9 Matching Annotations
  1. Dec 2015
    1. Gonzalez Canche`, M.S. (2014). Is the community college a less expensive path toward a bachelor’s degree? Public 2- and 4-year colleges’ impact on loan debt. The Journal of Higher Education, 85 (5), pg. 723-759.

      Gonzalez Canche` (2014) analyzed differences of loan amounts that students from two year public colleges compared to students attending four year public institutions in order to see if there is a difference between loan borrowing behavior among the two groups. The author used the Kernel matching procedure and the Ordinary Least Squares method to compare the two groups to determine if there is a significant difference (pg. 740). According to the previous studies cited in the article, students who attended for-profit institutions had the highest default rate with student loans, but previous studies did not account for student characteristics who may choose a for-profit versus non-profit institution (pg. 728).

      After Gonzalez Canche(2014) studied the different types of institutions students attend and matched students on various characteristics, is was determined that student who attended more affluent colleges and universities had lower amounts of debt upon graduation as well as a decreased likelihood of defaulting on loans that were taken out (pg. 727). For example, if a student attend a private, non-profit college with a higher level of socioeconomic statuses among students, than the students will be less likely to obtain student loan debt or default on their loans compared to students at less selective four-year universities or community colleges. Gonzalez Canche believes this is due to the students’ at more selective colleges having “more support to attend college from both of their parents, relatives, high school teachers and counselors” (pg. 740). In fact, it was noted that “community college students systematically had fewer sources of support than their counterparts in the four-year sector”, which could lead to community college students having higher loan amounts and are “at a greater risk of dropping out before earning their degree” (pg. 748).

      Gonzalez Canche(2014) points out that policymakers tend to encourage low-income students to attend community college prior to four-year universities, but according to the findings, this may not be the best option for low income students who also have “high probabilities of succeeding academically and professionally” (pg. 749). Even though community college students tended to have less support when pursuing their degree, the study found that students who began at the community college had similar amounts of loan debt upon graduation compared to their counterparts who started at the four-year public college (pg. 750). Gonzalez Canche recommends that policymakers, and others who work with students, should not necessarily tout the two year community college as a less expensive option and that it may, in fact, be better for some low and middle-income students to begin directly at the university (pg. 752).

      After these findings from Gonzalez Canche`, policymakers, teachers and counselors in high schools, and admissions staff at community colleges and universities should be aware of the additional debt that may be accrued while students attend community college, as a result of likely taking additional time to complete their degree, and additional student loan debt, compared to if the student would have started directly at the university. It cannot be ignored that Washington state has one of the highest amounts of state need-based grants for low-income students, so the university may be a more realistic and financially responsible decision for low-income students who qualify for need-based aid programs.

    2. Kelchen, R. and Goldrick-Rab, S. (2015). Accelerating college knowledge: A fiscal analysis of a targeted early commitment pell grant program. The Journal of Higher Education, 86 (2), pg. 200-231.

      Kelchen and Goldrick-Rab (2015) completed a cost-benefit evaluation of a Pell Grant program that would target students as early as eighth grade in order to guarantee low-income students that they would have financial support throughout their college education to subsidize, if not cover all of, their college education. The risk of implementing an expanded Pell Grant program in order to guarantee college tuition funds to low-income students in eighth grade is that some students may not remain low-income and then the program would over-award the Pell Grant to students who were no longer eligible (pg. 210). However, in the study the researchers found that 81 percent of low-income students remained eligible for low-income programs in tenth grade, but only 69% of students remained eligible between eighth and twelfth grade (pg 209). The authors attribute this decline to a reduced amount of students seeking out low-income programs (such as free/reduced lunch in high school) as a result of stigma and increased lunch options, low income students dropping out of high school, as well as some families having an increase in their family income (pg. 209).

      Even though over-awarding may occur because students do not necessarily remain eligible for low-income programs, the authors cost-benefit analysis still found that the costs of over-awarding financial aid are less than the expected “benefits… [of] at least $2.1 billion per cohort, suggesting that the program should be cost-effective under the majority of assumptions” (pg. 223). Much of the prior research shows that students self-select out of college before eighth grade because they do not believe they have the financial resources to pay for a college education, which is the argument for promising the Pell Grant to students across the nation if they meet certain income eligibility requirements in eighth grade (pg. 213).

      The state of Washington has implemented the College Bound Scholarship program, which promises eighth grade students who meet income eligibility requirements that their entire tuition will be paid for at any public state university or community college within the same state. According to the Washington Student Achievement Council’s website, this program has increased the college-going rates of low-income students compared to low-income students who do not sign up for the program. The authors recognized that Washington state was one of three states that started an early commitment program for low-income students, but the authors did not report on the results. The federal government should take notice of the impact of similar state programs throughout the nation to determine if the cost-benefit of implementing a federal program would be worth it. From the recent study by Kelchen and Goldrick-Rab as well as the results from Washington state, the answer seems to support the implementation of a federal early commitment Pell Grant program.

  2. Nov 2015
    1. Alexander, F.K., Harnisch, T., Hurley, D., and Moran, R. (2010). Maintenance of effort: An evolving federal-state policy approach to ensuring college affordability. Journal of Education Finance, 36 (1), pp. 76-87.

      Alexander, Harnisch, Hurley and Moran (2010) examine positive and negative impacts of the federal government implementing Maintenance of Effort (MOE) funding, in which the federal government matches funds to state governments who maintain higher education funding at or above previous levels of funding. “The congressmen [who supported the MOE in 2007] argued that such incentives would help ensure that federal monies were used to supplement state resources for public higher education – not supplant them” (pg. 77). This type of legislation was especially important during the recession because many state governments were looking to cut spending, but advocates argued that a decrease in higher education funding has negative impacts on the economic vitality of the state and nation (pg. 78).

      MOE programs have been used across other governmental sectors to encourage state governments to maintain funding levels for programs, such as Individuals with Disabilities Act (IDEA) and Temporary Assistance to Need Families (TANF). The authors point out that “student grant aid programs now exist in all but one state… [and] that many of these programs today disproportionately aid private-sector and high-priced institutions because they tend to aware more aid to students attending more costly institutions” (pg. 78). In the 1970’s, lobbyists from private institutions supported MOE programs “as a means to create state funding streams to all institutions”, which is one example of how an interest group can impact governmental funding (pg. 78).

      The authors recognize positive impacts of MOE funding for higher education as a way for the federal government to assist with its goal of “increasing educational attainment rates among the nation’s citizens”, yet at the same time, have the bulk of funding and responsibility fall to the states (pg. 81). Another positive impact is that states are discouraged from decreasing funding for higher education, which helps students by paying lower tuition rates and will also likely decrease the student loan debt (pg. 81).

      There are also groups such as the National Governors Association and the National Conference of State Legislatures who have argued against MOE funding (pg. 82). Some of the drawbacks include that the federal government is overstepping boundaries and the responsibility of higher education funding should fall to each state (pg. 84). Other arguments noted by the authors include that funding based on MOE standards creates inequities between states and a major problem with MOE funding is it discourages capital, research and development projects because, as an unintended consequence, these types of projects are not eligible for matching MOE funds (pg. 84).

      The authors point out certain states funding from 2006 compared to 2010 and Washington is listed as a state that increased its budget for higher education by nearly six million dollars in this timeframe (+0.45%) (pg. 86). The authors seem to advocate for a “shared responsibility between the federal and state governments to enhance college affordability” and recognize that MOE “provisions can serve as an effective policy tool in ensuring states’ commitment to funding higher education” (pg. 86).

      • N. Brusseau
    2. Tiboris, M. (2014). What’s wrong with undermatching? Journal of Philosophy of Education, 48 (4), pp. 646-664.

      Tiboris (2014) recognizes that the idea of ‘undermatching’ is a new topic being studied and needs additional research. However, from the studies that have been conducted it has been determined that “undermatched” students are those who choose to attend a post-secondary school that is less selective than those for which they are academically qualified, or are perhaps qualified to go to college but choose not to apply” (pg. 646). Studies have found that approximately forty percent of students “enroll in a college below the selectivity level they could have attended” (as cited in Tiboris, pg. 647). The concern with undermatching is that students who attend more prestigious institutions tend to have better career outcomes and higher pay compared to students who attend less prestigious colleges (pg. 647).

      This occurs across all students, but students from lower socioeconomic statuses or first-generation college students tend to be ‘undermatched’ at a higher rate (pg. 646). This is a problem because institutions may be reinforcing achievement gaps between certain populations and have a huge impact on students’ success later in life (pg. 649). In order to combat this trend, Tiboris argues that low-income students should be targeted to receive more information and funding opportunities to attend selective universities (pg. 649). However, this solution only assists students who actually want to attend a more selective institution because the student would then have a better understanding of their options and can more likely make the choice for themselves. But what if a student actually desired to attend the less selective college?

      Tiboris poses the question: is undermatching a problem? Tiboris believes that undermatching is not a problem as long as the student has made the decision about which college to attend autonomously, but more research is necessary (pg. 648). Tiboris recognizes that it may be difficult to determine if a student is making an autonomous choice, but believes that “critical reflection” is an essential component of making the decision (pg. 654). It must be noted that Tiboris seems unsure if critical reflection can, in fact, lead an individual to their true preference because they may be heavily influenced by “historical conditioning”, with regards to expectations for their population (pg. 657).

      Tiboris points out that students may autonomously choose a less selective institution for reasons such as “wanting to stay closer to home, a desire to maintain certain cultural or religious practices, [or] personal distaste for city life” (pg. 651). There may be a number of reasons a student chooses a less selective college over their ‘matched’ institution. In fact, while working in the Admissions Office at WSU Vancouver, I have worked with a number of students who are academically prepared for WSU Vancouver, but the way the courses are offered are inconvenient and so the student has decided to attend the local community college instead.

      Tiboris states that “…policies intended to reduce undermatching will be morally problematic if they fail to respect the diverse values and preferences of different groups…” (pg. 649). Instead, Tiboris’ recommends that “we make stronger efforts to help students recognize and work with the reality that their preferences are often artifacts of their upbringing and culture” and college take specific (pg. 658).

      N. Brusseau

    3. Houle, J.N. (2013). Disparities in debt: Parents socioeconomic resources and young adult student loan debt. Sociology of Education, 87 (1), pp. 53-69.


      Houle (2013) conducts a study to see if there are correlations between the amount of loans a student commits to while a college student and the student’s socioeconomic status. This study uses secondary data from the National Longitudinal Study of Youth 1997 as well as the Bureau of Labor Statistics from nearly 9,000 college students. It is important to note that the sample was representative compared to national college student data in regards to race/ethnicity, socioeconomic status, and accumulated student loan debt. However, the sample had “more advantaged backgrounds [compared to] the general population”, which Houle believes is attributed to the entire sample having college experience (pg. 58). The sample was then asked to respond to a survey about their total student loan debt, but did not differentiate between governmental and private student loans.

      Once the data was collected, Houle used the ordinary least squares regression model and Craggit model to analyze the data. Houle determined that approximately forty percent of respondents had some form of student loan debt with the average amount of $22,940, which were both similar to national averages (pg. 58). Some interesting findings include that students who completed their college degree tended to have significantly higher debt amounts compared to students who did not finish their college degree, students who attended private institutions tended to have higher amounts of student loan debt compared to students who attended public colleges, and African Americans were also noted as having significantly higher amounts of student loan debt compared to white students.

      I believe one of the most interesting findings is consistent with previous research as the “middle-income squeeze perspective”, where the middle-income students are the most likely to have the highest amounts of student loan debt compared to high-income and low-income students (pg. 58). Houle points out the progress that a program at UC-Berkeley may have for middle-income families in which the “Middle Class Access Plan” limits the cost of tuition for middle-income families at 15% of the family’s income (pg. 63).

      Even though these findings will hopefully encourage institutions to examine their own student population, this national study provides an example of possible methods that can be used. Administrators, political actors and college leadership should examine their own financial aid and scholarship policies to ensure the merit scholarships and grants are not only primarily being awarded to high-income and low-income students, while leaving the middle-income students to take on the most student debt. Houle recognizes that the study does not answer, or even ask, the question of “Will their debt (investment) pay off? Or, will their debt lead them to lag behind their more advantages counterparts?” (pg. 66). These types of questions need to continually be asked to validate whether or not the amounts of loans students are committing to will actually pay off.

      N. Brusseau

  3. Oct 2015
    1. Seneca, J.J. and Taussig, M.K. (1987). Educational quality, access, and tuition policy at state universities. The Journal of Higher Education, 58 (1), pp. 25-37.

      Seneca and Taussig (1987) investigate the impact tuition policies can have a two missions that many state universities seem to focus on – access for underserved populations and providing a high quality education. By analyzing data from thirty state universities, the authors hypothesized that as tuition policies force students to pay more for their college education (tuition increases), then the quality of education also increases. On the other hand, the authors also hypothesized that as a result of higher tuition rates, then access to that specific state university decreases for low-income families.

      As a current member of the Strategic Planning Committee at a state university, I can attest that the state university I have experience with is striving to increase access for underserved populations while at the same time, increasing the quality and distinctiveness of education. However, as a result of their study, Seneca and Taussig would likely argue that these two missions are difficult to fulfill simultaneously, especially without increasing the resources provided by financial aid.
      In the study, Seneca and Taussig (1987) analyzed data from thirty state universities to measure the level of access the university was providing – in other words, is the university’s student population proportionate and reflective of the state’s population. For example, Seneca and Taussig’s measure of access looked at the family income of a student relative to incomes in the state (pg. 30). They also measured the level of quality of education, which the researchers determined the SAT or ACT score would be the operationalized value of the concept of a high level of education. 
      Seneca and Taussig (1987) found that as tuition increased at state universities, then there was a negative effect on access, whereas when financial aid increased then a positive effect on access was determined. It was also found that as access increased, then the level of quality decreased (pg. 33).  The authors recognized specific limitations to their study, including access limited in terms of income levels rather than ethnicity, race and gender (pg. 35). I also believe the level of quality is not necessarily measured by a student’s incoming standardized test score and future studies should look at other ways to operationalize the quality of education.
      This study should serve as a discussion point for state universities who are determining priorities and tuition and financial aid policies, especially with regards to missions of access and quality education. This study could be replicated within the state of Washington to see if the higher education institutions in this state also show the same results as Seneca and Taussig determined.
    1. Witman, K., Chase, M., Bensimon, E.M., Hanson, D., & Longanecker, D. (2015). Moving the attainment agenda from policy to action. Change: The Magazine of Higher Learning, 47 (4), 6-15.

      In Whitman, Chase, Bensimon, Hanson and Longanecker’s (2015) article, the authors propose a model for how higher education institutions can put policy decisions into practice in order to increase access to college for underrepresented populations. The authors stress the importance of equity being at the forefront of policy implementation and involving faculty and other institutional staff in the process of policymaking “to produce dramatically greater and more sustainable change by merging these two domains of practice” (policy and practice) (pg. 8).

      Using Colorado’s Equity in Excellence program as a model and similar to Lasswell’s (1956) Stages Model, Witman et al. outline the “Policy and Practice Alignment Model”, which will be referred to as the PPA Model in this posting. The first stage of the PPA Model involves the creation of state equity policy goals based on disaggregated data by race/ethnicity to “identify equity gaps in student progress toward degree attainment” (pg. 9). These policy goals will then lead to the following phases (pg. 9):

      1. Laying the groundwork
      2. Defining the problem
      3. Assessing interventions
      4. Implementing solutions
      5. Evaluating results

      Once policy determines the achievement gaps to focus on, Whitman et al. recommend the “creation of a campus evidence-team” and a “campus-specific data portfolio” to implement policy at a specific campus (pg. 10). After this process had been conducted at a college in Colorado, it led to the math department making changes such as “providing professional development [for faculty] focused on how to be more inclusive in their syllabi, be more alert to power dynamics that prevent students from seeking help, understand what types of languages may engender stereotype threat, and learn how to help students who may lack experience interacting with faculty…and many are already showing positive results” (pg. 13). Other changes noted in the article include hiring of more diverse faculty, analyzing achievement gaps at the level of specific courses, and analyzing faculty practices that “may be failing to produce success, particularly for the marginalized students of color” (pg. 14).

      The Whitman et al. article can be compared to policy decisions and implementation in the state of Washington. For example, the Washington Student Achievement Council’s Report: Educational Attainment for All: Diversity and Equity in Washington State Higher Education (2013) (which can be found online at http://www.wsac.wa.gov/sites/default/files/DiversityReport.FINAL.Revised.07-2013_0.pdf), specifically brings attention to race/ethnicity disparities of college enrollment within the state, particularly among African American, Latino, Hawaiian/Pacific Islander and Native American students who graduated from a high school within the state of Washington.

      Policy makers and practitioners, within the state of Washington and other states, may use the Policy and Practice Alignment Model presented by Whitman et al. in order to guide their local decision-making process to advance equity issues across the nation.

      • N Brusseau (10-5-15)
    1. Niu, S.X. (2014). Leaving home state for college: Differences by race/ethnicity and parental education. Research in Higher Education. 56 (4) pg. 325-359.

      Attending college out-of-state is usually more expensive because of transportation and housing costs, but Niu (2014) makes the normative claim that “leaving home states for college provides additional benefits compared with attending college in home states” (pg. 347). This is mainly due to the finding that students who are attending out-of-state institutions are likely attending “a private, a 4-year, and a selective institution” (pg. 347), but Niu seems to believe that inequitable out-of-state college attendance should be noticed.

      Niu cites other researchers who found that high-income students were more likely to apply to many schools as well as more selective schools. Previous research found that a student’s “likelihood of leaving home for college was found to be positively affected by the father’s education and the parental income” (pg. 327).

      Niu conducted a study to examine where graduating seniors from 2010 actually attended, rather than focusing on college choices of students that were not confirmed with actual attendance in previous research. The study used secondary data from the SAT exam and then tracked where the students actually attended using data from the National Student Clearinghouse (pg. 329). In order to rank the selectivity of specific colleges, Niu used the Barron’s college selectivity index.

      Based on the college(s) a specific student chose to have their SAT scores sent to (in-state vs. out-of-state), Niu looked at whether a student was more or less likely to request out-of-state colleges in comparison to the student’s race/ethnicity and parental education.

      After descriptive and multivariate analyses were completed, Niu determined that White students had the highest rate of sending test scores to out-of-state colleges, while Hispanic students had the least likelihood of sending scores out-of-state (pg. 332). The increased likelihood of a student sending their test scores out-of-state was also correlated with higher levels of parental education. When this pattern was compared to where students actually attended, the correlation remained that White students with parents of high education levels were the most likely to attend out-of-state college, compared to Black, Hispanic and Asian students. This study notes that Black and Hispanic students who attended out-of-state colleges were likely attending colleges with ‘need-based’ financial aid practices, which provided additional need to students with low income.

      These factors are in support of Brody’s two articles posted in the “PolEdu” tag, which analyzes a student’s ability to relocate to attend college as well as have access to transportation in order to attend. Public policy makers should be aware of possible barriers to students and seek ways to assist the public with overcoming these additional barriers.

      -N Brusseau (9-28-15)

    1. http://files.eric.ed.gov/fulltext/ED555523.pdf

      Anderson, L. (2015). Addressing postsecondary access for undocumented students. ECS Educational Trends, February, 2015, 1-6.

      Schneider, A.L., Ingram, H. and Deleon, P. (2011). Democratic policy design: Social construction of target populations. In Sabatier, P.A. and Weible, C.M. (Eds.), Theories of the Policy Process (105-149). Boulder, Colorado: Westview Press.

      Anderson’s (2015) provides an overview of recent policy decisions with regards to undocumented students’ access to U.S. higher education institutions. Anderson notes President Obama’s creation of the Deferred Action for Childhood Arrivals Program (DACA), which provides the authorization to work for undocumented individuals, but does not provide a path to citizenship. One requirement to qualify for the DACA program is they have moved to the U.S. before age 16 and also maintained continuous residency (pg. 2). Anderson cites an estimate of 11.2 million undocumented people living in the U.S in 2012 (pg. 1). Federal and state governments are faced with policy questions for this group, including questions about access to higher education.

      Anderson notes many policy changes since 2001, but currently eighteen states made changes to policies to allow for undocumented students to pay in-state tuition, provided the individual meets specific requirements. Examples of state requirements include high school attendance or graduation from the state, or provide a signed statement that the individual will obtain legal status as soon as possible (pg. 2). Five of those 18 states allow undocumented students access to state financial aid programs (pg. 3).

      Anderson provides policy examples from different states to serve as a springboard for continuing discussions. The first state to allow undocumented students to pay in-state tuition was Texas in 2001, but there are requirements the student needs to meet (such as living in Texas for three years before high school graduation and not previously enrolled in college before 2001, among others). Anderson cites that more than 16,000 college students in Texas enrolled in college in 2011 under this policy (pg. 2). Illinois adopted a similar policy in 2003 and nearly 16,000 students enrolled in public institutions.

      Washington implemented policy changes to allow for undocumented students to be considered in-state residents in 2003 and in 2014 also made state financial aid available. In 2013, Washington reported over 1,000 undocumented students enrolled in college (pg. 4).

      Rhode Island and Colorado were also highlighted as changing policies to increase access to college for undocumented students. Anderson points out that states likely approach policy changes in different ways, but there are similarities to extend the right to higher education to include undocumented students (pg. 5).

      In conclusion, Anderson lists questions that legislators should consider when making policy changes with regards to undocumented individuals. The concluding questions encourage legislators to analyze potential policy changes impact for the state, consider if undocumented students would be held to the same requirements as U.S. citizens and also recognizing the number of undocumented students within their state. (pg. 6).

      Through these more recent changes in policy at the federal and state levels, the social construction of “illegal immigrant” may be shifting to a more positive framework. Schneider, Ingram and Deleon (2011) believe that “social constructions of target groups can change, and public policy design… [can be a] force for change” (pg. 123). Undocumented students access to higher education seems to be increasing through policy changes that are likely changing society’s social construction of undocumented individuals.

      • N Brusseau (9-20-15)