It Matters Long Before: How Early Exposure to Faculty and Advisors at Baccalaureate Institutions Relates to Upward Transfer

Abstract

A missing component in the current transfer literature is how community college students’ exposure to faculty and/or advisors at baccalaureate institutions early in their educational journey, such as meeting with transfer advisors or faculty members from a baccalaureate college or university, may shape their longer-term transfer outcomes. Our research addresses this gap, drawing upon longitudinal survey data and propensity score matching. The findings reveal a positive relationship between early exposure and transfer, suggesting that when students gain exposure to and potentially receive support from faculty and advisors at baccalaureate institutions, they may be better prepared for the upward transfer process. Our study highlights the role played by the transfer-receiving end in assisting community college students to fulfill their transfer aspirations. The larger transfer research agenda must continue to delve into the specific ways in which baccalaureate institutions can play a substantive role in preparing and supporting students both prior to and after transfer.

Keywords

community colleges postsecondary education propensity score matching upward transfer

Transfer from community colleges to baccalaureate institutions¹ has garnered perennial research and policy interest. This not only reflects transfer as a prominent part of the community college mission but is also motivated by persistently low transfer rates. Nationally, approximately 70% to 80% of all postsecondary students beginning at community colleges intend to earn a bachelor’s degree, but only around 20% out of the same student population actually do so within 6 years of initial enrollment.² The rise of “free” community college programs gives even more relevancy and weight to the study of transfer. As these programs aim to serve students from low-income and underserved backgrounds (Perna & Smith, 2020), they appeal to many baccalaureate-aspiring students who cannot afford a 4-year college tuition and may instead opt to start at a community college.

Despite abundant empirical work and education interventions aimed at supporting transfer students, the role of the receiving end—baccalaureate institutions—is underaddressed. One critical missing component is how interactions with faculty and/or advisors from baccalaureate institutions, while students are early in their community college journey, shape longer-term transfer outcomes. We know that transfer-aspiring students are deeply impacted by both receiving and sending institutions as they navigate transfer requirements, articulation agreements, and institutional fit (Wang, 2020); thus, early exposure to baccalaureate faculty and advisors can play an instrumental role in paving a smooth path. Ultimately, the responsibility for successful transfer rests on both sending and receiving institutions in offering resources to ensure seamless transitions (Fink & Jenkins, 2017). By highlighting faculty and advisors as actors situated within baccalaureate institutions, we underscore the equal, if not greater, responsibilities that baccalaureate institutions must shoulder in promoting access to transfer, as opposed to merely offering support posttransfer.

Background Literature and Conceptual Framework

Given the scarcity of empirical work addressing the relationship between transfer-aspiring students’ early exposure to faculty and/or advisors from baccalaureate institutions and upward transfer, the studies we identified and reviewed are inevitably situated within transfer students’ larger educational trajectories spanning community colleges and baccalaureate institutions. As a reflection of this limited extant literature base, the studies on interactions with faculty and advisors in our review concentrate on either the community college space (pretransfer) or the 4-year institution space (posttransfer), instead of precisely tackling the crossover space of our key interest—the interaction between pretransfer community college students and faculty/advisors from baccalaureate institutions. Nonetheless, the existing literature bears broad relevance to our study and reinforces the need to examine this crossover space where prospective transfer students gain exposure to baccalaureate faculty/advisors before the actual point of transfer.

Student-Faculty Interactions

Community college students rely on faculty members, at both transfer-sending and transfer-receiving institutions, as key resources in supporting their academic and professional successes (e.g., Packard et al., 2013; Sandoval-Lucero et al., 2014). Interacting with faculty can promote opportunities toward attaining validation. Students who obtained higher levels of faculty validation—through being mentored and feeling cared about and valued—were more likely to persist (Barnett, 2011). Similarly, interactions with supportive community college instructors elevated students’ comfort and willingness to seek faculty assistance (Bauer, 2014). These findings suggest that faculty validation, by virtue of these interactions, may have rippling effects on students’ sustained aspirations and efforts along their educational trajectories, including transfer.

Interactions with faculty were also positively connected to learning experiences and transfer outcomes among community college students in science, technology, engineering, and mathematics (STEM) fields (Lenaburg et al., 2012; Packard et al., 2013). Students’ transfer knowledge and efficacy were enhanced when community college STEM faculty frequently utilized the following tactics: advising on institutional differences, transfer adjustment, and STEM programs; sharing personal experiences in attending baccalaureate institutions; and discussing transfer outside of class time (Packard et al., 2013). Lopez and Jones (2017) found that more frequent interaction with faculty at both the community college and university, along with positive self-perception as a transfer student, were associated with STEM transfer students’ greater university adjustment. Collectively, these results demonstrate that high-quality engagement with faculty on both ends of transfer help pave the process through increased student knowledge and self-confidence.

Student-Advisor Interactions

Another major thread in the literature centers on the role advisors play in helping students chart a seamless academic path. Packard and Jeffers (2013) found that interactions with community college advisors effectively guided transfer students on appropriate classes that fulfilled credits at both community colleges and baccalaureate institutions. Donaldson et al. (2016) showed that community college students who were required to actively engage in degree-planning with their designated advisors through an “intrusive” advising model identified this structure as helpful. Hatch and Garcia’s (2017) study further revealed that newly enrolled community college students’ intention to persist was positively associated with “essential” advising practices that centered on developing a clear academic plan and pathway, supported by the accessibility of advisors who assisted students with academic planning in light of their external commitments.

Transfer Partnerships

Cultivating effective partnerships across community colleges and baccalaureate institutions is also crucial to students’ transfer and bachelor’s degree completion (Fink & Jenkins, 2017; Kisker, 2007). A handful of studies on this topic highlight the qualities that mark fruitful transfer partnerships. Hirst et al. (2014) found that community college STEM students who engaged in a summer research program through a partnership with a baccalaureate institution developed greater knowledge of and confidence in transferring, as well as increased aspirations to attend graduate school. Kisker (2007) maintained that all key stakeholders across institutions must be kept in the loop and possess clarity on expectations. Fink and Jenkins (2017) equally stressed the essential role of strong communication channels, adding that productive collaborations also prioritized transfer and showcased clear programmatic pathways. Equally important, Bragg (2019) highlighted several significant dimensions of high-performing transfer partnerships, including the intersection of culture, policy, and practice (Yeh & Wetzstein, 2019), as well as how these elements can act as push and pull factors shaping partnerships.

A Transfer-Receptive Culture

Pivotal to developing a genuine partnership is the cultivation of a transfer-receptive culture, defined as baccalaureate institutions providing “the support needed for students to transfer successfully—that is, to navigate the community college, take the appropriate coursework, apply, enroll, and successfully earn a baccalaureate degree in a timely manner” (Jain et al., 2011, p. 257). Informed by critical race theory, Jain et al. (2011) advanced five tenets undergirding a transfer receptive culture: (a) prioritizing transfer of nontraditional students, (b) offering outreach designed for transfer students, (c) lending financial and academic support, (d) honoring the commitments that transfer students face, and (e) possessing appropriate assessment and evaluation frameworks.

The framework of a transfer-receptive culture has guided a number of student-focused studies, such as Castro and Cortez’s (2017) study on Mexican community college transfer students’ experiences at a research-intensive university and a study on a transfer enrichment program by Jain et al. (2016), to name just a few. However, the transfer-receptive culture framework has yet to be more explicitly and richly integrated into research and practice around transfer partnerships.

This background literature offers a compelling rationale for taking on our research and elucidates the larger, collaborative institutional context within which a crossover space may be cultivated to foster robust advising, partnerships, and a transfer-receptive culture to serve prospective transfer students. Further, extant research is plagued by the thorny issue of selection bias, in that students seeking out faculty/advisors may already possess characteristics that are systematically different from their peers who did not do so. In an attempt to address this prevalent methodological limitation in prior research, our study draws on propensity score matching techniques, detailed in the Methods section, thus further adding to the rigor in this line of literature.

Conceptual Framework

Our conceptual framework (Figure 1) highlights transfer outcomes as shaped by the development of transfer student capital, notably through early exposure to baccalaureate faculty/advisors. Transfer student capital (Laanan, 1998) signifies the knowledge and skills students develop to navigate transfer, often accumulated through advising experiences, perceptions of transfer, interactions with faculty, and study skills acquisition (Laanan et al., 2010). The original conceptualization of transfer student capital does not, and rightfully so, make an explicit distinction between 2- and 4-year spaces that cultivate capital. However, faculty/advisors at baccalaureate institutions can arguably play a present and influential role long before transfer, especially given their potential to serve as authentic, firsthand sources of information on baccalaureate institutions’ educational requirements and experiences. Thus, prospective transfer students’ early exposure to these agents offers a viable jumping-off point toward building capital and represents the focal point of our investigation.

Figure 1.

Conceptual framework for the study.

Note that we conceptualize early exposure to baccalaureate faculty/advisors as the same venue of developing transfer student capital and do not view faculty and advisors as distinct entities for this particular purpose. Community college students often do not distinguish between the roles of faculty and advisors when seeking information on academic planning (Wang, 2020). When it comes to transfer, the boundaries between their responsibilities are further “blurred” as they both possess essential “advising” information and represent a symbolic window into the larger transfer-receiving culture at baccalaureate institutions.

Our conceptual framework also incorporates a set of background, environmental, and academic factors related to transfer outcomes and student selection into early exposure to faculty/advisors.³ Furthermore, our framework accounts for other plausible venues for developing transfer student capital, such as transfer-oriented activities at community colleges and additional forms of pretransfer engagement with baccalaureate institutions, including visiting a campus, taking courses, and interaction with students enrolled at baccalaureate institutions. See Table 2 for detailed measures.

Methods

Larger Study Context and Target Population

This research was part of a longitudinal study conducted at three large public 2-year institutions in a midwestern state, all with transfer as a core component of their mission. The larger project’s purpose was to investigate factors influencing upward transfer among students with initial exposure to a STEM major or coursework. Accordingly, the target population was 1st-year, degree-seeking students starting in Fall 2014 at the participating institutions, who either had declared a major in a STEM field or, for those without a declared major yet, enrolled in one or more courses within a STEM field.⁴ This focus on students with initial exposure to STEM allowed the study and its sample to assume relevance broader than STEM, since not all students eventually majored in STEM, as many core general education courses (e.g., science, math) were also included. In other words, students could take courses in the defined STEM areas to fulfill their foundational program requirements without majoring in STEM. Thus, our findings bear relevance beyond STEM majors.

Target Sample and Sampling Procedures

In Fall 2014, the larger project team sampled roughly 1,000 students from each of the three institutions for a final target sample size of about 3,000 students. This sampling approach balanced the need for sufficient statistical power and resource constraints. The sample was obtained using a stratified sampling strategy with two strata: race/ethnicity and STEM fields. Students of color⁵ were oversampled to ensure that the final analytic sample included a sufficient number of these students. In addition, for institutions where enrollment was small within specific STEM fields, an oversampling approach was also adopted (see weighting strategies in the online supplementary document, available on the journal website).

Study Sample

In Fall 2014, the research team invited the target sample to participate in the longitudinal study through the first survey. Approximately 1,670 students completed the survey and consented to being part of the longitudinal study, for a participation rate of 56%. Table 1 describes the characteristics of study-eligible students, the target sample, and survey respondents across two survey waves included in the current study.

Table 1

Fall 2014 Enrollment, Target Sample, and Survey Respondents

	Fall 2014 Enrollment		Target Sample		Survey Respondents (Fall 2014)		Survey Respondents (Fall 2017)
	N	%	N	%	N	%	N	%
Gender
Woman	1,490	38%	1,120	38%	690	42%	580	46%
Man	2,380	61%	1,860	62%	970	58%	680	54%
Other	10	<1%	10	<1%	10	<1%	<10	<1%
Race/Ethnicity
White	2,790	72%	1,910	64%	1,090	65%	840	67%
Native American	40	1%	40	1%	20	1%	10	1%
Black/African American	290	7%	290	10%	130	8%	80	7%
Hispanic/Latinx	300	8%	300	10%	170	10%	120	9%
Asian	210	5%	210	7%	130	7%	90	7%
Multiracial/unknown	250	7%	250	8%	130	8%	110	9%
Grand total	3,880		3,000		1,670		1,260

Note. Sample and subsample sizes rounded to the nearest 10. Column counts and percentages may not sum to totals due to rounding. See Table 2 for more detailed descriptive statistics of the study’s final analytic sample.

Given our study’s focus, we restricted our sample to the 1,170 students who indicated on the first survey their intent to transfer to a baccalaureate institution. This delineation is important because, on the survey, only students who indicated an initial intent to transfer were directed to a set of questions measuring whether they interacted with faculty and/or advisors from baccalaureate institutions to discuss transfer-related matters. This approach aligns with survey research in that respondents should be presented questions relevant to their goals and plans (Dillman et al., 2014). Upward transfer status was determined by a question on the Fall 2017 follow-up survey asking students’ institutional attendance patterns over the previous 3 years. A total of 880 out of the 1,170 transfer-aspiring students completed the follow-up survey, for a response rate of 75.2%. Since the number of students with missing data for at least one variable was small (n = 20, 2.3%), we handled missing data with listwise deletion, resulting in a final analytic sample size of 860.

We developed survey weights and incorporated them in our analyses to account for the complex sampling structure, nonresponse, and survey attrition and ensured that our analytic sample was representative of the target population. The associated technical procedures are detailed in the online supplementary document.

Variables

Table 2 presents all study variables and descriptive statistics of the final analytic sample. With a few exceptions noted in the table, measures came from two waves of the longitudinal survey.⁶

Table 2

List of Study Variables and Analytic Sample Descriptives

Variables	Description	Sample Statistics
Variables	Description	N	(%)
Independent (“treatment”) variable
Early exposure to faculty and/or advisor at baccalaureate institutions	1 = “yes” to at least one of the two survey items:• Have you met with a transfer advisor from a four-year college or university you wish to transfer to?• Have you met with a faculty member at a four-year college or university you wish to transfer to?	270	(31.4)
	0 = otherwise	590	(68.6)
Outcome variable
Upward transfer	1 = ever transferred to a baccalaureate institution between 2014 Fall and 2017 Fall	385	(44.8)
	0 = did not transfer	480	(55.8)
Control variables in postmatching analysis
Having visited a baccalaureate campus	1 = “yes” to survey item:• Have you visited the campus of a four-year college or university you wish to transfer to?	370	(43.0)
	0 = otherwise	490	(57.0)
Having taken courses at a baccalaureate institution	1 = “yes” to survey item:• Have you taken any courses at a four-year college or university you wish to transfer to?	115	(13.4)
	0 = otherwise	750	(87.2)
Having talked to students enrolled at baccalaureate institutions	1 = “yes” to survey item:• Have you talked to any students enrolled at the four-year college or university you wish to transfer to about their experiences?	440	(51.2)
	0 = Otherwise	420	(48.8)
		Mean	(SD)
Support for transfer	Mean scale score of latent factor consisting of three survey items (Cronbach’s alpha 0.728) measured on a 5-point Likert scale, with 5 indicating a great deal and 1 indicating none:	3.2	(0.9)
	• How much financial support do you have to transfer to a 4-year college or university? • How much support do you have from your family for transfer to a 4-year college or university? • How much support do you have from friends and peers for transfer to a 4-year college or university?		(0.9)
Transfer service usage	Mean scale score of latent factor consisting of three survey items (Cronbach’s alpha 0.847) measured on a 5-point Likert scale, with 5 indicating very often and 1 indicating never:	2.5	(1.0)
	• How often do you use each of the following services provided by your college or campus? – Advising for future transfer to a four-year college, either walk-in or online – Published transfer information or guidelines – Transfer credit assistance, which helps you in determining how your course credits transfer to other colleges and universities		(1.0)
Transfer-oriented interactions	Mean scale score of latent factor consisting of four survey items (Cronbach’s alpha 0.801) measured on a 5-point Likert scale, with 5 indicating very often and 1 indicating never:	2.5	(0.9)
	• How often do you contact each of the following individuals to discuss matters related to transfer to a 4-year college or university? – Instructors – Student peers – Academic advisors or counselors – Family members or friends
Transfer information acquisition	Mean scale score of latent factor consisting of two survey items (Cronbach’s alpha 0.692) measured on a 5-point Likert scale, with 5 indicating very often or extremely and 1 indicating never or not at all:	3.1	(1.0)
	• How much information do you have about how to transfer to a 4-year college or university? • How well do you understand which courses at your college are transferrable to a 4-year college or university?
		N	(%)
Background characteristics^a
Gender	1 = woman	425	(49.4)
	0 = man and other	440	(51.2)
Race/ethnicity	A series of dummy variables
	• Asian	70	(8.1)
	• Black/African American	55	(6.4)
	• Hispanic/Latinx	85	(9.9)
	• Other racially underrepresented students including Native American, multiracial, and unknown	80	(9.3)
	• White; reference category	575	(66.9)
Nontraditional age	1 = 24 or older	180	(20.9)
	0 = under the age of 24	680	(79.1)
Low income	1 = lower than $30,000	270	(31.4)
	0 = $30,000 or higher	595	(69.2)
Parental education	1 = at least one parent graduated from 4-year institution or higher	365	(42.4)
	0 = otherwise	495	(57.6)
English as second language	1 = English is a second language	150	(17.4)
	0 = otherwise	710	(82.6)
Marital status	1 = married	75	(8.7)
	0 = otherwise	790	(91.9)
Single parent status	1 = single parent	45	(5.2)
	0 = not single parent	815	(94.8)
Employment status	1 = full-time employment	145	(16.9)
	0 = otherwise	715	(83.1)
Financial dependency	1 = being financially dependent on parent(s) or legal guardian(s)	535	(62.2)
	0 = otherwise	325	(37.8)
Institutional type^b	1 = transfer as primary mission	400	(46.5)
	0 = dual mission of both transfer and workforce development	460	(53.5)
Enrollment status^b	1 = full-time student	650	(75.6)
	0 = otherwise	210	(24.4)
Math preparation	The number of years of high school coursework in math
	• 1 = did not take	5	(0.6)
	• 2 = 0.5 year	5	(0.6)
	• 3 = 0.5–2 years	25	(2.9)
	• 4 = 2–3 years	65	(7.6)
	• 5 = 3–4 years	220	(25.6)
	• 6 = 4 years or more	545	(63.4)
Science preparation	The number of years of high school coursework in science
	• 1 = did not take	<5	(0.2)
	• 2 = 0.5 year	5	(0.6)
	• 3 = 0.5–2 years	30	(3.5)
	• 4 = 2–3 years	105	(12.2)
	• 5 = 3–4 years	235	(27.3)
	• 6 = 4 years or more	480	(55.8)

Note. Sample and subsample sizes rounded to the nearest 5. Column counts and percentages may not sum to totals due to rounding or missing values.

Used to estimate the propensity scores and also included in the logistic regression analysis based on the matched sample.

Obtained from institutional records.

Dependent and independent variables

The main dependent variable was whether or not transfer-aspiring students had ever transferred to a baccalaureate institution as of Fall 2017. Early exposure, the main independent (or “treatment”) variable was measured by whether or not, during their first term of enrollment, transfer-aspiring students had met with transfer advisors and/or faculty members from a baccalaureate institution to which they wished to transfer. The group of students who had done so formed the “treatment” group, and other students were in the “control” group. Earlier, we established the substantive rationale for combining exposure to baccalaureate faculty and advisors. Here, we offer descriptive data and methodological implications associated with this decision. Of the 270 students in the “treatment” group, 75 had exposure to advisors only, 120 students to faculty only, and 75 to both advisors and faculty. As robustness checks of our approach of combining faculty and advisors, we conducted a set of additional analyses and found that combining the two entities as a single variable produced substantively similar but statistically more sound results relative to using them as distinct variables.⁷

Covariates

We adjusted for relevant covariates in two sets of analyses. The first was to predict student selection into the treatment by estimating propensity scores. The second was to investigate the relationship between early exposure and upward transfer, for which we added control variables measuring other elements of transfer student capital based on our conceptual framework. Specifically, we controlled for other ways in which students engaged with baccalaureate institutions, such as visiting campus, taking courses, and interaction with students enrolled at baccalaureate institutions. We included these variables postmatching, instead of using them as covariates for matching, because these variables represent activities that are likely to occur parallel to students’ early exposure to faculty/advisors.⁸ Therefore, rather than a precursor that propels students’ self-selection into early exposure to faculty/advisors, they are conceptually more sound as parallel activities that need to be accounted for in postmatching analysis to further isolate the relationship between early exposure to faculty/advisors and transfer outcomes.

Data Analysis

Propensity score matching

Students who gained early exposure may be a self-selected group, possessing background characteristics systematically different from their counterparts who did not have such exposure. To address this selection issue, a viable way to achieve balance in these background characteristics between the treatment and control groups is through the use of a propensity score. A propensity score is the conditional probability of being in the “treatment” group given background characteristics (Rosenbaum & Rubin, 1985). Once the propensity score is estimated, it can be used to match students in the treatment and control groups that have comparable propensity scores, thus achieving a matched sample that is balanced in those background characteristics. Note that our interest in this study is to investigate the effect of the treatment variable (i.e., early exposure) in the treatment group (i.e., ATT—average treatment effect on treated).

We estimated the propensity score by fitting a logistic regression model with the longitudinal weight, where early exposure was predicted by the set of covariates described earlier (see Table S1 of the online supplementary document for results). Once the propensity score was estimated, we examined the common support (i.e., the overlapped propensity score ranges) of the treatment and control groups. A visual inspection suggested a sufficient overlap between the two groups, with similar propensity score distributions (see Figure S1 in the online supplementary document). Next, students in the control and treatment groups were matched on the propensity score to construct a balanced sample. Following Rosenbaum and Rubin (1985), we employed Mahalanobis distance that measures the proximity between observations in the two groups, with a caliper of 0.25 standard deviations without replacement. To evaluate balance in the baseline characteristics, we compared standardized mean differences between the two groups before and after matching and found that matching substantively reduced the differences in the covariates, with no significant differences between the two groups in the matched sample. See Table S2 in the online supplementary document for detailed results.

Effect estimation and sensitivity test

We conducted a logistic regression model on the matched sample to estimate the effect of early exposure on transfer, first by modeling the main independent variable only, followed by adding the covariates to help reduce remaining bias. Although matching helped achieve a balanced sample on observables, if there were unobserved influential covariates, the estimated treatment effect would not be reliable. Therefore, we conducted a sensitivity analysis to examine the robustness of the treatment effect. The sensitivity analysis was performed by introducing a sensitivity parameter, Γ, which indicates the odds of hidden covariates. If Γ = 1, the probability of being in the treatment group is the same as that of being in the control group. In other words, the assignment into the treatment group is not affected by hidden covariates. As Γ increases, so does the probability of being in the treatment group due to hidden covariates. The effect of Γ can be evaluated by the change in the p-value of the treatment effect to infer whether the same conclusion about the treatment effect would hold if the odds of hidden covariates increase (Rosenbaum, 2002). We increased Γ from 1 to 1.5 with an increment of 0.05. These numbers are reasonable because it is uncommon for studies in social sciences to be insensitive to many unobserved covariates, and thus, setting the sensitivity parameters at greater values would not be appropriate (Keele, 2014). Our analyses were implemented using two R packages, Matching (Sekhon, 2011) and rbounds (Keele, 2014).

Discussion of Results

Our main findings are presented in Table 3. When only the “treatment” variable was included in the model, early exposure to faculty and/or advisors at baccalaureate institutions during the first term was associated with a greater likelihood of transfer to baccalaureate institutions. More specifically, the odds of transferring to a baccalaureate institution among students with early exposure was about 1.8 times the odds of their counterparts without early exposure. Interpreted in another way, the predicted probability of upward transfer for students with early exposure was 0.146 higher than that for otherwise similar students without early exposure. After controlling for additional variables, the same positive effect of early exposure still held. Sensitivity analysis results (Table S3 in the online supplementary document) supported that the results would be rather insensitive to unobserved covariates because the significance of the treatment effect would hold until the odds of unobserved covariates (i.e., Γ) increased up to 1.45.

Table 3

Effect of Early Exposure During the First Term on Upward Transfer

	B	SE	p value		Odds Ratio	Delta p
Model 1
Early exposure to faculty and/or advisor at baccalaureate institutions	0.592	0.127	.000	***	1.808	.146
Model 2
Early exposure to faculty and/or advisor at baccalaureate institutions	0.682	0.173	.000	***	1.978	.143
Having visited a baccalaureate campus	−0.100	0.160	.533		0.905	−.018
Having taken courses at a baccalaureate institution	−0.122	0.204	.550		0.885	−.021
Having talked to students enrolled at baccalaureate institutions	−0.130	0.149	.385		0.878	−.023
Support for transfer	−0.033	0.087	.707		0.968	−.006
Transfer service usage	−0.155	0.087	.073		0.856	−.027
Transfer-oriented interaction	−0.018	0.094	.846		0.982	−.003
Transfer information acquisition	0.246	0.088	.005	**	1.279	.047
Woman	0.321	0.142	.024	*	1.378	.063
Asian	0.103	0.325	.751		1.109	.019
Black/African American	−1.915	0.381	.000	***	0.147	−.193
Hispanic/Latinx	−0.158	0.302	.602		0.854	−.027
Other racially underrepresented students	−0.260	0.244	.287		0.771	−.044
Nontraditional age	−0.414	0.242	.088		0.661	−.067
Low income	0.044	0.181	.807		1.045	.008
Parental education	0.337	0.147	.022	*	1.401	.066
English as second language	−0.764	0.255	.003	**	0.466	−.110
Marital status	0.534	0.303	.078		1.707	.109
Single parent status	−0.843	0.459	.066		0.430	−.119
Employment status	−0.580	0.197	.003	**	0.560	−.089
Financial dependency	0.161	0.168	.337		1.175	.030
Institutional type	0.031	0.165	.852		1.031	.006
Enrollment status	−0.071	0.190	.709		0.932	−.013
Math preparation	0.110	0.116	.342		1.117	.021
Science preparation	0.075	0.104	.471		1.078	.014

Note. The delta p statistic (Petersen, 1985) indicates change in predicted probabilities of upward transfer between a group and its reference group when the variable is binary. For continuous variables, the delta p statistic means a predicted probability change by one-unit increase of the variables from the mean.

p < .05. **p < .01. ***p < .001.

We begin our discussion by offering a few general considerations. Although our study sample includes students with initial exposure to STEM programs or courses, it has broader transferability since many STEM courses are foundational across most areas of study. The STEM context does offer a sharpened lens into challenges facing student transfer, as the broader inequities and systemic issues in advising and transfer outcomes tend to be magnified due to highly structured curricula and stringent academic requirements common to STEM disciplines (Wang, 2020). Further, although the opportunity for early exposure to occur can be created by both students and faculty/advisors, given the control and power institutions have over the transfer process, students should not bear the responsibility of reaching out to baccalaureate institutions (Wang, 2020). Our findings embody a larger, symbolic yet powerful message that calls on baccalaureate institutions, including their faculty/advisors, to fully actualize their potential to become proactive and productive partners in serving pretransfer students.

Overall, our findings illuminate community college students’ early exposure to faculty/advisors at baccalaureate institutions as a vehicle toward promoting transfer, arguably through developing transfer student capital (Laanan et al., 2010), but also likely through cultivating students’ aspirational momentum, an integral concept of Wang’s (2017) theoretical model of momentum for community college student success. Aspirational momentum accounts for how community college students define, develop, reassess, and commit to their educational objectives. Prospective transfer students may gain aspirational momentum toward transfer through interacting with faculty/advisors from baccalaureate institutions early in their community college careers. Thus, early exposure serves as a catalyst for increasing both transfer student capital and aspirational momentum toward upward transfer.

This positive link between early exposure and transfer must also be understood in light of the common barriers that transfer students encounter, such as the lack of clarity around transfer requirements, inadequate advising, and a resulting loss of momentum toward transfer (Wang, 2017). Situating our findings within this context, when students interact with faculty/advisors at baccalaureate institutions about transfer, they are likely to gain knowledge and resources, from the transfer-receiving end, about the transfer admissions process, articulation agreements, as well as scholarships and financial aid opportunities (Packard & Jeffers, 2013). Such interactions may also help students avoid the accumulation of credits that do not transfer and facilitate a more efficient time to degree (Wang & Wickersham, 2014).

Equally important, early exposure is likely to broaden the web of transfer support across both community colleges and baccalaureate institutions. It may help alleviate issues and barriers associated with unsustainably high student-advisor ratios at community colleges (Wang, 2020), thus enhancing transfer-aspiring students’ advising experiences. Through this extended net of support, students may cultivate relationships with faculty/advisors across institutions that offer validation and emotional support for students to develop or deepen their self-confidence and motivation in regard to transfer.

Implications for Policy and Practice

For transfer policy and practice, our study suggests that integrating baccalaureate faculty/advisors in the transfer support system may strengthen the overall quality of pretransfer advising. In the broader scheme, transfer-aspiring students are prospective students for baccalaureate institutions, who not only have the capacity but also are obligated to create a transfer-receptive culture (Jain et al., 2011). Baccalaureate institutions must invest in serving prospective and enrolled transfer students to make transfer partnerships with community colleges truly equal and reciprocal.

If baccalaureate institutions are serious about recruiting and serving transfer students, they should work toward transforming faculty/advisor mindsets and campus culture toward greater involvement in the transfer process. At present, faculty/advisors at baccalaureate institutions are not sufficiently rewarded for serving transfers and do not necessarily view engaging with prospective transfer students as part of their official job responsibilities. It is pivotal that baccalaureate institutions develop a structure of support and recognition for cultivating partnerships with community colleges to enhance transfer-aspiring students’ access to faculty/advisors. Also important, carefully designed online or hybrid advising sessions hold the potential to balance the workload of faculty and advisors while offering those students without access to in-person meetings the opportunity to interact with faculty and advisors. Additionally, students who wish to transfer to institutions not geographically proximate to where they live would not be constrained in the presence of online advising, thus broadening transfer-aspiring students’ choice and exploration of transfer options.

Community colleges should also take steps toward maximizing students’ exposure to baccalaureate faculty/advisors. By emphasizing the considerable value that comes with early exposure, community college faculty and advisors will be encouraged to develop approaches that utilize this resource through classroom instructions or advising sessions. For example, community college faculty could include in their teaching materials relevant opportunities and resources, as well as offering reminders and encouragement when such opportunities become available. Similarly, advisors can incorporate information in their advising sessions regarding contacts at baccalaureate institutions. Community college administrators should also incorporate early exposure into broad-reaching channels of communication, such as orientation sessions and college newsletters. Furthermore, given that not all students are equally equipped with the same opportunity for making the connection with the receiving institutions on their own, community colleges must equitably support their students in this endeavor by proactively and fully facilitating such venues.

Directions for Future Research

Our findings serve as a jumping-off point toward unraveling more complexities and nuances around early exposure in future research, especially the specific nature, format, content, and quality of the interactions, and how such interactions are facilitated. This will allow us to construct a comprehensive vision of what constitutes thoughtful and effective early exposure experiences that benefit students the most. Qualitative and mixed methods studies are particularly well suited for addressing these issues. Further inquiry into early exposure will also benefit from a focus on relationship building and optimal models of collaboration between sending and receiving institutions. For example, how do community colleges and baccalaureate institutions choose their respective partners? What shapes the development of relationships and partnerships? What constitutes and characterizes an equitable and effective collaboration model?

Conclusion

As we close this piece amid the COVID-19 crisis, we see heightened urgency and relevance to support community college transfer students. These students are well positioned to address societal, community, and health needs brought on by the pandemic, as they are deeply involved with and dedicated to serving their communities with the level of education they desire (Wang, 2020). Our study highlights the shared responsibility of transfer—prospective transfer students can be holistically and better supported if access to faculty/advisors spans across community colleges and baccalaureate institutions. We call for further inquiry into the larger context of how baccalaureate institutions assist transfer students, and how to accomplish that in equitable, collaborative, and sustainable ways. The larger transfer research agenda must continue to illuminate impactful ways in which baccalaureate institutions render support for students—long before the point of transfer.

Supplemental Material

WangEtAl._OnlineAppendix.pdf – Supplemental material for It Matters Long Before: How Early Exposure to Faculty and Advisors at Baccalaureate Institutions Relates to Upward Transfer

Supplemental material, WangEtAl._OnlineAppendix.pdf for It Matters Long Before: How Early Exposure to Faculty and Advisors at Baccalaureate Institutions Relates to Upward Transfer by Xueli Wang, Seo Young Lee, Brett Ranon Nachman and Xiwei Zhu in Educational Researcher

Footnotes

Notes

Authors

XUELI WANG, PhD, is a professor at the University of Wisconsin–Madison, 270 Education Building, 1000 Bascom Mall, Madison, WI 53706; xwang273@wisc.edu . Her research centers on factors and contexts that shape students’ learning, experiences, and trajectories to success, with a focus on community colleges and STEM education.

SEO YOUNG LEE, PhD, is a psychometrician at Prometric, Suite 1400, 1501 South Clinton Street, Baltimore, MD 21224; seoyoung.lee@prometric.com . Her research includes the application of measurement, especially item response theory (IRT) and response time models, and statistical models on educational topics.

BRETT RANON NACHMAN, MS, is a doctoral candidate at the University of Wisconsin–Madison, 355 Education Building, 1000 Bascom Mall, Madison, WI 53706; bnachman@wisc.edu . His research focuses on autism in higher education, community college students’ experiences and pathways, and LGBTQ+ campus climate.

XIWEI ZHU, MS, is a doctoral student at the University of Wisconsin–Madison, 355 Education Building, 1000 Bascom Mall, Madison, WI 53706; xzhu253@wisc.edu . Her research focuses on teaching and learning at community colleges, especially how faculty define and engage in inclusive teaching.

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