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Article

Understanding the Relationship between Culturally Engaging Campus Environments and College Students’ Academic Motivation

by
Samuel D. Museus
1,* and
Kiana Shiroma
2,*
1
Department of Education Studies, University of California—San Diego, La Jolla, CA 92093, USA
2
Pre-Health/Pre-Law Advising Center, University of Hawaii at Manoa, Honolulu, HI 96822, USA
*
Authors to whom correspondence should be addressed.
Educ. Sci. 2022, 12(11), 785; https://doi.org/10.3390/educsci12110785
Submission received: 29 September 2022 / Revised: 29 October 2022 / Accepted: 30 October 2022 / Published: 4 November 2022
(This article belongs to the Special Issue Toward More Inclusive and Equitable College and University Environments)
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Abstract

:
Low rates of college completion are a major national dilemma, and one way in which college campuses can increase degree attainment rates is by fostering higher levels of academic motivation among students. This study analyzed the relationship between culturally engaging campus environments and growth in college students’ academic motivation. The survey data from a sample of 704 undergraduates enrolled at a public four-year university on the East Coast were analyzed. Bivariate correlations indicate that all nine indicators of culturally engaging campus environments were correlated with stronger academic motivation. When controlling for demographic and high school variables, cultural validation and humanized environments were directly and positively associated with growth in academic motivation. However, post hoc analysis reveals that cultural familiarity, culturally relevant knowledge, cross-cultural engagement, and collectivist orientation were all indirectly associated with motivation gains through cultural validation. The implications of this study for research include the need for research that analyzes these relationships with larger samples from more diverse institutions and utilizes methods that support stronger causal claims. Implications for practice include the importance of maximizing students’ access to culturally engaging environments and ensuring that they are designed with anti-deficit approaches that validate students’ backgrounds and identities to enhance academic motivation.

1. Introduction

Low rates of college completion continue to be a major national dilemma. Almost half of the students who matriculate at four-year college campuses will not earn a bachelor’s degree within six years [1]. These low attainment rates have negative consequences for individuals and society. For example, lower rates of degree completion contribute to decreased levels of civic engagement, increased poverty, and fewer occupational opportunities [2]. One way in which college campuses can increase degree attainment rates is by fostering higher levels of academic motivation among students.
While both qualitative and quantitative lines of evidence indicate that academic motivation is one factor that shapes students’ adjustment to and success in college [3,4], studies that shed light on the environmental factors that shape such motivation are sparse. To address this gap in knowledge, the current study examined the relationship between campus environments and growth in academic motivation. In the following section, we present the framework that guided the current study with the aim to explain the ways in which culturally engaging campus environments shape college student outcomes. Then, we review the literature on the link between campus environments and academic motivation and clarify the contribution of the current investigation. The remainder of the article focuses on the current analysis and its implications for future research and practice.

1.1. Culturally Engaging Campus Environments

Building on decades of research in the field of higher education, the Culturally Engaging Campus Environment (CECE; pronounced see-see) model of college success seeks to explain how particular types of campus environments can influence students’ experiences and outcomes. As shown in Figure 1, the model suggests that culturally engaging campus environments shape students’ dispositions, such as academic self-efficacy and motivation, which in turn influence their likelihood of persistence and degree completion [5]. The CECE model outlines nine indicators of culturally engaging environments that can be separated into two categories of cultural relevance and cultural responsiveness.
The CECE model’s first five indicators of cultural relevance delineate environments that are relevant to students’ communities and identities [5]. Cultural familiarity is the extent to which students are able to connect with faculty, staff, and peers with whom they share similar backgrounds and who understand them. Culturally relevant knowledge describes the degree to which campuses provide opportunities for students to learn and exchange knowledge about their own communities. Cultural community service refers to the opportunities that institutions provide students to give back to and positively influence their cultural communities (e.g., via community service, service learning, or problem-based research opportunities that help address challenges in their cultural communities). Opportunities for meaningful cross-cultural engagement describe the extent to which students can engage in meaningful interactions to address existing social and political issues with people of different cultural backgrounds. Lastly, cultural validation refers to the degree to which colleges and universities value their students’ cultural backgrounds and identities [5].
The CECE framework also delineates four indicators of cultural responsiveness, which take the diverse norms and needs of students’ communities into account in the design and delivery of support systems [5]. Collective orientations refer to the degree to which college campuses are driven by collectivist values. Humanized educational environments refer to the degree to which students can develop meaningful relationships with faculty and staff who care about them and are committed to their success. Proactive philosophies involve the degree to which postsecondary educators go beyond making information and support available to making extra efforts to ensure that students access that information and support. Finally, the availability of holistic support refers to the degree to which students have access to at least one person who they believe will connect them with the information that they require or provide them with the assistance that they seek, regardless of the type of information and support they need [5].
A growing body of qualitative evidence indicates that the elements of culturally engaging campus environments might be positively associated with a wide range of positive student outcomes. This scholarship primarily suggests that culturally engaging environments might be positively associated with increased involvement, a sense of belonging, and persistence in college [6,7,8,9,10,11,12]. The bulk of this research is qualitative, offering a nuanced analysis of how such environments shape the experiences of a relatively small number of students.
Nevertheless, some existing qualitative work does shed some light on the potential relationship between culturally engaging environments and academic motivation [13,14,15,16,17,18,19,20,21,22,23,24,25]. For example, Druery and Brooms analyzed the experiences of five Black students in a Black male initiative and illuminated how this culturally engaging program enhanced students’ engagement on campus and fostered their resilience [7]. Moreover, Hang and Walsh conducted a qualitative study of Hmong American college students and found that these types of environments contributing to a sense of belonging in higher education, which was in turn linked to heightened levels of motivation [17]. Therefore, this body of knowledge indicates that culturally engaging campus environments might primarily fuel students’ academic motivation by increasing their positive empowerment, positive engagement, and sense of connection to their campuses.
To date, scholars have only conducted a handful of quantitative inquiries into the relationship between culturally engaging campus environments and college outcomes [26,27,28,29]. When these scholars have controlled for a wide array of variables, their analyses indicate that certain elements of culturally engaging campus environments are positively and significantly associated with stronger self-efficacy and a greater sense of belonging in college. For example, Museus et al. [28] used multiple regression techniques and controlled for important demographic (e.g., age, race, gender, income) and experiential variables (e.g., enrollment intensity, credits completed, living situations) to examine the relationship between culturally engaging campus environments and sense of belonging among students across three campuses. Their results indicate that cultural familiarity, collectivist cultural orientations, cultural validation, proactive philosophies, and holistic support all exhibited positive and statistically significant relationships with students’ sense of belonging.
Extant research also suggests that the relationship between culturally engaging campus environments and college outcomes might be a complicated one [26,27,28,29]. For example, there is initial evidence that the influence of some aspects of culturally engaging environments—such as cultural familiarity, culturally relevant knowledge, cultural community service, and collectivist orientations—on students’ sense of belonging might be indirect, through their increasing the degree to which the campus validates students’ cultures, communities, and identities [28]. That is, if campuses provide opportunities for students to access those environments characterized by cultural familiarity, culturally relevant knowledge, cultural community service, and collectivist cultures, they are more likely to provide conditions in which students feel validated, which then results in stronger connections to the institution and the feeling that they belong within it. However, these studies are limited to analysis of how complex environments influence the sense of belonging, and scholars have yet to examine how these dynamics might shape other outcomes, such as academic motivation.

1.2. Culturally Engaging Campus Environments and Academic Motivation

Existing research demonstrates that both individual (e.g., race, socioeconomic status, self-efficacy, metacognition, and personality) and environmental factors might all shape academic motivation in college [30,31,32,33,34,35,36,37]. Regarding environmental influences, the existing evidence indicates that the nature and quality of the interactions that students experience might shape their motivation [33,34,36,38,39,40,41]. For example, scholarship shows that hostile environments, within which students experience daily racial discrimination and bullying from peers, can be associated with decreased academic motivation in college [36,39].
In contrast, more positive environments, and the interactions within them, might be correlated with greater academic motivation [33,34,37,38]. For example, Hoosainy et al. [33] used experimental methods to show that classes in which faculty members utilized pedagogical approaches that linked realistic contexts to learning activities led to increased academic motivation, compared with those who employed lecture-based teaching practices. In addition, using ANOVA techniques, Weinstein analyzed the survey data from 156 undergraduates at a single institution and found that faculty who had a sense of humor had a positive impact on students’ academic motivation. Komarraju et al. [34] employed multiple regression techniques to examine 242 undergraduates who were enrolled at a public university in the Midwest and found that students’ feeling that their professors respected them was statistically associated with increased academic motivation.
There are at least a few limitations of this existing research. First, while evidence is clear that environments matter, there is still a paucity of research on this topic, and a holistic understanding of how campus environments influence academic motivation is elusive. In addition, researchers have yet to utilize the CECE framework to guide the analysis of academic motivation in college. Such an approach can permit the analysis of the relationships between many aspects of culturally engaging environments and academic motivation simultaneously while controlling for other potentially confounding variables that are nonexistent. Via the current inquiry, we sought to fill these gaps in existing knowledge.

1.3. Purpose and Significance

As mentioned, the current inquiry is focused on examining the relationship between campus environments and growth in academic motivation in college. The current study aims to answer one overarching question: To what degree do culturally engaging campus environments predict growth in academic motivation among college students?
This study is significant for multiple reasons. The analysis addresses the relative paucity of research on the relationship between campus environments and academic motivation. In addition, the current inquiry constitutes the first empirical analysis of the relationship between culturally engaging environments and academic motivation in college. Such research is necessary to inform educational policy and practice that seeks to maximize motivation and eventual success among undergraduates in higher education.

2. Materials and Methods

It is important to note that the data used in the current analysis have been utilized in a previous publication examining the relationship between culturally engaging campus environments and academic self-efficacy [13]. The study methods have, therefore, already been thoroughly discussed in this prior work. To execute this study, a survey was conducted at a four-year public residential state university on the East Coast with an undergraduate student body that roughly reflects the majority of four-year college students throughout the U.S. According to IPEDS, during the time this analysis was conducted, the participating institution’s undergraduate student body was almost evenly split across sex (51% female and 49% male), predominantly White (58%), and with the majority in the traditional college age group (83% are under 25 years old). To conduct the current analysis, we used the CECE four-year college survey, which encompasses items designed to gather information about demographics (e.g., race, age, socioeconomic status, and sex), a 32-item scale that measures the 9 aforementioned CECE indicators, and several items that measure a range of college outcomes (e.g., self-efficacy, learning, belonging, etc.), including academic motivation.
The CECE four-year college survey was distributed to all 2951 undergraduate students who were enrolled at the participating university during the spring of 2018. An initial email soliciting participation in the survey was sent to all enrolled undergraduates, and four follow-up messages (one per week) were sent to those who had not yet completed the questionnaire. A total of 704 students responded to the survey, yielding a 24% response rate. Based on the available institutional data, the respondent sample was generally representative of the larger student population at the participating campus. Specifically, the representation of each identity subgroup in the sample fell within 10% of its representation in the focal population. Women (60%) were marginally over-represented compared with men (40%). In terms of race, a majority of respondents identified as White (60%), followed by Black (15%), Latina/x/o (6%), Asian American (5%), Multiracial (3%), and Native American (3%).

2.1. Variables

The means and standard deviations associated with each key variable included in the analysis are listed in Table 1. Given prior research indicating that demographics are associated with academic motivation (17–18, 23), we controlled for key demographic characteristics (age, race, socioeconomic status, and sex). Age was a continuous variable that measured participants’ self-reported age at the time of survey completion (ranging from age 18 to 30 and over). The self-reported race variables (Black, Latinx, Multiracial, and Native American) were dummy-coded, with White representing the reference category. The ordinal socioeconomic status variable measured the respondents’ self-reported socioeconomic backgrounds (0 = working-class, 1 = middle-class, 2 = upper-class (rich). The self-reported sex variable was also a dichotomous variable (0 = male, 1 = female). It is important to note that there is little existing evidence regarding the validity of students’ self-reporting of their socioeconomic background. However, this was the best measure available to control for this variable, and future research should investigate the optimal approaches and measurements to capture this aspect of students’ backgrounds.
Table 2 delineates the key variable definitions, alpha scores, and numerical codes. Principal components analysis (PCA) with varimax rotation was used to create each latent construct. Based on prior PCA recommendations [40,41,42,43,44,45,46,47,48,49,50,51,52,53], we retained (1) the principal components with eigenvalues above 1.0 and (2) the corresponding survey items with factor loadings above 0.40 and commonalities above 0.50. For each variable, all items were retained.
Due to prior evidence that individual characteristics might influence academic motivation [30,31,36] and the recognition that bias is inherent in self-reported gains [45,46,47], we followed recommendations to control for high school self-reported gains aligned with the focal college outcome, which suggest that controlling for precollege self-reported gains can account for respondents’ propensity to under- or overestimate their gains in college [48]. This high school growth in the academic motivation (α = 0.76) variable was a latent construct measuring the perceptions of growth in motivation to accomplish the following during high school: (1) work hard in school, (2) receive good grades, and (3) learn as much as possible from the high school entrance to high school graduation (coded 1 = much worse, 2 = somewhat worse, 3 = about the same, 4 = somewhat better, and 5 = much better).
Our focal predictors were the nine CECE indicators. To measure these indicators, we used the 32-item CECE scale that measures the 9 latent CECE constructs and that prior research has found to have high content and construct validity [49]. The scale measured each indicator using 3–6 items each. Cronbach’s alpha scores indicated that the items measuring the nine CECE indicators were characterized by relatively high reliability: cultural familiarity (α = 0.87), culturally relevant knowledge (α = 0.93), cultural community service (α = 0.95), opportunities for cross-cultural engagement (α = 0.87), culturally validating environments (α = 0.92), collectivist cultural orientations (α = 0.92), humanized educational environments (α = 0.92), proactive philosophies (α = 0.73), and the availability of holistic support (α = 0.90).
The focal outcome variable was students’ self-reported academic motivation, compared with when they first entered college. Academic motivation (α = 0.76) was a latent construct measuring the perceptions of growth in motivation to accomplish the following during college: (1) work hard in school, (2) receive good grades, and (3) learn as much as possible (1 = much worse, 2 = somewhat worse, 3 = about the same, 4 = somewhat better, and 5 = much better).

2.2. Data Analysis

According to our missing values analysis, one variable had missing data (9%), so we imputed the missing values using the expectation maximization (EM) method in SPSS. EM is efficient an efficient method to handle the data that are missing at random and provides estimates that are less biased than other methods (e.g., listwise deletion, pairwise deletion, mean imputation) [50]. To examine the relationships among the focal independent and dependent variables, we examined the bivariate correlations among them. Then, we entered the control, independent, and dependent variables into a multiple regression equation to assess the degree to which each culturally engaging campus environment indicator independently predicted growth in academic motivation when controlling for demographic characteristics and self-reported increases in academic motivation gains to college.
Before moving forward, it is important to note a couple of important limitations. First, this was a single institution study that included 704 students at one predominantly White four-year east coast university. However, while the single institution sample does constitute an important limitation, such studies can make significant contributions because they allow scholars to analyze phenomena that are not traditionally included in national datasets and shed important light on concepts and relationships that might not otherwise be understood. In the current study, the CECE model and survey focus on measuring the environmental constructs that are not typically found in national and regional surveys deployed by federal and state education agencies.
Second, as mentioned, our dependent variable included is a measure of self-reported gains in academic motivation during college. Researchers have provided evidence that self-reported gains are inherently biased and can lead to misleading results [45,46,47]. As previously discussed, we utilized the recommended method of addressing this limitation by controlling for precollege self-reported gains in the domain of the focal outcome [48]. It is possible, however, that such measures do not completely address potential bias in the participants’ self-reports of their academic motivation gains in college.

3. Results

The bivariate correlations are displayed in Table 3. The bivariate correlations among the nine CECE predictors ranged from 0.27 to 0.82 and were all positive and statistically significant at the 0.001 level. Given that a few of the CECE indicators were so strongly correlated, we analyzed the regression diagnostics to identify any potential multicollinearity. Although there is no existing consensus regarding which VIF and tolerance cutoff scores should be used, most researchers propose that VIF scores over 5 or 10 and tolerance scores less than 0.10 or 0.20 should be used to determine the multicollinearity is present and might bias estimates [45,46,47]. In the current analysis, all VIF statistics ranged from 1.0 to 4.6, and tolerance statistics were 0.22 or higher, suggesting that multicollinearity should not be a serious concern. The bivariate correlations between the CECE indicators and motivation ranged from 0.18 to 0.29 and were all statistically significant and positive at the 0.001 level.
The regression model produced an R-squared of 0.24 and an adjusted R-squared of 0.22. Among the demographic variables, age (β = 0.09, p < 0.01) and sex (β = 0.08, p < 0.05) were statistically significant, and both were positively related to the academic motivation outcome (Table 4). High school self-reported increases in motivation were also statistically and positively associated with the motivation outcome (β = 0.30, p < 0.001).
Our primary interest was in the predictive ability of the CECE indicators, and the results indicate that three of the nine indicators were statistically significant. Cultural validation (β = 0.24, p < 0.001) and humanized environments (β = 0.12, p < 0.01) were positively and significantly associated with academic motivation. In contrast, culturally relevant knowledge was statistically significant and negatively related to motivation (β = −0.16, p < 0.05). The other six CECE indicators were not statistically insignificant in the regression model.
Given that several significant positive bivariate correlations between CECE indicators and the academic motivation outcome became insignificant in the regression equation, and previous research suggests that some of these indicators might indirectly influence college outcomes [26,27], we conducted a post hoc analysis to examine whether such indirect relationships might exist in the current analysis. Prior research indicates that perceptions that campus environments are more characterized by cultural familiarity, culturally relevant knowledge, cultural community service, cross-cultural engagement, and collectivist orientations might lead to greater levels of validation, which in turn is associated with increased academic self-efficacy and sense of belonging in college [26,27]. If such relationships exist in the context of the current investigation, then several CECE indicators might be indirectly associated with academic motivation through their relationships with cultural validation.
To conclude that an indirect A => B => C relationship might exist, there must be evidence of a statistically significant association between the mediator (B) and outcome (C) variables, and a statistically significant correlation must exist between a predictor (A) and mediator (B). The initial regression provided evidence that cultural validation (the hypothesized mediator) is positively associated with academic motivation (the outcome), and this relationship is statistically significant. Therefore, the post hoc regression examined whether the other eight CECE indicators exhibited statistically significant relationships with the mediating indicator (cultural validation). The same demographic and precollege self-reported academic motivation gains were controlled in this post hoc model.
The post hoc regression generated an R-squared and adjusted R-squared of 0.69, indicating that this model explained a large portion of the variation in the cultural validation mediator. Regarding the specific relationships, four of the predictors were positively associated with the validation mediator, and all these relationships were statistically significant (Table 5). Culturally relevant knowledge (β = 0.61, p < 0.001) exhibited the strongest correlation with cultural validation, followed by collectivist orientations (β = 0.10, p < 0.001), cultural familiarity (β = 0.09, p < 0.01), and cross-cultural engagement (β = 0.08, p < 0.01). The other CECE predictors were not statistically associated with the validation mediator in the post hoc model. Therefore, the post hoc model provides some evidence that four out of the eight hypothesized indirect relationships might exist.

4. Discussion

A few major conclusions can be drawn from the current analysis. First, prior scholarship suggests that aspects of the campus environment might influence academic motivation [37] and peers [32,33,34,35,36,37,38,39,40,41,42,43,44,45]. For example, this scholarship indicates that connecting learning opportunities to real-world contexts and educators who use humor might be associated with higher levels of academic motivation. While these earlier findings provide some indication that culturally engaging environments might be important in maximizing academic motivation, the current inquiry adds to this knowledge by offering the first comprehensive systematic analysis of how the various elements of culturally engaging campus environments might be correlated with academic motivation in college.
Second, the current examination adds to the relatively small but growing body of knowledge about the potential impact of culturally engaging campus environments on student outcomes. Prior qualitative research provides some evidence that these types of environments might contribute to greater engagement, belonging, and success [19,20,21,22,23,54,55,56], and the existing quantitative analyses show that several CECE indicators are directly or indirectly associated with higher levels of academic self-efficacy and a greater sense of belonging in college [26,27,28,29,30,31,32,33,34,35,36,37,38,39]. The current investigation adds to this research by providing some initial empirical evidence that several aspects of culturally engaging environments might be related to increases in academic motivation during college as well.
Third, the findings complement the existing qualitative work that suggests a link between culturally engaging environments and undergraduates’ academic motivation [13,14,15,16,17,18,19,20,21,22,23,24,25]. For example, scholars have qualitatively documented how culturally engaging campus environments can increase college students’ engagement, resilience, and sense of belonging, which ultimately contribute to motivation [7,17]. The current study adds to this body of literature by providing evidence that these environments might be statistically linked to greater levels of academic motivation.
Fourth, the results of the current analysis reinforce the existing evidence that any potential influence of culturally engaging environments on student outcomes might be complex [26,27,28,29]. Extant research suggests that some elements of culturally engaging campus environments might not exhibit direct correlations with academic self-efficacy and sense of belonging when controlling for other CECE indicators but might be positively and indirectly related to these outcomes via their positive association with cultural validation [26,27,28,29]. The current study adds to this research by providing some initial evidence that the correlation between some CECE indicators and academic motivation also becomes statistically insignificant in a regression equation, and this change might be due to these indicators’ relationship with motivation being primarily indirect through validation. Specifically, our findings indicate that cultural familiarity, culturally relevant knowledge, cultural community service, and collectivist cultures might all be linked to college students feeling more validated, which might in turn be correlated with students being more motivated to succeed academically.
Related to the last point, our findings lead us to recommend caution when interpreting negative statistical relationships between the elements of culturally engaging environments and student outcomes. In the current analysis, the positive bivariate correlation between culturally relevant knowledge and academic motivation turned negative when these variables were entered into the regression equation, and this could be misleading. The fact that our post hoc analysis revealed a positive, indirect relationship between culturally relevant knowledge and academic motivation through the cultural validation indicator means that the culturally relevant knowledge coefficient might both positively influence academic motivation by increasing levels of validation and negatively shape motivation in other ways. For example, while the opportunities for racially minoritized students to learn about their communities’ histories and issues often include education about how inequitable social systems have disadvantaged these populations, the curricula that highlight minoritized communities can sometimes deploy deficit frames that blame these communities for the inequalities and challenges that they face [57]. Viewing students through such deficit framing might make them feel less motivated to succeed in college.

5. Conclusions

The results have multiple implications for research and practice. Regarding future research, scholars should seek to analyze larger samples from more diverse institutions. The previous research examining the relationship between culturally engaging environments and student outcomes has been multi-institutional or single-institutional studies (Museus et al., 2016, 2017, 2021). The current inquiry was also limited to one campus. To understand the degree to which the relationships between such environments and academic motivation are generalizable, future research should seek to capture more regionally and nationally representative samples.
In addition, researchers interested in better understanding the relationship between culturally engaging environments and academic motivation should consider utilizing methods that can support stronger causal claims in future studies. The current inquiry was based on cross-sectional data and self-reported gains. While we controlled for bias in self-reports, studies that deploy experimental and quasi-experimental designs are needed to make stronger causal claims. Many campuses now intentionally embed the elements of culturally engaging environments into the design and delivery of programs and services, and these initiatives might constitute valuable interventions to center in such future inquiries.
Regarding practice, the educators concerned with fostering greater academic motivation should make efforts to validate the cultural communities of all students (Rendón, 1994), if such action does not dehumanize other student populations. There is increasing evidence that they can achieve this by providing students with access to environments where they can connect with people who share their backgrounds (cultural familiarity), learn about their own cultural communities (culturally relevant knowledge), work across cultural differences to solve real-world social and political problems (cross-cultural engagement), and prioritize teamwork and mutual success (collectivist cultures). Faculty and staff should also prioritize cultivating humanized educational environments by ensuring that they convey and enact their commitment to students and their success. They can convey and enact this commitment by verbally communicating it with their words and by actions, such as being responsive to their undergraduates’ needs when these students encounter significant challenges on their journey.
It might be especially important to ensure that culturally relevant learning opportunities designed to also validate students’ cultural backgrounds and identities do not unintentionally have a negative impact on students’ academic motivation. It behooves educators to ensure that they are utilizing anti-deficit frames and validating students from diverse backgrounds when they design and deliver learning opportunities that center on issues relevant to students’ respective cultural communities. Such an approach might require that educators center on the structural causes of inequities and highlight the strengths of diverse communities—especially marginalized populations—when they center these groups in their curriculum. These efforts will also likely maximize the likelihood that culturally relevant learning opportunities increase and sustain, rather than diminish or eradicate, their students’ passion for education.

Author Contributions

Conceptualization, S.D.M. and K.S.; methodology, S.D.M. and K.S.; software, S.D.M.; validation, S.D.M. and K.S.; formal analysis, S.D.M. and K.S.; investigation, S.D.M. and K.S.; resources, S.D.M. and K.S.; data curation, S.D.M.; writing—original draft preparation, S.D.M. and K.S.; writing—review and editing, S.D.M. and K.S.; visualization, S.D.M.; supervision, S.D.M.; project administration, S.D.M. and K.S. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki and approved on 1 March 2018 by the Institutional Review Board (or Ethics Committee) of Indiana University (#1508894044).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

Data are available upon request.

Conflicts of Interest

The lead author is director of the National Institute for Transformation and Equity, which houses the CECE surveys and uses them to provide institutional assessment services to campuses across the U.S.

References

  1. U.S. Department of Education. Graduation Rates from First Institution Attended for First-Time, Full-Time Bachelor’s Degree-seeking Students at 4-Year Postsecondary Institutions, by Race/Ethnicity, Time to Completion, Sex, Control of Institution, and Acceptance Rate: Selected Cohort Entry Years 1996 through 2008; U.S. Department of Education: Washington, DC, USA, 2017.
  2. Museus, S.D.; Quaye, S.J. Toward an intercultural perspective of racial and ethnic minority college student persistence. Rev. High. Educ. 2009, 33, 67–94. [Google Scholar] [CrossRef]
  3. Martin, K.; Galentino, R.; Townsend, L. Community college student success: The role of motivation and self-empowerment. Community Coll. Rev. 2014, 42, 221–241. [Google Scholar] [CrossRef]
  4. Morrow, J.; Ackermann, M. Intention to persist and retention of first-year students: The importance of motivation and sense of belonging. Coll. Stud. J. 2012, 46, 483–491. [Google Scholar]
  5. Museus, S.D. The Culturally Engaging Campus Environments (CECE) Model: A new theory of success among racially diverse college student populations. In Higher Education: Handbook of Theory and Research; Paulsen, M.B., Ed.; Springer: New York, NY, USA, 2014; Volume 29, pp. 189–227. [Google Scholar]
  6. Blake, D.; Gasman, M.; Esmieu, P.L.; Samayoa, A.C.; Cener, J. Culturally relevant study abroad for students of color: Lessons from the Frederick Douglass Global Fellowship in London. J. Divers. High. Educ. 2020, 13, 158. [Google Scholar] [CrossRef]
  7. Druery, J.E.; Brooms, D.R. “It lit up the campus”: Engaging Black males in culturally enriching environments. J. Divers. High. Educ. 2019, 12, 330. [Google Scholar] [CrossRef]
  8. Gonzalez, E.; Ortega, G.; Molina, M.; Lizalde, G. What does it mean to be a Hispanic-Serving Institution? Listening to the Latina/o/x voices of students. Int. J. Qual. Stud. Educ. 2020, 33, 796–809. [Google Scholar] [CrossRef]
  9. Kiang, P.N. A thematic analysis of persistence and long-term educational engagement with Southeast Asian American college students. In Asian American Voices: Engaging, Empowering, Enabling; Zhan, L., Ed.; NLN Press: New York, NY, USA, 2009; pp. 21–58. [Google Scholar]
  10. Muñoz, S.M.; Espino, M.M. The freedom to learn: Experiences of students without legal status attending Freedom University. Rev. High. Educ. 2017, 40, 533–555. [Google Scholar] [CrossRef]
  11. Museus, S.D.; Neville, K.M. Delineating the ways that key institutional agents provide racial minority students with access to social capital in college. J. Coll. Stud. Dev. 2012, 53, 436–452. [Google Scholar] [CrossRef]
  12. Museus, S.D.; Ravello, J.N. Characteristics of academic advising that contribute to racial and ethnic minority student success at predominantly White institutions. NACADA J. 2010, 30, 47–58. [Google Scholar] [CrossRef]
  13. Samayoa, A.C. “People around Me Here, They Know the Struggle”: Students’ Experiences with Faculty Member’s Mentorship at Three Hispanic Serving Institutions. Educ. Sci. 2018, 8, 49. [Google Scholar] [CrossRef] [Green Version]
  14. Cisneros, J.; Bamgbola, O.; Guerrero, A.L.; Nguyen, C.N.; Pawa, V. An Examination of Asian International Students Sense of Belonging. J. Stud. Pers. Assoc. Indiana Univ. 2019, 92–109. Available online: https://scholarworks.iu.edu/journals/index.php/jiuspa/article/view/27216 (accessed on 1 July 2022).
  15. Francis, S.A.; Rios, A.G.; Olave, I.; Wassman, R. The invisible intersections of Afro-Latinx identity: A look within Indiana University’s African American and African diaspora studies department and Latino studies program curricula. J. Stud. Pers. Assoc. Indiana Univ. 2019, 65–91. Available online: https://scholarworks.iu.edu/journals/index.php/jiuspa/article/view/27221 (accessed on 1 July 2022).
  16. Garcia, G.A. Complicating a Latina/o-serving identity at a Hispanic serving institution. Rev. High. Educ. 2016, 40, 117–143. [Google Scholar] [CrossRef]
  17. Hang, A.; Walsh, N. Environmental Factors for Motivation of First-Generation Hmong American College Students in Academic Attainment. Educ. Q. Rev. 2021, 4. Available online: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3900498 (accessed on 1 July 2022).
  18. Kiyama, J.M.; Museus, S.D.; Vega, B.E. Cultivating campus environments to maximize success among Latino and Latina college students. New Dir. High. Educ. 2015, 2015, 29–38. [Google Scholar] [CrossRef]
  19. Shay, J.C. Engaging students at the intersections through multicultural centers: An application of the culturally engaging campus environment model. New Dir. Stud. Serv. 2017, 2017, 25–34. [Google Scholar]
  20. Montgomery, K.A. Supporting Chinese undergraduate students in transition at US colleges and universities. J. Int. Stud. 2019, 7, 963–989. [Google Scholar]
  21. Museus, S.D.; Mac, J.; Wang, A.C.; Sarreal, A.; Wright-Mair, R.; Manlove, J. How Asian American and Native American Pacific Islander-serving Institution (AANAPISI) Initiatives Respond to Institutional Racism. J. High. Educ. 2022, 93, 452–476. [Google Scholar] [CrossRef]
  22. Santa-Ramirez, S. Sink or swim: The mentoring experiences of Latinx PhD students with faculty of color. J. Divers. High. Educ. 2022, 15, 124–134. [Google Scholar] [CrossRef]
  23. Talusan, L.; Franke, R. Satisfactory Academic Progress and its Impact on First-Generation, Low-Income, Asian American Students. J. Crit. Scholarsh. High. Educ. Stud. Aff. 2019, 5. Available online: https://core.ac.uk/download/pdf/214368959.pdf (accessed on 1 July 2022).
  24. Williams, K.L.; Mobley, S.D.; Campbell, E.; Jowers, R. Meeting at the margins: Culturally affirming practices at HBCUs for underserved populations. High. Educ. 2022, 84, 1067–1087. [Google Scholar] [CrossRef]
  25. Wright-Mair, R.; Kluch, Y.; Swim, N.; Turick, R. Driving systemic change: Examining perceptions of high-impact practices for advancing diversity, equity, and inclusion in intercollegiate athletics. J. Issues Intercoll. Athl. 2021, 14, 599–625. [Google Scholar]
  26. Museus, S.D.; Williams, M.S.; Lourdes, A. Analyzing the Relationship between Campus Environments and Academic Self-Efficacy in College. J. Stud. Aff. Res. Pract. 2021, 1–15. [Google Scholar] [CrossRef]
  27. Museus, S.D.; Chang, T.H. The Impact of Campus Environments on Sense of Belonging for First-Generation College Students. J. Coll. Stud. Dev. 2021, 62, 367–372. [Google Scholar] [CrossRef]
  28. Museus, S.D.; Yi, V.; Saelua, N. The impact of culturally engaging campus environments on sense of belonging. Rev. High. Educ. 2017, 40, 187–215. [Google Scholar] [CrossRef]
  29. Museus, S.D.; Yi, V.; Saelua, N. How culturally engaging campus environments influence sense of belonging in college: An examination of differences between White students and students of color. J. Divers. High. Educ. 2018, 11, 467. [Google Scholar] [CrossRef]
  30. Blackwell, E.; Pinder, P. What are the motivational factors of first-generation minority college students who overcome their family histories to pursue higher education? Coll. Stud. J. 2014, 48, 45–56. [Google Scholar]
  31. D’Lima, G.M.; Winsler, A.; Kitsantas, A. Ethnic and gender differences in first-year college students’ goal orientation, self-efficacy, and extrinsic and intrinsic motivation. J. Educ. Res. 2014, 107, 341–356. [Google Scholar] [CrossRef]
  32. Harrison, C.K.; Martin, B.E.; Fuller, R. “Eagles don’t fly with sparrows”: Self-Determination Theory, African American Male Scholar-Athletes and peer group influences on motivation. J. Negro Educ. 2015, 84, 80–93. [Google Scholar] [CrossRef]
  33. Hossainy, F.N.; Zare, H.; Hormozi, M.; Shaghaghi, F.; Hossain, M. Designing and implementing a situated learning program and determining its impact on the students’ motivation and learning. Turk. Online J. Distance Educ. 2012, 13, 36–47. [Google Scholar]
  34. Komarraju, M.; Musulkin, S.; Bhattacharya, G. Role of student-faculty interactions in developing college students’ academic self-concept, motivation, and achievement. J. Coll. Stud. Dev. 2010, 51, 332–342. [Google Scholar] [CrossRef]
  35. Pan, Y.; Gauvain, M. The continuity of college students’ autonomous learning motivation and its predictors: A three-year longitudinal study. Learn. Individ. Differ. 2012, 22, 92–99. [Google Scholar] [CrossRef]
  36. Reynolds, A.L.; Sneva, J.N.; Beehler, G.P. The influence of racism-related stress on the academic motivation of Black and Latino/a students. J. Coll. Stud. Dev. 2010, 51, 135–149. [Google Scholar] [CrossRef]
  37. Weinstein, L. What motivates college students to learn? Coll. Stud. J. 2010, 44, 472–474. [Google Scholar]
  38. Chavous, T.M.; Richardson, B.L.; Webb, F.R.; Fonseca-Bolorin, G.; Leath, S. Shifting contexts and shifting identities: Campus race-related experiences, racial identity, and academic motivation among Black students during the transition to college. Race Soc. Probl. 2017, 10, 1–18. [Google Scholar] [CrossRef]
  39. Young-Jones, A.; Fursa, S.; Byrket, J.S.; Sly, J.S. Bullying affects more than feelings: The long-term implications of victimization on academic motivation in higher education. Soc. Psychol. Educ. 2015, 18, 185–200. [Google Scholar] [CrossRef]
  40. Hinton, P.R.; McMurray, I.; Brownlow, C. SPSS Explained; Routledge: New York, NY, USA, 2014. [Google Scholar]
  41. Larose, D.T.; Larose, C.D. Data Mining and Predictive Analytics; Wiley: Hoboken, NJ, USA, 2015. [Google Scholar]
  42. Osborne, J.W.; Costello, A.B. Sample size and subject to item ratio in principal components analysis. Pract. Assess. Res. Eval. 2004, 9, 11. Available online: http://PAREonline.net/getvn.asp?v=9&n=11 (accessed on 1 July 2022).
  43. Stevens, J.P. Applied Multivariate Statistics for the Social Sciences, 2nd ed.; Erlbaum: Hillsdale, NJ, USA, 1992. [Google Scholar]
  44. Tabachnick, B.G.; Fidell, L.S. Using Multivariate Statistics; Allyn and Bacon: Boston, MA, USA, 2001. [Google Scholar]
  45. O’brien, R.M. A caution regarding rules of thumb for variance inflation factors. Qual. Quant. 2007, 41, 673–690. [Google Scholar] [CrossRef]
  46. Schumacker, R.E. Regression discontinuity models and the variance inflation factor. Mult. Linear Regres. Viewp. 2008, 34, 13–18. [Google Scholar]
  47. Thompson, C.G.; Kim, R.S.; Aloe, A.M.; Becker, B.J. Extracting the variance inflation factor and other multicollinearity diagnostics from typical regression results. Basic Appl. Soc. Psychol. 2017, 39, 81–90. [Google Scholar] [CrossRef]
  48. Bowman, N.A. Understanding and addressing the challenges of assessing college student growth in student affairs. Res. Pract. Assess. 2013, 8, 5–14. [Google Scholar]
  49. Bowman, N.A. Can 1st-year college students accurately report their learning and development? Am. Educ. Res. J. 2010, 47, 466–496. [Google Scholar] [CrossRef]
  50. Porter, S.R. Self-reported learning gains: A theory and test of college student survey response. Res. High. Educ. 2013, 54, 201–226. [Google Scholar] [CrossRef]
  51. Bowman, N.A.; Hill, P.L. Measuring how college affects students: Social desirability and other potential biases in college student self-reported gains. New Dir. Inst. Res. 2011, 2011, 73–85. [Google Scholar] [CrossRef]
  52. Museus, S.D.; Zhang, D.; Kim, M.J. Developing and evaluating the culturally engaging campus environments (CECE) scale: An examination of content and construct validity. Res. High. Educ. 2016, 57, 768–793. [Google Scholar] [CrossRef]
  53. Schafer, J.L.; Olsen, M.K. Multiple imputation for multivariate missing-data problems: A data analyst’s perspective. Multivar. Behav. Res. 1998, 33, 545–571. [Google Scholar] [CrossRef] [PubMed]
  54. Museus, S.D. Generating Ethnic Minority Student Success (GEMS): A qualitative analysis of high-performing institutions. J. Divers. High. Educ. 2011, 4, 147. [Google Scholar] [CrossRef]
  55. Museus, S.D. The role of ethnic student organizations in fostering African American and Asian American students’ cultural adjustment and membership at predominantly White institutions. J. Coll. Stud. Dev. 2008, 49, 568–586. [Google Scholar] [CrossRef]
  56. Rendón, L.I. Validating culturally diverse students: Toward a new model of learning and student development. Innov. High. Educ. 1994, 19, 33–51. [Google Scholar] [CrossRef]
  57. Davis, L.P.; Museus, S.D. What is deficit thinking? An analysis of conceptualizations of deficit thinking and implications for scholarly research. Currents 2019, 1. Available online: https://quod.lib.umich.edu/cgi/t/text/idx/c/currents/17387731.0001.110/--what-is-deficit-thinking-an-analysis-of-conceptualizations?rgn=main;view=fulltext (accessed on 1 July 2022).
Education 12 00785 g001 550
Figure 1. Culturally Engaging Campus Environments and College Outcomes.
Figure 1. Culturally Engaging Campus Environments and College Outcomes.
Education 12 00785 g001
Table
Table 1. Descriptive Statistics.
Table 1. Descriptive Statistics.
MeanSt. Dev.
Age 21.204.50
Race
  Asian American0.050.22
  Black0.150.35
  Latina/o/x0.060.25
  Multiracial 0.030.16
  Native American0.030.18
Socioeconomic status0.570.55
Sex (Female)0.610.49
High School Motivation2.920.97
Cultural Familiarity (CF)3.070.99
Culturally Relevant Knowledge (CRK)2.860.97
Cultural Community Service (CCS)2.770.96
Cross-Cultural Engagement (CCE) 2.670.99
Cultural Validation (CV)3.020.96
Collectivist Cultural Orientations (CCO)3.040.99
Humanized Educational Environments (HE)3.370.99
Proactive Philosophies (PP)3.460.99
Holistic Support (HS)3.140.99
Academic Motivation (AM)3.550.97
Note: Race and sex variables were coded dichotomously (0 = no, 1 = yes), with White and male students serving as the referent categories respectively. For dichotomous variables, the reported mean is equivalent to the percentage of the sample who identify with the “1” category. Socioeconomic status was an ordinal variable indicating students self-reported background (0 = working class, 1 = middle class, 2 = upper class or rich). Race and sex subgroups with less than 10 cases were excluded from the analysis.
Table
Table 2. Names, Alpha Scores, Definitions, and Numerical Codes of Latent Constructs.
Table 2. Names, Alpha Scores, Definitions, and Numerical Codes of Latent Constructs.
Variable NameVariable Definitions and Codes
Control Variable
High school academic motivation
(α = 0.93) 		A latent construct measuring perceptions of growth in motivation to do the following during high school: (1) work hard in school, (2) get good grades, and (3) learn as much as possible from high school entrance to high school graduation.
Independent Variables
Cultural Familiarity
(alpha = 0.87)		A latent variable constructed using six indicators of the extent to which students were able to connect with people from similar backgrounds and who understand them: The extent to which (1) it is easy to find people on campus with similar backgrounds as me; (2) I frequently interact with people from similar backgrounds as me on campus; (3) it is easy to find people on campus who understand me; (4) it is easy to find people on campus who understand my struggles, and (5) people on campus are generally willing to take the time to understand my experiences.
Culturally Relevant Knowledge
(alpha = 0.93) 		A latent variable comprised of three indicators that measure the extent to which students had opportunities to learn and exchange knowledge about their own cultural communities: The extent to which (1) there are enough opportunities to learn about the culture of my own community; (2) there are enough opportunities to learn about my own cultural community’s history, and; (3) There are enough opportunities to gain knowledge about my own cultural community.
Cultural Community Service
(alpha = 0.95) 		A latent variable that was constructed using three items measuring the extent to which students had opportunities to give back and positively transform their cultural communities: The extent to which (1) there are enough opportunities to help improve the lives of people in my cultural community; (2) there are enough opportunities to give back to my cultural community, and; (3) there are enough opportunities to positively impact my cultural community.
Cross-Cultural Engagement
(alpha = 0.87)		A latent variable that was comprised of three survey items that measure the extent to which students had opportunities to engage in meaningful discussions with people from different cultures to solve real social and political problems across: The extent to which, (1) there are enough opportunities to discuss important social issues with people from different cultural backgrounds; (2) there are enough opportunities to discuss important political issues with people from different cultural backgrounds, and; (3) there are enough opportunities to discuss important diversity-related issues at the institution.
Cultural Validation
(alpha = 0.92) 		A latent variable that was constructed using three indicators measuring the extent to which students feel like they are valued by the campus community: The extent to which (1) people on campus value knowledge from my cultural community; (2) my cultural community is valued on campus, and; (3) people on campus value the experiences of people in my cultural community.
Collectivist Cultural Orientations
(alpha = 0.92)		A latent variable that was constructed using three indicators that measured the extent to which students had felt like the culture of campus was more collectivist and less individualistic: The extent to which (1) people on this campus help each other succeed; (2) people on this campus support each other, and; (3) people on this campus work together toward common goals.
Humanized Environments
(alpha = 0.92)		A latent variable that was constructed comprised of three indicators measuring the extent to which students felt like faculty and staff cared about them and were committed to their success: The extent to which (1) I view educators on campus as caring human beings; (2) educators care about students on this campus, and; (3) educators on this campus are committed to my success.
Proactive Philosophies
(alpha = 0.73) 		A latent variable constructed using two indicators measuring the extent to which students felt like faculty and staff proactively ensured that they had access to information, opportunities, and support: The extent to which (1) people on this campus often send me important information about new learning opportunities, and; (2) people on this campus often send me important information about support available on campus.
Holistic Support
(alpha = 0.90)		A latent variable consisting of three items measuring the extent to which students had access to one or more agents who they were confident would provide the information or support they need: The extent to which (1) if I need support, I know a person on campus who I can trust to give me that support; (2) if I have a problem, I know a person on campus who I can trust to help me solve that problem, and; (3) if I need information, I know a person on campus who I can trust to give me the information I need
Dependent Variable
Academic motivation
(α = 0.92)		A latent construct measuring self-reported growth in motivation to do the following during college: (1) work hard in school, (2) get good grades, and (3) learn as much as possible.
Note: All self-efficacy variables were coded on a five-point scale (1 = much worse, 2 = somewhat worse, 3 = about the same, 4 = somewhat better, 5 = much better). All campus environment survey items were coded: 1 = strongly disagree, 2 = somewhat disagree, 3 = neither agree nor disagree, 4 = somewhat agree, 5 = strongly agree.
Table
Table 3. Bivariate Correlations.
Table 3. Bivariate Correlations.
CFCRKCCSCCECVCCOHEEPPHSAM
CF---0.53 ***0.47 ***0.47 ***0.54 ***0.61 ***0.50 ***0.43 ***0.42 ***0.24 ***
CRK0.53 ***---0.82 ***0.45 ***0.80 ***0.51 ***0.40 ***0.42 ***0.31 ***0.24 ***
CCS0.47 ***0.82 ***---0.40 ***0.69 ***0.45 ***0.32 ***0.40 ***0.27 ***0.25 ***
CCE0.47 ***0.45 ***0.40 ***---0.48 ***0.61 ***0.45 ***0.47 ***0.29 ***0.16 ***
CV0.54 ***0.80 ***0.69 ***0.48 ***---0.54 ***0.42 ***0.45 ***0.35 ***0.31 ***
CCO0.61 ***0.51 ***0.45 ***0.61 ***0.54 ***---0.69 ***0.56 ***0.42 ***0.30 ***
HEE0.50 ***0.40 ***0.32 ***0.45 ***0.42 ***0.69 ***---0.46 ***0.47 ***0.28 ***
PP0.41 ***0.42 ***0.40 ***0.47 ***0.45 ***0.56 ***0.46 ***---0.55 ***0.22 ***
HS0.42 ***0.31 ***0.27 ***0.29 ***0.35 ***0.42 ***0.47 ***0.55 ***---0.18 ***
AM0.24 ***0.24 ***0.25 ***0.16 ***0.31 ***0.30 ***0.28 ***0.22 ***0.18 ***---
Note: *** indicates statistical significance at the 0.001 level. Variable abbreviations denoted in Table 2.
Table
Table 4. Regression Results.
Table 4. Regression Results.
Beta.St. Error.p-Value
Age0.090.010.01 **
Race
  Asian American0.010.150.73
  Black0.010.100.68
  Latina/o/x0.020.140.50
  Multiracial0.010.200.83
  Native American0.010.180.81
Socioeconomic status0.030.060.33
Sex (Female)0.080.070.02 *
High School Motivation0.300.040.00 ***
Cultural Familiarity0.020.050.70
Culturally Relevant Knowledge0.160.070.02 **
Cultural Community Service0.080.060.18
Cross-Cultural Engagement0.080.040.08
Cultural Validation0.240.060.00 ***
Collectivist Cultural Orientations0.110.060.07
Humanized Environments0.120.050.02 **
Proactive Philosophies0.020.050.64
Holistic Support0.000.040.90
Note: * indicates statistical significance at the 0.05 level. ** indicates statistical significance at the 0.01 level. *** indicates statistical significance at the 0.001 level.
Table
Table 5. Post-Hoc Results.
Table 5. Post-Hoc Results.
BetaSt. Errorp-Value
Cultural Familiarity 0.070.030.01 *
Culturally Relevant Knowledge 0.610.040.00 ***
Cultural Community Service 0.070.040.07
Cross-Cultural Engagement 0.080.040.02 **
Collectivist Cultural Orientations 0.100.030.00 ***
Humanized Environments 0.000.030.97
Proactive Philosophies 0.010.030.70
Holistic Support 0.040.030.12
Note: * indicates statistical significance at the 0.05 level. ** indicates statistical significance at the 0.01 level. *** indicates statistical significance at the 0.001 level.
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Museus, S.D.; Shiroma, K. Understanding the Relationship between Culturally Engaging Campus Environments and College Students’ Academic Motivation. Educ. Sci. 2022, 12, 785. https://doi.org/10.3390/educsci12110785

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Museus SD, Shiroma K. Understanding the Relationship between Culturally Engaging Campus Environments and College Students’ Academic Motivation. Education Sciences. 2022; 12(11):785. https://doi.org/10.3390/educsci12110785

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Museus, Samuel D., and Kiana Shiroma. 2022. "Understanding the Relationship between Culturally Engaging Campus Environments and College Students’ Academic Motivation" Education Sciences 12, no. 11: 785. https://doi.org/10.3390/educsci12110785

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