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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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A latent class analysis approach to the identification of doctoral students at risk of attrition
To advance understanding of doctoral student experiences and the high attrition rates among Science, Technology, Engineering, and Mathematics (STEM) doctoral students, we developed and examined the psychological profiles of different types of doctoral students. We used latent class analysis on self-reported psychological data relevant to psychological threat from 1,081 incoming doctoral students across three universities and found that the best-fitting model delineated four threat classes: Lowest Threat , Nonchalant , Engaged/Worried , and Highest Threat . These classes were associated with characteristics measured at the beginning of students’ first semester of graduate school that may influence attrition risk, including differences in academic preparation (e.g., amount of research experience), self-evaluations and perceived fit (e.g., sense of belonging), attitudes towards graduate school and academia (e.g., strength of motivation), and interpersonal relations (e.g., perceived social support). Lowest Threat students tended to report the most positive characteristics and Highest Threat students the most negative characteristics, whereas the results for Nonchalant and Engaged/Worried students were more mixed. Ultimately, we suggest that Engaged/Worried and Highest Threat students are at relatively high risk of attrition. Moreover, the demographic distributions of profiles differed, with members of groups more likely to face social identity threat (e.g., women) being overrepresented in a higher threat profile (i.e., Engaged/Worried students) and underrepresented in lower threat profiles (i.e., Lowest Threat and Nonchalant students). We conclude that doctoral students meaningfully vary in their psychological threat at the beginning of graduate study and suggest that these differences may portend divergent outcomes.
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- Award ID(s):
- 1661214
- PAR ID:
- 10415439
- Editor(s):
- Benetreau, Yann
- Date Published:
- Journal Name:
- PLOS ONE
- Volume:
- 18
- Issue:
- 1
- ISSN:
- 1932-6203
- Page Range / eLocation ID:
- e0280325
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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In this Great Ideas for Teaching Students (GIFTS) paper, we offer learning outcomes that we are beginning to recognize from our eight-week research experience for undergraduates (REU). There are four characteristics that have been found to be essential to success in Science, Technology, Engineering, and Mathematics (STEM) fields: a strong sense of STEM identity, scientific self-efficacy, a sense of belonging, and a psychological sense of community. This is especially true for first-year and transfer students pursuing STEM undergraduate degrees. A variety of studies have been published that go into detail about why these characteristics in particular have such a significant effect on student performance and retention. This paper will present Critical Self-Reflection as a practical way to integrate development of these characteristics into student research experiences to foster experiential learning that goes beyond increasing technical skills. STEM students are not often trained to critically self-reflect on their experiences in classroom and research settings. An inability for undergraduates to reflect intentionally on their experiences creates greater risk for attrition from STEM disciplines. Curated reflective experiences in collaborative learning settings can offer professional development opportunities to enhance students’ social and technical communication skills. There are four phases within the scaffolded Critical Self-Reflection framework: Learning to Reflect, Reflection for Action, Reflection in Action, and Reflection on Action. When applying the evidence-based practice, STEM undergraduate researchers describe their perceptions via three activities: creating a legacy statement, participating in facilitated dialogue sessions, and writing curated reflection journal entries within an REU. Through critical self-reflection exercises, we are beginning to find growth of first-year and transfer STEM undergraduates in the following areas: understanding of their role in the lab; confidence in their researcher identity; expression of agency; observation and communication skills; and intentionality for action. Participating in this self-reflection allows students to make meaning of their experience enabling them to hone the aforementioned characteristics that creates a pathway from their undergraduate experience to undergraduate degree completion, graduate degree attainment, and to the STEM workforce.more » « less
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Abstract BackgroundAlthough most engineering graduate students are funded and usually complete their degrees faster than other disciplines, attrition remains a problem in engineering. Existing research has explored the psychological and sociological factors contributing to attrition but not the structural factors impacting attrition. Purpose/HypothesisUsing systems theory, this study seeks to understand nuance in how underlying structural causes affect engineering graduate students' attrition experiences in ways that may differ from their official reasons for departure. Design/MethodsData were collected through semi‐structured interviews with seven departing or already departed engineering doctoral students from R1 graduate programs across the United States. Using thematic analysis, root cause analyses were conducted to understand participants' attrition experiences to explore how structures influence causes of departure. ResultsThe ways participants discuss root causes of their departure indicate differences in formal reasons for departure and underlying causes of departure. We highlight the role of informal and formal policy as root causes of a different attrition rationale often passed off as interpersonal issues. When interpreted as evidence of structural issues, the causes of departure show ways in which action–inaction, policy–“null” policy serve as structural features governing student attrition decision processes. We also highlight a form of benign neglect toward struggling graduate students. ConclusionThis study reveals important nuances underlying face‐value reasons of attrition indicating foundational structural issues contributing to engineering graduate student attrition. Coaching faculty in team management and encouraging close revision of departmental policies could help mitigate students' negative graduate experiences and decrease unnecessary attrition.more » « less
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1371/journal.pone.0280325
