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Engineer Identity and Degree Completion Intentions in Doctoral Study

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Title: Engineer Identity and Degree Completion Intentions in Doctoral Study
Language: English
Authors: Bahnson, Matthew (ORCID 0000-0002-0134-0125), Satterfield, Derrick (ORCID 0000-0002-4197-0551), Perkins, Heather (ORCID 0000-0002-8757-0545), Parker, Mackenzie (ORCID 0000-0002-5891-3908), Tsugawa, Marissa (ORCID 0000-0001-6009-8810), Cass, Cheryl, Kirn, Adam (ORCID 0000-0001-6344-5072)
Source: Journal of Engineering Education. Apr 2023 112(2):445-461.
Availability: Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
Peer Reviewed: Y
Page Count: 17
Publication Date: 2023
Sponsoring Agency: National Science Foundation (NSF)
Contract Number: EEC1763288
EHR1535254
EHR1535453
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Engineering Education, Technical Occupations, Self Concept, Academic Persistence, Intention, Doctoral Students, Student Experience, Student Characteristics, Teacher Student Relationship, Peer Relationship
DOI: 10.1002/jee.20516
ISSN: 1069-4730
2168-9830
Abstract: Background: Degree completion rates for doctoral engineering students remain stagnant at levels lower than necessary to meet national and global workforce needs. Increasing degree completion can improve opportunities for individuals and provide the human resources needed to address engineering challenges. Purpose/Hypothesis: In this work, we measure the association of engineering identity variables with degree completion intentions for students who have persisted in doctoral study. We add to existing literature that suggests the importance of advisor and peer relationships, and the number of years in the doctoral program. Design/Method: We use data collected via a national cross-sectional survey of doctoral engineering students, which included measures of social and professional identities, graduate school experiences, and demographics. Surveys were collected from 1754 participants at 98 US universities between late 2017 and early 2018. The analyses reported here use multiple regression to measure associations with engineering doctoral degree completion intentions. Results: Research interest and scientist performance/competence are individually associated with degree completion intentions in students who are persisting in doctoral study. Overall, graduate engineering identity explains significant portions of variation in degree completion intentions (9.5%) beyond advisor and peer relationship variables and the number of years in graduate programs. Conclusions: Researcher interest and scientist performance/competence may be key opportunities to engage doctoral student engineering identity to improve degree completion rates. Accordingly, institutions can foster students' interest in research and build their confidence in their scientific competence to support students as they complete the doctoral degree.
Abstractor: As Provided
Entry Date: 2023
Accession Number: EJ1373726
Database: ERIC
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  Value: <anid>AN0163111926;6m401apr.23;2023Apr18.06:25;v2.2.500</anid> <title id="AN0163111926-1">Engineer identity and degree completion intentions in doctoral study </title> <p>Background: Degree completion rates for doctoral engineering students remain stagnant at levels lower than necessary to meet national and global workforce needs. Increasing degree completion can improve opportunities for individuals and provide the human resources needed to address engineering challenges. Purpose/Hypothesis: In this work, we measure the association of engineering identity variables with degree completion intentions for students who have persisted in doctoral study. We add to existing literature that suggests the importance of advisor and peer relationships, and the number of years in the doctoral program. Design/Method: We use data collected via a national cross‐sectional survey of doctoral engineering students, which included measures of social and professional identities, graduate school experiences, and demographics. Surveys were collected from 1754 participants at 98 US universities between late 2017 and early 2018. The analyses reported here use multiple regression to measure associations with engineering doctoral degree completion intentions. Results: Research interest and scientist performance/competence are individually associated with degree completion intentions in students who are persisting in doctoral study. Overall, graduate engineering identity explains significant portions of variation in degree completion intentions (9.5%) beyond advisor and peer relationship variables and the number of years in graduate programs. Conclusions: Researcher interest and scientist performance/competence may be key opportunities to engage doctoral student engineering identity to improve degree completion rates. Accordingly, institutions can foster students' interest in research and build their confidence in their scientific competence to support students as they complete the doctoral degree.</p> <p>Keywords: graduate education; identity; persistence; quantitative; survey</p> <hd id="AN0163111926-2">INTRODUCTION</hd> <p>National agencies have recognized the need for more qualified, advanced engineering degree holders to meet current and future challenges (Council of Graduate Schools, [<reflink idref="bib19" id="ref1">19</reflink>]; National Academies of Science, Engineering, and Medicine [NASEM], [<reflink idref="bib52" id="ref2">52</reflink>]; Sowell et al., [<reflink idref="bib68" id="ref3">68</reflink>]). Increased matriculation and doctoral degree completion would contribute to filling the need for doctoral engineers. Yet low degree completion rates remain problematic for increasing the number of advanced engineering degree holders, with 40%–60% of doctoral students departing without the doctorate (Sowell et al., [<reflink idref="bib68" id="ref4">68</reflink>]).</p> <p>While persistence in the doctoral degree is not always appropriate, improving engineering graduate education systems to ensure those with the desire, talent, and ability are able to complete their doctoral degree is one avenue to increasing the number of practicing engineers. Investigations of degree completion intentions provide valuable insight into interventions that can lead to structural educational innovations to improve graduate engineering degree completion. In this research, we build on concepts informing degree completion intentions, focusing on doctoral students' relationships and identities to identify interventions that may increase degree completion rates.</p> <p>The apprenticeship model employed in doctoral training necessitates the involvement of an advisor. The essential nature of the advisor–trainee relationship logically provides an avenue to improve degree completion rates (Iraniparast, [<reflink idref="bib36" id="ref5">36</reflink>]; Noy & Ray, [<reflink idref="bib53" id="ref6">53</reflink>]; Schlosser et al., [<reflink idref="bib67" id="ref7">67</reflink>]; Zhao et al., [<reflink idref="bib73" id="ref8">73</reflink>]). However, attempts to improve advisor relationships with strategies like mentorship have resulted in limited improvements in degree completion rates (Blume‐Kohout, [<reflink idref="bib8" id="ref9">8</reflink>]; Kerr et al., [<reflink idref="bib38" id="ref10">38</reflink>]; Zhao et al., [<reflink idref="bib73" id="ref11">73</reflink>]). Similarly, peer relationships have been recognized as important support systems for engineering doctoral students, in addition to the relationship they have with their advisors (Borrego et al., [<reflink idref="bib9" id="ref12">9</reflink>]; Cunningham, [<reflink idref="bib22" id="ref13">22</reflink>]; Jeong et al., [<reflink idref="bib37" id="ref14">37</reflink>]; Sattler et al., [<reflink idref="bib66" id="ref15">66</reflink>]).</p> <p>In this research, we seek to quantitatively measure the association between advisor relationship and peer relationship, the number of years in the doctoral program, and the association of engineering identity with degree completion intentions. Engineering identity has been recognized as a significant factor in undergraduate degree completion (Godwin et al., [<reflink idref="bib31" id="ref16">31</reflink>]; Meyers et al., [<reflink idref="bib47" id="ref17">47</reflink>]; Patrick et al., [<reflink idref="bib55" id="ref18">55</reflink>]); however, graduate engineering identity has not yet been quantitatively connected to degree completion (Rodriguez et al., [<reflink idref="bib63" id="ref19">63</reflink>]). We seek to identify how graduate engineering identity relates to degree completion intentions in addition to advisor and peer relationships. Understanding the contributions of relationships and identities to degree completion intentions yields insights into potential interventions to increase degree completion.</p> <p>The Graduate STEM Education for the 21st Century report highlights the need to investigate doctoral students' experiences to identify opportunities to improve degree completion rates (NASEM, [<reflink idref="bib52" id="ref20">52</reflink>]). We begin with the existing qualitative research, which indicates the significant influence of relationships with advisors and research peers on degree completion. Quantitative assessment of these relationships will provide additional insight into the association of each with degree completion intentions. Next, we unpack the relationship between the number of years in the doctoral program and degree completion intentions. Finally, we introduce the relation between graduate engineering identity and degree completion intentions, which is yet to be quantitatively established. We review each of these areas to better evaluate how academic relationships, the number of years in the program, and engineering identity relate to degree completion intentions.</p> <hd id="AN0163111926-3">LITERATURE REVIEW</hd> <p></p> <hd id="AN0163111926-4">Academic relationships and degree completion</hd> <p>Academic relationships with advisors and peers influence doctoral student experiences (Bahnson et al., [<reflink idref="bib4" id="ref21">4</reflink>]; Bégin & Gérard, [<reflink idref="bib6" id="ref22">6</reflink>]; Gittings et al., [<reflink idref="bib28" id="ref23">28</reflink>]; Kerr et al., [<reflink idref="bib38" id="ref24">38</reflink>]; NASEM, [<reflink idref="bib52" id="ref25">52</reflink>]; H. Perkins et al., [<reflink idref="bib58" id="ref26">58</reflink>]; Ro & Loya, [<reflink idref="bib62" id="ref27">62</reflink>]; Sowell et al., [<reflink idref="bib68" id="ref28">68</reflink>]). For instance, faculty and peer relationships significantly contributed to a sense of belonging, but not directly to degree commitment for first year biology doctoral students (Jeong et al., [<reflink idref="bib37" id="ref29">37</reflink>]). Doctoral students' sense of belonging can facilitate their intentions for degree completion (Bahnson et al., [<reflink idref="bib4" id="ref30">4</reflink>]). Academic relationships, in turn, can support and hinder student belonging in engineering.</p> <hd id="AN0163111926-5">Advisor relationships</hd> <p>An effective advisor relationship is an essential aspect of graduate degree completion across graduate programs (Main, [<reflink idref="bib42" id="ref31">42</reflink>]; Millett & Nettles, [<reflink idref="bib49" id="ref32">49</reflink>]; NASEM, [<reflink idref="bib52" id="ref33">52</reflink>]). A quality relationship with and ongoing access to a primary or research advisor strongly supports graduate degree persistence (Bégin & Gérard, [<reflink idref="bib6" id="ref34">6</reflink>]; Gittings et al., [<reflink idref="bib28" id="ref35">28</reflink>]; Main, [<reflink idref="bib42" id="ref36">42</reflink>]; NASEM, [<reflink idref="bib52" id="ref37">52</reflink>]). Advisors who provide graduate students with consistent and constructive guidance throughout the students' research experience generate a stronger, more successful advising relationship and independence for the student (Blume‐Kohout, [<reflink idref="bib8" id="ref38">8</reflink>]; Burt et al., [<reflink idref="bib13" id="ref39">13</reflink>]; Kerr et al., [<reflink idref="bib38" id="ref40">38</reflink>]; Zhao et al., [<reflink idref="bib73" id="ref41">73</reflink>]). While the importance and influence of advisor relationships on degree completion are evident, the influence of and changes to advisor relationships have yet to lead to increased degree completion (Burt et al., [<reflink idref="bib13" id="ref42">13</reflink>]). The association between advisor relationship and degree completion intentions has yet to be quantitatively assessed in engineering graduate students.</p> <hd id="AN0163111926-6">Research peer relationships</hd> <p>Peers provide similar support as advisors do, but the two types of relationships serve different functions. Peer relationships within a research lab or group independently support graduate student development through skill development and experience, impacting the ability to complete their degree (Borrego et al., [<reflink idref="bib9" id="ref43">9</reflink>]). Research group peers support graduate student skill development in writing skills, community discussion, presenting, feedback interactions, problem‐solving, and troubleshooting (Burt, [<reflink idref="bib12" id="ref44">12</reflink>]; Cunningham, [<reflink idref="bib22" id="ref45">22</reflink>]; Maher et al., [<reflink idref="bib41" id="ref46">41</reflink>]). Peers serve an essential role in providing opportunities for peer mentorship, education, and enculturation into the norms and identity of engineering (Gardner, [<reflink idref="bib27" id="ref47">27</reflink>]). Peer support improves presentations, feedback, and problem‐solving within research groups (Burt, [<reflink idref="bib12" id="ref48">12</reflink>]); assists in goal setting and monitoring progress (Sattler et al., [<reflink idref="bib66" id="ref49">66</reflink>]); and aids in developing confidence in engineering and research skills (Cunningham, [<reflink idref="bib22" id="ref50">22</reflink>]). When communities fail to support development, students may question their experiences and purpose within engineering (Cicek et al., [<reflink idref="bib18" id="ref51">18</reflink>]; Diefes‐Dux et al., [<reflink idref="bib25" id="ref52">25</reflink>]). Research group peers engage in support functions and knowledge sharing with advanced students and postdocs mentoring students into the discipline culture, thereby assisting in professional identity development (Crede & Borrego, [<reflink idref="bib20" id="ref53">20</reflink>]).</p> <hd id="AN0163111926-7">Association of years in graduate program</hd> <p>The length of time in the graduate program plays a role in graduate engineering identity development (Bahnson et al., [<reflink idref="bib4" id="ref54">4</reflink>]). Multiple factors explain these phenomena, and they have not been clearly explored in the literature. At the beginning of their doctoral studies, students likely have very high intentions to complete their doctoral degree. The rigors and difficulties of doctoral study may not be obstacles to degree completion intentions in the first year. As students progress, the reality of balancing coursework, research, other professional responsibilities, and personal lives becomes entrenched, and students' intentions to complete the degree may be affected.</p> <p>The number of years a student has spent in the graduate program is an essential factor in controlling for the expected development of students as they progress through the program. As students complete more years in their program, they accumulate knowledge and skills, develop their professional identity, and become acculturated to who advanced engineers are and what they do (Lave & Wenger, [<reflink idref="bib39" id="ref55">39</reflink>]). Students with more years in their program have differences in their academic relationships, identities, and experiences (Bahnson et al., [<reflink idref="bib4" id="ref56">4</reflink>]).</p> <p>The psychological theory of escalation of commitment claims that the more people invest time, resources, and efforts into a project, the greater the likelihood that they will continue to do so (Moon, [<reflink idref="bib50" id="ref57">50</reflink>]). Pursuing a graduate degree requires significant resource investment in terms of money, time, effort, and emotion, especially for the longer term requirement of the doctoral program (Berdanier et al., [<reflink idref="bib7" id="ref58">7</reflink>]). Students may be more likely to complete a degree in which they have invested significant resources.</p> <p>Not all persistence is necessarily positive, just as not all attrition is necessarily negative (McGee et al., [<reflink idref="bib44" id="ref59">44</reflink>]; McGee & Martin, [<reflink idref="bib45" id="ref60">45</reflink>]). Some students may change their intentions about their degree, discover new interests, or dislike doctoral study and research (Satterfield et al., [<reflink idref="bib65" id="ref61">65</reflink>]). Beyond academic reasons, life changes may necessitate a change in degree intentions or increase the appeal of employment that does not require a doctoral degree (Sallai et al., [<reflink idref="bib64" id="ref62">64</reflink>]).</p> <p>However, an analysis examining the relationship between years in the program and degree completion intentions may be subject to survivorship bias. Survivorship bias occurs when the effects of previous attrition are overlooked or ignored. For example, doctoral engineering students in a cross‐sectional sample may report uniformly high degree completion intentions, leading researchers to assume intentions to persist are not predictive of actual persistence, given their lack of variability in the sample. Students with lower degree completion intentions may have left the population before the sample was drawn. Due to these issues, persistence in the doctoral degree may skew measures of degree completion intentions. The potential implications for degree completion intentions require testing for differences based on years in the program and then controlling for the number of years in the program for any cross‐sectional analyses. This helps determine if there is an attenuation of degree completion intentions across years in the program, and then controls for any potential effects in future analyses. Similarly, implications and conclusions drawn from cross‐sectional analyses require the recognition that students who persist may be systematically distinct from students who leave doctoral study before completing the doctorate.</p> <hd id="AN0163111926-8">Graduate engineering identity model</hd> <p>Seeing oneself as an engineer—that is, having an engineering identity—is associated with persistence, motivation, and career choice across multiple engineering contexts (Crede & Borrego, [<reflink idref="bib21" id="ref63">21</reflink>]; Godwin, [<reflink idref="bib29" id="ref64">29</reflink>]; Godwin et al., [<reflink idref="bib31" id="ref65">31</reflink>]; Godwin & Kirn, [<reflink idref="bib30" id="ref66">30</reflink>]). Godwin's undergraduate engineering identity framework (e.g., Godwin et al., [<reflink idref="bib31" id="ref67">31</reflink>]) generated insightful research into engineering identity as a tool to understand professional identity in engineers. Godwin's model focused on areas of development necessary for undergraduate student engineers: interest, performance/competence, and recognition in physics and math. Given the importance of Godwin's undergraduate engineering identity framework, researchers have extended and adapted engineering identity to study engineering graduate students (Choe & Borrego, [<reflink idref="bib16" id="ref68">16</reflink>]; H. Perkins et al., [<reflink idref="bib59" id="ref69">59</reflink>]). Engineering interest, recognition, and competence combined with interpersonal communication skills strongly predict engineering identity in graduate students (Choe & Borrego, [<reflink idref="bib17" id="ref70">17</reflink>]). Exploratory work examining engineering graduate students who debated leaving the field demonstrates that factors related to identity are vital in their intentions to persist (Berdanier et al., [<reflink idref="bib7" id="ref71">7</reflink>]).</p> <p>Kirn and colleagues utilized a mixed‐methods approach to extend engineering identity to graduate students, including qualitative interviews, focus groups, and survey testing, when developing graduate engineering identity (GEI) domains. Intensive qualitative interviews and analyses characterized three unique domains that represented graduate conceptions of what it means to be an engineer and belong in engineering (H. Perkins et al., [<reflink idref="bib59" id="ref72">59</reflink>]; H. Perkins et al., [<reflink idref="bib57" id="ref73">57</reflink>]). Kirn and colleagues validated the identity domains of researcher, scientist, and engineer through focus groups exploring each identity domain and graduate student experiences more generally. Qualitative interviews and focus groups preceded and guided the development of a 15‐min survey focused on each of these domains (Cass et al., [<reflink idref="bib15" id="ref74">15</reflink>]; Miller et al., [<reflink idref="bib48" id="ref75">48</reflink>]; H. Perkins et al., [<reflink idref="bib59" id="ref76">59</reflink>]; H. Perkins et al., [<reflink idref="bib57" id="ref77">57</reflink>]; Tsugawa‐Nieves et al., [<reflink idref="bib69" id="ref78">69</reflink>]). Developing a quantitative measure of GEI for each domain followed procedures outlined in previous engineer identity work (Godwin, [<reflink idref="bib29" id="ref79">29</reflink>]). Subsequent piloting of these measures occurred with students at two geographically diverse institutions (H. Perkins et al., [<reflink idref="bib57" id="ref80">57</reflink>]). Pilot testing established satisfactory validity and reliability for the GEI scale (H. Perkins et al., [<reflink idref="bib57" id="ref81">57</reflink>]).</p> <p>The three identity domains of GEI—researcher, scientist, and engineer—each have the sub‐constructs of recognition, performance/competence, and interest (H. Perkins et al., [<reflink idref="bib59" id="ref82">59</reflink>]; H. Perkins et al., [<reflink idref="bib57" id="ref83">57</reflink>]). The identity domains of GEI reflect the focus of engineering graduate education on research and scientific discovery. This distinction indicates that GEI, similar to undergraduate engineering identity, contributes uniquely to student development at the graduate level. While each domain reflects a specific identity space, the domains overlap such that, as a graduate student, an engineer identity is linked to researcher identity through the student's engineering research. At the same time, researcher and scientist identities align more closely as engineering students develop these specific domains through graduate study. Similarly, the sub‐constructs of recognition, performance/competence, and interest within each domain share features across domains. For example, a student may experience recognition as an engineer and researcher based upon engineering research, thereby supporting both engineering recognition and researcher recognition sub‐constructs. Distinct manifestations of these sub‐constructs emerged as well. For instance, graduate students demonstrate performance/competence based on experiences in classes, lab, or comprehensive exams such that some experiences support performance/competence as an engineer or scientist differently. This model of GEI aligns closely with other graduate student engineering identity models developed within specific institutional contexts (Choe & Borrego, [<reflink idref="bib16" id="ref84">16</reflink>]; Choe & Borrego, [<reflink idref="bib17" id="ref85">17</reflink>]).</p> <hd id="AN0163111926-9">Graduate engineering identity research</hd> <p>Limited research focuses on engineering identity in graduate students (Rodriguez et al., [<reflink idref="bib63" id="ref86">63</reflink>]) with some encouraging insights. Previous work utilizing measures of advisor and peer interactions shows that lab composition bolsters GEI (Crede & Borrego, [<reflink idref="bib20" id="ref87">20</reflink>]; H. L. Perkins et al., [<reflink idref="bib60" id="ref88">60</reflink>]); strong advisor and peer relationships relate to higher researcher and scientist recognition (Bahnson et al., [<reflink idref="bib3" id="ref89">3</reflink>]); and research experiences positively contribute to GEI (Bahnson et al., [<reflink idref="bib2" id="ref90">2</reflink>]). GEI is related to academic relationships and the amount of time in the degree program (Bahnson et al., [<reflink idref="bib4" id="ref91">4</reflink>]). While this body of work explores the different structures that relate to GEI, it has not examined the implications of a GEI for degree completion quantitatively. Utilizing GEI constructs together, we examine how GEI builds upon academic relationships and the number of years in a program in association with degree completion intentions. Together, these variables potentially explain a large amount of variation in degree completion intentions for doctoral degree seeking engineering students who remain enrolled in graduate study.</p> <hd id="AN0163111926-10">CURRENT STUDY</hd> <p>The work presented assesses the quantitative relationship between advisor relationship and intentions to complete the doctoral degree while providing insights into future research. Given existing research, peer relationships likely relate to degree completion intentions independent of advisor relationships. Peer relationships have not been quantitatively connected with degree completion. Measuring the association between peer relationships and degree completion intentions separately from advisor relationship allows our study to identify distinctions in academic relationships that may provide alternative avenues to increasing degree completion.</p> <p>In this project, we seek to examine how advisor and peer relationships quantitatively relate to degree completion intentions (including the number of years in the program) to build upon existing qualitative research that demonstrates the importance of these variables in degree completion. In addition, we investigate how GEI may improve the quantitative association with degree completion intentions beyond interpersonal relationships.</p> <p></p> <ulist> <item> What is the relationship between advisor and research peer academic interpersonal relationships and the number of years in the doctoral program with degree completion intentions?</item> <p></p> <item> When advisor and peer relationships and years in program are included, what is the relationship between GEI and degree completion intentions in doctoral engineering students?</item> </ulist> <p>We ask the first question to quantitatively establish relationships based in qualitative research. The second question goes a step further to quantify the relationship between GEI and degree completion intentions. We answer these research questions with multiple regression of research data collected from a national sample of graduate engineering students. The answers to these questions provide empirical evidence to bolster continued efforts in increasing persistence to doctoral degree while identifying new avenues for intervention.</p> <hd id="AN0163111926-11">METHODS</hd> <p>These analyses use data collected to investigate graduate engineering student experiences, identities, identity‐based motivations, and future‐time perspectives (Cass et al., [<reflink idref="bib15" id="ref92">15</reflink>]; H. L. Perkins et al., [<reflink idref="bib60" id="ref93">60</reflink>]). A 15‐min online survey was developed from qualitative interviews and focus groups examining these constructs (Cass et al., [<reflink idref="bib15" id="ref94">15</reflink>]; Miller et al., [<reflink idref="bib48" id="ref95">48</reflink>]; H. Perkins et al., [<reflink idref="bib59" id="ref96">59</reflink>]; H. L. Perkins et al., [<reflink idref="bib60" id="ref97">60</reflink>]; Tsugawa‐Nieves et al., [<reflink idref="bib69" id="ref98">69</reflink>]). Pilot testing of the survey established the validity and reliability of the survey constructs (H. L. Perkins et al., [<reflink idref="bib60" id="ref99">60</reflink>]). This paper focuses on the GEI constructs and advisor and research peer relationships measures.</p> <p>The analyses presented here connect the importance of advisor and research peer relationships and years in program to GEI and degree completion intentions. Previous work has focused on qualitative analyses or quantitative analyses that do not connect the academic relationships to both GEI and degree completion. We use multiple regression to layer each set of variables to better understand the relationship of each upon degree completion. The results provide implications for practice for engineering doctoral education programs, advisors, and doctoral students.</p> <hd id="AN0163111926-12">Positionality</hd> <p>The authors predominantly identify as White and recognize our privileged positions within the educational system. The authors identify as engineering educators with the first and third trained as applied social psychologists and others trained in an engineering field in addition to engineering education. Our perspective as engineering educators shapes our approach to this research such that we intend to generate knowledge useful to improving the experience of doctoral engineering students. We approach this research cognizant of our varied backgrounds and contributions while sharing an interest in improving the experience and degree completion rate for graduate engineering students from all backgrounds. Engineering identity research provides us an avenue to contribute to engineering equity while providing empirical research useful to engineering educators, institutions, and policy makers. The multiple perspectives in training and personal background enable us to view the impacts and meaning of our research beyond our individual training. The rich experiences of the author team allow for a more nuanced approach to our data collection, analysis, discussion, and translation of our work into actionable implications.</p> <hd id="AN0163111926-13">Recruitment</hd> <p>The recruitment process is described briefly here, with additional detail reported elsewhere (refer to Bahnson et al., [<reflink idref="bib4" id="ref100">4</reflink>]; H. Perkins et al., [<reflink idref="bib58" id="ref101">58</reflink>]). The American Society for Engineering Education's (ASEE's) list of US doctorate‐granting engineering programs defined the population of engineering programs (ASEE, [<reflink idref="bib1" id="ref102">1</reflink>]). Programs were selected based on state, program type, and the number of doctoral degrees granted in 2014 (Yoder, [<reflink idref="bib72" id="ref103">72</reflink>]). Probability proportional sampling generated a random sample list of programs to represent the national population. A survey invitation was emailed to selected program directors to forward to students or requesting they provide a list of graduate engineering students for participation. Participants completed the survey online using the Qualtrics platform. The primary investigator's Institutional Review Boards approved all research materials and methods.</p> <hd id="AN0163111926-14">Participants</hd> <p>Participants from 98 universities participated (<emph>n =</emph> 2348) representing approximately 30% of programs contacted. We removed participants if they did not complete at least half of the survey, resulting in 1754 completed surveys for analysis (for details, refer to Bahnson et al., [<reflink idref="bib4" id="ref104">4</reflink>]). Two nonengineering PhD students and master's degree (<emph>n =</emph> 564) seeking students were removed, resulting in engineering PhD (<emph>n =</emph> 1188) for analysis.</p> <p>The sample participant demographics match current US engineering graduate student demographics (H. L. Perkins et al., [<reflink idref="bib60" id="ref105">60</reflink>]; Yoder, [<reflink idref="bib72" id="ref106">72</reflink>]). Table 1 provides demographic data. Participants indicated gender and sex by selecting one or more of seven options (female, male, genderqueer, agender, transgender, cisgender, and a gender not listed [with write in response optional]). Very few participants chose genderqueer, agender, transgender, or a gender not listed options. Participants indicated race/ethnicity by selecting one or more of eight categories with no participants identifying as only "American Indian or Alaska Native." While representative of engineering graduate students, the whiteness and maleness of our sample must be noted as a limitation (Pawley, [<reflink idref="bib56" id="ref107">56</reflink>]). SPSS v25 was used to generate descriptive statistics (IBM Corp., [<reflink idref="bib35" id="ref108">35</reflink>]).</p> <p>1 TABLE Doctoral student demographics.</p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left">Race/ethnicity by gender with percent of race/ethnicity–gender category for doctoral degree seeking students</th></tr><tr><th align="left" /><th align="left">Gender identity, <italic>n</italic> (%)</th></tr><tr><th align="left">Race/ethnicity</th><th align="left">Female</th><th align="left">Male</th><th align="left">Another gender</th><th align="left">Total</th></tr></thead><tbody valign="top"><tr><td>Asian</td><td>105 (33.2)</td><td>211 (66.8)</td><td>0 (0)</td><td>316 (31.9)</td></tr><tr><td>African American</td><td>7 (35)</td><td>13 (65)</td><td>0 (0)</td><td>20 (2)</td></tr><tr><td>Hispanic/Latinx</td><td>12 (33.3)</td><td>24 (66.7)</td><td>0 (0)</td><td>36 (4)</td></tr><tr><td>Middle Eastern or North African</td><td>18 (39.1)</td><td>28 (60.9)</td><td>0 (0)</td><td>46 (4.6)</td></tr><tr><td>Native Hawaiian or Pacific Islander</td><td>0 (0)</td><td>1 (100)</td><td>0 (0)</td><td>1 (0.01)</td></tr><tr><td>White</td><td>209 (37.8)</td><td>340 (61.5)</td><td>3 (0.6)</td><td>554 (55.9)</td></tr><tr><td>Another not listed</td><td>5 (29.4)</td><td>9 (52.9)</td><td>3 (17.6)</td><td>17 (1.7)</td></tr><tr><td>Total</td><td>356 (36)</td><td>626 (63.3)</td><td>6 (0.1)</td><td>989 (100)</td></tr></tbody></table> </ephtml> </p> <p>1 <emph>Note</emph>: Two hundred doctoral students did not indicate one or both of race/ethnicity and gender. Students who indicated multiple races/ethnicities were included in "another not listed."</p> <hd id="AN0163111926-15">Measuring degree completion intentions</hd> <p>Our ability to measure future behavior often uses attitudes about and intentions toward future behavior as a proxy variable. As with any future behavior measurement, degree completion intentions represent a measure for the intention to complete behavior that cannot be equated with actual behavior. In cross‐sectional research, asking students if they intend to complete their degree is a reliable proxy for degree completion (Bean, [<reflink idref="bib5" id="ref109">5</reflink>]; Cabrera et al., [<reflink idref="bib14" id="ref110">14</reflink>]; Davidson et al., [<reflink idref="bib24" id="ref111">24</reflink>]; Hausmann et al., [<reflink idref="bib33" id="ref112">33</reflink>]; Pascarella et al., [<reflink idref="bib54" id="ref113">54</reflink>]). Measures of degree completion intentions remain inconsistent across empirical studies (Davidson et al., [<reflink idref="bib24" id="ref114">24</reflink>]). Within engineering education research, single‐item measures previously used include: "I intend to complete my degree at <name of institution>" (i.e., Hausmann et al., [<reflink idref="bib33" id="ref115">33</reflink>]). We measured degree completion intentions with a single item rated strongly disagree (<reflink idref="bib1" id="ref116">1</reflink>) to strongly agree (<reflink idref="bib5" id="ref117">5</reflink>): "I intend to complete my graduate degree" (Table 2). This item provides our dependent variable.</p> <p>2 TABLE Variables and measures characteristics for doctoral students and example items.</p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left" /><th align="left" /><th align="left">Doctoral</th><th align="left" /></tr><tr><th align="left" /><th align="left">Number of items</th><th align="left"><italic>n</italic></th><th align="left"><italic>M</italic></th><th align="left">SD</th><th align="left"><italic>α</italic></th><th align="left">Example item</th></tr></thead><tbody valign="top"><tr><td>Dependent variable</td><td /><td /><td /><td /><td /><td /></tr><tr><td>Degree completion intentions</td><td>1</td><td>1186</td><td>4.70</td><td>0.71</td><td>–</td><td>I intend to complete my graduate degree</td></tr><tr><td>Independent variables</td><td /><td /><td /><td /><td /><td /></tr><tr><td>Graduate engineering identity</td><td /><td /><td /><td /><td /><td /></tr><tr><td>Researcher:Recognition</td><td>7</td><td>1182</td><td>4.21</td><td>0.77</td><td>.91</td><td>My advisor(s) see me as a RESEARCHER</td></tr><tr><td>Researcher:Interest</td><td>3</td><td>1188</td><td>4.33</td><td>0.77</td><td>.92</td><td>I am interested in learning more about how to do RESEARCH</td></tr><tr><td>Researcher:Perfor/Comp</td><td>6</td><td>1188</td><td>4.23</td><td>0.74</td><td>.86</td><td>I understand the concepts needed to analyze and interpret data</td></tr><tr><td>Scientist:Recognition</td><td>7</td><td>1184</td><td>3.58</td><td>0.95</td><td>.91</td><td>My peers see me as a SCIENTIST</td></tr><tr><td>Scientist:Interest</td><td>3</td><td>1188</td><td>4.50</td><td>0.69</td><td>.95</td><td>I enjoy learning SCIENCE</td></tr><tr><td>Scientist:Perfor/Comp</td><td>5</td><td>1181</td><td>4.25</td><td>0.65</td><td>.87</td><td>I can overcome setbacks when learning SCIENCE</td></tr><tr><td>Engineer:Recognition</td><td>7</td><td>1185</td><td>3.93</td><td>0.92</td><td>.92</td><td>Others ask me for help with ENGINEERING</td></tr><tr><td>Engineer:Interest</td><td>2</td><td>1189</td><td>4.23</td><td>0.86</td><td>.91</td><td>I find satisfaction when doing ENGINEERING</td></tr><tr><td>Engineer:Perfor/Comp</td><td>5</td><td>1187</td><td>4.33</td><td>0.74</td><td>.92</td><td>I understand concepts I have studied in ENGINEERING</td></tr><tr><td>Advisor relationship</td><td>8</td><td>1179</td><td>4.05</td><td>0.88</td><td>.92</td><td>My advisor is easy to approach</td></tr><tr><td>Peer relationship</td><td>4</td><td>1055</td><td>3.93</td><td>0.81</td><td>.77</td><td>Students in my research group are supportive of one another</td></tr><tr><td>Years in program</td><td>1</td><td>1165</td><td>2.09</td><td>1.95</td><td>–</td><td /></tr></tbody></table> </ephtml> </p> <p>2 <emph>Note</emph>: All responses except number of years started used a five‐point Likert‐type scale from strongly disagree (<reflink idref="bib1" id="ref118">1</reflink>) to strongly agree (<reflink idref="bib5" id="ref119">5</reflink>); Participants selected the year they started their engineering graduate degree from a drop‐down menu; change in <emph>n</emph> is due to pairwise deletion; <emph>α</emph> = Cronbach's alpha; Perfor/Comp = Performance/Competence.</p> <hd id="AN0163111926-16">Measures</hd> <p>This analysis uses advisor and peer relationship and the number of years in program as well‐established variables that interact with degree completion intentions and engineering identity in graduate education. The combination of these variables represents the first use of these in one model to improve understanding of doctoral engineering student persistence. The first two, advisor and research peer relationship scores, represent academic relationships necessary for doctoral student development and degree completion. The third variable, the number of years in the program, controls doctoral students' timebound development. Finally, we add GEI to investigate the importance of professional identity beyond the established importance of advisor and research peer relationships and the number of years in program (Bahnson et al., [<reflink idref="bib4" id="ref120">4</reflink>]; Cass et al., [<reflink idref="bib15" id="ref121">15</reflink>]; Choe & Borrego, [<reflink idref="bib16" id="ref122">16</reflink>]; H. L. Perkins et al., [<reflink idref="bib60" id="ref123">60</reflink>]). Table 2 includes the mean, standard deviation (SD), and the number of participants (n) for each variable for doctoral students.</p> <p>Independent variables used a five‐point Likert‐type scale from strongly disagree (<reflink idref="bib1" id="ref124">1</reflink>) to strongly agree (<reflink idref="bib5" id="ref125">5</reflink>) with multiple items averaged for a variable score:</p> <p></p> <ulist> <item> Advisor relationship score: The mean of eight items with the root "My advisor ..." represents the advisor relationship score (Table 3). Cronbach's alpha was excellent based on standard requirements (Table 3 ; Whitley & Kite, [<reflink idref="bib71" id="ref126">71</reflink>]).</item> <p></p> <item> Research peer relationship score: The mean of four items asking about research group relationships represented peer relationships (Table 3). Cronbach's alpha is within acceptable standard requirements (Table 3 ; Whitley & Kite, [<reflink idref="bib71" id="ref127">71</reflink>]).</item> <p></p> <item> Years in program: Participants selected the year they started their engineering graduate degree from a drop‐down menu. The year selected was converted to the number of years in the program as of 2018 for analysis. Years in Program ranged from 1 to 9 years, with the majority in the first five years (25% in Year 1; 19% in Year 2; 19% in Year 3; 14% in Year 4; 10% in Year 5; 12% in Year 6 or more).</item> <p></p> <item> Graduate engineering identity: The GEI scale results in nine sub‐construct scores for each domain by sub‐construct (Bahnson et al., [<reflink idref="bib4" id="ref128">4</reflink>] ; H. Perkins et al., [<reflink idref="bib58" id="ref129">58</reflink>]). Cronbach's alpha in this sample is consistent with previous data (<emph>α</emph> between.86 and.95 for doctoral students; Table 2).</item> <item>octoral student multiple regression.</item> </ulist> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left">Model</th><th align="left" /><th align="left"><italic>b</italic></th><th align="left">SE <italic>b</italic></th><th align="left"><italic>β</italic></th><th align="left"><italic>t</italic></th><th align="left"><italic>p</italic></th><th align="left">95% CI [LB, UB]</th><th align="left">Tolerance</th><th align="left">VIF</th></tr></thead><tbody valign="top"><tr><td>1</td><td>(Constant)</td><td>4.29</td><td>0.11</td><td>–</td><td>40.84</td><td><.001</td><td>[4.09, 4.50]</td><td>–</td><td>–</td></tr><tr><td /><td>Advisor</td><td>0.10</td><td>0.03</td><td>.12</td><td>3.99</td><td><.001</td><td>[0.05, 0.15]</td><td>1.00</td><td>1.00</td></tr><tr><td>2</td><td>(Constant)</td><td>3.97</td><td>0.13</td><td>–</td><td>31.11</td><td><.001</td><td>[3.72, 4.23]</td><td>–</td><td>–</td></tr><tr><td /><td>Advisor</td><td>0.06</td><td>0.03</td><td>.07</td><td>2.15</td><td>.032</td><td>[0.01, 0.11]</td><td>0.86</td><td>1.16</td></tr><tr><td /><td>Peer</td><td>0.13</td><td>0.03</td><td>.14</td><td>4.30</td><td><.001</td><td>[0.07, 0.18]</td><td>0.86</td><td>1.16</td></tr><tr><td>3</td><td>(Constant)</td><td>3.90</td><td>0.13</td><td>–</td><td>29.78</td><td><.001</td><td>[3.64, 4.16]</td><td>–</td><td>–</td></tr><tr><td /><td>Advisor</td><td>0.07</td><td>0.03</td><td>.08</td><td>2.48</td><td>.013</td><td>[0.01, 0.12]</td><td>0.85</td><td>1.18</td></tr><tr><td /><td>Peer</td><td>0.12</td><td>0.03</td><td>.14</td><td>4.10</td><td><.001</td><td>[0.06, 0.18]</td><td>0.86</td><td>1.17</td></tr><tr><td /><td>Years in program</td><td>0.03</td><td>0.01</td><td>.08</td><td>2.53</td><td>.012</td><td>[0.01, 0.05]</td><td>0.98</td><td>1.02</td></tr><tr><td>4</td><td>(Constant)</td><td>2.80</td><td>0.19</td><td>–</td><td>14.46</td><td><.001</td><td>[2.42, 3.18]</td><td>–</td><td>–</td></tr><tr><td /><td>Advisor</td><td>0.03</td><td>0.03</td><td>.03</td><td>0.91</td><td>.363</td><td>[−0.03, 8.00]</td><td>0.77</td><td>1.31</td></tr><tr><td /><td>Peer</td><td>0.09</td><td>0.03</td><td>.10</td><td>3.01</td><td>.003</td><td>[0.03, 0.14]</td><td>0.81</td><td>1.24</td></tr><tr><td /><td>Years in program</td><td>0.03</td><td>0.01</td><td>.07</td><td>2.34</td><td>.019</td><td>[0.009, 0.05]</td><td>0.92</td><td>1.09</td></tr><tr><td /><td>Researcher:Recognition</td><td>−0.02</td><td>0.04</td><td>−.02</td><td>−0.38</td><td>.702</td><td>[−0.09, 0.06]</td><td>0.49</td><td>2.04</td></tr><tr><td /><td>Researcher:Interest</td><td>0.15</td><td>0.03</td><td>.16</td><td>4.04</td><td><.001</td><td>[0.08, 0.22]</td><td>0.57</td><td>1.77</td></tr><tr><td /><td>Researcher:Perfor/Comp</td><td>−0.01</td><td>0.04</td><td>−.01</td><td>−0.32</td><td>.752</td><td>[−0.09, 0.07]</td><td>0.49</td><td>2.04</td></tr><tr><td /><td>Scientist:Recognition</td><td>0.01</td><td>0.03</td><td>.01</td><td>0.25</td><td>.802</td><td>[−0.05, 0.06]</td><td>0.62</td><td>1.61</td></tr><tr><td /><td>Scientist:Interest</td><td>0.03</td><td>0.04</td><td>.03</td><td>0.77</td><td>.442</td><td>[−0.05, 0.11]</td><td>0.54</td><td>1.86</td></tr><tr><td /><td>Scientist:Perfor/Comp</td><td>0.15</td><td>0.05</td><td>.15</td><td>3.23</td><td>.001</td><td>[0.06, 0.25]</td><td>0.43</td><td>2.34</td></tr><tr><td /><td>Engineer:Recognition</td><td>−0.03</td><td>0.03</td><td>−.03</td><td>−0.80</td><td>.423</td><td>[−0.09, 0.04]</td><td>0.49</td><td>2.05</td></tr><tr><td /><td>Engineer:Interest</td><td>0.01</td><td>0.04</td><td>.01</td><td>0.28</td><td>.780</td><td>[−0.06, 0.09]</td><td>0.41</td><td>2.45</td></tr><tr><td /><td>Engineer:Perfor/Comp</td><td>0.03</td><td>0.05</td><td>.03</td><td>0.57</td><td>.566</td><td>[−0.07, 0.12]</td><td>0.36</td><td>2.76</td></tr></tbody></table> </ephtml> </p> <p>3 <emph>Note</emph>: The linear model of predictors of intentions to persist for doctoral students with 95% bias‐corrected and accelerated confidence intervals reported in parentheses and multicollinearity diagnostics. <emph>R</emph><sups>2</sups> change = .015 for Step 1 (<emph>p</emph> < .001); <emph>R</emph><sups>2</sups> change = .018 for Step 2 (<emph>p</emph> < .001); <emph>R</emph><sups>2</sups> change = .006 for Step 3 (<emph>p</emph> = .012); and <emph>R</emph><sups>2</sups> change = .071 for Step 4 (<emph>p</emph> < .001).</p> <hd id="AN0163111926-17">Data analysis plan</hd> <p>Each variable's skewness, kurtosis, tolerance, and variance inflation factor (VIF) were analyzed to confirm they were within acceptable ranges. In preparation, correlation analysis was performed on all variables to assess multicollinearity (Table S1). Variables significantly correlated within acceptable levels, with none exceeding a standard of <emph>r</emph> = 0.7 (Field, [<reflink idref="bib26" id="ref130">26</reflink>]). Correlation and collinearity diagnostics were analyzed in regression models to ensure the integrity of the data.</p> <p>The number of years participants have been in the program may be unduly influenced by survivorship. People who have left the doctoral program may have had lower degree completion intentions or those who have remained in may have had higher degree completion intentions. The mean of degree completion intention by the number of years in the program is tested with analysis of variance (ANOVA) to ensure changes in degree completion intention are not due solely to the number of years the participants have been in their engineering doctoral program (in other words, to help rule out the potential survivorship bias described earlier).</p> <p>The analysis used listwise deletion, which excludes the entire participant when items are skipped. We chose this method to avoid imputing data due to the importance of self‐definition in identity research. The sample is sufficiently large to offset any reduction in power due to the reduced sample size (<emph>n</emph> = 1188). In addition, analyses previously reported indicated variable data were missing at random, indicating further analyses were appropriate (Perkins et al., [<reflink idref="bib61" id="ref131">61</reflink>]).</p> <p>Data were analyzed with multiple regression analyses with the enter or block entry method and included multiple phases of variable entry with SPSS v25. Multiple regression measures the predictive value of multiple variables on a single dependent variable. Block entry allows for the addition of variables in theoretically based groups. This method also allows the measurement of the change in predictive value for each additional block of variables. The dependent variable was degree completion intentions for all analyses, with independent variables entered in blocks. The phased entry for variables was in four sets: (<reflink idref="bib1" id="ref132">1</reflink>) advisor relationship score, (<reflink idref="bib2" id="ref133">2</reflink>) research peer relationship score, (<reflink idref="bib3" id="ref134">3</reflink>) the number of years in the program, and (<reflink idref="bib4" id="ref135">4</reflink>) GEI subcomponent scores. The variables were entered with the well‐established variables first (advisor, research peer, and number of years in program) as the beginning of the model with GEI added last to demonstrate any improvement in the regression model from GEI inclusion.</p> <hd id="AN0163111926-18">RESULTS</hd> <p>Most variables correlated significantly (<emph>p</emph> < .001) as expected with none strong enough to indicate multicollinearity issues (Table S1). The mean of degree completion intention was not significantly different by the number of years in program (<emph>F</emph>(<reflink idref="bib8" id="ref136">8</reflink>) = 1.279, <emph>p</emph> = .250; Table S2). Tolerance and VIF multicollinearity diagnostics were within acceptable ranges (Tolerance >0.02; VIF <10; Bowerman & O'Connell, [<reflink idref="bib11" id="ref137">11</reflink>]; Field, [<reflink idref="bib26" id="ref138">26</reflink>]; Menard, [<reflink idref="bib46" id="ref139">46</reflink>]; Myers, [<reflink idref="bib51" id="ref140">51</reflink>]). The multiple regression coefficients are presented in Table 3. As expected in step 1, advisor relationship score associates with degree completion intentions while accounting for 1.4% of the variation in doctoral students: <emph>F</emph>(<reflink idref="bib1" id="ref141">1</reflink>, 1021) = 15.94, <emph>p</emph> < .001, <emph>R</emph><sups>2</sups> = .01. In step 2, addition of peer relationship scores significantly improved predictiveness of the model: <emph>F</emph>(<reflink idref="bib2" id="ref142">2</reflink>, 1020) = 17.36, <emph>p</emph> < .001, <emph>R</emph><sups>2</sups> = .03. Advisor relationship remained significant (<emph>p</emph> = .032), with peer relationship score contributing significantly to the model (<emph>p</emph> < .001). In step 3, the number of years in the program also significantly increased predictiveness of the model to 3.6% <emph>F</emph>(<reflink idref="bib1" id="ref143">1</reflink>, 1019) = 5.48, <emph>p</emph> < .001, <emph>R</emph><sups>2</sups> = .04. In step 4, addition of GEI sub‐construct measures significantly improved the model, explaining 9.9% of variance in degree completion intentions for doctoral students <emph>F</emph>(<reflink idref="bib9" id="ref144">9</reflink>, 1010) = 10.41, <emph>p</emph> < .001, <emph>R</emph><sups>2</sups> = .10. The addition of GEI sub‐constructs further reduced the impact of advisor relationship score to a nonsignificant level (<emph>p</emph> = .363) and reduced the significance of peer relationship score (<emph>p</emph> = .003) and years in program (<emph>p</emph> = .019). Some GEI sub‐constructs significantly and independently contributed to the model: researcher interest (<emph>p</emph> < .001) and scientist performance/competence (<emph>p</emph> = .001).</p> <hd id="AN0163111926-19">DISCUSSION</hd> <p>Together academic relationships, time in program, and GEI explain variations in degree completion intentions in students persisting in doctoral engineering programs. Our results illustrate the usefulness of GEI in understanding degree completion intentions within this context. The results also question common explanations for degree completion intentions. Particularly, the lowered significance of the advisor relationship variable challenges existing literature on research advisor relationships when trying to explain persistence, attrition, and degree completion rates. The discussion that follows specifies meaningful relationships identified in the results, which provide information and guidance for programs and advisors in their efforts to address doctoral degree completion.</p> <hd id="AN0163111926-20">Academic relationships</hd> <p>Academic relationships, including the advisor and peer relationships, represent a necessary aspect for graduate student success and degree completion (NASEM, [<reflink idref="bib52" id="ref145">52</reflink>]). Reflecting existing scholarship, advisor and peer relationships significantly associated with degree completion intentions for doctoral students in our analyses. The advisor relationship alone explained a very small portion of the variation for retained students. Given the emphasis on advisor relationships in graduate education literature, we expect the explained variance to be more considerable than 1.4%. Given the low quantitative relationship and the highly significant qualitative relationship (Curtin et al., [<reflink idref="bib23" id="ref146">23</reflink>]; Golde, [<reflink idref="bib32" id="ref147">32</reflink>]), advisor relationships may be a baseline necessary for degree completion intentions; however, when advisor relationships are generally positive, the relationship does not meaningfully increase degree completion intentions.</p> <p>Research peer relationships marginally increased the explained variation to a total of 3.1% in our analyses of doctoral student responses. Again, the impact of the peer relationship score reflects less explanatory power than expected based on existing literature. A potential explanation may be that peer relationships function well enough to not detract from degree completion and, at the same time, actively contribute to degree completion intentions.</p> <p>In our analyses of persisting students, research peer relationship scores significantly associated with degree completion intentions of doctoral students before GEI variables were added to the model. Peer relationships reflect a multifaceted relationship that supports student development through research, lab, classroom, and social interactions (Bahnson et al., [<reflink idref="bib3" id="ref148">3</reflink>]; Crede & Borrego, [<reflink idref="bib20" id="ref149">20</reflink>]; H. Perkins et al., [<reflink idref="bib57" id="ref150">57</reflink>]). Peers serve an essential role as informal educators, research trainers, and enculturation sources for the norms and identity of engineering, communication, and goal setting (Burt, [<reflink idref="bib12" id="ref151">12</reflink>]; Cunningham, [<reflink idref="bib22" id="ref152">22</reflink>]; Gardner, [<reflink idref="bib27" id="ref153">27</reflink>]; Sattler et al., [<reflink idref="bib66" id="ref154">66</reflink>]). Given the importance of peer relationships, a lack of effect after GEI is included in our analyses may result from a baseline effect: students require supportive peer relationships in the research setting, but increasingly supportive relationships do not significantly or meaningfully improve degree completion intentions.</p> <p>Positive advisor and peer relationships support students in their development from complementary perspectives (Hocker et al., [<reflink idref="bib34" id="ref155">34</reflink>]). The advisor and peer relationship measures each include an item about being supported by their advisor and peers (Appendix). Support likely depends on the individual student, their needs, and the social context of the lab, program, and university. Advisors may provide social support from an experienced professional standpoint while peers may provide social support outside of the lab by engaging in nonacademic social activities. A multidimensional advisor relationship contributes to identity development and degree completion from multiple roles, research director, dissertation chair, mentor, friend, or role model (NASEM, [<reflink idref="bib52" id="ref156">52</reflink>]). Recent discussions have emphasized the need for mentorship of graduate students, often placing the expectations on advisors (NASEM, [<reflink idref="bib52" id="ref157">52</reflink>]). However, identified sources of support and mentorship originate from various sources, such as online resources, other faculty, postdoctoral students, research advisors, and dissertation committees (Boulder, [<reflink idref="bib10" id="ref158">10</reflink>]). The limited explanatory power for advisor and peer relationships may further contribute to suggestions that graduate students require a broader base of mentorship and positive academic relationships (NASEM, [<reflink idref="bib52" id="ref159">52</reflink>]).</p> <hd id="AN0163111926-21">Importance of number of years in program</hd> <p>The number of years in their graduate degree significantly improved the model in correspondence with existing literature (Bahnson et al., [<reflink idref="bib4" id="ref160">4</reflink>]), although the improved explanation of degree completion intentions was marginal for persisting students. The duration of the doctoral endeavor enculturates students in their field, deepening their commitment to complete the degree. Identities develop as graduate students advance in years, with more robust identity components predicting degree completion intentions for students with more years of experience (McAlpine & Lucas, [<reflink idref="bib43" id="ref161">43</reflink>]). However, the increase in explained variance in our model may be understood as the influence of survivorship within the doctoral program. Given a cross‐sectional design, we are unable to determine if participants had higher degree completion intentions than their peers at earlier points within doctoral training.</p> <hd id="AN0163111926-22">Doctoral graduate engineering identity predicts degree completion intentions</hd> <p>For doctoral students, the model reflects expected variable relationships based on previous GEI research (Bahnson et al., [<reflink idref="bib4" id="ref162">4</reflink>]; H. Perkins et al., [<reflink idref="bib58" id="ref163">58</reflink>]; Verdín et al., [<reflink idref="bib70" id="ref164">70</reflink>]). Overall, the model combines and builds upon existing quantitative investigations of graduate student experiences by including multiple measures (advisor and peer relationships, number of years in the program, and GEI sub‐constructs) meaningfully associated with degree completion intentions. In particular, the GEI sub‐constructs of researcher interest and scientist performance/competence individually contributed significantly to the model. This result demonstrates a relationship not previously identified in the literature. The researcher interest sub‐construct indicates the role of doctoral engineering training in supporting students in developing their research interests, while the performance/competence sub‐construct refers to how programs develop scientists beyond the advisor and peer relationship dynamics. Taken alongside overall engineering identity, the clear relationship between researcher interest and scientist performance/competence with degree completion intentions represents a previously assumed, but undemonstrated relationship. GEI provides a window into the experiences meaningful for doctoral students to continue growing and developing as engineers. Our results point to novel opportunities to improve degree completion intentions for engineering doctoral students.</p> <hd id="AN0163111926-23">IMPLICATIONS</hd> <p>The implications for practice in engineering doctoral education highlight potential alternative directions for improving degree completion intentions among students who have not left their graduate programs. Within the limits of our research design, these same alternative directions could also improve degree completion rates. Based on our findings, implications for improving degree completion intentions could focus on (<reflink idref="bib1" id="ref165">1</reflink>) research peer relationships, (<reflink idref="bib2" id="ref166">2</reflink>) research community, (<reflink idref="bib3" id="ref167">3</reflink>) professional identity development, and specifically (<reflink idref="bib4" id="ref168">4</reflink>) researcher interest and scientist performance/competence.</p> <p>Interventions for doctoral students often seek to improve or develop relationships with research advisors or faculty as an avenue to improve degree completion rates. While our findings support the importance of advisor relationship, our results suggest interventions may be more effective if applied to research peer relationships. Peer relationships serve a complementary purpose for degree completion intentions and may be an underutilized area of improvement by faculty and departments. Systematic integration of peer relationship development into coursework, lab culture, and early experiences may foster student persistence. Integrating peer relationships into the educational structure can demonstrate the importance of research collaboration and academic and social support engineering peers. First, departments and institutions can provide training for graduate students on developing relationships beyond the classroom (i.e., teamwork assignments) and with less experienced peers to improve their ability to provide social support within lab groups. Second, considering not all doctoral students have other graduate students in their research groups, departments or research labs could develop ways to include potentially isolated students in research and in social activities as a way to integrate them into the research community. Ensuring that research community develops around potentially isolated students could help integrate them within the engineering community and improve their ability to see themselves in engineering.</p> <p>Past research has shown that the longer doctoral students are in their programs, the less likely they are to complete their degree (Lovitts, [<reflink idref="bib40" id="ref169">40</reflink>]). Our model demonstrated the importance of considering how long a student is in their program with reference to the development of professional identity. The variable—time in program (how many years into graduate program)—demonstrated the increase in degree completion intentions between early and late‐career doctoral students, indicating that professional identity development support and structures for early and late‐career doctoral students may need to be distinct. Early career students may need support developing advisor and peer relationships, for instance, and benefit from early wins in research experiences as an opportunity to support continued research interest and performance/competence as a scientist. Advanced students may have faced difficulties such as failed experiments, rejected publications, and pressures to produce results that may erode the excitement and interest in engineering research projects more readily accessible earlier in their graduate career. Faculty and departments should focus on maintaining or developing new research interests and opportunities for students to demonstrate stage‐appropriate competence as scientists.</p> <p>Two sub‐constructs of GEI, researcher interest and scientist performance/competence, independently and significantly associate with degree completion intentions where faculty could focus to support doctoral students. Regarding the first sub‐construct, the need to promote researcher interest for doctoral students may not be intuitive to faculty and advisors. Yet the rigors of doctoral research can be daunting, with fluctuations in interest and engagement as students face successes and failures throughout their program. Advisors and programs could provide training and guidance on maintaining research interest by walking through setbacks and failures to explore different research approaches. The training could also help students build their scientist performance/competence of the research process, particularly in writing about their research process. Simultaneously, scientist performance/competence could be supported by promoting students' successes as they add new scientific experiences and abilities throughout their doctoral training. Ensuring scientific milestones are recognized throughout the research process may further support students' sense of their own ability to complete scientific tasks.</p> <p>Overall GEI could be leveraged to improve degree completion intentions for doctoral students. Faculty, advisors, and graduate programs could implement interventions that foster professional identity development. We would like to recognize that the issues impacting doctoral student degree completion intentions are complex, multifaceted, and under‐researched. We encourage the research community to share their successes, failures, and assessments of programs, systems, and relationships to help the broader field improve degree completion rates.</p> <hd id="AN0163111926-24">LIMITATIONS</hd> <p>We identify multiple limitations to our current work to provide clear directions for future research. Every project cannot measure every variable, and choices must be made. Our work is largely exploratory, seeking to understand fundamental relationships between academic relationships, GEI, and degree completion intentions. Future research should focus on specific areas (e.g., engineering discipline) to increase the number and clarity of variables to be considered and included in analyses.</p> <p>A primary limitation of this work is the reliance on a single item to measure degree completion intentions at a single time point. While single‐item measures of degree completion intentions are used (refer to Hausmann et al., [<reflink idref="bib33" id="ref170">33</reflink>]), multi‐item measures create a more accurate and stable construct representation (Whitley & Kite, [<reflink idref="bib71" id="ref171">71</reflink>]). Future research would benefit from a multi‐item measure of degree completion intentions and a longitudinal design. Together, these would increase the reliability of predicting degree completion. A longitudinal design allows measurement of change over time within individuals for degree completion intentions, GEI, advisor relationship, and peer relationships. Degree completion could be captured to assess the validity of degree completion intention measures and could better measure the exact relationships between these variables as students advance through their degree programs.</p> <p>Other mentorship from faculty, research advisors, community members, and dissertation committees may contribute to persistence in ways not measured in our project. While advisor scores did not independently relate to degree completion intentions in the full model, the advisor relationship remained a meaningful variable in the model. The lack of significant independent relation may be due to a more complex connection between advisor relationship and degree completion intentions than identified in this research. For instance, advisor relationship score association with degree completion intentions may be mediated by GEI. While the importance of advisor relationships is demonstrated in previous research, the advisor relationship score used in this research may not capture the constructs that directly impact degree completion intentions. Similarly, our peer relationship items limit the relationship to those with research lab peers. The importance of peer support may not be captured due to limitations on the types of peers included in the survey items. Future research should measure a broader set of peer relationships and potential items.</p> <p>Differences in GEI sub‐constructs exist for doctoral students based on the field or discipline of engineering they study (Bahnson et al., [<reflink idref="bib4" id="ref172">4</reflink>]). Differences between disciplines may distort the impact of GEI sub‐constructs on degree completion intentions. Differences in GEI may indicate how disciplines apply advisor and peer influence, where some disciplines promote supportive relationships more successfully than others (Bahnson et al., [<reflink idref="bib4" id="ref173">4</reflink>]). Future research should investigate GEI sub‐constructs as well as advisor and peer relationships within distinct engineering disciplines on degree completion intentions.</p> <p>We chose years in the graduate program as a definable variable that graduate students readily provided. Reliance on the years in their program may unduly limit participants to those who had strong degree completion intentions and remained in their program. Our survivorship analysis addresses this concern; however, longitudinal research could provide a more reliable control for differences based on the year in the doctoral program. Similarly, alternative measures of development could be considered in future research. For instance, degree milestones for doctoral students such as completing comprehensive exams, oral exams, dissertation proposals, or defense could be used to measure academic progress in the program. However, these variables do not adequately relate to development as an engineer, given the heterogeneity of terms, meanings, and time sequences of these degree milestones.</p> <p>Finally, intersecting social and personal identities such as gender, sexual identity, or race/ethnicity relate to academic relationships, experiences, and degree completion. For example, experiences of discrimination within academic relationships likely decrease degree completion intentions. Our sample, as in the field of engineering as a whole, is comprised of mostly White and male participants. Additional work that integrates personal identity factors may illuminate areas for improvement and intervention.</p> <hd id="AN0163111926-25">CONCLUSIONS</hd> <p>Researcher interest and scientist performance/competence sub‐constructs of GEI individually associated with degree completion intentions in doctoral students who remain enrolled in graduate study. The overall model predicts degree completion intentions with all GEI constructs, advisor relationships, peer relationships, and years in doctoral program. Developing GEI may be one option for increasing the retention of doctoral students to degree completion. Inclusion of GEI variables predicts more of the variation in degree completion intentions among students who have been retained in their programs than more well‐established predictors of success in doctoral education (i.e., advisor and peer relationship scores and the number of years since starting a program). Existing systems and initiatives should be evaluated in light of these findings to investigate how existing practices support or hinder GEI, relationships with advisors and peers, as well as relevant differences based on the number of years in a program the student has completed. Similarly, when developing interventions to increase degree completion, researchers should consider the impact of the intervention based on the support for identity and the interaction of advisor relationships and research peer relationships on the intervention implementation and long‐term success. Assessment to determine if the intervention engages identity and supports positive advisor and peer relationships based on the year a student is in the program may improve the efficacy of the intervention and increase engineering graduate student persistence.</p> <hd id="AN0163111926-26">ACKNOWLEDGMENTS</hd> <p>The authors would like to thank the National Science Foundation for funding this research as part of grants EHR‐1535254, EHR‐1535453, and EEC‐1763288. Additionally, we would like to thank the PRiDE and NCSU Research Groups for their contributions to our research process. Finally, we would like to thank Dr. Catherine Berdanier for her feedback on drafts of this work.</p> <hd id="AN0163111926-27">APPENDIX</hd> <p></p> <hd id="AN0163111926-28">ADVISOR AND PEER RESEARCH GROUP ITEMS</hd> <p></p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left">Items rated on a five‐point Likert‐type scale from strongly disagree (1) to strongly agree (5)</th></tr></thead><tbody valign="top"><tr><td>My advisor ...</td><td>... Has clearly stated his or her expectations for satisfactory participation in my program</td></tr><tr><td>... is easy to approach</td></tr><tr><td>... is knowledgeable about my research</td></tr><tr><td>... encourages and supports my research</td></tr><tr><td>... values my work</td></tr><tr><td>... provides advice in a timely manner</td></tr><tr><td>... is also my mentor</td></tr><tr><td>... and I have a positive relationship</td></tr></tbody></table> </ephtml> </p> <p></p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left">Are you a member of a lab or research group with other graduate students?</th></tr></thead><tbody valign="top"><tr><td>Research group peers</td><td>Students in my research group are supportive of one another</td></tr><tr><td>I am an active member of my research group</td></tr><tr><td>I spend time with members of my research group outside of work</td></tr><tr><td>Overall, I feel that my experience with my research group has been positive</td></tr></tbody></table> </ephtml> </p> <p>GRAPH: Table S1. 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Journal of Further and Higher Education, 31 (3), 263 – 281. https://doi.org/10.1080/03098770701424983</bibtext> </blist> </ref> <aug> <p>By Matthew Bahnson; Derrick Satterfield; Heather Perkins; Mackenzie Parker; Marissa Tsugawa; Cheryl Cass and Adam Kirn</p> <p>Reported by Author; Author; Author; Author; Author; Author; Author</p> <p></p> <p>Matthew Bahnson is a Postdoctoral Fellow in Engineering Education in the Department of Mechanical Engineering at the Pennsylvania State University, 206 Reber Building, University Park, PA 16802‐4400, USA;.</p> <p>Derrick Satterfield is a Doctoral Candidate in the Engineering Education Department at the University of Nevada, Reno, 1664 North Virginia Street, Reno, NV 89557, USA;.</p> <p>Heather Perkins is a Visiting Assistant Professor at Indiana University, 1101 East 10th Street, Bloomington, IN 47405, USA;.</p> <p>Mackenzie Parker is a Graduate Research Assistant in the Engineering Education Department at the University of Nevada, Reno, 1755 North Virginia Street, Reno, NV 89557, USA;.</p> <p>Marissa Tsugawa is an Assistant Professor at Utah State University, 4160 Old Main Hill, Logan, UT 84322, USA;.</p> <p>Cheryl Cass is a Senior Global Academic Program Manager at SAS, 100 SAS Campus Drive, Cary, NC 27513, USA;.</p> <p>Adam Kirn is an Associate Professor at the University of Nevada, Reno, 1664 North Virginia Street, Reno, NV 89557, USA;.</p> </aug> <nolink nlid="nl1" bibid="bib19" firstref="ref1"></nolink> <nolink nlid="nl2" bibid="bib52" firstref="ref2"></nolink> <nolink nlid="nl3" bibid="bib68" firstref="ref3"></nolink> <nolink nlid="nl4" bibid="bib36" firstref="ref5"></nolink> <nolink nlid="nl5" bibid="bib53" firstref="ref6"></nolink> <nolink nlid="nl6" bibid="bib67" firstref="ref7"></nolink> <nolink nlid="nl7" bibid="bib73" firstref="ref8"></nolink> <nolink nlid="nl8" bibid="bib38" firstref="ref10"></nolink> <nolink nlid="nl9" bibid="bib22" firstref="ref13"></nolink> <nolink nlid="nl10" bibid="bib37" 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Items – Name: Title
  Label: Title
  Group: Ti
  Data: Engineer Identity and Degree Completion Intentions in Doctoral Study
– Name: Language
  Label: Language
  Group: Lang
  Data: English
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Bahnson%2C+Matthew%22">Bahnson, Matthew</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-0134-0125">0000-0002-0134-0125</externalLink>)<br /><searchLink fieldCode="AR" term="%22Satterfield%2C+Derrick%22">Satterfield, Derrick</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-4197-0551">0000-0002-4197-0551</externalLink>)<br /><searchLink fieldCode="AR" term="%22Perkins%2C+Heather%22">Perkins, Heather</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-8757-0545">0000-0002-8757-0545</externalLink>)<br /><searchLink fieldCode="AR" term="%22Parker%2C+Mackenzie%22">Parker, Mackenzie</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-5891-3908">0000-0002-5891-3908</externalLink>)<br /><searchLink fieldCode="AR" term="%22Tsugawa%2C+Marissa%22">Tsugawa, Marissa</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0001-6009-8810">0000-0001-6009-8810</externalLink>)<br /><searchLink fieldCode="AR" term="%22Cass%2C+Cheryl%22">Cass, Cheryl</searchLink><br /><searchLink fieldCode="AR" term="%22Kirn%2C+Adam%22">Kirn, Adam</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0001-6344-5072">0000-0001-6344-5072</externalLink>)
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="SO" term="%22Journal+of+Engineering+Education%22"><i>Journal of Engineering Education</i></searchLink>. Apr 2023 112(2):445-461.
– Name: Avail
  Label: Availability
  Group: Avail
  Data: Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
– Name: PeerReviewed
  Label: Peer Reviewed
  Group: SrcInfo
  Data: Y
– Name: Pages
  Label: Page Count
  Group: Src
  Data: 17
– Name: DatePubCY
  Label: Publication Date
  Group: Date
  Data: 2023
– Name: SourceSuprt
  Label: Sponsoring Agency
  Group: SrcSuprt
  Data: National Science Foundation (NSF)
– Name: NumberContract
  Label: Contract Number
  Group: NumCntrct
  Data: EEC1763288<br />EHR1535254<br />EHR1535453
– Name: TypeDocument
  Label: Document Type
  Group: TypDoc
  Data: Journal Articles<br />Reports - Research
– Name: Audience
  Label: Education Level
  Group: Audnce
  Data: <searchLink fieldCode="EL" term="%22Higher+Education%22">Higher Education</searchLink><br /><searchLink fieldCode="EL" term="%22Postsecondary+Education%22">Postsecondary Education</searchLink>
– Name: Subject
  Label: Descriptors
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Engineering+Education%22">Engineering Education</searchLink><br /><searchLink fieldCode="DE" term="%22Technical+Occupations%22">Technical Occupations</searchLink><br /><searchLink fieldCode="DE" term="%22Self+Concept%22">Self Concept</searchLink><br /><searchLink fieldCode="DE" term="%22Academic+Persistence%22">Academic Persistence</searchLink><br /><searchLink fieldCode="DE" term="%22Intention%22">Intention</searchLink><br /><searchLink fieldCode="DE" term="%22Doctoral+Students%22">Doctoral Students</searchLink><br /><searchLink fieldCode="DE" term="%22Student+Experience%22">Student Experience</searchLink><br /><searchLink fieldCode="DE" term="%22Student+Characteristics%22">Student Characteristics</searchLink><br /><searchLink fieldCode="DE" term="%22Teacher+Student+Relationship%22">Teacher Student Relationship</searchLink><br /><searchLink fieldCode="DE" term="%22Peer+Relationship%22">Peer Relationship</searchLink>
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.1002/jee.20516
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 1069-4730<br />2168-9830
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Background: Degree completion rates for doctoral engineering students remain stagnant at levels lower than necessary to meet national and global workforce needs. Increasing degree completion can improve opportunities for individuals and provide the human resources needed to address engineering challenges. Purpose/Hypothesis: In this work, we measure the association of engineering identity variables with degree completion intentions for students who have persisted in doctoral study. We add to existing literature that suggests the importance of advisor and peer relationships, and the number of years in the doctoral program. Design/Method: We use data collected via a national cross-sectional survey of doctoral engineering students, which included measures of social and professional identities, graduate school experiences, and demographics. Surveys were collected from 1754 participants at 98 US universities between late 2017 and early 2018. The analyses reported here use multiple regression to measure associations with engineering doctoral degree completion intentions. Results: Research interest and scientist performance/competence are individually associated with degree completion intentions in students who are persisting in doctoral study. Overall, graduate engineering identity explains significant portions of variation in degree completion intentions (9.5%) beyond advisor and peer relationship variables and the number of years in graduate programs. Conclusions: Researcher interest and scientist performance/competence may be key opportunities to engage doctoral student engineering identity to improve degree completion rates. Accordingly, institutions can foster students' interest in research and build their confidence in their scientific competence to support students as they complete the doctoral degree.
– Name: AbstractInfo
  Label: Abstractor
  Group: Ab
  Data: As Provided
– Name: DateEntry
  Label: Entry Date
  Group: Date
  Data: 2023
– Name: AN
  Label: Accession Number
  Group: ID
  Data: EJ1373726
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1373726
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1002/jee.20516
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 17
        StartPage: 445
    Subjects:
      – SubjectFull: Engineering Education
        Type: general
      – SubjectFull: Technical Occupations
        Type: general
      – SubjectFull: Self Concept
        Type: general
      – SubjectFull: Academic Persistence
        Type: general
      – SubjectFull: Intention
        Type: general
      – SubjectFull: Doctoral Students
        Type: general
      – SubjectFull: Student Experience
        Type: general
      – SubjectFull: Student Characteristics
        Type: general
      – SubjectFull: Teacher Student Relationship
        Type: general
      – SubjectFull: Peer Relationship
        Type: general
    Titles:
      – TitleFull: Engineer Identity and Degree Completion Intentions in Doctoral Study
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            NameFull: Satterfield, Derrick
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              Type: published
              Y: 2023
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              Value: 1069-4730
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