Estructura legislativa anterior

Mean SE Mean SE Significance

CULTURAL CAPITAL

College aspirations prox.

Network 3.061 .092 3.013 .130

Parent HS or less .241 .036 .314 .048

Parent some college .277 .039 .327 .047 *

Parent BA .244 .032 .199 .043 Parent involved in cultural activities w/student 2.730 .054 2.870 .063 * Parental encouragement 2.291 .041 2.372 .043 * Participation in extracurricular activities 3.201 .145 2.836 .183 SOCIAL CAPITAL Parent to parent involvement .701 .025 .768 .028 * Parent to school involvement .268 .019 .288 .029 # of friends w/ 4-year plans 3.980 .051 3.671 .076 *** SOCIAL CAPITAL- COLLEGE LINKING Counselor .906 .021 .913 .023 Coach .095 .019 .135 .035 Friend .589 .034 .604 .045 College representative .741 .032 .786 .036 School library .169 .028 .196 .039 *p.05, **p<.01, ***p<.001

Results of the Independent T-Test analysis found significant mean value

differences in college choice behavior across all three models of the present study. Race was significant in the applied and enrolled models, but only for Asian students in the enrolled model. Differences in human capital investments operationalized by level of academic preparation were uncovered across all three models with students who applied, were admitted, and enrolled at highly selective colleges associated with greater levels of academic preparedness. Mean value differences in economic capital were significant in

the applied and enrolled model, particularly related to the importance of college affordability and if a loan was offered. Significant economic capital value differences were found in the admitted model only around if a loan was offered. The economic capital variables were associated with positive college choice behavior in the admitted model, but in the applied and enrolled models these variables were associated with positive and negative college choice behavior. Cultural capital value differences were associated with positive college choice behavior in the applied and admitted models, with the exception of parental education levels of some college, but no BA degree, which was associated with negative college choice behavior across all three models. However, in the enrolled model, all significant differences in cultural capital values were associated with negative college choice behavior. Social capital value differences as operationalized in peer networks were significant across all three models, with variances in peer social capital associated with positive college choice behavior. Finally, only in the applied model were significant differences found in the use of college linking resources, however these differences were associated with positive college choice behavior.

The statistically different mean value differences in college choice behavior throughout the three models across demographics and the different forms of human, economic, cultural, and social capital warranted further investigation through logistic regression analysis. Results from the logistic regression analysis are presented next and in Tables 8, 9, and 10.

Logistic Regression Analysis

Logistic regression analysis was completed to better understand the influence of demographics, human, economic, cultural, and social capital on the likelihood of

academically qualified, low income students applying, being admitted to, and

eventually enrolling at highly selective postsecondary institutions. First, the decision to apply to a highly selective postsecondary institution was regressed on the applied model for the entire sample of academically qualified, low income students. Next, the decision to admit at a selective postsecondary institution was regressed on the admitted model only for those students in the initial sample who had applied. Finally, the decision to matriculate at a highly selective postsecondary institution was regressed on the enrolled model only for those students who had been admitted. In the enrolled model, the type of financial aid offered at the first postsecondary institution attended was added as a

covariate.

The results of the logistic regression analysis are presented according to each of the three models to better understand the influence these various forms of capital have in each of the different phases of the college choice process. Results for the applied model are presented in Table 8, the admitted model in Table 9 and the enrolled model in Table 10. The results of the logistic regression analysis provided important information about how the various forms of capital influenced behavior at certain phases of the college choice process and not others, and how certain forms of capital predict behavior across all phases of the college choice process.

Applied Model

In the applied model, academically qualified, low income students’ decisions to apply to a highly selective postsecondary institution were regressed on the different demographic, human, economic, cultural, and social capital constructs. The pseudo r- square values confirm the model predicts an acceptable amount of the variance in

application behavior (Cox and Snell = .247, Nagelkerke = .356) and the results

therefore merit further consideration. The most significant predictors of application to a highly selective postsecondary institution were race, academic profile, peer and proximal networks and use of college linking resources. Economic and cultural capital constructs were not significant predictors of application to a highly selective postsecondary

institution. Academically qualified, low income student application to a selective postsecondary institution was largely influenced, therefore, by the student’s race, academic preparation, and availability of resources in their respective social network. Demographics

Academically qualified, low income Asian and Black students were significantly more likely to apply to a highly selective postsecondary institution than academically qualified, low income White students controlling for all other variables in the model. Asian students were more than three and a half times as likely to apply and Black students were more than two and half times as likely to apply. These results are consistent with previous research that concluded Asians and Blacks have higher

educational aspirations than Whites and tend to submit greater numbers of applications to postsecondary schools (e.g. Berkner & Chavez, 1997; Hurtado, et al., 1997; Perna, 2000). Being Hispanic or of a race that was not Asian, Black or Hispanic did not significantly influence application behavior.

Human Capital

Consistent with previous research (e.g., Ellwood & Kane, 2000), enhanced academic preparation was associated with a greater likelihood of applying to a selective postsecondary institution. A student’s academic preparation had the most significant

influence, increasing by nearly five times the odds that a student would apply to a highly selective postsecondary institution. All other variables in the human capital construct (savings efforts for college, importance placed on career and education, and participation in academic enhancement programs) had no significant influence on an academically qualified, low income student’s application to a highly selective college. Economic Capital

The logistic regression analysis yielded no significant findings around the

influence of any of the variables that comprised the economic capital construct during the application phase.

Cultural Capital

The number of people in the student’s proximal network that had postsecondary aspirations for the student had a significant effect on the likelihood of application. With each additional person in the student’s proximal network who had postsecondary

aspirations for the student, the student’s odds of applying to a highly selective college increased by 15%. Level of parental education, involvement in cultural activities, participation in extracurricular programs, and parental encouragement did not

significantly increase the odds that an academically qualified, low income student would apply to a highly selective college.

Social Capital

Although the findings suggest parental engagement did not predict student application to a highly selective postsecondary institution, the same is not true for peers. Significant effects were found for the number of the student’s friends who planned to attend a four year institution. Each additional friend with four year college aspirations increased the odds that an academically qualified, low income student would apply to a

highly selective college by nearly one and a half times. Parental involvement with the student’s school and parental relationships with the parents of the student’s closest friends did not significantly increase the odds that an academically qualified, low income student would apply to a highly selective college.

College Linking Resources

Significant effects were uncovered in the use of counselors, coaches, and college representatives to gain information about the college choice process. Academically qualified, low income students who used coaches and college representatives in the college choice process were nearly two times more likely to apply to a highly selective postsecondary institution than students who did not use these resources, and students who sought information from a school counselor were more than two times as likely to submit an application as students who did not use a counselor. These findings underscore the importance of these college linking resources given the significance of their influence in the first stage of the college choice process. For example, although the directionality of this effect is uncertain, it can also be speculated that it is unlikely a student would have decided to submit an application to a school without first having sought information about that school. Using a friend or the school library to acquire information during the college choice process did not significantly increase the odds that an academically qualified, low income student would apply to a highly selective college.

Table 8. Imputed logistic regression results predicting application to highly selective postsecondary institutions among academically qualified, low income students (Weighted N= 348,044)

B Std. Error Exp (B)