Factors Affecting Student Veterans’ College Choice
Student veterans represent a significant block of students in American higher education, which also means significant revenue for the institutions that enroll them. Many platforms, such as Viqtory Media’s Military Friendly survey and recognition, attempt to market institutions to military servicemembers and veterans. Such services often entail significant expenditures of institutional staff time for surveys and money for associated marketing materials (e.g., Military Friendly recognition badge). However, the return on investment (ROI) from that time and money is unknown. In this study, we aim to identify how student veterans choose their higher education institution, which in turn may be used by institutions to make decisions about internal funding priorities related to student veterans. ROI can only be considered at the institutional level due to variations in expenses and enrollments; however, we believe this study will help institutions by providing data for preliminary considerations and an instrument for individual institutions to administer to their own student veterans for unique local data in ROI calculations.
Service Members in Higher Education
The preceding decades of armed conflict in the Middle East and other areas around the globe have produced many former service members with access to substantial education benefits. Between 2001 and 2019, over 2.7 million United States service members deployed in support of the Global War on Terror (Garshick et al., 2019). The number of student veterans in higher education has remained relatively consistent, averaging around 950,000 benefits-seeking individuals nationally for the 5 years preceding the most recent available data (U.S. Department of Veterans Affairs, 2019). Of these 950,000, only 15% of student veterans are traditional-age college students, as many delayed entry into higher education because of military service. Further, 47% have children, 47.3% are married, and 62% are first-generation college students (U.S. Department of Veterans Affairs, 2020).
Though there are a significant number of student veterans in higher education, research suggests they experience academic success at a lower rate than other students (Yurasek et al., 2017) and are severely misunderstood by institutions (Vacchi, 2012). Retention and persistence are key to student veteran success after college, as civilian education and training are significant aspects of successful reintegration and adjustment to the civilian world (Domenici et al., 2013; Ghosh et al., 2020). Many student veterans fail to persist in higher education, as nearly half of this population will withdraw from their studies at least once during the pursuit of their academic credentials (Marcus, 2017). The Million Records Project (Cate, 2014) examined nearly 900,000 veterans over 10 years, finding that, while student veterans earn post-secondary degrees at similar rates to other students, it takes them longer to do so. Student veterans may additionally struggle with social connection and identity in higher education (Olt, 2018; Smith-Osborne, 2012). While the military lifestyle is that of considerable structure and discipline, the experience of being a college student is vastly different (Hopkins et al., 2010).
Characteristics of Student Veterans
It is important to note that it is difficult to accurately judge the makeup of the student veteran population in higher education. Self-identification, usually through the form of claiming educational benefits, is often the only way institutions identify members of this population. While many student veterans do claim benefits, it is important to acknowledge that enrollment data associated with those who self-report does not represent the entirety of the population.
Individuals who join the military can come from a variety of socioeconomic and racial backgrounds. As such, the cross-section of this population that inhabits the halls of higher education is equally diverse. Student veterans come from underrepresented racial/ethnic backgrounds at a greater frequency than both traditional and non-traditional civilian student counterparts (Bond Hill et al., 2019). Student veterans are, however, overwhelmingly male as a reflection of military service demographics, with 78% of those enrolled as undergraduates being male (Holian & Adam, 2020). While the student veteran population does have characteristics that are solely its own, there are multiple similarities between this population and non-traditional college students, in that many are older, financially independent, delayed entry, and parents (Ford & Vignare, 2015).
Development of a Veterans College Choice Framework
The Evolution of College Choice Models
College choice has been examined for decades. Higher education institutions “want to plan and forecast their enrollment more effectively, and they want to influence the college-going decision-making of desired students” (Paulsen, 1998, p. 5). Researchers (Chapman, 1981; IIoh, 2018) have identified college choice models that have influenced student decision-making in post-secondary education. Hossler and Palmer (2008) provided a historical overview of how college choice models have evolved. In the early 1900s, students made career choices about going to college and what college to attend because their choices determined the professional outcome of their lives.
By the 1980s, there was an interest and growth in college choice models as research on post-secondary decision-making theories evolved (Hossler & Palmer, 2008). Research on common factors influencing student decisions throughout each progression of college choice models provided a deeper understanding of the personal, social, and institutional influences of student choices. Common themes throughout each model included academic preparedness, personal identities, financial costs and aid, parents and family, college environment and location, and external societal influences (LaFave et al., 2018). The ongoing analysis of college choice models continues to provide an understanding of student influences and decisions. Furthermore, institutions needed to unravel the relationship between students’ decisions on enrollment, retention, and graduation trends. “With major changes to our higher education landscape, new ways of understanding [college choice], empirically and conceptually, are essential” (Iloh, 2018, p. 240).
General College Choice Models
Chapman’s Model
Chapman’s Model of College Choice provided a simplistic approach to examining student-generated decisions about college. Chapman (1981) identified external factors and student characteristics as the prominent influence on a student’s perception of higher education. This model defined a distinction between student characteristics and external factors, which could lead to a student’s decision unilaterally. Furthermore, Chapman detailed the external influences to be personal and important relationships with the student, specific features of the college, and how well the college communicated with the student.
Hossler and Gallagher’s Model
Hossler and Gallagher’s Model is one of the most discussed college choice models (Bergerson, 2009). Hossler and Gallagher’s College Choice Model used predisposition, search, and choice as the foundations for decision-making (Bergersen, 2009). The model helped differentiate the traditional decision-making influenced by money and financial assistance to the overall college experience, making it more persuasive (Bergersen, 2009). Around the early 1990s, this model transitioned the mindset of how higher education institutions marketed to and recruited students (Hossler & Palmer, 2008). Contrary to the straightforwardness of the model, Hossler and Gallagher created a major paradigm shift in higher education enrollment management.
Perna’s Model
Perna’s (2006) model shifted research to focus on student behavior and the impact it has on choices. College choice behaviors are influenced by students’ perceptions of societal expectations of college, as well as human capital components in combination with the financial analysis. Perna discovered students were making decisions based on an analysis of the overall college investment. Perna and Titus (2004) described the key components of the analysis as including the student’s academic (knowledge, skills, and perceptions) and family (emotional, physical, and financial) supports. Perna’s model took the decision-making process to such an individual level that the model examined the student’s internal thought processes (Perna & Titus, 2004), which led to the value habitus had on forming a student’s reality in succeeding in college (Perna, 2006). This reality determined the student’s decision to attend college prior to any decision on where that would be.
Perna (2006) identified four components in this decision-making process. First, Perna described the importance of habitus. Habitus refers to the social constructs of a person and how individual dispositions are formed. Next, the model identified the impact of the student’s environment, more specifically focusing on relationships or the deficits of support within the school and community context. The model emphasized the need to examine the environment in which the student lived. Perna also identified the impact of the college or institution itself, and thus, the third component was identified as the admission process at the institution, including institutional merit, regulations, admission policies, size, and marketing, which became factors for how a student reached a decision.
The last component in Perna’s model diagnosed external influences, identified as the social, economic, and policy context (Perna & Titus, 2004). In general, Perna’s model provided an overview of the recruitment challenges facing colleges and universities across the country (Perna & Titus, 2004). Perna’s model recognized that students choose to examine a variety of factors influencing their college decisions and compare options based on personal importance. This challenge altered the college recruitment process. Therefore, institutions across the country continually develop strategies centered around personalized recruiting packages that are customizable to each student.
Iloh’s Model
Since the early 1900s, institutions focused on college choice (Paulsen, 1998). Iloh’s Model represented a shift from how college choice variables were diagnosed, specifically that “the dominant college choice model and similar others are fundamental to our past and current understanding of college choice because they showcase important components of the path from college aspirations to enrollment” (Iloh, 2018, p. 231). Iloh (2018) argued the misconceptions associated with college choice models, ultimately developing their own model that observed the interconnectedness of influences and correlation to the decision-making process. The Iloh Model provided “an attempt to understand evolution and variation in college decisions and trajectories by way of intentional focus on each context and their relationship to each other” (Iloh, 2018, p. 239). Iloh argued the distinction between the college-going decision and the college choice decision, examining information, time, and opportunity as the crucial axes. The model indicated “how diverse prospective students, who are social actors embedded in complex ecosystems, decide on their higher education pathway” (Iloh, 2018, p. 235).
Student Veterans and College Choice
Unfortunately, while there is a great deal known about the experiences of student veterans through an established body of literature on college choice, there is no broad, scholarly knowledge at the intersection of those two. We were unable to identify any large-scale, broad investigations of how student veterans select their college. There was, however, a small body of literature on college choice variables among veterans, though primarily qualitative and focused narrowly on specific institutions or sectors. Earle (2014) conducted a qualitative investigation and found that key choice factors were the geographic proximity to post-military living or family, affordability with veteran education benefits, availability of a desired major, and the overall reputation of the institution.
Molina’s (2015) quantitative analysis of survey data considered veterans’ factors in choosing to enroll in higher education generally and the factors that led them to enter either the for-profit, two-year, or four-year sector. Hill’s (2016) qualitative investigation looked at the choice to attend a for-profit institution and subsequently to transfer to a community college, finding these decisions were driven by financial and convenience factors. In a similar qualitative approach, Circle (2017) focused on community college choices and found that flexibility in transfer, geographic location, perceived veterans’ support services, cultural fit, and institutional perception affected the decision to attend the specific institution. Ives (2017) conducted a mixed methods study of student veterans’ choices of four-year institutions as they transferred away from two-year institutions, finding that perceived academic quality and previous faculty recommendations as most important.
Current Study
With this nationwide pilot study, we sought to begin to fill that gap in knowledge, addressing the following research question: What factors are most important to student veterans as they choose an institution of higher education?
Method
Participants
This study was approved by the lead author’s institutional review board, and all participants provided informed consent before completing the survey. Eighty-seven participants (52 males, 34 females, and 1 non-binary) completed the veterans’ college choice survey in its entirety, which were 78% of the 111 participants who completed at least part of it. The average age of the sample was 37 years old (M = 37.29; SD = 9.16). A majority of the participants self-identified as White (~77%), followed by Asian (~7%), Black (~6%), American Indian or Alaska Native (~5%), Native Hawaiian (~1%), and other (~2%). Most participants selected the Army (~47%) as their most recent branch of active-duty military service, followed by the Air Force (~20%), Navy (~18%), Marines (~14%), and Coast Guard (~1%). When asked for information relevant to the current college experience, about 50% of participants indicated that they completed most classes face-to-face, ~35% reported taking only online classes, and ~12% indicated a mixed modality in their coursework. A majority of the participants currently attended a public, 4-year institution (~65%). Approximately 54% of the sample indicated that they decided, before entering active-duty military service, that they wanted to take college-level classes at some point. Approximately 61% of the sample reported that they selected their specific higher education institution after active-duty military service.
Materials and Scale Development Procedure
A primary goal of the current study was to better understand the factors that are most important to student veterans as they choose an institution of higher education. To achieve this goal, the researchers developed a survey instrument to collect information from this population regarding their motivations for college choice. There were several steps involved in this scale development process. First, the researchers began developing the survey items to align with Iloh’s (2018) theoretical framework on college choice because it expanded on traditional college choice models to emphasize specific factors that influence decision-making. Most notably, this model emphasizes three contextual factors in the decision-making process: time, information, and opportunity. At this initial stage of development, these three components formed the foundation of how the survey items were developed and organized. The lead researcher used this framework to develop a prototype survey instrument based on his own experience and items that had been discussed in the Veterans Knowledge Community of Student Affairs Administrators in Higher Education (NASPA).
Next, we solicited feedback from a panel of experts to further refine the survey questions and to help us establish appropriate content validity for the survey. Twelve experts were recruited to evaluate the questions and to provide suggested edits relevant to their background and knowledge of the target population. These experts were members of the Veterans Knowledge Community of NASPA. Based on the feedback from these experts, some of the original items were revised, and one new item was added (Item 21 – Veterans Upward Bound Program).
The final survey consisted of 26 items. Three items were used to understand the timing of the student’s college choice decisions (e.g., when did you choose your current/most recent institution?). Twenty-three items measured college choice motivations relevant to the importance of information about the institution (e.g., university marketing campaigns, the university being listed as a military-friendly school, and the prestige/reputation of the institution or program), and the importance of opportunities offered to student veterans by the institution (e.g., offering transfer policies relevant to military training, military tuition discounts or scholarships, and the geographic proximity of the institution). Mean responses and standard deviations are reported in Table 1.
Table 1
College Choice Factors Mean Level of Importance.
| SURVEY ITEMS | LEVEL OF IMPORTANCE | ||||||
|---|---|---|---|---|---|---|---|
| OVERALL SAMPLE | COLLEGE SELECTIONBEFORE/AFTER SERVICE | ATTENDING COLLEGE ONLINE/ON-CAMPUS | PUBLIC 4-YEAR/OTHER INSTITUTION | ||||
| BEFORE | AFTER | ONLINE | CAMPUS | PUBLIC | OTHER | ||
| Availability of my desired academic program | 4.49 (0.81) | 4.25 (.71) | 4.50 (.81) | 4.89 (.32) | 4.39 (.92) | 4.51 (.85) | 4.47 (.73) |
| Cost affordability | 3.70 (1.17) | 4.13 (.64) | 3.66 (1.27) | 4.17 (1.20) | 3.43 (1.33) | 3.89 (1.15) | 3.33 (1.16) |
| College/university employee responsiveness to my inquiries | 3.69 (1.07) | 3.88 (.83) | 3.77 (1.07) | 3.72 (1.18) | 3.48 (1.29) | 3.70 (1.15) | 3.67 (.92) |
| Military tuition discount scholarship | 3.52 (1.49) | 3.88 (1.13) | 3.23 (1.64) | 3.61 (1.69) | 4.00 (1.41) | 3.30 (1.58) | 3.93 (1.20) |
| The prestige or reputation of the institution and/or program | 3.49 (1.14) | 3.38 (1.06) | 3.60 (1.03) | 3.61 (1.20) | 3.81 (1.33) | 3.44 (1.17) | 3.60 (1.10) |
| Campus environment | 3.49 (1.32) | 3.63 (.74) | 3.42 (1.26) | 1.78* (1.06) | 3.95* (1.02) | 3.30 (1.38) | 3.87 (1.14) |
| Transfer policies related to military training (Joint Service Transcript, Community College of the Air Force, etc.) | 3.36 (1.46) | 3.25 (1.58) | 3.08 (1.49) | 3.72 (1.49) | 3.14 (1.56) | 3.23 (1.44) | 3.60 (1.49) |
| The geographic proximity to where I live now | 3.36 (1.56) | 3.20 (.93) | 3.27 (1.56) | 1.17* (1.42) | 3.38* (1.75) | 3.44 (1.60) | 3.21 (1.47) |
| Perceived availability of the institution’s support services for student veterans | 3.31 (1.21) | 3.38 (.92) | 3.15 (1.29) | 2.89 (1.32) | 3.57 (1.25) | 3.25 (1.27) | 3.43 (1.10) |
| The geographic proximity to where I first moved after military service | 2.78 (1.69) | 2.00 (.76) | 2.42 (1.61) | 1.72 (1.27) | 2.81 (1.75) | 2.51 (1.72) | 3.31 (1.51) |
| Family members | 2.52 (1.41) | 3.25 (1.39) | 2.26 (1.36) | 2.06 (1.26) | 2.81 (1.78) | 2.39 (1.39) | 2.77 (1.43) |
| The geographic proximity to where I entered the military from | 2.38 (1.59) | 4.13* (.84) | 1.87* (1.29) | 2.67 (1.61) | 2.76 (1.76) | 2.11 (1.51) | 2.90 (1.63) |
| Friends who are not military connected | 2.34 (1.20) | 2.36 (.74) | 2.13 (1.13) | 1.39 (.70) | 2.50 (1.32) | 2.07 (1.06) | 2.83 (1.32) |
| Marketing from the college/university (commercials, billboards, online ads, etc.) | 2.32 (1.18) | 3.13 (1.25) | 2.11 (.99) | 2.28 (1.27) | 2.29 (1.15) | 2.09 (1.01) | 2.77 (1.36) |
| Student veterans/military members I personally know | 2.29 (1.31) | 2.38 (1.41) | 1.87 (1.09) | 2.58 (1.31) | 2.52 (1.25) | 2.09 (1.23) | 2.67 (1.40) |
| U.S. News “Best Colleges for Veterans” List | 2.21 (1.36) | 2.13 (1.55) | 1.83 (1.06) | 2.08 (1.38) | 2.71 (1.42) | 1.82 (1.13) | 2.33 (1.46) |
| Previous enrollment (i.e., you were enrolled here while on active duty) | 2.21 (1.41) | 1.13 (.64) | 1.67 (1.20) | 1.72 (1.27) | 2.25 (1.55) | 1.88 (1.25) | 2.35 (1.49) |
| Military base education center | 2.17 (1.32) | 2.63 (1.30) | 1.85 (1.09) | 1.61 (1.04) | 2.52 (1.44) | 1.93 (1.16) | 2.63 (1.50) |
| Military Times “Best for Vets” Colleges List | 2.17 (1.34) | 2.00 (1.51) | 1.77 (1.09) | 2.08 (1.38) | 2.48 (1.44) | 1.82 (1.14) | 2.33 (1.46) |
| Viqtory Media “Military Friendly Schools” List | 2.10 (1.31) | 2.88 (1.25) | 1.70 (.95) | 2.08 (1.24) | 2.52 (1.37) | 1.68 (1.02) | 2.09 (1.45) |
| Best Colleges “Guide for Servicemembers and Veterans” List | 2.08 (1.31) | 2.13 (1.55) | 1.64 (.96) | 1.92 (1.17) | 2.25 (1.50) | 1.67 (1.01) | 2.27 (1.34) |
| Veterans Upward Bound program | 2.01 (1.33) | 2.50 (1.69) | 1.58 (1.01) | 1.44 (.71) | 2.14 (1.39) | 1.54 (.87) | 2.30 (1.61) |
| Veteran social media groups | 1.99 (1.20) | 2.75 (1.28) | 1.70 (.97) | 1.33 (.77) | 1.95 (1.07) | 1.77 (1.02) | 2.40 (1.40) |
[i] Note: Mean values are presented with standard deviation in parentheses. Bold values with asterisks represent significant mean differences between groups (p ≤ .05). Participants rated each survey item on the level of importance when deciding which institution to pursue for their current degree program using 1–5 Likert-type scale (1 = not at all important; 5 = very important). Survey items are presented in descending order of importance based on the overall sample. Additional information is provided for the following sub-groups: when the college selection was made (before or after military service), the modality selected (online or on-campus), and the type of institution selected (public 4-year or other).
To distribute the survey to student veterans, the researchers relied on personal and professional contacts as well as a third-party data collection site. The Veterans’ Knowledge Community of NASPA also provided support in sharing the study with their hundreds of member institutions. We also used the online recruitment platform Amazon Mechanical Turk (MTurk) to recruit participants with military experience who fit our student experience and inclusion criteria. To meet the criteria, participants had to be at least 18 years of age, served in an active-duty component of U.S. military service, enrolled or have been enrolled in college within the past 5 years (full or part-time) at an American institution of higher education, not currently on active duty, and not currently enrolled in ROTC or a U.S. military academy. We did not consider college choice variables for student veterans who elected not to attend college. All data collection took place online using the survey platform Qualtrics.
Results
College Choice Motivations: Level of Importance
Participants were asked to rate items on a 1–5 Likert-type scale based on the level of importance when selecting a college (1 = not important at all; 5 = extremely important). Based on the descriptive information provided, participants rated the availability of their desired academic program being offered at the target institution as the most important factor in their college choice decisions (M = 4.49, SD = .81). Participants also rated institution responsiveness to inquiries, prestige/reputation of the institution, campus environment, affordability, and financial assistance as important when selecting a college; all mean scores for these items were rated at 3.5 or above. Participants indicated that transfer policies, geographic proximity, and perceived support offered by the institution are somewhat important; all mean scores for these items ranged from 3–3.5. Military base education centers and college marketing appeared to be of less importance to the current sample when making college choice decisions; all mean scores for these items were below the mid-point of the scale.
Additional analyses were conducted to examine possible differences regarding college choice decisions based on specific demographic information. We examined if college selection decisions (before or after military service), the modality selected (online or on-campus), and the type of institution selected (public 4-year or other) impacted the level of importance for each survey item. Overall, most of the factors rated as being important when selecting a college did not differ based on these selected sub-groups, with the following exceptions. Individuals who selected their college before active military service reported “the geographic proximity to where I entered the military from” as more important in their college decisions than those who selected their college after military service (p < .001). Those who reported attending college on-campus reported the “campus environment” and “friends who are not military connected” as being more important when selecting a college to attend than those attending college online (ps <.001). Those who attend college on-campus also reported “geographic proximity to where I live now” (p = .002) and “where I first moved after military service” (p = .05) as more important compared to those who attend college online. The mean response and standard deviation results are reported in Table 1.
Exploratory Factor Analysis
An exploratory factor analysis was conducted on the 23 items used to measure college choice based on information about the institution and opportunities available to student veterans. The goal of this analysis was to explore possible groupings of items to factors that might further elucidate college choice decisions. Using Iloh’s (2018) theoretical framework, we expected to see the survey items load to three factors: relevant information, opportunity, and time.
Principal components analysis with a varimax rotation indicated a three-factor structure. Eigenvalues were used to establish each factor and its importance.
Eigenvalues greater than 1 represented a unique factor. Factor one (Eigenvalue 7.82) was comprised of eight items that explained 34% of the variance with factor loadings from .580 to .837. Items with information about “best of” college lists (e.g., “Best for Vets”) had the strongest correlations with this factor (>.80). Factor two (Eigenvalue 2.41) was comprised of six items that explained 11% of the variance with factor loadings from .430 to .738. Items relevant to geographic proximity (e.g., “college is close to where I live now”) and personal supports (e.g., “veterans/military members I personally know”) had the strongest correlations to this factor (>.60). Factor three (Eigenvalue 1.86) was comprised of nine items that explained 8% of the variance with factor loadings from .422 to .798. Items pertaining to college opportunities (e.g., affordability and programs specific to veterans) had the strongest correlations to this factor (>.50). Full explanatory factor analysis results are presented in Table 2.
Table 2
Factor Loadings with Varimax Rotation for Three-Factor Solution of College Choice Items.
| SURVEY ITEM | FACTOR LOADINGS | ||
|---|---|---|---|
| 1 | 2 | 3 | |
| Availability of my desired academic program | .440 | ||
| Cost/affordability | .565 | ||
| College/university employee responsiveness to my inquiries | .498 | ||
| Military tuition discount/scholarship | .483 | ||
| The prestige or reputation of the institution and/or program | .473 | ||
| Campus environment | .422 | ||
| Transfer policies related to military training | .437 | ||
| The geographic proximity to where I live now | .682 | ||
| Perceived availability of the institution’s support services for student veterans | .449 | ||
| The geographic proximity to where I first moved after military service | .537 | ||
| Family members | .430 | ||
| The geographic proximity to where I entered the military from | .457 | ||
| Friends who are not military connected | .645 | ||
| Marketing from the college/university (commercials, billboards, online ads, etc.) | .580 | ||
| Student veterans/military members I personally know | .738 | ||
| U.S. News “Best Colleges for Veterans” List | .815 | ||
| Previous enrollment (i.e., you were enrolled here while on active duty) | .580 | ||
| Military base education center | .679 | ||
| Military Times “Best for Vets” Colleges List | .835 | ||
| Viqtory Media “Military Friendly Schools” List | .795 | ||
| Best Colleges “Guide for Servicemembers and Veterans” List | .837 | ||
| Veterans Upward Bound program | .798 | ||
| Veteran social media groups | .758 | ||
[i] Note: In general, factor 1 items relate to marketing and information about the institution; factor 2 items relate to personal support and geographic considerations; factor 3 items relate to opportunities provided by the institution (including academic and financial support).
Based on Iloh’s (2018) theoretical model, information about the institution, available opportunities for student veterans, and timing are important motivators when making college choice decisions. With this model in mind, as well as the analysis of three-factor loadings and the nature of each item assessed, we grouped the survey items measuring college choice motivations into specific categories. Survey items that load to factor 1 relate best to marketing and information about the institution (e.g., marketing campaigns, social media, and military friendly school). Iloh suggested that the type of information shared and how that information is delivered can be helpful in shaping college choice decisions. Interestingly, this factor had the largest eigenvalue; however, the survey items that loaded to the marketing and information factor were rated as being of lower importance among the current sample.
Survey items that load to factor 2 represent personal support, geographic considerations, and timing (e.g., location of the school in relation to current living arrangements). This second factor may fit well with the dimension of timing within Iloh’s model and provides context and understanding regarding what is happening in a person’s life that may influence their college choice decisions. Finally, survey items that load to factor 3 represent opportunities provided by the institution. These opportunities include academic and financial support which are critical dimensions of Iloh’s model in establishing college choice decisions. Items from this third factor (e.g., availability of the desired program and costs) were rated as some of the most important factors when making college choice decisions by the current sample.
Discussion
Our findings aligned with expectations from the general college choice studies and the models that our instrument was based on. Our findings for the most important factors were aligned with prior research as: (#1) availability of my desired academic program (Earle, 2014; Iloh, 2018), (#2) cost/affordability, and (#4) military tuition discount/scholarship (Bergersen, 2009; Circle, 2017; Earle, 2014; Hill, 2016; Iloh, 2018; Perna, 2006), (#3) college/university employee responsiveness to my inquiries (Chapman, 1981; Iloh, 2018), and (#5) the prestige or reputation of the institution and/or program (Circle, 2017; Earle, 2014; Ives, 2017; Perna, 2006). Aside from #4 – military tuition discount/scholarship, none of these items are military-specific, and even that item is functionally a sub-component of #2 – cost/affordability. Further, each of these items relates to institutional practice and not marketing or rankings.
However, several findings from this study stood out as unique. While several previous models and studies emphasized geographic proximity as being important (Circle, 2017; Earle, 2014), the three questions posed in this study about geographic proximity only scored in the middle of responses. However, geographic proximity to where student veterans lived now after military service and the campus environment were strongly correlated to the college choice of student veterans studying on campus. These items reasonably did not correlate to college choice for student veterans studying online. Items in the bottom third of factor importance consisted primarily of veteran-specific items related to marketing. These factors had not been studied before; however, discussions with the expert panel who reviewed our instrument suggested that these items would not be important to student veteran college choice.
Implications
While only representing preliminary findings from a nationwide pilot study, the practical implications for higher education institutions are significant. Beyond basic program availability, the most important factors to enrolling student veterans were common concepts shared among most students (e.g., affordability and good customer service). Rather than investing significant staff time and financial resources into “Military Friendly”-type marketing, our findings suggest that institutions would see more ROI by spending to be military friendly and then advertise how they are (e.g., providing military/veteran scholarships and better staffing areas that support student veterans). However, further research is needed to verify these findings. We believe that our survey instrument can be used by those working with student veterans to assess how they are attracting the student veterans to their institution, and we also believe that future funded research could utilize this survey in a more comprehensive and representative nationwide study.
Limitations
As a pilot study, this study was primarily limited by its small sample size. With 111 respondents completing any of the survey and only 87 of those completing the full survey, there are significant limitations on generalizability. Respondents were notably overrepresented from the expected student veteran population in the areas of gender identity (female), race (White and Asian), and degree level (graduate). There are also limitations relevant to a small sample and statistical power. When conducting an exploratory factor analysis (EFA), a larger sample is preferred. However, prior research has established that even small samples (e.g., N = 50) can yield reliable findings (see de Winter et al., 2009). In addition, many of the factor loadings associated with the EFA were below .60. Future research may benefit from collecting more data as a larger sample may yield findings that are more stable and precise (see MacCallum et al., 1999).
In future applications of this survey instrument, researchers will need a larger sample of student veterans that is representative of national student veteran demographics. We believe this will likely require funding to incentivize participation, such as a $20 gift card to each respondent. However, a larger distribution network will also be required. Student Veterans of America is, perhaps, the largest surveyor of student veterans, which can make it difficult for other surveys to be distributed on similar cycles. Either getting Student Veterans of America to assist with distribution or surveying opposite of their cycle will be important. Utilizing additional professional associations and personal contacts will also likely be necessary. Funding to distribution sites could also assist in getting additional institutional participation, such as a $500 grant to institutions that distribute the survey through their veterans’ financial aid certifying officials.
Conclusion
This nationwide pilot study of a survey instrument to measure student veterans’ factors in selecting an institution of higher education found that the availability of programming, affordability, effective communication, and support services were of primary importance to student veterans. Of the least importance were military-specific marketing measures, such as the Viqtory Media “Military Friendly” survey and listing. Future applications of this survey instrument include individual institutions assessing why their student veterans choose to enroll there, as well as future research on a larger, more representative sample.
Data Accessibility Statement
The raw data from this study is available from the lead author upon request.
Ethics and Consent
This study (#22_0018) was approved by the Fort Hays State University Institutional Review Board.
Competing Interests
The authors have no competing interests to declare.
Author Contributions
Each of the authors in this study participated in all aspects of the preparation, study, and writing. Phillip Olt led the overall project as well as the study design, survey development, implementation, and writing. Whitney Whitaker led the data collection and analysis. Seth Kastle led the literature review and survey distribution. Taylor Kriley led the theoretical development of the survey.