As mentioned in the previous section, Fong et al. (2019) finds that the pedagogy course showed greater benefit to TAs, though the pedagogy course and the teaching mid-semester feedback both showed greater increases in reflective teaching efficacy and belief that teaching influences learning (Fong et al., 2019; Pollard, 2021). Torre Ayala (2013) describes five categories of conceptions of teaching engineering: delivering knowledge, helping understand and apply concepts, motivating students, helping students learn how to approach problems, and preparing to make students socially conscious. The study identifies four categories of experiences which shaped future engineering professors’ conception of teaching engineering: observing professors, their own student experience, talking about teaching, and their own teaching experience. This contrasts with the simple, traditional saying of “teaching as they were taught”, as identified and countered by Oleson and Hora (2014) and Pollard (2021). This observation aligns with work in the ASEE community emphasizing that teaching identity develops through reflective practice and instructional experiences rather than passive replication of prior instruction (Huang et al., 2005; Turns et al., 2014; Wankat and Oreovicz, 2015). However, the study does not cover how prior teaching context influences the conceptions of learning held by future engineering professors, nor does it cover the changes in the engineering education environment after publication, such as the surge of adoption of distance learning (Torre Ayala, 2013). Experiences as TAs and as instructors give doctoral students the opportunity to test and adjust their teaching philosophies in practical settings, solidifying the aspects of their teaching philosophies which work and shifting those which do not (Pollard, 2021).

Torre Ayala (2013) identifies that future engineering professors show an interest in teaching students to consider the social impact of engineering, while lacking the requisite preparation to teach this. This feeling of lacking preparation is reflected in de Lima et al. (2024), which describe how engineering doctoral teaching assistants can make learning spaces more equitable and accessible for students. The doctoral teaching assistants expressed a need for additional training in regard to encountering discrimination in the classroom, as they generally rated the importance of inclusivity in engineering education above their capability to influence inclusivity (de Lima et al., 2024).

Watson and Strong (2013) examined the different educational philosophies held by graduate students at the Georgia Institute of Technology, finding that while progressivism, or the practice of integrating real-world experiences with classroom study, was endorsed by the Educational Philosophy Inventory, the philosophies which they experienced as students were more often reflected in their current and future teaching practices (Watson and Strong, 2013). As a result, Watson and Strong (2013) suggest that interventions should be considered to teach graduate students about various teaching philosophies and their classroom implications. In addition, they found a discrepancy in the teaching philosophies which were reported as being in use by graduate students and the teaching practice which were planned to be used in future teaching practices, which Pollard (2021) suggests that these discrepancies are due to factors such as time constraints and the decreased priority of teaching-related tasks compared to research-related tasks.

Through the mentorship experiences granted by an engineering PhD program, students are able to connect with faculty both academically and personally (Ambler et al., 2016). A mentor can help minimize the difficulties and barriers a student may face through the research process, as well as develop personal connections which can evolve into friendships (Mirabelli et al., 2020; Ambler et al., 2016). However, formal mentoring relationships regarding teaching are not part of engineering doctoral curriculums (Stice et al., 2000, as cited in Buswell, 2020). Additionally, in being a mentor, academics have greater opportunities to self-reflect and encounter new ways of thinking through interactions with mentees, though research relating to the effects of being a mentor is sparce (Ambler et al., 2016).

The experiences of being a mentor and being a mentee provide engineering PhD students with the space to reflect on their conceptions of teaching. While parts of the teaching philosophies developed by engineering PhD students are formed through their experiences as students, additional training and professional development programs can help shape their philosophies, though these resources may not always be readily accessible. Additionally, these teaching philosophies may not be necessarily congruent with their teaching in practice due to factors such as time constraints and the general decreased priority of teaching-related tasks compared to research related tasks. More details regarding the perceived importance of teaching are found in the next section.

Research regarding the importance of teaching in academia typically describes this through the perspective of balancing teaching and research activities (Robert and Carlsen, 2017). While professors often personally value teaching as highly as research, they usually direct their and their departments’ priorities towards research (Savkar and Lokere, 2010). However, Cadez et al. (2015) found that research productivity is not related to teaching quality, and that high quality research is positively related to teaching quality. However, the research orientation of a school as a whole is negatively related to teaching quality (Cadez et al., 2015).

Miskioglu et al. (2020) finds that the number of classes taught per mechanical engineering faculty member, both tenure-track and tenured, at R1 institutions is between 1–4 classes per year, much lower than those at more teaching-focused institutions. The tenure-track faculty also generally indicated that they felt that teaching load had a lower likelihood to affect. Additionally, faculty at R1 institutions indicated that they were typically expected to have more than 10 journal publications by the time they applied for tenure, whereas faculty at non-R1 institutions state that they were expected to have fewer than 10 journal publications. Similarly, Lane et al. (2019) describes how doctoral students perceived a stigma which discouraged exploring teaching experiences. The discrepancy in value between research and non-research work leads to the perception that a large investment of time in non-research work would lead to falling short of promotion standards for faculty (Terosky et al., 2014). Similar concerns have been raised in ASEE scholarship highlighting how doctoral students often receive limited structured preparation for teaching despite future faculty expectations (Felder and Brent, 2024; Kajfez and Matusovich, 2020).

The different perceptions graduate TAs hold regarding the importance of teaching in their careers can impact their approaches to interactions with students, as suggested by Kajfez and Matusovich (2020). Graduate TAs who strongly identify with teaching have more applicable experience with instruction, while those who weakly identify with teaching have more ability to connect course material with industry experiences and develop coursework to more closely align with real-world experiences (Kajfez and Matusovich, 2020). These experiences as TAs work as peripheral participation in teaching, shaping the experiences and trajectories of engineering PhD students through the more critical observation of teaching and studying enabled through the role (Pollard, 2021).

While individual work outcomes do not typically have detrimental effects on teaching quality, the ways departments work within a university do affect teaching quality, such as requiring more journal publications to achieve tenure. This leads to a greater time investment in research which may detract from maximizing the effectiveness of teaching, both outside of the classroom as well as within it. The next section will discuss the expectations of PhD students for the in-class experience.

Kumar (2021) details the perspective of graduate teaching assistants regarding engineering education in distance teaching courses. Given the relative novelty of the distance teaching model in comparison to the more traditional, in-person formats, student feedback and communication were imperative to ensure the efficacy of the instructional process. Kumar (2021) identifies a variety of challenges of graduate teaching assistants prior to beginning to teach online: technology issues, communication gaps between TA and students/TA and instructor, anxieties related to teaching online for the first time or lack of expertise in assigned area, and lack of clarity relating to TA expectations and duties. Some of these concerns align with the concerns of graduate TAs in in-person classrooms, while others are unique to the format of online teaching. The experiences of being a graduate teaching assistant are known to affect the self-efficacy of graduate students regarding teaching, however the effects of being a graduate teaching assistant in an online classroom on future teaching is less known (Kumar, 2021; Torre Ayala, 2013).

Di Benedetti et al. (2022) found that there was a disconnect between the roles and personal identities of TAs serving as teachers. TAs did not feel empowered to make decisions and influence their students how the TAs feel fit but instead fell back on the opinions of the instructor leading the class, seeking approval over autonomy even when unnecessary (Di Benedetti et al., 2022). While TA orientation programs can develop confidence and self-efficacy, the specific content and focus of these programs impact the outcomes in the TAs (Rosse-Richards et al., 2013; Dawe et al., 2017; Wright et al., 2019). Engineering education research has similarly documented how reflective teaching experiences and structured preparation influence TA identity and instructional confidence (Huang et al., 2005; Borrego et al., 2010; Turns et al., 2014).

Once entering teaching roles, new faculty describe feeling unprepared to adequately serve their teaching roles, though the availability and quality of teaching training can vary in every university (Buswell, 2020). Buswell (2020) recommends a greater investment of resources in R1 institutions towards existing infrastructure supporting teaching and preparation to teach and suggests that additional teaching opportunities and mentorship may be suitable to better position graduate students in the job market. Similarly, Bonner et al. (2020) recommends intensive and required doctoral teaching seminars to sufficiently teach course design, as students who discount the importance of teaching or believe they have the necessary teaching skills without prior experience may opt out of such a course. In contrast, Lam et al. (2024) finds that participants in the Future Faculty Teaching Fellowship, a Preparing Future Faculty program, rated teaching at their home institution to be generally more helpful compared to pedagogy coursework, suggesting that increased teaching opportunities may be more helpful for graduate students.

Hassel and Ridout (2018) describes the expectations instructors have of students, where instructors expected their students to positively engage with the lecture and regularly attend the course. Additionally, students tended to agree with these expectations, of positive engagement and regular attendance. The importance of this positive engagement is reflected by Freeman et al. (2014), which finds that active learning increases examination performance in STEM courses and shows a significantly lower failure rate than lecturing. This emphasis on active engagement is well established in engineering education literature, particularly within ASEE and IEEE communities examining active learning and challenge-based instruction (Prince, 2004; Roselli and Brophy, 2006). However, Fraser and Killen (2003) find that instructors expected their students to be more independent and self-driven while still attending lectures, while students disagreed by generally undervaluing the importance of lecture attendance.

TAs can feel a lack of empowerment to make their own decisions regarding a classroom situation, and there are a variety of forms an engineering course can take, and these forms have shared and unique complications, such as the differing social dynamics within in-person and online teaching. In addition, the expectations of instructors and their relationship with student expectations are important regarding effective learning. These factors suggest that a better understanding of the perspective of engineering doctoral students regarding teaching before they transition into faculty roles may be necessary to provide guidance to provide better experiences to students. To achieve this understanding, a qualitative analysis of semi-structured interviews was chosen for data collection in this study.

This study is guided by a conceptual framework that integrates perspectives on teaching and mentoring identity formation, social learning through communities of practice, and self-efficacy development. Together, these perspectives provide a lens for understanding how engineering doctoral students construct expectations about teaching and mentoring during their doctoral training.

Teaching and mentoring identity formation literature emphasizes that instructional identities develop over time through reflection, practice, and interaction with institutional norms rather than through simple replication of prior experiences. From a communities of practice perspective, doctoral students engage in peripheral participation in teaching and mentoring through roles such as teaching assistants, informal mentors, and observers of faculty practice, gradually negotiating their identities as future educators. Additionally, self-efficacy theory highlights how mastery experiences, vicarious learning, and social persuasion contribute to doctoral students’ confidence in teaching and mentoring roles.

While these perspectives inform interpretation, the study remains inductive in design, allowing themes to emerge from participants’ narratives rather than applying a predetermined analytical framework.

Potential participants were identified and reached out to through email found on student directories. An initial screening survey was designed and administered to potential participants to collect data on career preferences, teaching experiences as a TA or as an instructor, racial/ethnic background, and engineering department. Only responses from doctoral students who intended to continue a career in academia completing their program were invited to participate in the interview. Semi-structured interviews were conducted to collect data, utilizing improvised questions to probe additional information from pre-planned questions. This format enhanced the data collection process through this flexibility (Creswell and Poth, 2016; Ruslin et al., 2022; Kittur and Tuti, 2024). The planned duration for each interview was between 45 and 60 min. This duration was decided to minimize fatigue for the participants while allowing time for participants to reflect on their experiences (Ruslin et al., 2022; Galletta and Cross, 2013).

Doctoral students from more than 20 U.S.-based R1 institutions were contacted through publicly available departmental directories. Twenty-three students completed an initial screening survey, all of whom met the inclusion criterion of intending to pursue academic faculty careers. Fourteen students agreed to participate in interviews; however, data collection was concluded after ten interviews due to the achievement of thematic saturation, as no new codes or themes were emerging in later interviews. Participants were drawn from multiple institutions and engineering disciplines, and none had prior relationships with the researchers.

Interviews were conducted through Audio-only Zoom calls to record interviews with the participants. The audio recordings were digitally transcribed automatically, allowing for the focus of the interview to shift to easing the conversation’s flow, asking follow-up questions, and improving rapport with the participant, key elements in completing an effective semi-structured interview (Mannan and Afni, 2020). An interview guide was designed with a series of open-ended questions and closed-ended questions, with a significant portion of time dedicated to asking additional follow-up questions to have a more comprehensive record of the participants’ perspectives and experiences. Ten interviews were conducted, which were recorded with the consent of each participant. An incentive of $20 Amazon gift cards was offered to each participant.

To improve readability of interview excerpts, minor grammatical corrections were made using generative AI. These edits were limited to removing verbal disfluencies (e.g., repeated words, filler phrases, incomplete sentences) and correcting basic grammar. No paraphrasing, rewording, or alteration of meaning was performed. All edited excerpts were manually verified against the original transcripts by the authors to ensure fidelity to participants’ intended expressions. Please refer to Appendix A for examples of raw vs. edited interview excerpts.

To ensure that patterns and themes could emerge directly from participants’ responses, an inductive coding approach was utilized to analyze the transcripts (Neuendorf, 2018). The interviews were coded through NVivo, eliminating redundant codes through iterative review. Initial coding began with open, descriptive codes closely aligned with participants’ language. Through iterative rounds of coding and constant comparison across transcripts, these initial codes were refined, merged, or subdivided into more analytically meaningful categories. Broad codes such as Teaching Philosophy and Mentoring Philosophy were subsequently differentiated into sub-codes capturing specific dimensions (e.g., approachability, motivation, autonomy, boundaries). This iterative process continued until a stable codebook was established and no new codes emerged. A comprehensive codebook was developed, detailing each code and its description. This codebook was subsequently used to analyze the remaining transcripts, with new codes being added and existing codes being refined as more transcripts were analyzed. The codes were then categorized into themes to answer the research question. Although data analysis was inductive, interpretation of the findings was informed by existing theoretical perspectives on identity formation, social learning, and self-efficacy to contextualize participants’ experiences within the broader engineering education literature.

The ways that the participants think about teaching and mentoring did not exist in a vacuum but rather were shaped by their past formal and informal experiences as students, mentees, teachers, and mentors. These philosophies were not singular, monolithic ideals, but rather ideas that shifted and formed with different experiences.

To understand how the different experiences of the participants led to differing expectations in teaching expectations, it is important to identify and understand how they may value teaching differently based on those experiences.

To understand how the students’ expected in-class experiences as instructors have been shaped, it is important to understand what their current experiences are and how they relate to their expectations. The experiences that PhD programs offer to their students are broad, varying from the practical shaping from TA and RA positions to the more social shaping from mentor-mentee relationships.

Most participants mentioned that they initially generated their notions of what was important teaching through their experiences as a student, while they clarified and adapted their teaching philosophy through their teaching experiences in their PhD program. This experience is reflected in Korpan (2019), which mentions that TAs begin their work with “strong conceptions and dispositions relating to teaching,” where they need support to learn how to reflect on their teaching and improving holistically (Korpan, 2019). More specifically, the interactions between the participants and their advisors in their PhD program had great influence on their teaching philosophies. This reflects Mena et al.’s (2013) work, in which they found that TAs who were tasked with being class instructors would feel comfortable informally approaching faculty members they were familiar with to seek advice on the day-to-day teaching experience and on how to approach specific situations. Though this comfort may be a typical experience and not a universal experience, as discussed by Buswell (2020), where most engineering PhD students with an interest in teaching were encouraged to pursue a teaching-focused career while some felt they were not given this support and others felt resistance from their advisors.

In our study, Bri (Material Science, 2 years into PhD program) discussed these effects through her experiences as a mentor to her religious group, where being a mentor encompassed a broad area of guidance, not just including the intended religious purpose, but also academic and personal guidance as well. These groups were effectively a counterspace, helping Bri build mentoring relationships and develop her mentoring philosophy outside of her academic groups (Artiles et al., 2025). In Ambler et al. (2016), the academic and social benefits of mentoring are discussed, where the intertwining of personal and professional discussions gave way to self-reflection and new ways of thinking for not just the mentee, but the mentor as well. Similarly, Sherwood et al. (2018) finds that serving as peer mentors can lead to personal and social benefits, such as the development of agency and communication skills. These benefits go on to help the transition into leadership roles (Sherwood et al., 2018).

Taken together, these findings extend existing work on teaching identity by showing that doctoral students do not simply “inherit” teaching philosophies from prior experiences. Instead, they actively construct instructional and mentoring philosophies through a combination of observation, limited instructional roles, informal mentoring, and reflection during their doctoral training. This highlights doctoral education itself as an early and influential stage of faculty identity development, rather than viewing identity formation as something that primarily occurs after entering academic positions.

Participants mentioned concerns regarding the balance of effort between teaching and research, where time spent teaching may be rewarded more if it were reallocated towards research. Wankat et al. (2023) reflect this reasoning shown by the participants, stating that teaching and learning are much less rewarded than disciplinary research. While the imbalance of importance between teaching and research has been improving over time, the rewards structures in colleges of engineering generally still show preference towards research ability over teaching ability (Wankat et al., 2023). While efforts are being made to encourage teaching through greater consideration in tenure processes, these efforts have not been universally successful in “offsetting oversimplified approaches such as points schemes based on journal impact factors” (Schimanski and Alperin, 2018). Similarly, Robert and Carlsen (2017) discuss how STEM professors felt that they were not adequately prepared for anything aside from research and suggest that the support offered to future faculty regarding pedagogy training should be considered separately from the type of support offered to current faculty, exposing them to more research-based teaching strategies. This is due to the idea that early experiences as doctoral students can exert a greater influence on professors.

While there is a common perception of teaching-research trade-offs in academia, Shortlidge and Eddy (2018) find that PhD students investing in evidence-based learning is slightly positively related to research quality without a decrease in research productivity. In other words, teaching quality does not inherently compromise research quality or productivity but instead teaching and research can be synergistic (Shortlidge and Eddy, 2018). Despite this, the academic lifestyle can bring about work-life imbalance and interfere with daily life (Bowering and Reed, 2021). However, this is not to say that it is impossible to find sustainable lifestyles in academia, as there are ways to manage lifestyles in academia to find work-life balance and mental/physical wellness (Owens et al., 2018). These concerns illustrate how participants are already internalizing institutional reward structures and projecting them onto their future academic roles, shaping how they anticipate balancing teaching and research long before becoming faculty.

In regard to the expectations of female engineering PhD students, Amy (Aerospace Engineering, 2 years into PhD program) describes how she would like to be able, as a future faculty member, to mentor young women in aerospace engineering, citing her experiences feeling underrepresented in her undergraduate studies.

Amy identifies this mentorship as being an important responsibility to her future students as a result of this lack of representation in undergraduate degrees. Similarly, Judson et al. (2019) mention that higher female faculty also on average advise more students than male faculty, and Kamerlin and Wittung-Stafshede (2020) discuss how, as one progresses through engineering higher education, the relative proportion of men increases, reinforcing Amy’s experiences and compounding the amount of work she may end up doing as a faculty member. However, in terms of work-life balance, Toffoletti and Starr (2016) state that female academicians often emphasize family commitments, regardless of parental status, in their descriptions of work-life balance. This specific detail was not mentioned by any of the female participants, though this may be due to a limited sample size or phrasing of questions.

These findings contribute to conversations on doctoral socialization by showing that perceptions of teaching-research trade-offs are not formed during faculty careers but are already embedded during doctoral training through observation of advisors, peers, and institutional norms. Doctoral students are not only learning how to conduct research, but also absorbing implicit messages about how teaching is valued in academia.

Participants’ expectations for classroom teaching were strongly shaped by the extent of their instructional exposure, revealing how even limited instructor-of-record experiences significantly recalibrate perceptions of teaching challenges and responsibilities. Those with experiences as primary instructors described the differences between their expected difficulties before and after their experiences.

As Tony (3 years of instructor experience) and Austin (no instructor experience) illustrate, participants without experience as primary instructors typically are more concerned with their potential new role as an instructor and the social responsibilities that come with that role, whereas those with more experience are less concerned with the management of the social standards and more concerned with ensuring that students are able to effectively learn.

One of the concerns expressed by the participants regarded managing student motivation. Liu et al. (2012) emphasizes the importance of student motivation, illustrating how increased motivation results in a significant increase in academic performance. When students feel their assessments are unimportant, they do not try their best to maximize their results (Liu et al., 2012). However, instructors are able to entice student motivation through the promotion of student engagement and providing an environment for mutual support between students (Tinto, 2025). Interactions between students and faculty as well as the pedagogical techniques employed by faculty can increase motivation (Tinto, 2025). Positive expectations for students by faculty can affect the expectations held by students, which in turn affects student motivation (Tinto, 2025). Regarding the development of teaching skill and confidence, the participants identified both taking classes on pedagogy and having the experience of teaching classes as being keys to this development. This is reflective of how self-efficacy can develop as described by Bandura (1997), which finds that the vicarious experiences, physiological feelings, social persuasion, and mastery experiences affect one’s self-efficacy. Wendt et al. (2015) specifically discusses how engineering students without teaching design experience develop self-efficacy in teaching engineering design through the vicarious experiences of watching a more experienced teacher execute a similar activity as well as practicing implementing their own lessons in a controlled environment helped develop self-efficacy.

This finding extends prior literature on TA preparation and teaching confidence by demonstrating that expectations for teaching are not merely skill-based but perception-based. Instructor experience reshaped how participants understood student heterogeneity, workload, and instructional responsibility, suggesting that experiential exposure plays a critical role in aligning expectations with the realities of academic teaching.

Although this study did not explicitly compare teaching expectations across institutional types or student populations, participants’ expectations were nonetheless shaped by contextual factors embedded in their teaching and mentoring experiences. Expectations related to workload, student engagement, and instructional responsibility varied based on exposure to large versus small classes, laboratory versus lecture-based instruction, and online versus in-person teaching formats. Participants who had experience leading large classes or serving as primary instructors described heightened concerns regarding time management, student heterogeneity, and maintaining instructional quality, whereas those with limited teaching responsibility expressed fewer contextual concerns.

Additionally, while student body demographics were not directly addressed by participants, several expressed a growing sense of social responsibility and mentorship, particularly related to supporting underrepresented or marginalized students. These findings suggest that doctoral students’ teaching expectations are shaped not only by pedagogical experiences but also by perceived social and institutional responsibilities. Future research should explicitly examine how teaching expectations differ across institutional contexts (e.g., R1, teaching-focused, community colleges), student demographics (e.g., nontraditional, transfer, first-generation students), and instructional settings (e.g., large lectures, laboratories, hybrid environments).

To clarify the theoretical grounding of the findings, Table 4 maps the major emergent themes to the guiding theoretical perspectives informing this study. Although data analysis was inductive, teaching and mentoring identity formation, communities of practice, and self-efficacy theory served as sensitizing lenses during interpretation. This mapping illustrates how participants’ narratives align with established theoretical constructs while preserving the data-driven nature of the analysis.

The theoretical contribution of this study lies in its integration of identity formation, communities of practice, and self-efficacy perspectives to explain how engineering doctoral students develop expectations for teaching and mentoring prior to entering faculty roles. By empirically demonstrating that these expectations emerge through multiple formal and informal experiences rather than through replication of prior instruction alone, this study extends existing theoretical work by highlighting the early and often under examined phase of faculty identity development during doctoral training.

Notably, one participant explicitly connected her desire to mentor students to her experiences as a woman in an underrepresented engineering field, highlighting how identity and representation can influence perceptions of teaching and mentoring responsibility. Although this study did not aim to compare perspectives across demographic groups, participants’ narratives suggest that personal background and lived experiences may shape how doctoral students conceptualize teaching and mentoring. For example, some participants discussed mentorship in relation to representation and supporting underrepresented students, while others reflected on how their years of teaching experience influenced their confidence and expectations for classroom management. These observations indicate that factors such as gender, prior teaching exposure, and stage within the doctoral program may influence how teaching and mentoring philosophies are formed. Future research could more intentionally examine how demographic characteristics intersect with doctoral training experiences to shape expectations of academic teaching roles.

Overall, this study contributes to engineering education literature by positioning doctoral training as an overlooked but critical phase in the formation of future faculty teaching and mentoring expectations. Rather than focusing on formal TA training or early faculty development, this work demonstrates how informal experiences, observation of faculty, and limited instructional roles during doctoral study collectively shape how future instructors conceptualize their academic responsibilities.

A limitation of this study is that it does not explicitly disaggregate teaching expectations by institutional type, student demographics, or instructional format; instead, it captures expectations as they emerge from doctoral students’ localized experiences within their programs. Another limitation of this study is its focus on engineering doctoral training within the United States, primarily at R1 research-intensive institutions. Doctoral training models, expectations for teaching, and faculty responsibilities differ substantially across international contexts and institutional types, such as teaching-focused universities or community colleges. While this study does not attempt to compare these contexts, explicitly situating the findings within the U.S. R1 system is important for appropriate interpretation. Future research should examine how teaching and mentoring philosophy development differs across national contexts and institutional missions.

This study is exploratory and context-specific, drawing on in-depth interviews with a small group of engineering doctoral students situated within U.S. R1 institutions. While the sample size supports rich, detailed analysis, the findings are not intended to be generalized across all doctoral training contexts. Instead, the study offers nuanced insights that may resonate with readers in similar institutional environments and provides a foundation for future research examining teaching and mentoring expectations across broader and more diverse contexts.