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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. 

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.