INTRODUCTION

Estimates state that the United States will need an additional one million science, technology, engineering, and mathematics (STEM) professionals over the next decade to maintain relevance in these fields (President’s Council of Advisors on Science and Technology [PCAST], 2012). An annual increase in the number of students who graduate with a STEM degree will be required to meet such demands. Of all students who enter a STEM degree program, less than 40% finish their degrees (PCAST, 2012); therefore, reducing attrition rates and retaining more students in STEM will be essential for reaching the projected number of STEM professionals needed.

Although often overlooked, community colleges are a critical component of undergraduate STEM education in the United States, and thus are key in mitigating the predicted shortage of STEM workers. Community colleges train a large portion of the current STEM workforce, as 44% of those who earn a STEM degree report attending a community college at some point (Hagedorn and Purnamasari, 2012). Community colleges have been recognized for their role in advancing students toward degree completion (Cohen and Brawer, 1989; Smith and Vellani, 1999; Hagedorn and Purnamasari, 2012; Ma and Baum, 2016), and as recently as the Fall of 2019, 34% of all undergraduate students in the United States were enrolled in community colleges (National Center for Education Statistics, 2019).

Community colleges increase access to education by offering convenient and cost-effective options for students, open admission, and many courses (Kasper 2003; Boggs, 2011). They enroll the most diverse student body in higher education in terms of demographic dimensions (Boggs, 2011), and they enroll a large proportion of minority, first-generation, low-income, and non-traditional age (23+ years) students (Ma and Baum, 2016). According to the American Association of Community Colleges, 28% of community college students are Hispanic, 13% are Black, 6% are Asian (AACC, 2021), 60% are women, 29% are first-generation college students, 56% receive financial aid, and the average student age is 27, (AACC, n.d.). Thus, community colleges will play a key role in the push to not only increase but also diversify the future STEM workforce (Briggs, 2017; Benish, 2018).

Community colleges increase access to higher education, with millions of students attending them for at least some portion of their higher education (Boggs, 2011). There are well-intended national calls to make the STEM transfer pathway more robust (National Research Council, 2012), yet the experiences of community college students remain surprisingly understudied (Schinske et al., 2017)—particularly lacking is investigation into the transfer process itself. Some researchers state that students can face what is known as “transfer shock” as they transfer from 2- to 4-year universities (Cejda, 1997). Transfer shock refers to declines in academic success, such as a drop in grade point average upon transfer (Rhine et al., 2000), and/or social factors, such as lacking a sense of belonging at the university (Strayhorn, 2018). These experiences can lead to a misalignment between student intentions and outcomes and present barriers to persistence. While 80% of students attending a community college intend to earn a bachelor’s degree, only 14% of students who start at a community college and transfer to a 4-year university earn a bachelor’s degree within 6 years (Jenkins and Fink, 2016). Thus, we need to focus on understanding factors that both inhibit and promote transfer student completion of a bachelor’s degree.

Transferring midway through an academic journey can compound the many barriers that students already face when pursing a degree in STEM (Packard et al., 2012), such as departmental and classroom culture, time to degree, and cost (National Academies of Sciences, Engineering, and Medicine, 2016). Barriers that impact community college transfer students during their transition can include a lack of information, poor advising, and varying degrees of preparedness (Hagedorn et al., 2008). The community college environment can differ dramatically from a 4-year college environment when students transfer to more selective and/or large universities with bigger class sizes (Rhine et al., 2000; Umbach et al., 2019). Researchers looking at community college transfer students’ academic adjustment found that students who reported positive course learning experiences at the university are more likely to adjust, whereas those with a perceived negative stigma around being a transfer student are less likely to adjust (Laanan et al., 2010). A study examining STEM transfer students found that social factors such as gender and student connections with faculty play an important role in the academic adjustment of transfer students, as do academic factors such as having a large number of transfer credit hours (Jackson and Laanan, 2015). Another study examining STEM transfer student experiences found that parent’s education level, interactions with faculty, and perception of the university influenced students’ academic adjustment (Lopez and Jones, 2017). There are clearly many factors that will impact how a transfer student adapts to the university posttransfer. Given that STEM fields are historically exclusionary, it is critical to understand key supports for STEM transfer students, particularly those who come from marginalized, low socioeconomic, and/or groups otherwise underrepresented in science (Carter et al., 2019; Berhe et al., 2022).

Our work here centers on qualitatively understanding the various ways in which STEM transfer students navigated their transition to one 4-year, public research institution. Through focus groups, STEM students shared their experiences transferring to our university, allowing us to identify the academic and social factors that tended to positively and negatively impact their adaptations to the transition. The purpose of this work is to summarize the various obstacles and supports that STEM transfer students report grappling with in their transition from community college to a 4-year institution and ultimately encourage institutions to apply lessons learned to their transfer support structures and programs.

THEORETICAL FRAMEWORK

A Model for Analyzing Human Adaptation to Transition

To understand student adaptation to transfer, we used a model designed to understand how humans adapt to transitions (Schlossberg, 1981). The model—a model for analyzing human adaptation to transition, which we will refer to as “MAAT” (Figure 1)—aims to provide a tool for understanding differences in experiences among individuals going through a particular transition and has been used to examine various life transitions, such as career transitions for nurses (Wall et al., 2018) and the transitions faced by athletes after concluding their athletic careers (Wylleman et al., 2004). The MAAT proposes that the perception of the transition, characteristics of the pretransition and posttransition environment, and characteristics of the individual will influence if and how one moves from transition to adaptation.

Transition

The MAAT defines “transition” as “an event or non-event resulting in a change in assumptions about oneself and the world, thus requiring a corresponding change in one’s behavior and relationships” (Schlossberg, 1981, p. 5). A non-event is described as the loss of an event that was expected to occur. Within this model, three major factors influence the individual’s adaptation to a transition: the perception of the transition, the characteristics of the pre- and posttransition environments, and the characteristics of the individual experiencing the transition (Schlossberg, 1981). The transition that we examined is the transition from a community college to a 4-year university.

Perception of the Transition

According to the MAAT, most transitions can be understood through a common set of variables: affect, timing, and degree of stress (Schlossberg, 1981). Any change or transition, regardless of characteristics, involves some degree of stress, even if primarily positive or negative in affect. One might consider oneself “on-timing” or “off-timing” for the transition based on what is perceived to be the correct timing within a society for a major life event (Neugarten, 1976).

Characteristics of the Pretransition and Posttransition Environments

Environment within the MAAT is described broadly and includes interpersonal support systems, institutional supports, and physical settings (Schlossberg, 1981). Interpersonal support systems are thought to be important for successful adaptation. Institutional supports describe any place that an individual can turn to for help throughout the transition. The factors of the physical setting involved in the transition can contribute to the stress or general well-being experienced by the individual, which may play a role in the individual’s ability to adapt to the particular transition.

Characteristics of the Individual

The characteristics of the individual going through the transition will impact the individual’s ability to adapt to that particular transition (Schlossberg, 1981). Some important characteristics to consider include the life stage of the individual, social identities, being a member of an underrepresented group, and previous experiences with similar transitions. For undergraduate STEM students, additional characteristics may be important to consider, such as their self-efficacy, sense of belonging, and science identity (Estrada et al., 2011; Strayhorn, 2018).

Adaptation

The MAAT describes “adaptation” as “a process during which an individual moves from being totally preoccupied with the transition to integrating the transition into his or her life” (Schlossberg, 1981, p. 7). Understanding the experiences of community college transfer students during their transition and what impacts their ability to adapt may lead to new ways to support and retain these students.

METHODS

Recruitment

This study was conducted at a large public northwestern urban commuter university. Our university is classified by the Carnegie Classification of Institutions of Higher Education as high research activity with a 4-year, medium full-time, selective, high transfer-in undergraduate profile (Carnegie Classification of Institutions of Higher Education, n.d.). In the Spring of 2019, a survey was sent to all declared STEM majors as part of a larger research study. The survey collected demographic data and was designed to measure student integration into science, STEM involvement, and sense of belonging (Shortlidge, E. E., Goodwin, E. C., Gray, M. J., & Estes, S. R., unpublished data). At the end of the survey, participants were asked various demographic questions and whether they would be interested in participating in a focus group to share more about their experiences as STEM students. Survey participants who indicated that they were willing to be contacted were emailed by a researcher to confirm interest and availability. We wanted to learn about the transfer student experience, so students were selected to participate in focus groups from the pool of volunteers based on their community college transfer status. This work is part of a larger, mixed-methods study on factors that support student belonging and retention in STEM, and students were also selected to participate based on whether or not they were a member of a STEM intervention program (SIP) on our campus. SIPs have been created nationwide to increase access to STEM fields and to ultimately improve student retention to graduation (Rincon and George-Jackson, 2016). SIPs often recruit and support students who are historically marginalized by STEM fields (Fagen and Labov, 2007), and approximately 10% of our university’s STEM students are involved with SIPs. This study was approved by the Portland State University Institutional Review Board (no. 174450).

Focus Groups

We conducted five semistructured focus groups with STEM transfer students at the end of the Spring 2019 quarter. We used a semistructured focus group format, following a predetermined list of questions but allowing for a natural flow of conversation and follow-up questions as appropriate (Clifford et al., 2016). Each focus group had one primary facilitator and a secondary facilitator. The primary facilitator was the same for each focus group.

We separated transfer student focus groups by SIP status. We did this for two reasons: 1) we were concerned that students who were not part of SIPs would not be comfortable discussing their experiences if they felt that the other students had disproportionately increased opportunities (Onwuegbuzie et al., 2009); and 2) focus groups were conducted as part of a larger, mixed-methods study on STEM student retention and the role of SIPs. The intention of the present work is to better understand the holistic experience of STEM transfer students at our university. We felt that a collective research setting would present a unique perspective, differently nuanced than that of individual interviews, as focus groups allow participants to produce a collective discussion and understanding of a shared problem or experience (Wilkinson, 1998).

We (E.E.S., M.J.G.) iteratively developed the focus group questions in part to better understand the constructs intended to be measured by the survey instrument (e.g. science identity and sense of belonging; Shortlidge, E. E., Goodwin, E. C., Gray, M. J., & Estes, S. R., unpublished data), as well as to generally understand the students’ transitions to our university (for a full list of questions, see Supplemental Material, Appendix 1). Each focus group lasted 1 hour, was held on campus, followed the predetermined script, took place within the same 2-week time period at the end of the academic year, and was audio- and video-recorded. Focus group participants were compensated with a $25 gift card.

Participants

A total of 33 community college transfer students participated in the five focus groups (ranging from two to 10 per group). Table 1 illustrates descriptive demographics of the focus group participants. We would like to point out a few things regarding our focus group sample that could limit the transferability of the data. Students at our university who identify as BIPoC students (Black, Indigenous and people of color) make up approximately 40% of the overall population. BIPoC students were thus overrepresented (53%) in the focus groups that contained students who were part of SIPs compared with the university as a whole. On the other hand, BIPoC students were vastly underrepresented in our other, non-SIP focus groups. Many SIPs specifically recruit minoritized students to apply, or in the case of the National Science Foundation (NSF)-funded Louis Stokes Alliance of Minority Participation program, are designed specifically to support students minoritized in STEM. We recognize this discrepancy as a limitation of the generalizability of our results. Otherwise, the demographics of our sample do not vary significantly from our STEM population, except they are all transfer students—and transfer students comprise approximately 60% of our overall STEM population. It is also important to note that, while the demographics of our sample mostly align with our university’s population, the average age of our students is older than that of many other universities (our mean student age is 26 years). This likely impacts the perceptions and experiences discussed by our participants; however, the age mean is in alignment with the broader transfer student population (AACC, n.d.). We did not disaggregate or analyze our results by demographic factors, as these were focus groups and not all students had a chance to, nor were they expected to, equally respond to each prompt as they would in an interview; therefore, such disaggregation would not appropriately represent the data.

Qualitative Data Analysis

Each focus group was transcribed verbatim (Rev.com, San Francisco) and de-identified. Researchers (M.J.G., S.A.G., N.N.N., E.E.S.) read through a subset of the transcripts to identify overarching themes. The researchers also had access to the secondary facilitator’s (M.J.G.) focus group notes. Three researchers (M.J.G., S.A.G., N.N.N.) then iteratively developed a codebook using multiple methods. We used inductive content analysis to derive themes and codes from the focus group participant responses that arose organically and were not necessarily anticipated (Patton, 1990; Saldana, 2015). We also used deductive content analysis to identify existing ideas within the data that related to integration into science, sense of belonging, and human adaptation to transition (Patton, 1990; Saldana, 2015). The codebook was iteratively developed by the research team (see Supplemental Material, Appendix 2). We used the final codebook to code two of the five transcripts to full consensus. One researcher (M.J.G.) then coded the remaining three focus group transcripts and conferred with the other researchers regarding any questions or instances where the appropriate code to apply was not entirely clear. As a research group, we then aligned the codes developed in our iterative analysis with the factors of the original transition model (MAAT; Figure 1). Our qualitative analysis revealed that we were well positioned to use our student data to expand the original model, as we could fully represent our students’ experiences and tailor the model to the STEM transfer student experience. This expansion resulted in what we call the amended model of adaptation to transfer transition (AMATT; Figure 2).

For this study, we conducted focus groups in an effort to broadly understand the transfer experiences of STEM students at our university. Focus groups produce group-level data in addition to individual-level data (Hydén and Bülow, 2003) and have been recognized as a method whereby participants can produce a collective understanding of a phenomenon (Wilkinson, 1998). Due to the nature of focus groups, not every student answered every focus group question, nor was this expected (Parker and Tritter, 2006). We are currently conducting individual interviews with transfer students, and the interview questions have been acutely informed by the focus group results reported here. Forthcoming reports of those interviews will add to the literature base by contributing individual, nuanced transfer stories.

We did not set out to gather levels of agreement with specific components of the AMATT, nor to specifically identify individual-level experiences, thus we do not quantify each category of response. Instead, we holistically analyzed the data, taking the individual and collective experiences into account so we could map student experiences by these factors. These data are meant to put forth an overview of the sorts of experiences that may occur during the transfer experience from a community college to a university.

RESULTS

Our analysis expands upon Schlossberg’s model to understand human adaptation to transition by keeping the existing elements within the model that were discussed by participants and adding emergent themes from our analysis, resulting in the AMATT (Figure 2). Community college transfer students participating in the study discussed many factors that impacted their adaptation to the transition to university. These factors can be described within the following categories: perception of the transition, environmental characteristics, and individual characteristics. In addition to these categories, participants also described what we deemed as being two divergent paths of adaptation: surviving and thriving. Our model also demonstrates which characteristics appeared to contribute to a “survive” adaptation and which characteristics appeared to contribute to a “thrive” adaptation and the potential relationships between characteristics (Figure 2). We describe each characteristic presented in the model and how it may have related to thriving or surviving. Typically, the most positive responses were contributors to students thriving in their transition, whereas commonplace or negative experiences contributed to surviving.

Perception of Transition

According to Schlossberg’s model of human adaptation to transition, most transitions can be represented by a common set of variables that describe the perception of the transition (Schlossberg, 1981). The most common variables discussed by the focus group participants included timing, degree of stress, and affect (Figure 2).

Timing.

One might consider oneself “on-timing” or “off-timing” for major life events based on what is perceived to be the “correct” timing within a society (Neugarten, 1976). This can be true for college students, who may have an internal perception of when is the correct time to start and finish their degrees and to be in college. Timing was discussed among focus group participants.

On-Timing.

Few participants discussed feeling on-time within their degree program. One participant expressed excitement about the transition from the community college to the university, as it allowed the student to be in alignment with peers, while few others expressed that their age did not impact their perception of their experiences, suggesting that they did not feel off-time for their transition to the university (Table 2).

Off-Timing.

Participants discussed feeling off-time across focus groups. Participants discussed how being a non–traditional age student impacted them emotionally, while others discussed how this impacted their educational experience (Table 2).

It is pertinent to note here that our university’s average student age (undergraduate and graduate) is typically reported to be 26 or 27 years old. Although perhaps unique across some institutions of higher education, this non–traditional student age is a prominent student group that we have a limited understanding of (Spitzer, 2000). The perception of timing held by these participants may have been impacted by the average age of students at our university.

Degree of Stress.

Any transition, regardless of other characteristics, causes stress (George, 1993; Miller, 2016; Schlossberg, 1981). The level of stress caused by a transition impacts adaptation to that transition. Participants expressed experiencing what we categorized as being “low” degrees of stress or “high” degrees of stress throughout their transitions from community college to a 4-year university (Table 2). Each group discussed experiencing a high degree of stress more often than they discussed experiencing a low degree of stress.

Affect.

Some transitions can generate positive feelings, while others generate negative feelings, but most transitions are likely to have both positive and negative affect (Schlossberg, 1981). Among the focus group participants, we found discussion of positive, neutral, and negative perceptions of the transition from a community college to a 4-year university, with negative perceptions of the transition itself being the most discussed by the participants (Table 2).

Environmental Characteristics

In Schlossberg’s model of human adaptation to transition, environment is described broadly (Schlossberg, 1981). The original model describes three aspects of the environment: institutional supports, interpersonal support systems, and the physical setting. In addition to these aspects, as depicted in the AMATT (Figure 2), our participants discussed the pretransition environment, posttransition environment, and a lack of quality supports within their environments.

Institutional Supports.

Institutional support describes any formal or informal agency that an individual can turn to for help (Schlossberg, 1981). Institutional support has been recognized for the role that it plays in increasing undergraduate student persistence (Thomas, 2014; Toven-Lindsey et al., 2015). Our participants discussed receiving academic support, professional support, and financial support (Table 3). The participants often described receiving academic support in the form of working with peers, while others reported positive or negative experiences with academic advising, particularly as it relates to transfer credits to degree. Professional support was often described in the form of help with research or internship placements, and some participants discussed receiving support with finding a job or getting career advice from a mentor. Financial support was discussed by participants as receiving scholarships or having the funds needed to purchase class materials; for other students, finances were the reason that they attended our relatively “low-cost” university.

Interpersonal Support Systems.

Interpersonal support is thought to be essential to successful adaptation to transition (Schlossberg, 1981). The focus group participants discussed receiving interpersonal support in the forms of social and emotional support (Table 3). A study examining undergraduate Latinx students found that social support was positively associated with adjustment to college (Alvan et al., 1996). Emotional support has also been found to be important for undergraduate students’ adjustment to college (Azmitia et al., 2013). Participants discussed receiving social support from peers, faculty, and family. Participants discussed experiencing emotional support through receiving reassurance and encouragement, feeling comfortable in their environment, and being able to share honest experiences among peers.

Physical Setting.

Physical setting encompasses factors such as weather and location that may contribute to stress, well-being, and general outlook, therefore playing a role in adaptation to the transition (Schlossberg, 1981). Participants considered the location of the university as well as physical aspects of the campus, such as the size or layout of the campus (Table 3).

Pre- and Posttransition Environment.

Participants mentioned aspects of their community colleges (pretransition environment), including the size of the community college and their instructors (Table 3). Participants also discussed aspects of the 4-year university (posttransition environment; Table 3). Two main themes arose within the discussion of the posttransition environment: default university and feelings of morale. Many participants discussed feeling as if the university that they transferred to was their only option due to factors related to location or finances (default university). Feelings of morale describes the positive emotional response that comes with belonging to a group (Bollen and Hoyle, 1990). Some participants expressed positive feelings of morale toward the 4-year university.

Lack of Quality Supports.

While some participants felt they received adequate support, others felt there was an overall lack of quality support in their transition. The lack of quality support category was broad and included social, emotional, academic, professional, and financial support (Table 3).

Individual Characteristics

According to Schlossberg’s model of human adaptation to transition, the third major determinant of adaptation to the transition is the individual experiencing the transition (Schlossberg, 1981). As depicted in the AMATT (Figure 2), a number of individual-level characteristics or attributes seemed to influence transfer student adaptation to being a STEM student at a 4-year university. The most salient characteristics among our participants included: life stage, being a member of an underrepresented group in STEM fields, previous experience with a similar transition, and being a member of a SIP (Table 4). The participants also explored their perceptions of what it means to be a scientist, have a science identity, their self-efficacy, and sense of belonging to their fields and/or the university (Table 4). There is evidence in the literature that these constructs are important characteristics for STEM students’ persistence (Estrada et al., 2011, 2018; Simon et al., 2015; Rainey et al., 2018; Strayhorn, 2018), and we wanted to explore what they mean to students in this study; the focus group questions were therefore designed in part to probe these topics.

Both the life stages of the participants and having identities that are considered underrepresented in STEM fields, such as being a first-generation college student (Engle and Tinto, 2008), influenced the perceptions held by the participants and impacted the experiences they had throughout their transitions (Table 4). Schlossberg’s model suggests that those who have successfully adapted to a transition in the past will likely be able to adapt to another transition of a similar nature (Schlossberg, 1981). We found evidence of such adaptation among our participants, with some reminiscing on how the transition to the community college was more difficult than the transition to the university. The participants supported by a SIP often emphasized the impact that this organized support had on their experiences. Example quotes from students with each of these characteristics can be found in Table 4.

Science Identity, Self-Efficacy, and Belonging.

The participants also discussed their perception of what it means to be a scientist, their science identity, self-efficacy, and sense of belonging (Table 4). Within the participants’ perceptions of what makes someone “a scientist,” two major themes arose—they tended to perceive scientists as having either intrinsic or extrinsic traits. Some participants viewed scientists as having intrinsic traits, such as curiosity and a drive to persist within research. Students also believed that scientists held extrinsic traits, such as having a specific appearance or being involved in the scientific process. The participants’ perceptions of a scientist seemed to be related to and influenced by other individual characteristics, such as their own personal science identities or having a research experience (Figure 2). Students developing a science identity can be critical to persisting in STEM (Chemers et al., 2011; Estrada et al., 2011, 2018), and those who identify with a role are more likely to follow the norms associated with that role and then pursue a career within that role (Estrada et al., 2011). The student participants could be roughly categorized into having a strong science identity, an emerging science identity, or lacking a science identity (Table 4).

The participants displayed varying levels of self-efficacy, or their belief in their personal ability to achieve their goals (Bandura, 1977), and what contributed to or hindered their self-efficacy. They talked of elements of having high self-efficacy, such as being very sure of their goals and how their abilities were reinforced through past successes. The participants also disclosed barriers to self-efficacy. This included being impacted by a lack of motivation, being unsure of their goals, having a lack of time due to their involvement in many things, and having a lack of community. Some participants displayed a high level of self-efficacy, while few participants displayed low levels of self-efficacy (Table 4).

Having a sense of belonging is also deemed as crucial for persistence in college (O’Keeffe, 2013; Strayhorn, 2018), in particular for STEM majors and specifically for students of marginalized groups (Rainey et al., 2018). Participants’ emotions ranged across the board on how they expressed having or not having a sense of belonging, and there were various factors that supported or hindered the feeling of belonging. They talked about belonging as it relates to both the university as a whole or to a group at the university. Examples of groups at the university include academic clubs, professional clubs, departments, multicultural centers, SIPs, or sports teams. Those with a strong sense of belonging attributed it to many factors, including having a physical space to go to with affinity groups, being highly involved within the campus, having a diverse community, and feeling comfortable in their environment. Other participants had a weak or completely lacking sense of belonging. The barriers to belonging included having to commute to the university, having little time for getting involved, and feeling a lack of connection to their peers (Table 4).

Adaptation

Schlossberg’s model defines adaptation as the process during which “an individual moves from being totally preoccupied with the transition to integrating the transition into their life” (Schlossberg, 1981, p. 7). Qualitatively, it became clear that although most students were adapting to the university, there were significant differences in how they were adapting. Participants presented evidence of adapting to the university after their transition from the community college in various ways. Some were absolute (thriving), others less so (surviving; Table 5).

DISCUSSION

In this study, we aimed to holistically understand STEM community college students’ transitions and adaptations to a 4-year university. Expanding upon Schlossberg’s model for analyzing human adaptation to transition (MAAT) and listening to the perspectives of our STEM transfer students, we created the AMATT to illustrate how many different factors play a role in a STEM community college transfer students’ adaptation to the transition. The AMATT includes characteristics that others have proposed as being important for STEM students’ persistence to graduation, such as science identity, self-efficacy, and sense of belonging (Estrada et al., 2011, 2018; Simon et al., 2015; Rainey et al., 2018; Strayhorn, 2018). Our model also indicates that there are two types of adaptation: surviving and thriving. We adapted Schlossberg’s model to include these different levels of adaptation, categorized the characteristics of the transition experience as elements that contribute to a survive adaptation or a thrive adaptation, and outlined potential relationships among the characteristics in the AMATT (Figure 2).

Transitioning to a Four-Year University Is Complex

While community colleges increase access to education and many students attend community college for at least some portion of their higher education experiences (Boggs, 2011), transitioning from a community college to a 4-year university can bring forth barriers to persistence (Hagedorn et al., 2008). These barriers can lead to misalignment between students’ intentions and outcomes. Our derived model demonstrates just how complex the transition experience can be, emphasizing the need to support such students throughout this journey. While our model is not representative of every characteristic that could impact adaptation to the transition, it demonstrates many characteristics that impacted our students’ transfer experiences, including their perceptions of the transition, environmental characteristics, and individual characteristics.

The perception of the transition describes the student’s attitudes toward the transition from a community college to a 4-year university. Very little work has been done on how community college students feel about having to transfer to a 4-year university or how these perceptions influence the transition experience, but our model suggests that the perceptions of timing, degree of stress, and affect associated with the transition impact if and how a student adapts to the transition.

Environmental characteristics, such as institutional supports or physical settings involved in the transition process, were found to impact how a student adapted to the 4-year university. Prior research on community college students’ transitions to a 4-year university found that the quality of academic advisement, access to financial aid, and social and cultural issues can impede a successful transition (Gard et al., 2012). Our work complements those findings, in that having easy access to quality academic, financial, social, and emotional support seemed to buttress a thrive adaptation. Our model also demonstrates that the characteristics of the pretransition and posttransition environment influence adaptation. This is in alignment with prior research on community college transfer students, with one study finding that attending a large community college was positively associated with student success, but that a large university size was negatively related to transfer student persistence (Umbach et al., 2019). Characteristics of the physical setting impacted adaptation, for example, one student discussed how a large classroom influenced the transition experience:

Individual characteristics impact adaptation to the transition. Others have shown that a transfer student’s individual characteristics such as parent educational level (Lopez and Jones, 2017) and gender (Jackson and Laanan, 2015) can impact academic adjustment, with first-generation students and women students being less likely to adjust academically at the 4-year university. Our model reinforces this, demonstrating that many different individual characteristics such as life stage, being underrepresented or minoritized in STEM, having experience with a previous transition of a similar nature, and being a SIP participant can be impactful to adaptation (Table 4). Additional STEM-specific individual characteristics are discussed later. Further research is needed to understand how hidden identities or undiscussed social factors may impact STEM students’ adaptation to the transition (Henning et al., 2019; Cooper et al., 2020). It is possible that certain factors did not come up in discussion due to the focus group setting and that tailored individual interviews and surveys could further unpack the salient individual factors.

This model could be used in future research to evaluate which characteristics are most impactful on the transition experience. It could also be expanded upon or adapted to reflect the experiences of students at other types of universities. Transferring from a community college should not hinder one’s ability to persist to graduation, and developing a deeper understanding of which characteristics contribute to a transition experience that supports a thrive adaptation will allow us to help students through that transition in meaningful ways.

Adaptation: Thriving vs. Surviving

The AMATT highlights the many varied inputs involved in a community college students’ adaptation to the transition. We saw a clear qualitative difference among our participants: some were thriving, while others were simply surviving. Students who had more alignment with the thrive adaptation seemed to have more supports in place, both academically and socially. Having more supports may provide a critical buffer, giving students something to lean on or someone to turn to when they face barriers to persistence. One student discussed how having communities within the university helped in getting through a particularly difficult course, while others discussed receiving academic support from faculty and their peers:

The students who were more aligned with characteristics of surviving expressed a lack of quality supports to lean upon. For example, one student explains a lack of social support, and another describes a lack of quality academic support:

Students who are simply surviving the adaptation to the university may be more vulnerable to barriers to persistence. They may also not be able to take advantage of opportunities that contribute to a thrive adaptation or that will help them succeed beyond college. One student discussed financial barriers to participation:

Further research is needed to better interrogate and understand the paths leading to survive and thrive adaptations and how these different ways of adapting impact students in the long run, to graduation and beyond.

Adapting in STEM

While Schlossberg’s model is useful in describing the general experience of adapting to a life transition, having a model for STEM community college transfer students’ adaptation to the 4-year university allows for a deeper understanding of the characteristics impacting these students. Students pursing a STEM degree already face many barriers, and transferring midway through this journey can compound these barriers (Packard et al., 2012). Individual characteristics in our model that are fundamental to the STEM student experience—including their perceptions of scientists and their individual science identity, self-efficacy, and sense of belonging—have proven to be key elements to persistence in STEM fields (Estrada et al., 2011; Estrada et al., 2018; Rainey et al., 2018; Simon et al., 2015; Strayhorn, 2018). The students who expressed these factors more readily also appeared to be more closely aligned with a thrive adaptation. We believe that, if universities and community colleges alike can intentionally focus on bolstering the factors in the AMATT (Figure 2) that tend to lead to a thriving adaptation, more students may have the chance to persist to graduation posttransition.

Leveraging Structured STEM Support Programs

Because we conducted and analyzed focus groups with community college transfer students both supported by SIPs and not supported by SIPs, we were able to clearly detect and begin to understand differences in their experiences. The experiences that SIP and non-SIP students discussed regarding their transitions and adaptations, were at times viscerally different between the groups. Understanding these differences may allow us to leverage the support provided by SIPs and find ways to facilitate thriving for more community college transfer students.

Both SIP and non-SIP participants revealed several negative transition experiences and that these experiences caused them a high degree of stress. This suggests that being part of a SIP does not necessarily eliminate “transfer shock” but instead may provide students with the tools to better cope with challenges experienced at the university and promote a quicker, more robust adaptation.

SIP participants readily discussed positive environmental characteristics that aligned with the thrive adaptation, including institutional supports and interpersonal support systems, whereas more non-SIP participants were prone to explaining a lack of quality supports—in particular, a lack of social and emotional support. In fact, we did not code focus groups with SIP participants as discussing a lack of emotional support. SIP participants more frequently discussed having feelings of morale regarding the university. Conversely, non-SIP participants framed the university as their “default” option and noted that they did not have a choice regarding where they could attend. SIP participants also discussed their identities as a member of an SIP and how this supported the development of their science identity, sense of belonging, and self-efficacy. These factors seemed to contribute to a thrive adaptation, whereas, non-SIP participants more often discussed that they did not always feel the need to belong to the university.

By examining the differences between students’ experiences and affordances, we can begin to understand what types of support may facilitate a thrive adaptation for community college transfer students, even if they do not have specific programmatic support. It is critical to see these often ephemeral, yet impactful interventions as opportunities for learning, growth, and institutionalization of the aspects that appear to facilitate student success at individual institutions.

Limitations

There are several limitations to our study in addition to the demographic representation discussed earlier (Participants). First, this study was not initially designed around the human adaptation to transitions theory, but instead this framework was deemed suitable during the data analysis stage after data collection occurred. Second, this study describes the collective experience of a subset of self-selecting students and therefore is not representative of all students at our university or other institutions. Third, while we intentionally designed the focus groups to separate SIP and non-SIP students, this may have led to SIP students sharing more, as they might have been familiar and comfortable with other participants due to their participation in the same programs; conversely, this may have also caused SIP participants to hold back from openly sharing their experiences if they were concerned about future interactions with other participants. Fourth, while we intentionally conducted focus groups to understand the collective transfer student experience, we recognize that there are limitations to focus group data. Those limitations include that some students may not have spoken up due to the group dynamics or may not have answered every question posed by the facilitators (Parker and Tritter, 2006). Finally, our research is not representative of students who did not adapt to the transition or students who left college, as they all were currently “adapting.” Studying an attrition group with the AMATT, thus identifying a new pathway of nonadaptation, could lead to key insights, such as when survive characteristics outweigh thrive characteristics to a student’s detriment. Equipping the AMATT with such an additional pathway could be highly informative.

CONCLUSION

STEM students transferring from a community college to a 4-year university face a complex transition wherein many characteristics will contribute to their ability or inability to adapt. This adaptation may also look different for students depending on any number of factors. While community college transfer students can cope with the transition to a university and survive, all students deserve to have access to the support that they need to thrive. Helping students adapt in a way that allows them to thrive may lead to better student retention and could help set students up for success beyond the university. This work centers and leverages the student voice to supplement a growing understanding of STEM community college students’ pathways to the 4-year university and provides a model for practitioners who aim to better support the transfer student experience.

ACKNOWLEDGMENTS

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