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1. Investigating the Formation of Engineers and the Future Professoriate: Linking Writing Approaches and Attitudes to Doctoral Socialization, Persistence, and Attrition

   Berdanier, Catherine G. ( June 2019 , 126th ASEE Annual Conference & Exposition)

   This poster reports on results to date of an ongoing NSF RFE Grant, entitled “Investigating the Formation of Engineers and the Future Professoriate: Linking Writing Approaches and Attitudes to Doctoral Socialization, Persistence, and Attrition.” The objective of this study is to investigate the linkage between engineering writing and disciplinary discourse with other mechanisms of engineering graduate socialization, such as identity formation, socialization, persistence, and desire to pursue academic careers. This study is designed as an embedded exploratory mixed methods study of current graduate engineering students and recent non-completers that seek to answer the following research questions: 1. How do graduate students at various stages in their PhD programs in engineering perceive the role of academic writing as it relates to academic socialization and success in future academic careers? 2. How are these perceptions different or similar for graduate students who are considering leaving or have left their PhD programs before graduating? 3. Can existing surveys of writing concepts, attitudes, and self-efficacies predict students’ risk for attrition? 

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2. “If I knew what else I should do, I would have left by now:” Two engineering PhD students’ experiences with Master’s-level departure

   Zerbe, E. ; Berdanier, C.G.P. ( October 2019 , IEEE Frontiers in Education Conference)

   This Research Full Paper presents two examples of doctoral engineering attrition. To date, little research has been conducted on the many compounding factors that lead to attrition in graduate programs. In this paper, we present the narratives of two doctoral PhD students, Kelsey and Amy, who were deciding on departing from the engineering PhD. These narratives embody a deeper investigation of academic self-concept development through graduate school, with a focus on the decision-making processes to continue in the PhD program or decide to depart with a Master’s degree. At the time of the interviews, both participants were still enrolled in their programs, but one had definite plans to depart and left shortly after the interview. This study is one of the first that highlights the role of the Master's degree as an off-ramp from the engineering doctorate and lends insight to narratives surrounding attrition in engineering: Despite academic success in their courses and successful research progress, these participants decided to depart even after passing significant milestones such as qualifying exams. This research presents the beginning of a larger research project with a goal of generating a more complete narrative of the attrition process for the students, with an explicit focus on Master's-level departure. 

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3. Exploring the Viability of Agent-Based Modeling to Extend Qualitative Research: Comparison of Computational Platforms

   Splendido, S. ; Berdanier, C.G.P. ( January 2023 , ASEE annual conference exposition)

   The purpose of this methods paper is to identify the opportunities and applications of agent-based modeling (ABM) methods to interpretative qualitative and educational research domains. The context we explore in this paper considers graduate engineering attrition, which has been a funded research focus of our group for ten years. In attrition research, as with all human research, it is impossible and unethical to imperil real graduate students by subjecting them to acute stressors that are known to contribute to attrition in order to “test” different combinations of factors on persistence and attrition. However, agent-based modeling (ABM) methods have been applied in other human decision-making contexts in which a computer applies researcher programmed logic to digital actors, invoking them to make digital decisions that mimic human decision making. From our research team’s ten years of research studying graduate socialization and attrition and informed from a host of theories that have been used in literature to investigate doctoral attrition, this paper compares the utility of two programming languages, Python and NetLogo, in conducting agent-based modeling to model graduate attrition as a platform. In this work we show that both platforms can be used to simulate attrition and persistence scenarios for thousands of digital agent-students simultaneously to produce results that agree with both with previous qualitative data and that agree with aggregate attrition and persistence statistics from literature. The two languages differ in their integrated development environments (IDE) with the methods of producing the models customizable to fit the needs of the study. Additionally, the size of the intended agent pool impacted the efficiency of the data collection. As computational methods can transform educational research, this work provides both a proof-of-concept and recommendations for other researchers considering employing these methods with these and similar platforms. Ultimately, while there are many programming languages that can perform agent-based modeling tasks, researchers are responsible for translating high quality, theory-driven, interpretive research into a computational model that can model human decision-making processes. 

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4. Correlations between graduate student writing concepts and processes and certainty of career trajectories

   https://doi.org/10.1109/FIE.2018.8658678  

   Berdanier, Catherine G.P. ; Zerbe, Ellen ( October 2018 , 2018 IEEE Frontiers in Education Conference (FIE))

   At the graduate level, most milestones are based on the ability to write for an academic audience, whether that be for dissertation proposals, publications, or funding opportunities. Writing scholars often discuss the process by which graduate students learn to join their academic “discourse communities” through academic literacies theory. Graduate attrition researchers relate the feeling of belonging with persistence in doctoral programs; however, there has not to date been any research that directly studies engineering writing attitudes and perceptions with student career trajectories, persistence, or attrition. To meet this need, this paper presents research from a larger study analyzing graduate level engineering writing and attrition. The explicit objective of this paper is to present quantitative data relating current graduate engineering students' attitudes, processes, and concepts of academic writing with the certainty of their career trajectory. Five scales measuring aspects of writing were deployed to engineering programs at ten research intensive universities across the United States, with a final total of n=621 graduate student respondents that represent early-career, mid-career, and late-career stages of the graduate timeline. Results indicate that graduate student processes and conceptions of engineering writing correlate with the likelihood of pursuing careers in various engineering sectors after completing their graduate degree programs. 

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5. Persistence at what cost? How graduate engineering students consider the costs of persistence within attrition considerations

   https://doi.org/10.1002/jee.20528  

   Sallai, Gabriella M. ; Bahnson, Matthew ; Shanachilubwa, Kanembe ; Berdanier, Catherine G. P. ( May 2023 , Journal of Engineering Education)

   While previous work in higher education documents the impact of high tuition costs of attending graduate school as a key motivator in attrition decisions, in engineering, most graduate students are fully funded on research fellowships, indicating there are different issues causing individuals to consider departure. There has been little work characterizing nonfinancial costs for students in engineering graduate programs and the impact these costs may have on persistence or attrition.

   Framed through the lens of cost as a component of the expectancy–value theory framework and the graduate attrition decisions (GrAD) model conceptual framework specific to engineering attrition, the purpose of this article is to characterize the costs engineering graduate students associate with attending graduate school and document how costs affect students' decisions to persist or depart.

   Data were collected through semistructured interviews with 42 engineering graduate students from R1 engineering doctoral programs across the United States who have considered, are currently considering, or have chosen to depart from their engineering PhD programs with a master's degree.

   In addition to time and money, which are costs previously captured in research, participants identified costs to life balance, costs to well‐being, and identify‐informed opportunity costs framed in terms of what “could have been” if they had chosen to not go to graduate school. As these costs relate to persistence, students primarily identified their expended effort and already‐incurred costs as the primary motivator for persistence, rather than any expected benefits of a graduate degree.

   The findings of this work expand the cost component of the GrAD model conceptual framework, providing a deeper understanding of the costs that graduate students relate to their persistence in engineering graduate programs. It evidences that motivation to persist may not be due to particularly strong goals but may result from costs already incurred. Through this research, the scholarly community, students, advisors, and university policymakers can better understand the needs of engineering graduate students as they navigate graduate study.

    

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