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1. Current Trends in Attrition Considerations of Graduate Engineering Students in the United States

   Bahnson, M.; Berdanier, C.G.P (January 2023, International journal of engineering education)

   Available attrition statistics for graduate engineering students do not adequately inform current attrition research because they focus on degree completion rather than attrition or early departure; aggregate science, technology, engineering, and mathematics (STEM) students; and reflect out-of-date data. While recently some work has begun to explore doctoral attrition qualitatively, the purpose of this study is to describe current trends in graduate engineering students’ consideration of departure from their programs of study by capturing current numerical data specific to engineering about students’ recent attrition considerations. This is important because, since the last studies were conducted, higher education systems have experienced a global pandemic, economic downturn, and sociopolitical turmoil in the United States. Graduate students (n = 2204) in the U.S. completed a survey. The sample includes master’s (n = 535) and doctorate (n = 1646) degree-seeking students from 27 engineering disciplines and includes U.S. domestic and international populations. A majority of students considered leaving their degree program in the month before they took the survey: nearly 70% of Ph.D. and 39% of master’s students, while 31% of Ph.D. and 16% of master’s students seriously considered leaving their program without their degree. Descriptive statistics provide early departure considerations by engineering discipline, gender identity, race/ethnicity, nationality, and year in program by degree sought. Comparisons between groups are presented for gender, nationality, and career stage. It is essential to have an updated and discipline-specific benchmark of attrition considerations for continued engineering education research purposes, for mentorship, and for administrative purposes. Early departure from graduate school remains a threat to innovation and broadening participation in engineering and the professoriate. 

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2. Witnessing “De‐Socialization”: Investigating unexpected longitudinal trends in engineering doctoral socialization

   https://doi.org/10.1002/jee.70040  

   Jwa, Kyeonghun; Berdanier, Catherine GP (January 2026, Journal of Engineering Education)

   Abstract BackgroundGraduate‐level education is gaining attention in engineering education scholarship. While “socialization” is a key term in doctoral literature, little is known about how socialization occurs over time. One common assumption asserts that socialization increases over time, encompassing factors such as belongingness, research ability, and advisor relationship as students acclimate to the norms and values of their advisors, departments, universities, and disciplines. We investigate engineering doctoral student socialization trends: students likely to complete their degrees and those who have questioned whether to persist in their programs. Understanding these trends is essential, as many students consider leaving their programs. Purpose/HypothesisThis paper aims to understand how socialization processes occur over several years in engineering students who questioned leaving their PhD programs. Design/MethodWe present longitudinal survey data collected from two cohorts (N_A = 113 andN_B = 355) of engineering doctoral students at R1 universities in the United States. Data were collected over 2 years through SMS surveys with participants receiving text messages three times per week. We analyzed data using descriptive and time series analysis methods. ResultsBoth cohorts showed lower levels of belongingness over time, reported declining advisor relationships, and experienced higher levels of stress. Students later in their programs also reported deteriorating overall social relationships. These findings contradict canonical socialization theory, which expects socialization to naturally improve over time. ConclusionWhile many assume socialization occurs passively and students acculturate into their department and research team over time, our results show students who question whether to persist are de‐socializing from graduate school. 

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3. Mitigating Ceiling Effects in a Longitudinal Study of Doctoral Engineering Student Stress and Persistence

   https://doi.org/10.28945/5118  

   Bahnson, Matthew; Sallai, Gabriella; Jwa, Kyeonghun; Berdanier, Catherine (January 2023, IJEE International Journal of Engineering Education)

   Aim/Purpose: The research reported here aims to demonstrate a method by which novel applications of qualitative data in quantitative research can resolve ceiling effect tensions for educational and psychological research.Background: Self-report surveys and scales are essential to graduate education and social science research. Ceiling effects reflect the clustering of responses at the highest response categories resulting in non-linearity, a lack of variability which inhibits and distorts statistical analyses. Ceiling effects in stress reported by students can negatively impact the accuracy and utility of the resulting data.Methodology: A longitudinal sample example from graduate engineering students’ stress, open-ended critical events, and their early departure from doctoral study considerations demonstrate the utility and improved accuracy of adjusted stress measures to include open-ended critical event responses. Descriptive statistics are used to describe the ceiling effects in stress data and adjusted stress data. The longitudinal stress ratings were used to predict departure considerations in multilevel modeling ANCOVA analyses and demonstrate improved model predictiveness.Contribution: Combining qualitative data from open-ended responses with quantitative survey responses provides an opportunity to reduce ceiling effects and improve model performance in predicting graduate student persistence. Here, we present a method for adjusting stress scale responses by incorporating coded critical events based on the Taxonomy of Life Events, the application of this method in the analysis of stress responses in a longitudinal data set, and potential applications.Findings: The resulting process more effectively represents the doctoral student experience within statistical analyses. Stress and major life events significantly impact engineering doctoral students’ departure considerations.Recommendations for Practitioners: Graduate educators should be aware of students’ life events and assist students in managing graduate school expectations while maintaining progress toward their degree. Recommendation for Researchers: Integrating coded open-ended qualitative data into statistical models can increase the accuracy and representation of the lived student experience. The new approach improves the accuracy and presentation of students’ lived experiences by incorporating qualitative data into longitudinal analyses. The improvement assists researchers in correcting data with ceiling effects for use in longitudinal analyses.Impact on Society: The method described here provides a framework to systematically include open-ended qualitative data in which ceiling effects are present.Future Research: Future research should validate the coding process in similar samples and in samples of doctoral students in different fields and master’s students. 

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4. Students' Experiences of Unfairness in Graduate Engineering Education

   Bahnson, M.; Satterfield, D.; Wyer, M.; Kirn, A. (January 2021, The Collaborative Network for Engineering and Computing Diversity)

   null (Ed.)

   A pilot inventory to develop measures of bias and discrimination experienced by engineering doctoral students asked if they have been treated unfairly by their primary advisor, secondary advisor, and other faculty. Analyses of pilot data (n = 250) revealed Women, Students of Color, and sexual minorities perceived experiences of unfair treatment in intricate patterns. Post hoc analyses show that Women experience more incidences of unfair treatment than men. Race/ethnicity identity groups report a different number of unfair treatment incidences, with Students of Color generally reporting more experiences than white students. Being a sexual minority contributed to reporting more incidences of unfair treatment. Unfair treatment from faculty significantly predicted students changing and considering changing research labs when controlling for gender, race/ethnicity, and sexuality. Unfair treatment from faculty significantly impacted engineering identity when controlling for gender, race/ethnicity, sexuality, lab changers, and change considerers. Analyses of pilot data demonstrated the negative impact of unfair treatment on students and their development as engineers. 

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5. Elements of disenchantment: Exploring the development of academic disenchantment among US engineering graduate students

   https://doi.org/10.1002/jee.20624  

   Shanachilubwa, Kanembe; Sallai, Gabriella; Berdanier, Catherine_GP (January 2025, Journal of Engineering Education)

   Abstract BackgroundGiven high attrition rates and lack of interest in faculty careers, it is crucial to understand how doctoral engineering students conceptualize academia and academic careers. Purpose/HypothesisThis study aims to characterize the development of academic disenchantment among engineering students who have considered departure from their doctoral programs. Schema theory was used to explore how students develop and evolve in their conceptualizations of academia through their lived experiences. Design/MethodData were collected from 42 graduate students from research‐intensive universities across the United States who participated in qualitative, semi‐structured interviews investigating expectations for graduate school, experiences, attrition and persistence considerations, and career trajectories. The transcripts were thematically analyzed through open and axial coding to understand how students constructed their schemas of the academy. FindingsExperiences and quotations of four participants are presented to describe the results of the transcripts. Participants' misaligned expectations of their graduate program's values and practices, coupled with a lack of agency and support, led them to see their graduate programs as antagonistic to their short‐ and long‐term career success. Even for students who may likely persist through to PhD degree completion, the development of disenchantment dissuades students—even those who once desired a faculty career—from interest in the academy. ConclusionsBy understanding how disenchantment arose in our participants' experiences, we better understand how to equip students with resources that will help them navigate graduate programs. This research advances the literature by identifying underutilized opportunities to prepare students to cope with the challenges of engineering doctoral education. 

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