Abstract
As state-level merit-based financial aid programs proliferate, analysts both find that these programs have a disproportionate effect on students traditionally under-represented in postsecondary education and question the use of limited public resources in an inefficient and inequitable manner. This study, using survey data regarding the perceptions of all potentially eligible scholarship recipients, explores the impact the Tennessee Education Lottery Scholarship on college access for minority and low-income students. The empirical results indicate that African American and low-income students are more likely to perceive their eligibility for merit-based scholarships as having an impact on their decision on whether or not to attend college. A consequential policy implication is that a liberally awarded merit-based scholarship program, while inefficient, may provide sustainable access for those students in greatest need of financial aid.
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Notes
Since the publication of these reports, the Civil Rights Project has moved to University of California, Los Angeles.
With regard to survey mechanics, high school principals from sampled schools received a letter requesting participation signed by the Executive Director of the Tennessee Higher Education Commission and the State Commissioner of Education. This official letter served to legitimate and convey the importance of survey completion with the ultimate hope that high schools would agree to participate. It is unlikely, however, to have engendered a particular substantive student response bias with regard to the questions analyzed in this study. In part, this is due to the frequency in which Tennessee high school students are surveyed. Moreover, a student response bias is unlikely because there was no link to the Tennessee Student Assistance Corporation, the state agency most recognized by students as making financial aid decisions.
As discussed earlier, the data were obtained through a stratified, rather than simple, random sample. The standard errors obtained from an estimation method that ignore a complex sampling design would be biased downward thereby making it much easier to obtain statistically significant findings.
In its first year, the Tennessee Lottery experienced sales that topped the billion dollar mark. By statute, approximately 25% of state lottery sales (or $250 million for academic year 2004–2005) was appropriated for merit aid scholarships.
Since the initial adoption of the lottery scholarship program, the State of Tennessee has enacted two major changes. First, in 2004, the state raised the eligibility criteria for the standardized test component from a 19 ACT score to a 21 ACT score. While raising the standardized test component of the scholarship eligibility requirement could be a tremendous setback for a program that is potentially situated to serve as an exemplar for providing wide access in a politically palatable manner, the 21 ACT score remains liberal relative to other state programs. Second, in 2005, the state increased the award amounts of the base scholarships by 10% and increased the need-based supplemental award by 50%. Eligible students with income levels below $36,000 will now receive scholarships up to $4,800 per year, which exceeds the cost of tuition at all Tennessee public universities. This suggests that Tennessee is committed to its original aim to increase college access.
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Acknowledgement
We thank Laura Perna, Michael Paulson, Ken Redd, and two anonymous reviewers for their helpful comments on earlier versions of this article.
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Appendix: Selected Explanatory Variables
Appendix: Selected Explanatory Variables
The explanatory variables constructed for this study are grounded in previous studies from the college access literature. The purpose of this appendix is both to cite these relevant studies informing our study and, when applicable, to report how our measurement approach or data limitations may affect our findings.
Socioeconomic Status I—Income
Hu and Hossler (2000) advocate the use of a three-layered set of dummies: $35,000 or less; $50,000 or beyond; and $35,000–$50,000 (reference category). Including what amounts to be one additional dummy indicator into our specification does not alter either our principal income-oriented or race-based substantive conclusions. Perna and Titus (2004), however, make a persuasive case to create some sort of continuous SES composite index, rather than a single (or separate) measure(s) of financial resources. We take particular note to their comments regarding the interpretation of family income and potential for missing data problems. Nevertheless, given the importance of the $36,000 threshold (which will enable some students to increase their scholarship awards by one-third), missing family income data is rare (approximately 5%). We further justify this approach since this study considers only Tennessee students, who demonstrate less disparity than there may be across the nation. Admittedly, Perna and Titus (2004), who are inspired by Adelman (2002), raise a reasonable issue of weighting family income by family size. We are, however, unable to do this with our data.
Socioeconomic Status II—Parents Education
St. John and Paulsen (2001) and Paulsen and St. John (2002) contribute to the inclusion and construction of this variable. Additionally, Hu and Hossler (2000) recommend an alternative framework comprised of a set of dummies: high school or below; post college and beyond; some college or college (reference group). Our principal empirical results remain virtually unchanged (from a substantive standpoint) if we adopt this coding scheme.
Socioeconomic Status IV—Financial Aid Awareness
According to Long (2004), lack of information about financial aid programs may have implications for college access. Thus, we create a dichotomous measure of student familiarity with financial aid opportunities other than the Tennessee Education Lottery Scholarship. Some of the types of financial aid listed in the questionnaire include: Pell grants, Federal loans (Stafford/Perkins), TSAA/state grants, institutional scholarships and grants, ROTC scholarships, and scholarships offered by local organizations (i.e., churches, Rotary Club, etc.).
Scholarship Eligibility I—Standardized Test Performance
Tennessee is by and large an ACT-oriented state. Approximately 85% of the high school graduating class of 2004 took the ACT with a very small proportion of students electing to take the SAT. Over the last 15 years, higher education researchers have consistently found a positive relationship between test score performance and investment in higher education (Hossler et al. 1989; St. John 1991; Perna 2000; Beattle 2002; Perna and Titus 2004). By attempting to fuse the merit aid and college access literatures, some of our variable operationalizations may appear a bit unorthodox. Given the outcome variable of interest (perceived effect of merit aid on whether to attend college), we believe that this dichotomous eligibility variable is the most appropriate measure. We should note, however, that our results remain virtually unchanged (in terms of direction of effects and statistical significance of coefficients) irrespective of a variety of operational choices (i.e., a fully “continuous” measure of ACT or some other categorical breakdown).
Academic Preparation II—Highest Level of Math Taken
Perna and Titus (2004) cite several scholarly works (Adelman 1999; Perna 2005; Stevenson et al. 1994) that suggest high school curriculum is an unreliable measure of college preparation. Instead, Perna and Titus (2004), following Adelman (1999), suggest a variable that reflects the highest level of coursework completed in certain subjects (particularly math) as a more viable alternative. As such, we created a set of dummy categories—took Algebra I and Geometry, took Algebra II, and took one advanced math—and compared them with a reference group of other or no math.
Academic Aspirations
Based on the work of DesJardins (2001) we consider the idea of highest expected educational level. This is expressed operationally as a series of dummy indicators: high school or vocational degree; Associate’s (2-year degree); Bachelor’s (4-year degree-reference group); master’s degree; and Ph.D. or professional degree (i.e., law, medicine). Hu and Hossler (2000) offer a simpler taxonomy by collapsing these into three categories: vocational-technical and 2-year college; master’s or professional degree; and, 4-year college (reference group). Our overall conclusions are robust to this design consideration. We should note, however, that given that the dependent variable in Columns 3 and 4 of Table 2 is defined, in part, by students’ educational plans, we restrict their inclusion to Column 1.
Academic Achievement—High School Rank and School Quality
The merit-aware index recommended by Goggin (1999) serves as a proxy to high school rank and school quality included in St. John et al. (2001). This measure is produced by subtracting the school’s mean ACT score from the respondent’s. We should note that mean Tennessee high school ACT scores were purchased from ACT (http://www.act.org), in Iowa City, IA. The merit-aware index is constructed as follows: MAI = ACTstudent − ACTschool average.
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Ness, E.C., Tucker, R. Eligibility Effects on College Access: Under-represented Student Perceptions of Tennessee’s Merit Aid Program. Res High Educ 49, 569–588 (2008). https://doi.org/10.1007/s11162-008-9096-5
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DOI: https://doi.org/10.1007/s11162-008-9096-5