5.6 Poster 2

Universal-Diverse Orientation Among First-Year College Students

Lisa B. Spanierman, Ph.D., Helen A. Neville, Ph. D., Hsin-ya Liao, M.A., Ying-Fen Wang, M.Ed., & Sean Cheng, B. S. University of Illinois at Urbana-Champaign

As college campuses become increasingly racially and ethnically diverse, it has become important to learn more about students’ diversity attitudes and behaviors. Although unique experiences may occur for students throughout their academic careers, we believe that the first year is a critical time in their development. In order to develop effective diversity related programming, it is essential to examine students’ diversity orientations upon their entrance to the university. Little empirical research exists on the variables that may shape the diversity attitudes and behaviors of incoming first-year students. Therefore, the purpose of this investigation was to begin to develop a contextual model of first-year students’ diversity attitudes.

The present investigation used a mixed methods approach to examine students’ Universal Diverse Orientations (UDOs; acceptance and appreciation of similarities and differences among people as a function of culture). Based on a contextual model, we assessed the effects of a number of factors: (a) demographic and personal characteristics, (b) contextual factors (e.g., racial and class background), and (c) and racial attitudes as potential predictors of first-year students’ UDOs. Furthermore, we explored the effects for four racial/pan-ethnic groups (i.e., African American/Black, Asian American, Latino/a, and White) and a bi-/multi-racial group. Lastly, we also included a component that assessed parents’ UDOs to determine if parent scores were related to their children’s universal-diverse orientations.

Participants • Web-Based Survey. 1222 first-year college students at a large, predominately White university in the Midwest participated in the present study. 544 were men (44.5%) and 618 were women (50.6%); M = 18.18 years, SD = .60. Participants were: Asian/Asian American (n = 298; 24.4%), Black (n = 147; 12.0%), Latino/a (n = 124; 10.1%), Native American (n = 3; 0.2%), White (n = 551; 45.1%), Bi/Multi-racial (n = 78; 6.4%), and other (n = 20; 1.6%). • Parent Phone Interviews. 675 student participants provided parent contact information. Of the 339 parents who we were able to contact, 308 of them agreed to complete the survey; 222 (72%) were women and 86 (28%) were men. • Archival Data. A total of 915 student participants provided the name of their high school; information from 778 high schools was obtained. In addition, 731 participants provided permanent home addresses but only 724 of those were in the U.S. and were thus usable. ProcedureEarly in the fall semester, first-year students were contacted to participate in our web-based study via email. The incentive to participate was entry into a drawing to win cash a reward which resulted in a 52% response rate. In addition to completing web surveys, participants were asked to provide the following information: (a) name of the high school where they graduated from, (b) permanent home address, and (c) parent contact information. Parent telephone interviews were conducted throughout the remainder of the semester. Measures• Miville-Guzman Universal-Diverse Orientation Scale-Short (MGUDS-S; Fuertes, Miville, Mohr, Sedlacek & Gretchen, 2000). The 15-item scale was used to assess participants’ universal diverse orientations (i.e., openness to and appreciation of diversity). Coefficient alphas ranged from .81 (parent sample) to .87 (Asian subsample). • Color-blind Racial Attitudes Scale-Short (CoBRAS-S; Neville et al., 2004). The 14-item scale measured the extent to which participants minimize and/or distort the existence of racism in the U.S. For the present study, coefficient alphas ranged from .55 (Asian subsample) to .76 (total sample).• Demographic questionnaire was used to obtain information such as: age, sex, religion, race of close friends, name of high school, and permanent home address.• Census data regarding neighborhood racial and class composition were obtained through the U.S. Census Bureau website.• High school composition information was collected through on-line resources.

The results indicated that females, higher levels of religiosity, more multicultural courses taken, greater preference to vote for Kerry/Edwards, lower levels of ingroup friendships, higher levels of outgroup friendship, and lower levels of color-blind racial attitudes were significantly associated with higher levels of UDOs.

Table 1. Correlations of Demographic/Personal Variables and Color-Blind Racial Attitudes on UDOs among the Total Sample

Universal-Diverse Orientation

Demographic/Personal Variables Gender (Male = 0 and Female = 1) .24*** (1158) Religiosity .17*** (1159) Multicultural Courses .16*** (1158) Political Ideology (Bush/Cheney = 0 & Kerry/Edwards = 1) .23*** (757) Ingroup Friendship -.14*** (1063) Outgroup Friendship .27*** (1011) Color-Blind Racial Attitudes -.30*** (1176) Note. Numbers in the parenthesis are the sample size. *** p < .001.

Table 2. Regression Results Predicting UDO by Racial/Pan-Ethnic Groups

Universal-Diverse Orientation (as measured by the

MGUDS-Short) Racial/Pan-Ethnic Group

Asian/ Asian American

(n = 288)

Black (n = 125)

Latino/a (n = 117)

White

(n = 514) R2 .28 .18 .15 .29 SE (.61) (.68) (.68) (.60) R2 Change (After Adding Color-Blind Racial Attitudes)

.26*** .17* .13 .25***

Demographic/Personal Variables Gender .28*** .23* .14 .19*** Religiosity .20** .02 .05 .16** Multicultural Courses .03 .04 .14 .10* Political Ideology .15 † -.10 .09 .22*** Ingroup Friendship .05 -.16 .15 -.22*** Outgroup Friendship .26** .28** .10 .20*** Color-Blind Racial Attitudes -.15 † -.11 -.17 -.23*** Note. Standardized coefficients are presented. Higher values correspond respectively to female, higher levels of religiosity, more multicultural courses taken, greater preference to vote for Kerry/Edwards than Bush/Cheney, higher levels of ingroup friendships, higher levels of outgroup friendships, and higher levels of color-blind racial attitudes. † p = .06. *p < .05. ** p < .01. *** p < .001.

To examine contextual factors associated with individuals’ diversity attitudes, Pearson Product-Moment correlations were calculated between UDO and various contextual factors.

Table 3. Correlations of Contextual Variables on UDO

Total Sample

Asian/ Asian American

Black Latino/a White

HS-Asian .01 (777) -.03 (189) .02 (110) -.03 (73) .05 (347) HS-Black .10** (777) .05 (189) -.12 (110) .18 (73) .08 (347)

HS-Hispanic .11** (777) .05 (189) .13 (110) .05(73) .10 (347) HS-White -.15*** (777) -.05 (189) .06 (110) -.14 (73) -.13*(347)

SES .14*** (708) .03 (156) .04 (99) .16 (70) .09 (328) Dropout .09* (708) .03 (155) .08 (99) .01 (70) .09 (329)

Renter .12** (723) .10 (163) .13 (92) -.20 (79) .10 (320) Note. HS-Asian = Percentage of Asian students in the high school; HS-Black = Percentage of Black students in the high school; HS-Hispanic = Percentage of Hispanic students in the high school; HS-White = Percentage of White students in the high school; SES = Percentage of low SES students in the high school; Dropout = Dropout rate of the high school; Renter = Percentage of specified renter-occupied housing units in the neighborhood. Numbers in the parenthesis are the sample size. *p < .05. ** p < .01. *** p < .001.

Lastly, we assessed parents’ UDOs to determine if parent scores were related to their children’s universal-diverse orientations.

Table 4 Correlations of Parents’ Universal-Diverse Orientation and Students’ Universal-Diverse Orientation

Students’ Universal-Diverse Orientation Total

Sample Asian/

Asian American

Black

Latino/a

White Bi-/Multi-

Racial Parents’ Universal Diverse Orientation

.16** (308)

-.08 (50)

-.02 (46)

.22 (21)

.21** (160)

.26 (27)

Note. Numbers in the parenthesis are the sample size. ** p < .01.

Part I. Effects of Demographic/Personal Variables and Racial Attitudes on Universal-Diverse Orientations (UDOs)

Part II. Effects of Contextual Variables on UDOs

Part III. Effects of Parents’ Universal-Diverse Orientation

We then performed multiple regression analyses to examine the relative importance of the above predictors on UDOs by each racial/pan-ethnic group. Later, we performed a hierarchical regression to examine the incremental effect of color-blind racial attitudes after controlling for the demographic/personal variables; this incremental effect was significant in Asian/Asian American, Black, and White samples (p < .05).

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Although many of the demographic/personal variables were significantly associated with students’ UDOs for the entire sample, this was primarily true for the White sample only. This might be due to the fact that racial minorities exhibit higher levels of UDO. Additionally, color-blind racial beliefs significantly predicted UDO for the White sample only. For White students, the strongest predictors of UDO were political ideology, friendship group composition (i.e., ingroup and outgroup friendships), and color-blind racial beliefs. For Blacks and Asian/Asian Americans, we found that gender and outgroup friendships were significant predictors of UDO; religiosity was also a significant predictor for Whites and Asian/Asian Americans. Among the Latino sample, no predictors were significant. Many of the contextual variables (e.g., neighborhood racial composition, high school social class composition, etc.) were associated with the total sample UDOs, but not for any specific racial group. Lastly, we found that parents’ UDOs were significantly associated with children’s UDO for the White sample only. Because we only recruited participants from one university in the Midwest, we recommend that the present study be replicated with students in diverse geographical locations to determine the generalizability of the findings. Furthermore, future research should focus on additional contextual variables such as focus on diversity issues in the high school. Because the results were strikingly different for Whites and racial minorities in this study, perhaps diversity interventions should be designed differently for these student populations. For example, developing awareness of institutional racism and White privilege might be more important for White students than for racial minority students. Conversely, it seems important that university administrators facilitate environments in which all students, regardless of race, can establish friendships with people of other races.