanent URL

https://peer.asee.org/30197

Download Count

53

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Paper Authors

biography

Chloe Wiggins Designing Education Lab

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Chloe Wiggins is a graduate of Stanford University who majored in Civil Engineering with a concentration in structures and construction.

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Sheri Sheppard Stanford University

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Sheri D. Sheppard, Ph.D., P.E., is professor of Mechanical Engineering at Stanford University. Besides teaching both undergraduate and graduate design and education related classes at Stanford University, she conducts research on engineering education and work-practices, and applied finite element analysis. From 1999-2008 she served as a Senior Scholar at the Carnegie Foundation for the Advancement of Teaching, leading the Foundation’s engineering study (as reported in Educating Engineers: Designing for the Future of the Field). In addition, in 2011 Dr. Sheppard was named as co-PI of a national NSF innovation center (Epicenter), and leads an NSF program at Stanford on summer research experiences for high school teachers. Her industry experiences includes engineering positions at Detroit's "Big Three:" Ford Motor Company, General Motors Corporation, and Chrysler Corporation.

At Stanford she has served a chair of the faculty senate, and recently served as Associate Vice Provost for Graduate Education.

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Shannon Katherine Gilmartin SKG Analysis

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Shannon K. Gilmartin, Ph.D., is a Senior Research Scholar at the Michelle R. Clayman Institute for Gender Research and Adjunct Professor in Mechanical Engineering at Stanford University. She is also Managing Director of SKG Analysis, a research consulting firm. Her expertise and interests focus on education and workforce development in engineering and science fields.

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Benedikt von Unold Stanford University

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Benedikt studied Medical Engineering and Mechanical Engineering at the Technical University of Munich (TUM). In 2017, he joined the Designing Education Lab at Stanford University to learn more about the integration of user backgrounds in design. He was involved in various entrepreneurial activities and worked as a student in small, medium and large companies. The creation of innovation was both an essential part in his studies as it was in his jobs.

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Tua A. Björklund Aalto University Design Factory

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Tua Björklund is one of the co-founders and the head of research at Aalto University Design Factory. She conducts and leads research, teaches product design, and facilitates pedagogical development at the Design Factory. Tua has a DSc degree in industrial engineering and management and a MA degree in cognitive science.

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Michael Arruza Cruz

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Abstract

As engineering education research has evolved, its maturity as a research field is reflected in the literature through the issues that are explored and a growing diversity of contributors and points of view. New questions are being raised around: Who becomes an engineer? Why do people become engineers? How do background characteristics like culture or gender (consolidated in this paper with the word ‘peopleness’), and constructs like diversity or identity influence these questions? We define ‘peopleness’ as “awareness and empathy of the range of people who are affected by a product or service as related to their background characteristics.” This paper investigates how peopleness is being explored in engineering education research.

The primary tool of this study is a program created to rank how closely related a paper was to given words (in this particular study, keywords were related to culture, diversity, gender, and identity). The program mathematically represents words as vectors (specifically, the program uses the GLOVE vectors developed by Jeffrey Pennington, Richard Socher, and Christopher D. Manning of Stanford) such that words with similar meanings have vectors that are closer in euclidean distance. The vectors are used in the program to find documents most likely to relate to a specific topic chosen by the researcher by using word vector distances across a document as a measure of the presence of a topic in a document. A paper could be ranked ‘quite relevant’, ‘slightly relevant’, ‘borderline’, or ‘probably not relevant’. This program was run on engineering education articles, design reports, and transcripts of interviews with recently graduated engineering students about innovation in their work. The population for this study includes articles published in three peer-reviewed and highly focused journals on engineering and engineering education journals from 1996 to 2016: International Journal of Engineering Education (IJEE), Journal of Engineering Education (JEE), and Journal of Women and Minorities in Science and Engineering (JWMSE).

To begin this investigation, we considered publications in these journals during the last ten years, that used the words “culture,” “diversity,” “gender,” or “identity” and picked papers we deemed relevant based on frequency and placement of the keywords. Based on this approach, we identified and considered 118 papers in the JEE sample and 104 papers in the IJEE sample. Since JWMSE’s audience is broader, this study focuses only on the articles related specifically to engineering (including engineering courses and introductory science and mathematics courses typically included in required curriculum for engineering students) to make the samples more comparable. This approach yielded 118 papers in the JWMSE sample. Each publication had different proportions of relevant papers for each keyword.

The program was then run on the hand-coded papers. On average, the program found just 48% of the papers hand-coding deemed relevant to be ‘quite relevant’. When the program was broadened to also include ‘slightly relevant’ papers, the agreement with hand-coding increased to on average over 90%. The agreement varied for each keyword. This paper also outlines two further application examples of the program in the field of engineering to illustrate its potential.

This program has much potential for future use. There is room for further exploration of what differentiates papers that are ‘quite relevant’ and ‘slightly relevant.’ There are also questions of how often the program misses a relevant document and how often it mischaracterizes a document as relevant. Its use for identifying different text mediums could also be explored. In terms of peopleness, there is a good amount of work being done by engineering education researchers. Certain dimensions (gender) have been more explored than others, but even within this focus, there is room for different ways of thinking and researching gender’s impact in engineering education. A more automated means, as proposed in this paper, of identifying how writings and publications are including important topics can be a means of tracking research trends over time.

Wiggins, C., & Sheppard, S., & Gilmartin, S. K., & von Unold, B., & Björklund, T. A., & Arruza Cruz, M. (2018, June), Coding for Culture, Diversity, Gender, and Identity: the Potential for Automation in Research Paper presented at 2018 ASEE Annual Conference & Exposition , Salt Lake City, Utah. https://peer.asee.org/30197

ASEE holds the copyright on this document. It may be read by the public free of charge. Authors may archive their work on personal websites or in institutional repositories with the following citation: © 2018 American Society for Engineering Education. Other scholars may excerpt or quote from these materials with the same citation. When excerpting or quoting from Conference Proceedings, authors should, in addition to noting the ASEE copyright, list all the original authors and their institutions and name the host city of the conference. - Last updated April 1, 2015