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New Epistemological Perspectives on Quantitative Methods: An Example Using Topological Data Analysis

Authors: Allison Godwin, Brianna Benedict, Jacqueline Rohde, Aaron Thielmeyer, Heather Perkins, Justin Major, Herman Clements & Zhihui Chen

Background: Education researchers use quantitative methodologies to examine generalizable correlational trends or causal mechanisms in phenomena or behaviors. These methodologies stem from (post)positivist epistemologies and often rely on statistical methods that use the means of groups or categories to determine significant results. The results can often essentialize findings to all members of a group as truth knowable within some quantifiable error. Additionally, the attitudes and beliefs of the majority (i.e., in engineering, White cis men) often dominate conclusions drawn and underemphasizes responses from minoritized individuals. In recent years, engineering education research has pursued more epistemologically and methodologically diverse perspectives. However, quantitative methodologies remain relatively fixed in their fundamental epistemological framings, goals, and practices.

Purpose: In this theory paper, we discuss the epistemic groundings of traditional quantitative methods and describe an opportunity for new quantitative methods that expand the possible ways of framing and conducting quantitative research—person-centered analyses. This article invites readers to re-examine quantitative research methods.

Scope: This article discusses the challenges and opportunities of novel quantitative methods in engineering education, particularly in the limited epistemic framings associated with traditional statistical methods. The affordances of person-centered analyses within different epistemological paradigms and research methods are considered. Then, we provide an example of a person-centered method, topological data analysis (TDA), to illustrate the unique insights that can be gained from person-centered analyses. TDA is a statistical method that maps the underlying structure of highly dimensional data.

Discussion/Conclusions: This article advances the discussion of quantitative methodologies and methods in engineering education research to offer new epistemological approaches. Considering the foundational epistemic framings of quantitative research can expand the kinds of questions that can be asked and answered. These new approaches offer ways to conduct more interpretive and inclusive quantitative research.

Read online for free at Studies in Engineering Education: New Epistemological Perspectives on Quantitative Methods: An Example Using Topological Data Analysis

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(VIDEO) Equipping Educators with Tools to Promote Latently Diverse Students

Presenters: Allison Godwin, Brianna Benedict, Jacqueline Rohde, H. Ronald Clements, Joana Marques Melo, & Heather Perkins

Summary: The history of look-a-like and think-a-like engineers means those who look or think like a “stereotypical engineer” may feel more welcome in engineering and may be why engineering has attracted and graduated similar students. This workshop considers the unique ways of being, thinking, and knowing—what we call latent diversity—that can be highlighted and valued. We will explore these through students’ narratives and engage educators in reflecting on ways to promote inclusion.

View online at YouTube: Equipping Educators with Tools to Promote Latently Diverse Students

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Using Topological Data Analysis in Social Science Research: Unpacking Decisions and Opportunities for a New Method

Authors: Allison Godwin, Aaron Robert Hamilton Thielmeyer, Jacqueline Rohde, Dina Verdín, Brianna Shani Benedict, Rachel Ann Baker & Jacqueline Doyle

Abstract: This research paper describes a new statistical method for engineering education, Topological Data Analysis (TDA), and considers the important decisions made during analysis and their impact on the quality of the results. We also describe why this new method may provide novel ways of understanding multidimensional data for student attitudes, beliefs, and mindsets.

TDA is a statistical method that can map structure within highly dimensional, noisy, and incomplete data. It is also insensitive to the particular distance function chosen to detect the persistent structure or typology in the data. In some ways, TDA is like a robust cluster analysis. However, unlike cluster analysis, which attempts to break datasets into distinct (or probabilistic) groups, TDA allows for data with progressions rather than clear distinctions. Rather than being focused on breaking data into defined groups, TDA maps the connections among data and provides additional details within the data structure that cannot be captured using cluster analysis. Since its development in 2009, TDA has been used in a number of different fields including medicine, business, and sports. However, few studies have used this technique with social science data. We believe that this technique can be particularly useful to engineering education researchers who deal with complex data that is often multidimensional, noisy, and incomplete.

In this paper, we discuss the considerations that researchers must understand in conducting TDA with engineering education data. In analysis, a researcher must choose a filtering method, number of nearest neighbors (k), number of filter slices (n), overlap in data, and cut height (ε) for each dimension. The importance and effect on the consistency and quality of the data differs for each decision. Some have a large impact on the results of the analysis [e.g., cut height (ε)], while others have a moderate impact on the resulting map appearance but not key structural features identified [e.g., number of filter slices (n)].

We illustrate these methodological decisions as well as the results of TDA and its usefulness for engineering education using data from a project investigating first-year engineering students’ underling attitudes, beliefs, and mindsets to characterize the latent diversity of these students. A paper-and-pencil survey was administered to 3,855 students at 32 ABET accredited institutions across the U.S. in fall 2017. After cleaning the data using attention checks within the survey, a total of 3,711 student responses were examined for validity evidence. Exploratory factor analysis (for newly developed scales) and confirmatory factor analysis (for existing scales) was conducted. The resulting factors with strong validity evidence and high variability among engineering students were used in the TDA to map students’ latent diversity. The results of this map indicate six distinct data progressions as well as a sparse group of students whose responses were not similar to the majority of the dataset. This work illustrates the opportunities for using TDA and provides a discussion of the different researcher decisions that are involved in this statistical technique.

Read online for free at ASEE PEER: Using Topological Data Analysis in Social Science Research: Unpacking Decisions and Opportunities for a New Method

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Uncovering Latent Diversity: Steps Towards Understanding ‘What Counts’ and ‘Who Belongs’ in Engineering Culture

Authors: Brianna Shani Benedict, Dina Verdín, Rachel Ann Baker, Allison Godwin & Thaddeus Milton

Abstract: Curricular expectations for engineering students are steadily expanding to encompass a diverse set of competencies and skills that ensure students are prepared to address the global challenges of engineering. This expansion highlights a need for educators to not only rethink how they educate the next generation of engineers, but also a need to cultivate “diversity of thought” within the culture of engineering. Earlier studies about diversity have focused on understanding how to increase the number of underrepresented students (i.e., women, students of color, and first-generation college students) who persist in STEM fields. However, there is a shift in how we (i.e., society, industry, and academia) define what it means to be diverse. In this paper, we examined how 12 diverse first-year engineering students described how their peers enact different ways of thinking and being in engineering, as well as how those differences influence whether their peers are perceived as someone who belongs in engineering. The participants acknowledged the cultural and gender differences among their peers; however, they primarily described how their peers were different based on their skill-set (i.e., technical, creative, and interpersonal), ways of thinking, and interests. These findings begin to help us understand how students define normative attitudes in engineering and the perception of what it means to be an engineer.

Read online for free at ASEE PEER: Uncovering Latent Diversity: Steps Towards Understanding ‘What Counts’ and ‘Who Belongs’ in Engineering Culture

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Unpacking Latent Diversity

Authors: Allison Godwin

Abstract: This theory paper explores how diversity apart from social identities like race and gender is framed in the engineering education literature and how these concepts promote a different but compatible approach to understanding diversity—latent diversity. Latent diversity is a new approach to diversity work that captures underlying affective and cognitive differences that provide potential sources for innovation but are not visible. This approach does not examine other non-visible social identities like sexual orientation, first-generation status, socioeconomic status, etc. Prior literature suggests that diversity in approaches, problem solving, and ways of thinking improve innovation in engineering design more reliably than does diversity along the lines of age, race, gender, etc. However, the process of enculturating students into engineering through engineering curriculum often creates homogeneity in students’ approaches to problems, ways of thinking, and attitudes. In this paper, I explore a limited set of existing research on diversity from these underlying perspectives including identities, alternative ways of thinking and being, motivation, cognitive diversity, and innovation and creativity. This work synthesizes the findings of these studies to paint a rich picture of how students develop different attitudes and skills to navigate their paths within engineering. Additionally, this work provides an evidence-based argument for the importance of recognizing and understanding latent diversity to promote a more inclusive environment in engineering and recruit, educate, retain, and graduate more innovative and diverse engineers. This paper opens the conversation about a new, but complementary, focus for developing a STEM workforce rich in talent and capable of adapting to the changing STEM landscape.

Read online for free at ASEE PEER: Unpacking Latent Diversity

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(VIDEO) Latent Diversity in Engineering: an Introduction

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CAREER: Characterizing Latent Diversity Among a National Sample of First-Year Engineering Students

Allison Godwin
Brianna Shani Benedict
Dina Verdín
Aaron Robert Hamilton Thielmeyer
Rachel Ann Baker
Jacqueline Ann Rohde

Excerpt: Students often have limited perceptions of what it means to be or think like an engineer. Often this perception stems from social norms and the culture of engineering that emphasizes particular values and roles that engineering includes. The result of this culture is that only particular types of students are recognized as an engineer, and the process of educating engineers homogenizes rather than diversifies students’ skills and potential for innovation. This process of homogenization develops engineering graduates that are more alike in their problem-solving approaches, ways of thinking, and identities as engineers than as unique innovators [1]– [3]. Students who do not conform to this mold of “being an engineer” are often alienated from engineering, do not develop engineering identities, and leave engineering, which reduces the much-needed human potential for innovation [4], [5].

Read online for free at ASEE PEER — CAREER: Characterizing Latent Diversity Among a National Sample of First-year Engineering Students

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CAREER: Actualizing Latent Diversity in Undergraduate Engineering Education

Allison Godwin
Brianna Shani Benedict
Jacqueline Ann Rhode
Dina Verdín
Aaron Robert Hamilton Thielmeyer
Herman Ronald Clements III
Zhihui (Sherry) Chen

Excerpt: Cultivating a culture of inclusion is critical to engineering education. The environment in which students learn shapes not only their competencies but also who they become or their identities as engineers. Developing an engineering identity has been found to be important for a number of different outcomes including academic and personal development [1]–[5] as well as retention [6]–[8]. Students form their engineering identity in relation to the ways of being, thinking, and knowing that are valued in engineering culture. As a result, students who do not align with the cultural values in engineering may experience a lack of belonging [9], [10], which can ultimately lead to negative experiences and even attrition. For example, one of our participants, Mark, expressed that he loved studying mathematics, but he felt that “there wasn’t much room for creativity in engineering”. This mismatch in his goals and values led him to switch out of engineering to major in business. Ultimately, he felt that this change allowed him to be exposed to more diverse ways of thinking about problems in business applications.

Read online for free at ASEE PEER — CAREER: Actualizing Latent Diversity in Undergraduate Engineering Education

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“Adversary or Ally”: Undergraduate Engineering Students’ Perceptions of Faculty

H. Ronald Clements III
Brianna Shani Benedict
Allison Godwin
Jacqueline Ann Rohde
Sherry Chen

Abstract: This research paper examines students’ perceptions of faculty and how it influences their identity trajectory. First-year students enter undergraduate engineering education with rich stories of how they came to choose engineering as a career pathway. Over time, the culture of engineering and network of peers, faculty members, and professionals shape students’ stories and identity trajectories. How students “cast” faculty members in their story, often as helpful or hurtful actors, have implications for their identity trajectory, success, and, ultimately, retention in engineering. In this paper, we used two composite narratives constructed from longitudinal narrative interviews with 16 students to illustrate how students cast faculty into a role as either a support or an obstacle, based on their classroom experiences and interactions with them. This paper highlights the interactions that led these students to view faculty as helpful or harmful and explores the effects resulting: influence over student identity trajectory by fostering or hindering relationship building and networking, as well as influencing intellectual growth and personal ability beliefs.

Read online for free at ASEE PEER: “Adversary or Ally”: Undergraduate Engineering Students’ Perceptions of Faculty

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