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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. 

In architecture and engineering, design professionals may use the term “optimization” to describe a range of design approaches. These working definitions of optimization may not align with one another, or with the formal definition of mathematical optimization in engineering education. This paper presents a thematic analysis of 13 interviews with design professionals who use optimization in their work. Using the communication theory of coordinated management of meaning (CMM) to understand how the interviewer and interviewee were negotiating possible definitions, four themes are identified: optimization as performance improvement, as achieving varied goals, as a systematic process, and as a formal problem structure with variables and objectives, which is most aligned with the mathematical definition. Interviewees used these varied definitions dynamically in conversation, which informs researchers and educators about their potential use in practice. 

Abstract BackgroundPostdoctoral training holds an increasingly important place in preparation for leading academic and research positions. While little empirical research has described postdoctoral training beyond the sciences, across all fields, “misaligned expectations” are often touted as a key source of postdoctoral strife. Purpose/HypothesisThis article describes mentorship competency beliefs within engineering and computer science fields, which increasingly engage in postdoctoral training. Design/MethodAn embedded mixed‐methods design was used to quantitatively identify mentorship profiles from survey data using latent profile analysis (LPA) from a sample ofn = 118 postdoctoral scholars andn = 165 postdoctoral supervisors. Qualitative thematic analysis of interviews withn = 29 postdoctoral scholars andn = 20 postdoctoral supervisors was used to identify meaning in the differences between quantitative profiles. The combination of LPA with thematic analysis enabled the triangulation of distinct postdoctoral mentorship profile definitions. ResultsLPA identified six postdoctoral fellow profiles and four supervisor profiles, which became clearly definable through thematic analysis. Postdoc profiles included Technical Manager, Autonomy Focused Advisor, Stretched Mentor, Well‐Rounded Mentor, Exemplar Mentor, and Leader‐Mentor, while supervisor profiles included Autonomous Mentor, Reflective Mentor, Research Lab Mentor, and Confident Leader‐Mentor. Some of these are aligned, but several are not, giving insight into the phenomenon of “misaligned expectations” in postdoctoral literature. ConclusionsThe mentorship profiles illustrate the misalignment in expectations, which leads to negative mentorship experiences for many postdoctoral scholars.