Financial Constraints - IA de Investigación especializada en el MIT

Financial Constraints
& Collegiate Student Learning:
A Behavioral Economics Perspective

Benjamin Castleman & Katharine Meyer

Gaps in college completion persist between low- and high-income students.
These disparities can be attributed in large part to a lack of college affordabil-
ity and information asymmetries about the process of accessing financial as-
sistance as well as other campus-based resources and supports. While substan-
tial policy investments have been made to address these inequalities, como
expanded financial aid programs and increased investments in college advis-
En g, these programs are not always fully utilized by students who might bene-
fit from them. En este ensayo, we apply a behavioral economics perspective to ex-
amine how financial constraints affect students’ navigation of the complex pro-
cesses–financial, academic, and otherwise–required to succeed in American
higher education. We conclude with a discussion of evidence-based behavior-
al strategies that policy-makers and educators can draw on to proactively miti-
gate these behavioral obstacles and improve student success.

F or nearly half a century, higher education policy at the federal and state

levels has focused on increasing college access for low-income youth.
Policies have included need-based grants and loans to defray the cost
of pursuing postsecondary education, such as the federal Pell Grant and nu-
merous state-funded means-tested grant programs. The federal and state gov-
ernments have also invested in advising and tutoring programs, such as GEAR
UP and Upward Bound at the federal level and Advise TN in Tennessee, as a
way to support low-income students’ college readiness and preparation. Encima
esta vez, college enrollment has increased steadily, with notable gains among
low-income populations.1 However, despite increases in college enrollment,
college completion rates have stagnated. Just under half of all degree-seeking
college students in 1996 completed an associate’s or bachelor’s degree with-
in six years of entry; in the five most recent cohorts of incoming college stu-
abolladuras, roughly the same proportion of students–55 percent–completed a

© 2019 por la Academia Americana de las Artes & Ciencias
Publicado bajo Creative Commons
Atribución 4.0 Internacional (CC POR 4.0) licencia
https://doi.org/10.1162/DAED_a_01767

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degree.2 Socioeconomic disparities in college completion are pronounced
and growing. Over half of the youth born into the top income quintile earn a
bachelor’s degree by age twenty-five compared with fewer than 10 por ciento de
youth born into the bottom income quintile.3

Históricamente, much of the focus on improving student success once enrolled
in college has been on students’ academic experience, including several essays
in this volume that address the classroom experience. In other work, both pol-
icy-makers and researchers have pointed to developmental education as an
impediment to student persistence and completion. Two-thirds of communi-
ty college students enrolling in 2003–2004 took at least one remedial course,
as did about 40 percent of students enrolling at public four-year institutions.4
Yet the evidence on the effectiveness of remedial courses is mixed. Some stud-
ies find that students who take remediation are more likely to persist in col-
lege,5 while others find null or even negative effects of remedial courses.6 Fur-
thermore, disparities in college completion remain even upon controlling for
academic achievement.7

In parallel, there have been numerous initiatives aimed at improving ac-
ademic advising to increase completion rates. Coaching and mentoring pro-
grams yielded more consistent results than remediation at improving student
performance and persistence, though advisors often address myriad student
necesidades, not just promoting academic engagement.8 Many community colleges
have also invested in developing “structured” or “guided” pathways for stu-
dents that include specialized course plans that help clarify for students what
courses will count toward their intended degree or transfer path, as well as in-
creased advising and monitoring of student performance to trigger early in-
terventions.9 While there exists a correlation between structured pathway
participation and student persistence, few research studies have captured the
effects of these innovations.

More recently, there has been growing recognition that making college af-
fordable to attend does not on its own ensure that students will have the fi-
nancial resources to complete postsecondary education. While the Pell Grant
and numerous state grants are renewable, students may lose aid because
they do not maintain sufficient academic performance, because they fail to
reapply for aid each year, or because they take too many courses that do not
count toward their degree and use up their aid eligibility before they gradu-
ate. Even for students who maintain their aid and use it efficiently, rising col-
lege costs mean that many students face gaps between their grant aid and the
cost of attendance, which students may have to fill through a combination of
loans, trabajar, and family resources. Además, many students face a host of
costs not directly related to pursuing their degree–transportation, child care,

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Dédalo, la Revista de la Academia Estadounidense de las Artes & SciencesFinancial Constraints & Collegiate Student Learning

food–that they may not be able to cover through financial aid and income
they earn while in school. Low-income students also arrive on campus with
fewer insights into the academic resources available to them and often strug-
gle to feel a sense of belonging among their more advantaged peers, cual
hampers their ability to engage with their studies.

While large, structural policy changes are necessary to combat many of
the challenges students encounter in their pursuit of a postsecondary creden-
tial, insights from the behavioral sciences also provide a lens through which
investigadores, practitioners, and policy-makers can understand how students
move through the postsecondary system. Over the past fifty years, numerous
studies in behavioral economics, neurociencia, and social and cognitive psy-
chology have explored how individuals make decisions, particularly under
incertidumbre. Recientemente, higher education scholars have applied lessons from
these disciplines to better understand how students and their families make
decisions about the investment in a college education. In this essay, we ex-
plore how behavioral science insights can help policy-makers and higher ed-
ucation professionals understand the challenges students face in college per-
sistence and we consider the potential of behaviorally informed interventions
to improve college completion rates.

E ach day, we face hundreds of choices about how to allocate our scarce

resources, particularly our time and money. Should I buy a salad or a
burger for lunch? Should I walk to the store or drive? Should I study
for the test in two weeks or watch American Ninja Warrior? Al mismo tiempo,
we are making choices about how we would like to allocate our resources in
the mid-range to distant future. Should I go to college or work for a few years?
Should I try to save up and buy a house or am I likely to move from this city
soon? Traditional economic theory posits that individuals think about the
costs and benefits of each of these decisions and choose the option that max-
imizes their utility and has the greatest benefits for the lowest cost. When it
comes to investing in additional years of education, this cost-benefit frame-
work evaluates potential costs (such as tuition and foregone wages) relative
to benefits (such as higher earnings after graduation and forging relationships
with classmates).10

Behavioral science research, sin embargo, has documented that individuals
make different choices based on a number of external factors that tradition-
al models would not expect to affect decision-making: Por ejemplo, haciendo
a different choice in the morning than in the evening about what they would
like to have for dinner that night. This framework for understanding human
behavior recognizes that our ideal behavior is often different from our actual

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148 (4) Fall 2019Benjamin Castleman & Katharine Meyer

behavior depending on whether we are engaging in slow, forward-thinking
procesos, or under stress and cognitive demands that shift us to faster, pres-
ent-oriented thinking.11 The hypothesis is not that people make irrational de-
decisiones, necessarily, but that they often make decisions using “bounded ra-
tionality”: eso es, rational given a set of practical constraints.12 Starting with
cognitive psychologists Daniel Kahneman and Amos Tversky’s influential
work in the 1970s, behavioral science research has long explored how the
framing and context of choices affect individuals’ decisions within bounded
rationality, when they may not have the information, tiempo, or cognitive band-
width to engage in a thorough cost-benefit analysis.13

One easily relatable response to a complex decision is to put off the choice
until later, under the hope that it will be easier to handle complexity tomor-
row.14 However, individuals are less likely to make optimal choices when
the decision and rewards or costs are immediate, a phenomenon known as
time-inconsistent preferences. Por ejemplo, people have different stated prefer-
ences about how they will spend their time or financial resources in the future
based on whether they are asked their preferences well in advance or imme-
diately ahead of time.15 Planning ahead of time, people often prefer options
that have greater benefits in the long run, even if there are short-term costs.16
Related, individuals are more likely to show a present bias and prefer a small-
er reward now than to wait for a larger reward in the future; aunque, indi-
viduals are more likely to prefer the long-term reward when the short-run re-
ward is moved just a little into the future (por ejemplo, if an immediate reward
is delayed fifteen minutes).17 Time-inconsistent preferences are often influ-
enced by loss aversion: a strong reaction to the idea of losing out on something,
such as money or time, that we have already mentally designated for anoth-
er purpose.18

In the face of some of these challenges, individuals may rely on heuristics
or “rules of thumb” to make decisions rather than a careful evaluation of costs
and benefits. Heuristics are shortcuts that the brain can use to simplify deci-
sion-making. One example is availability bias: the tendency to use easily ac-
cessible information to make decisions.19 When it comes to important deci-
sions about financial aid refiling once enrolled in college, Por ejemplo, college
students may rely on the experiences of their friends, who may not have got-
ten any additional scholarships for their sophomore year, instead of applying
themselves and seeing what happens. Another common heuristic employed
in decision-making is the use of anchors or reference points.20 Often this comes
in the shape of relying on peer behavior or achievements to benchmark ef-
fort and performance. Por ejemplo, a growing literature finds that one’s po-
sition relative to one’s peers can strongly affect student outcomes. One study

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Dédalo, la Revista de la Academia Estadounidense de las Artes & SciencesFinancial Constraints & Collegiate Student Learning

examined the longer-run outcomes of students from different classrooms
with similar academic achievement at the elementary level. The researchers
found that the students at the top of their class have higher test scores, tener
more confidence, and are more likely to pursue science and technology ca-
reers compared with students with similar academic performance but that
had joined higher-achieving classes in which they were at the bottom of their
immediate peer group.21 In higher education, particularly for courses with
heterogeneity in average performance across course sections or discussions,
similar peer effects may manifest as similarly performing students encounter
different average peer environments.

One particularly powerful heuristic that policy-makers and businesses fre-
quently leverage is individuals’ tendency to go with the default option.22 When
people have to make a decision, there is frequently a stated default. Para examen-
por ejemplo, when you sign up for a new account with an online store, the stated de-
fault is to sign up also for their email list. You have the option to uncheck that
box agreeing to subscribe, but few people do. Closely related to default op-
tions is a status quo bias: the tendency not to change systems already in place.23
To continue the email-marketing example, once individuals have subscribed
to an email, the typical unsubscribe rate per messaging campaign is less than
1 percent.24 Both default and status quo bias are a product of individuals’ ten-
dency to avoid hassle factors: the small but time-consuming processes needed
to accomplish a goal, even if an onerous investment of time tackling the has-
sles in the present would result in substantially better outcomes in the longer-
term.25 It feels easier just to delete Amazon’s daily promotional emails than to
log into your account and manage your email subscription preferences.

In the K–12 setting, defaults and status quo bias have proven powerful
tools to get parents to sign up to receive important updates about their chil-
dren’s performance and attendance rates. When parents had to reply and opt-
in to receiving that information, solo 8 percent of parents signed up; cuando
the school set the default as parents receiving information, with the option
of opting-out, 96 percent remained enrolled in the program.26 In addition to
lessons about how defaults and status quo bias could affect college student
engagement with important sources of information about college and fi-
nancial aid deadlines, in the postsecondary context, researchers have advo-
cated for changing structural defaults such as modifying the default loan re-
payment plan.27 Currently, the default “standard” repayment plan assumes
a fixed monthly repayment amount that is consistent throughout the period
of repayment. Recognizing that individuals’ incomes tend to grow over time,
there is also an income-based repayment plan that asks individuals to pay a
percent of their income and adjusts the monthly repayment amount lower or

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148 (4) Fall 2019Benjamin Castleman & Katharine Meyer

higher depending on how much individuals are earning. While anyone can
opt-in to the income-based repayment plan, due to individuals’ strong prefer-
ence for the default option, many students who would benefit from the flex-
ible and often lower payments under income-based repayment end up start-
ing with the standard, fixed monthly repayment plan, and given the status quo
inclinación, few students switch. Federal interventions have proven that targeted
outreach sharing information about income-based repayment plans and par-
ticularly messaging that highlights loss aversion can increase take-up of the
income-based plans, though advocates argue that setting it as the default re-
payment option would be more effective.28

R esearch on the psychological effects of scarcity inform why low-

income students and their families may have an even harder time en-
gaging with the necessary steps to maintain financial aid, remain en-
rolled, and succeed in college. When Congress established the Pell Grant in
1972 to ensure that financial barriers would not prevent academically pre-
pared students from enrolling in college, the average award covered nearly
all of students’ tuition and fees at public colleges and universities. In the de-
cades since, the purchasing power of the Pell Grant has declined substantial-
ly, while tuition, fees, and the cost of attendance have increased.29 Students
have three primary options for covering gaps between the grant aid they re-
ceive and the full cost of attendance: borrowing money, either through feder-
al or state student loan programs or from private sources; working to generate
income while in college; or drawing on family resources. The combination of
borrowing, working, and drawing on family resources may impose substan-
tial stress on students and contribute to their heightened levels of financial
anxiety about how they will pay for college from one semester to the next.

Behavioral economics and psychology research demonstrate a strong link
between the financial stress and anxiety individuals experience and the cog-
nitive bandwidth that they can apply toward challenging and complex tasks.
Many factors affect the cognitive bandwidth people are able to dedicate to
Toma de decisiones: por ejemplo, time limits, hunger, or stress from poverty.30
Students whose time is divided between courses, trabajar, and family commit-
ments may be more likely to lose sight of deadlines or have insufficient cog-
nitive attention to devote to their coursework or other important procedur-
al tasks, like reapplying for financial aid. This challenge is likely even great-
er for low-income students who are also racial or ethnic minorities on their
campus and face the cognitive demands of navigating racial bias.31 In one ex-
perimento, researchers found that sugarcane farmers from India scored higher
on cognitive tests after the harvest–when they were at their wealthiest–than

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Dédalo, la Revista de la Academia Estadounidense de las Artes & SciencesFinancial Constraints & Collegiate Student Learning

prior to the harvest, suggesting that financial stress impedes individuals’ abil-
ity to access their various cognitive resources and knowledge.32 In the college
contexto, one experiment found that when college students were prompted to
think about the financial burden of college, they performed worse on cogni-
tive tasks.33 Interestingly, when students were reminded of the financial bur-
den of college–the costs–but concurrently prompted to think about their
future occupation–the benefits–this cognitive impairment was lifted, sug-
gesting implications for designing outreach and messaging campaigns to stu-
dents to alleviate the cognitive stress of student borrowing.34 Attention to
pressing financial issues–for example, paying for car repairs or childcare–
may “crowd out” individuals’ focus on medium- to long-term financial issues
such as refiling the FAFSA (Free Application for Federal Student Assistance)
or constructing the optimal loan package.35

I n addition to increases in traditional college costs such as tuition and fees

and the academic consequences of students working and borrowing to
address the gaps between grant aid and cost, the demographics of who
goes to college have also shifted. Hoy, more low-income students are enroll-
ing in college than ever before.36 About 40 percent of students enrolled in a
degree-granting postsecondary institution are over the age of twenty-five,
with the majority of Pell Grant recipients over the age of twenty-one.37 Com-
munity colleges enroll approximately 40 percent of all first-time college stu-
dents in the United States.38 College students today also have many respon-
sibilities other than school; nearly one-third of all female undergraduate
students have a child, as do 18 percent of male undergraduates.39 With this
compositional shift has come the introduction of and increase in additional
cost categories (like childcare costs) that tax the mental bandwidth available
to students to dedicate to college learning.

The share of students enrolled in a community college is an especially rel-
evant shift to the discussion of financial stress and student persistence rates.
Over the past few decades, about one-quarter of full-time undergraduate stu-
dents and 42–44 percent of all undergraduates are enrolled in a public, two-
year institution, making up a large share of the undergraduate population.40
Several features of the community college landscape in particular likely exac-
erbate the behavioral biases that students exhibit when interacting with the
complex financial aid and course registration systems. Community colleges
primarily comprise students who commute to and from campus and who bal-
ance extensive work and family commitments outside of school.41 Communi-
ty colleges also tend to rely on communications channels–principally email,
although increasingly technology-assisted advising tools as well–that have

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148 (4) Fall 2019Benjamin Castleman & Katharine Meyer

low visibility and may not effectively reach students.42 This combination of
limited time on campus, limited attention because of other demands in their
lives, limited access to advising, and ineffective institutional communication
channels may mean that students are simply unaware of opportunities to earn
guaranteed admissions to four-year universities in their state.

In addition to these large factors affecting student engagement and ac-
cess to advising, low-income, adult, and student parents also face challeng-
es in individual course engagement. When it comes to course success, el
broad strokes formula is straightforward: show up to class, pay attention, y
study.43 Insights from behavioral sciences help explain why students in gener-
al might not complete these steps. Por ejemplo, time-inconsistent preferenc-
es might sway a student to sleep a few additional hours after an overnight shift
rather than go to class.44 But additional responsibilities (such as a full-time
job) and costs (such as children) outside of the college context introduce oth-
er obstacles to success and exacerbate behavioral responses to these challeng-
es. Por ejemplo, student parents need to secure another adult to watch their
children during class; 60 percent of student mothers and 38 percent of stu-
dent fathers are single parents, requiring them to find other family members
or professional care to watch their children.45 When a caregiver is sick and un-
able to take care of the children, the student parent has few options to make
it to class. To take another example, as noted above, students living off cam-
pus must find and often pay for parking at school. Unanticipated mechanical
or logistical issues may prevent them from being able to attend class. At any
of these barriers, it is easy to imagine how some of the behavioral and psycho-
logical responses we highlighted earlier can come into play: the stress and re-
duced cognitive bandwidth from a sudden loss of childcare might reduce stu-
dents’ ability to engage fully with difficult homework tasks, and time-incon-
sistent preferences might make a student less likely to incur the short-term
cost of a cab to get to class, even if the long-term benefits of attending class
outweigh the upfront financial outlay.

Succeeding in a course often requires substantial student-faculty interac-
ción, such as students going to office hours for clarity on a point made in class
or to tell a professor when they have a major life event or financial obstacle that
might affect their course performance. Having meaningful interactions with
faculty members is an important predictor of college persistence and comple-
tion.46 But low-income students are less likely to engage with faculty members,
and socioeconomic gaps in developing those student-faculty relationships may
help explain some of the socioeconomic gaps in college graduation rates.47
While more affluent students often have parents or other adult mentors in
their life who let them know about the importance of faculty engagement (y

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Dédalo, la Revista de la Academia Estadounidense de las Artes & SciencesFinancial Constraints & Collegiate Student Learning

can also personally answer a host of questions their child might have about ac-
ademic success strategies), parents of low-income college students often lack
the information necessary to advise their children. Además, students in a
community college setting may not have peers with high levels of faculty inter-
actions and course engagement to anchor their behavior to.48

Since the early 2000s, there has been broad recognition among educators,

investigadores, and policy-makers that informational and behavioral bar-
riers associated with completing the FAFSA can impede college-ready,
financially eligible students from receiving need-based federal or state finan-
cial assistance for postsecondary education.49 Ten percent of college fresh-
men who would be eligible for means-tested financial aid do not fill out the
FAFSA, and other academically prepared high school students may not make
it to college because they do not complete the FAFSA and thus do not receive
aid that would make college more affordable for them and their families.50

Awareness of the barriers created by the FAFSA has led to numerous ini-
tiatives to simplify the application, to make the process of applying for aid
more visible and understandable, and to increase students’ access to profes-
sional assistance when completing the FAFSA. Most of these efforts, howev-
es, have focused on initial FAFSA completion, especially among high school
seniors in traditional public school settings. Comparatively less attention has
been paid to the challenges students may face maintaining aid they initially
receive, despite the fact that students have to renew their FAFSA every year
to maintain access to federal–and in many cases state and institutional–fi-
nancial aid. Descriptive research suggests that a sizeable share of college stu-
dents fail to refile their FAFSA each year, even those who receive federal Pell
Grants and who are in good academic standing. Drawing on data from the
National Center for Education Statistics’ Beginning Postsecondary Study, re-
searchers found that one in six college freshmen who received a Pell Grant
and who had a GPA of 3.0 or higher did not successfully complete the FAFSA
for their second year in college.51 Among those academically successful stu-
dents who return for sophomore year, one in ten do not complete the FAFSA
and therefore do not receive financial assistance for their second year. El
study authors estimate that these nonfilers forgo approximately $2,000 in federal grant assistance, on average, by not refiling; and not surprisingly, fail- ure to refile the FAFSA is strongly and negatively associated with staying in college or earning a degree. Behavioral economics insights help explain why students who already completed the FAFSA at least once, received grant aid, and were doing well ac- ademically might nevertheless fail to renew their FAFSA. To begin, first-year 203 l D o w n o a d e desde h t t p : / / directo . mi t . / e d u d a e d a r t i c e – pd / l f / / / / 1 4 8 4 1 9 5 1 8 3 1 3 7 8 d a e d _ a _ 0 1 7 6 7 pd / . f por invitado 0 7 septiembre 2 0 2 3 148 (4) Fall 2019Benjamin Castleman & Katharine Meyer students at residential colleges and universities are often living away from home for the first time and are no longer as closely connected to school coun- selors or other mentors on whom they may have relied for assistance ap- plying for financial aid. The lack of regular connection with family, pro- fessional support, or mentors may mean that reapplying for financial aid is less at the top of students’ minds. Even for students who remember that they need to refile the FAFSA, the lack of access to trusted sources of assis- tance may mean that students indefinitely put off FAFSA refiling in favor of more demanding or immediate tasks. This is particularly the case among stu- dents new to college, who may have limited attention to devote to FAFSA refiling amidst an array of new academic and social commitments. The be- havioral challenge of refiling their FAFSA is likely to be particularly daunting for students at community colleges. Advising resources at community col- leges are often severely limited and students typically have to work through confusing bureaucracies to get one-on-one academic or financial counsel- ing.52 The nonresidential aspect of community college also translates into stu- dents spending less time on campus than do their peers at residential four- year institutions, making it more difficult to find time to meet with financial aid support staff. These obstacles contribute to Pell Grant recipients at com- munity colleges being almost ten percentage points less likely to refile their FAFSA than their peers at four-year institutions, holding constant other stu- dent and institutional characteristics.53 In addition to the direct complexities and behavioral barriers associated with refiling the FAFSA, students may not maintain financial aid because they do not believe they are still eligible for fi- nancial support. More than half of all Pell Grant recipients report not reap- plying for financial aid because they thought they were no longer eligible.54 This may be due in part to institutions informing students that they are not maintaining satisfactory academic progress (SAP). In order to maintain eli- gibility for federal financial aid, students typically have to maintain a 2.0 GPA or higher and complete at least two-thirds of the credits for which they enroll. Yet SAP requirements may not be communicated clearly or proactively to stu- dents when they first matriculate to college, y, while enrolled, they may not receive timely updates that could serve as early indicators that they need to ac- cess additional academic support like tutoring. Como resultado, students may not understand the link between their academic performance and their ongoing access to financial aid. Drawing on both national and state administrative data, researchers have found that over 20 percent of first-year Pell Grant recipients are at risk of failing to meet SAP requirements because they do not maintain a sufficient GPA.55 Among community college first-year Pell Grant recipients, one in four 204 l D o w n o a d e desde h t t p : / / directo . mi t . / e d u d a e d a r t i c e – pd / l f / / / / 1 4 8 4 1 9 5 1 8 3 1 3 7 8 d a e d _ a _ 0 1 7 6 7 pd / . f por invitado 0 7 septiembre 2 0 2 3 Dédalo, la Revista de la Academia Estadounidense de las Artes & SciencesFinancial Constraints & Collegiate Student Learning is at risk of not meeting SAP requirements because their GPA is too low. The authors find mixed evidence on how failing to meet SAP requirements affects students’ persistence in or completion of college, but the interplay of academ- ic performance and maintenance of financial aid eligibility may further exac- erbate the broader set of financial challenges that can impede student success in college. W hile many institutions, and particularly two-year colleges, serve a high proportion of low-income and adult learners, many low- income students struggle to find other students at their school from a similar background and facing similar economic challenges. This is es- pecially the case at more selective institutions: students from the bottom in- come quintile represent about 4 percent of enrollees at highly selective “Ivy Plus” colleges and about 7 percent of students at selective private colleges.56 Despite these institutions having more resources and higher graduation rates, some students feel isolated, struggle to connect with their peers, and experi- ence low levels of social belonging with their campus.57 These low levels of in- tegration (or belonging) with the academic and social culture of their cam- pus are associated with lower likelihoods of remaining enrolled and gradu- ating.58 Students may also experience stereotype threat, broadly defined as stress that their struggles might confirm another person’s stereotype about a group to which the student belongs, such as being a low-income or older student.59 Students experiencing these psychological stresses tend to perform worse on verbal and math assessments and broadly have lower levels of per- sistence in college. Financial constraints may also serve as a more directly limiting factor in how college students form relationships; in surveys, more than half of all low-income college students reported they were unable to participate in so- cial activities because they could not afford them and felt pressure to spend money they did not have to keep up with social engagements.60 Particularly to the extent that college serves as a place where students make connections for their professional careers, the pricing out of social engagement may prevent lower income students from receiving the social mobility benefits of college.61 When low-income students experience financial stresses and psychologi- cal barriers to connecting with their institution, they are less likely to seek out help.62 Qualitative surveys of undergraduate students suggest that first-gen- eration college students are less likely to discuss social/emotional issues with their family and exhibit more symptoms of depression and lower life satis- faction than their continuing-generation peers. 63 Often students are unaware of available resources to address their problems, or may view seeking help 205 l D o w n o a d e desde h t t p : / / directo . mi t . / e d u d a e d a r t i c e – pd / l f / / / / 1 4 8 4 1 9 5 1 8 3 1 3 7 8 d a e d _ a _ 0 1 7 6 7 pd / . f por invitado 0 7 septiembre 2 0 2 3 148 (4) Fall 2019Benjamin Castleman & Katharine Meyer as a sign of weakness and confirmation of their self-doubts about belonging in college.64 This creates a vicious cycle in which small challenges snowball, with advisors and faculty unaware of issues and the need for intervention. A s outlined in this essay, there are several financial challenges that make it difficult for low-income students to engage fully in the colle- giate learning process. Not only have tuition and fees increased, with students working and borrowing more to fund their education, but the types of students enrolling in college have additional financial constraints, such as childcare and transportation, that make academic engagement difficult. At several institutions, students encounter dramatic financial inequities that re- sult in stress and lower senses of social belonging, both of which negatively affect their likelihood of engaging with classroom materials and successfully persisting through degree completion. Here we propose evidence-based strat- egies that policy-makers and educators can draw on proactively to mitigate these behavioral responses and improve rates of student success. We identi- fy the most promising changes that different levels of the higher education system could implement at the federal/state level, the state/institution level, and the institution/faculty level. We strongly recommend targeted financial investments at the federal/state level and note that while the interventions and programs we propose at the state/institution and institution/faculty lev- els will also help students, they are not a replacement for increased appropri- ations to support the higher education system. At the federal and state levels, policy-makers should invest additional appropriations into supporting higher education, at the very least attempt- ing to return appropriation levels to those of the early 2000s. Between 2003 y 2012, average state funding for public colleges decreased by 12 por ciento, with average per-student funding decreasing by 24 por ciento, dropping from $6,211 per student to $4,695 per student in 2012.65 Although state appropria- tions have started to increase over the past few years, per-student appropri- ations remain lower than 2001 niveles, with about 46 percent of higher edu- cation revenues coming from tuition compared with 30–35 percent in the early 2000s.66 Declines in state appropriations relate to declines in institu- tional expenditures per student, cual, at certain types of institutions, can make a big difference in the likelihood that a student graduates. Researchers have found that most of the decline in college completion rates over the past few decades at nonselective, public four-year colleges can be attributed to ris- ing student-faculty ratios, although those shifts explain little of the variation in two-year college completion rates.67 Given limited resources, states could prioritize increasing appropriations to schools that enroll more low-income 206 l D o w n o a d e desde h t t p : / / directo . mi t . / e d u d a e d a r t i c e – pd / l f / / / / 1 4 8 4 1 9 5 1 8 3 1 3 7 8 d a e d _ a _ 0 1 7 6 7 pd / . f por invitado 0 7 septiembre 2 0 2 3 Dédalo, la Revista de la Academia Estadounidense de las Artes & SciencesFinancial Constraints & Collegiate Student Learning students and institutions that have experienced the biggest drops in per-pupil appropriations over the past decade. We caution, sin embargo, that the mixed ef- fects of performance-based funding suggest that policies that differentially target institutions by student composition or student outcomes often have unintended consequences for equity and the types of credentials colleges en- courage students to pursue.68 In addition to increased state appropriations in public higher education institutions, the federal government has the ability to increase investment in and availability of federal financial aid programs. The federal government has made some progress on this front, recently restoring “year round Pell Grants” (YRP), which allow recipients to access up to 50 percent of their annual award for summer studies (for a total academic year use of 150 percent of an award). Quasi-experimental research shows that YRP availability results in increased summer enrollment, higher associate’s degree graduation rates, and greater benefits for older students.69 However, to the point that students often strug- gle to refile the necessary paperwork to access fall/spring semester federal fi- nancial aid, low-income students and students enrolling part time or living off campus may struggle to connect with financial aid offices to access YRP aid, motivating additional interventions to increase awareness of the pro- gram. Estados, localities, and institutions also have a role to play in providing financial aid to supplement federal investments, with many merit-based pro- grams and place-based full-tuition “promise” programs positively affecting student enrollment and graduation.70 States and institutions also have opportunities to invest in targeted sup- port programs and offer additional advising resources to students to mitigate the costs of college enrollment and increase the likelihood that students will succeed in the classroom. Programs such as the Accelerated Study in Asso- ciate Programs (ASAP) at the City University of New York (CUNY) commu- nity colleges combine institution-level investments in intensive advising and structured pathways with student financial support (such as subway cards, textbook assistance, and tuition waivers) that have significant effects on stu- dents’ persistence and degree attainment, as measured in a large-scale ran- domized controlled trial.71 While access to high-quality advising can lead to substantial improvements in students’ postsecondary outcomes,72 many col- lege advisors are overworked and unable to address all students’ needs, and advising resources are often particularly limited at the broad access public in- stitutions attended by most students.73 There are also some state policies that, at face value, target improving on- time graduation and students’ academic engagement but have unintended consequences. Excess credit hour (ECH) state policies act as a “stick” incentive 207 l D o w n o a d e desde h t t p : / / directo . mi t . / e d u d a e d a r t i c e – pd / l f / / / / 1 4 8 4 1 9 5 1 8 3 1 3 7 8 d a e d _ a _ 0 1 7 6 7 pd / . f por invitado 0 7 septiembre 2 0 2 3 148 (4) Fall 2019Benjamin Castleman & Katharine Meyer by charging higher tuition rates for credits students take beyond a certain threshold: Por ejemplo, más que 140 credits in North Carolina or more than 125 percent of the credits required for a student’s degree in Virginia.74 While intended to incentivize students to graduate quickly, ECH policies have had no effect on on-time graduation rates and have increased the amount of debt students take on, particularly for low- and middle-income students.75 Elimi- nating these policies would likely alleviate the negative effects on student bor- rowing and could free up resources to direct to proven strategies. At the institution and faculty/course levels, colleges have the opportunity to implement informational campaigns and interventions to help buffer stu- dents from the cognitive stress of financial insecurity and improve students’ sense of belonging on campus. One writing exercise invited freshmen to read letters from seniors reflecting on their first year and talking about how they came to develop a sense of community on campus; students participating in the intervention earned higher GPAs throughout college and the Black-White GPA gap was cut in half by their senior year of college.76 This model has a prov- en track record scaled up. Implemented at a public four-year institution with low graduation rates as well as at a highly selective college, one study found randomly assigning freshman students to complete social belonging modules as part of their orientation resulted in economically disadvantaged students earning higher freshman GPAs and reporting more close mentors and college friends at the end of their freshman year.77 Other interventions have targeted how students perceive college culture and goals differently by their backgrounds. First-generation and low-income students, Por ejemplo, feel a greater sense of belonging, perform better on ac- ademic tasks, and have lower cortisol levels when an institution emphasiz- es the collaborative nature of the college community.78 Similar interventions have called out students’ different backgrounds in panels and asked partic- ipants to reflect on how their backgrounds affected their college transition. First-generation freshman students who attended these “difference educa- tion” panels earned higher GPAs at the end of the year compared with their peers who attended a general information session.79 While it is important to implement these interventions with fidelity and adapted to each institution- al context (and to acknowledge that the bulk of this research to date has fo- cused on younger students), these interventions have promising records of accomplishment and are a viable avenue for colleges and individual classes to pursue.80 Colleges might also invest in improved, targeted communications about the availability of student support services, such as tutoring, that are likely to have a positive effect on student learning. Por ejemplo, one intervention 208 l D o w n o a d e desde h t t p : / / directo . mi t . / e d u d a e d a r t i c e – pd / l f / / / / 1 4 8 4 1 9 5 1 8 3 1 3 7 8 d a e d _ a _ 0 1 7 6 7 pd / . f por invitado 0 7 septiembre 2 0 2 3 Dédalo, la Revista de la Academia Estadounidense de las Artes & SciencesFinancial Constraints & Collegiate Student Learning found that sending students postcards about peer tutoring programs on cam- pus resulted in a 23 percent increase in tutoring attendance over the control group, with most students induced to attend multiple tutoring sessions.81 The intervention was low-cost, at about $4 a $15 per student, but while the in-
tervention succeeded in increasing student take-up of tutoring services, allá
was no effect on students’ grades.82 Behavioral interventions that address stu-
dents’ time-inconsistent preferences in signing up for tutoring can effectively
change behavior, but the effectiveness of these interventions is limited by the
quality of the services students are nudged to participate in.83

Improving student learning and the value of the college experience re-
quires multifaceted solutions, including targeting policies that less obvious-
ly affect students’ daily course engagement. The rising costs of college, chal-
lenges acquiring and maintaining aid, the changing landscape of who goes to
college and where, and the vast inequality and psychological stress students
experience at even the most well-resourced schools all point to policy solu-
tions that improve the financial well-being of students so that they may fully
dedicate themselves to their studies.

about the authors

Benjamin Castleman is Associate Professor of Education and Public Policy
and Director of the Nudge4 Solutions Lab at the University of Virginia. He has
published in such journals as Journal of Policy Analysis and Management, Diario de
Labor Economics, and Journal of Human Resources.

Katharine Meyer is a Postdoctoral Research Associate at the Annenberg In-
stitute for School Reform at Brown University. She has written for Journal of
Policy Analysis and Management and Journal of Student Financial Aid, and contributed
to the volume The First Year of College: Investigación, Teoría, and Practice on Improving the
Student Experience and Increasing Retention (2017).

notas finales

1 National Center for Education Statistics, Digest of Education Statistics, “Table
302.10. Recent High School Completers and Their Enrollment in College, by Sex
and Level of Institution: 1960 through 2016,” https://nces.ed.gov/programs/
digest/d17/tables/dt17_302.10.asp.

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148 (4) Fall 2019Benjamin Castleman & Katharine Meyer

2 Doug Shapiro, Afet Dundar, Faye Huie, et al., Completing College: A National View of Stu-
dent Completion Rates–Fall 2011 Grupo (Herndon, Va.: National Student Clearing-
house Research Center, 2017).

3 Martha Bailey and Sue Dynarski, “Gains and Gaps: Changing Inequality in U.S. Columna-
lege Entry and Completion,” NBER Working Paper No. 17633 (Cambridge, Masa.:
National Bureau of Economic Research, 2012).

4 National Center for Education Statistics, Remedial Coursetaking at U.S. Público 2- y
4-Year Institutions: Alcance, Experience, and Outcomes (Washington, CORRIENTE CONTINUA.: National Cen-
ter for Education Statistics, 2016), https://nces.ed.gov/pubs2016/2016405.pdf.
5 Eric P. Bettinger and Bridget Terry Long, “Addressing the Needs of Underprepared
Students in Higher Education: Does College Remediation Work?” Journal of Hu-
hombre recursos 44 (3) (2009): 736–771; and Christopher Jepsen, “Basic Skills in Cali-
fornia’s Community Colleges: Evidence from Staff and Self Referrals,” paper pre-
sented at the American Educational Research Association conference, Puede 2006,
San Francisco, California.

6 Paco Martorell and Isaac McFarlin Jr., “Help or Hindrance? The Effects of College
Remediation on Academic and Labor Market Outcomes,” The Review of Econom-
ics and Statistics 93 (2) (2011): 436–454; Juan Carlos Calcagno and Bridget Long,
“The Impact of Postsecondary Remediation Using a Regression Discontinuity Ap-
proach: Addressing Endogenous Sorting and Noncompliance,” NBER Working Pa-
per No. 14194 (Cambridge, Masa.: National Bureau of Economic Research, 2008);
and Judith Scott-Clayton and Olga Rodriguez, “Development, Discouragement, o
Diversion? New Evidence on the Effects of College Remediation Policy,” Education
Finance and Policy 10 (1) (2015): 4–45.

7 Phillippe Belley and Lance Lochner, “The Changing Role of Family Income and Abil-
ity in Determining Educational Attainment,” Journal of Human Capital 1 (1) (2007):
37–89.

8 Eric Bettinger and Rachel Baker, “The Effects of Student Coaching: An Evaluation
of a Randomized Experiment in Student Advising,” Educational Evaluation and Policy
Análisis 36 (1) (2011): 3–19; and Andrew C. Barr and Benjamin L. Castleman, “Ad-
vising Students to and through College: Experimental Evidence from the Bottom
Line Advising Program” (Bostón: Bottom Line, 2016).

9 Thomas Bailey, Shanna Smith Jaggars, and Davis Jenkins, “What We Know about
Guided Pathways” (Nueva York: Teachers College Community College Research
Center, Columbia University, 2015).

10 Gary Becker, Human Capital: A Theoretical and Empirical Analysis, with Special Reference to

Educación (chicago: University of Chicago Press, 1964).

11 Daniel Kahneman, Thinking, Fast and Slow (Nueva York: Farrar, Straus and Giroux,
2011); y B. j. casey, Rebecca Jones, and Leah Somerville, “Braking and Acceler-
ating of the Adolescent Brain,” Journal of Research on Adolescence 21 (1) (2011): 21–33.
12 Herbert Simon, Models of Bounded Rationality (Cambridge, Masa.: The MIT Press,
1982); and Daniel Kahneman, “A Perspective on Judgment and Choice: Cartografía
Bounded Rationality,” American Psychologist 58 (9) (2003): 697–700.

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Dédalo, la Revista de la Academia Estadounidense de las Artes & SciencesFinancial Constraints & Collegiate Student Learning

13 Amos Tversky and Daniel Kahneman, “Judgment under Uncertainty: Heuristics and
Biases," Ciencia 185 (4157) (1974): 1124–1131; and Daniel Kahneman and Amos Tver-
sky, “Prospect Theory: An Analysis of Decision under Risk,” Econometrica 47 (2)
(1979): 263–291. For a more comprehensive overview of behavioral science in-
sights, we recommend Kahneman, Thinking, Fast and Slow.

14 Richard Thaler and Shlomo Benartzi, “Save More Tomorrow: Using Behavioral Eco-
nomics to Increase Employee Saving,” Journal of Political Economy 112 (S1) (2004):
164–187.

15 Gal Zauberman and John Lynch, “Resource Slack and Propensity to Discount De-
layed Investment of Time Versus Money,” Journal of Experimental Psychology 134 (1)
(2005): 23–37; and Stefano DellaVigna, “Psychology and Economics: Evidencia
from the Field,” Journal of Economic Literature 47 (2) (2009): 315–372.

16 Daniel Read, George Loewenstein, and Shobana Kalyanaraman, “Mixing Virtue and
Vice: Combining the Immediacy Effect and the Diversification Heuristic," Diario
of Behavioral Decision Making 12 (4) (1999): 257–273.

17 George Ainslie, Picoeconomics (Cambridge: Prensa de la Universidad de Cambridge, 1992).
18 Kahneman and Tversky, “Prospect Theory”; and Simon Gachter, Henrik Orzen,
Elke Renner, and Chris Starmer, “Are Experimental Economists Prone to Framing
Effects? A Natural Field Experiment,” Journal of Economics Behavior and Organization
70 (3) (2009).

19 Tversky and Kahneman, “Judgment under Uncertainty.”
20 Dan Ariely, George Loewenstein, and Drazen Prelec, “Tom Sawyer and the Con-
struction of Value,” Journal of Economic Behavior and Organization 60 (2006): 1–10.
21 Richard Murphy and Felix Weinhardt, “Top of the Class: The Importance of Ordi-
nal Rank,” NBER Working Paper No. 24958 (Cambridge, Masa.: National Bureau
of Economic Research, 2018).

22 William Samuelson and Richard Zeckhauser, “Status Quo Bias in Decision Mak-
En g,” Journal of Risk and Uncertainty 1 (1) (1988): 7–59; Richard Thaler and Cass Sun-
stein, Nudge: Improving Decisions about Health, Wealth and Happiness (Londres: Pingüino
Books, 2008); and Brigitte Madrian and Dennis Shea, “The Power of Suggestion:
Inertia in 401(k) Participation and Savings Behavior,” Quarterly Journal of Economics
116 (4) (2001): 1149–1187.

23 Samuelson and Zeckhauser, “Status Quo Bias in Decision Making.”
24 Mailchimp, “Email Marketing Benchmarks,” https://mailchimp.com/resources/

email-marketing-benchmarks/.

25 John Beshears, James Choi, David Laibson, and Brigitte Madrian, “Simplification
and Saving,” Journal of Economic Behavior and Organization 95 (2012): 130–145; y
Sendhil Mullainathan and Eldar Shafir, Scarcity: Why Having Too Little Means so Much
(Nueva York: Times Books, 2002).

26 Peter Bergman and Todd Rogers, “The Impact of Defaults on Technology Adop-
ción, and Its Underappreciation by Policymakers,” Harvard Kennedy School Fac-
ulty Research Working Paper No. RWP17-021 (Cambridge, Masa.: Harvard Kenne-
dy School, 2017).

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148 (4) Fall 2019Benjamin Castleman & Katharine Meyer

27 Angela Boatman, Brent Evans, and Adela Soliz, “Understanding Loan Aversion in
Educación: Evidence from High School Seniors, Community College Students,
and Adults,” AERA Open 3 (1) (2017): 1-dieciséis.

28 Social and Behavioral Sciences Team, 2016 SBST Project Abstracts (Washington, CORRIENTE CONTINUA.:
Executive Office of the President, National Science and Technology Council,
2016), https://sbst.gov/download/2016%20Abstracts.pdf.

29 Sandy Baum, Jennifer Ma, and Matea Pender, Trends in Student Aid 2017 (Nueva York:
The College Board, 2017); and Robert Kelchen, Sara Goldrick-Rab, and Braden
Hosch, “The Costs of College Attendance: Examining Variation and Consisten-
cy in Institutional Living Cost Allowances,” The Journal of Higher Education 88 (6)
(2017): 947–971.

30 Mullainathan and Shafir, Scarcity; Lisa A. Gennetian and Eldar Shafir, “The Per-
sistence of Poverty in the Context of Financial Instability: A Behavioral Perspec-
tivo,” Journal of Policy Analysis and Management 34 (4) (2015): 904–936; and Frank
Schilbach, Heather Schofield, and Sendhil Mullainathan, “The Psychological Lives
of the Poor,” American Economic Review 106 (5) (2016): 435–440.

31 The authors thank Beverly Tatum for this important insight into how the cognitive
stressors of students’ multiple identities combine to affect college persistence.
32 Anandi Mani, Sendhil Mullainathan, Eldar Shafir, and Jiaying Zhao, “Poverty Im-

pedes Cognitive Function," Ciencia 341 (6149): 976–980.

33 Mesmin Destin and Ryan Svoboda, “Costs on the Mind: The Influence of the Finan-
cial Burden of College on Academic Performance and Cognitive Functioning,” Re-
search in Higher Education 59 (3) (2018): 302–324.

34 Ibídem.
35 Anuj Shah, Sendhil Mullainathan, and Eldar Shafir, “Some Consequences of Having
Too Little," Ciencia 338 (6107) (2012): 682–685; and Abhijit V. Banerjee and Esther
Duflo, Poor Economics: A Radical Rethinking of the Way to Fight Global Poverty (Nueva York:
Public Affairs, 2011).

36 National Center for Education Statistics, Digest of Education Statistics, “Table
302.30. Percentage of Recent High School Completers Enrolled in College, by In-
come Level: 1975 through 2016,” https://nces.ed.gov/programs/digest/d17/tables/
dt17_302.30.asp.

37 Ibídem.; and U.S. Departamento de Educación, Office of Postsecondary Education, 2016–
2017 Federal Pell Grant Program End-of-Year Report (Washington, CORRIENTE CONTINUA.: A NOSOTROS. Depart-
ment of Education, 2018), https://www2.ed.gov/finaid/prof/resources/data/pell
-data.html.

38 Authors’ calculations from National Center for Education Statistics, 2012/2014
Beginning Postsecondary Students Longitudinal Study, https://nces.ed.gov/
surveys/bps/.

39 Institute for Women’s Policy Research, “Fact Sheet” (Washington, CORRIENTE CONTINUA.: Instituto
for Women’s Policy Research, 2014), https://iwpr.org/wp-content/uploads/
wpallimport/files/iwpr-export/publications/C424_Student%20Parents_final
.pdf.

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Dédalo, la Revista de la Academia Estadounidense de las Artes & SciencesFinancial Constraints & Collegiate Student Learning

40 Baum et al., Trends in Student Aid 2017.
41 Kelli Bird and Benjamin Castleman, “Here Today, Gone Tomorrow? Investigating
Rates and Patterns of Financial Aid Renewal among College Freshmen,” Research in
Higher Education 57 (4) (2016): 395–422; and Anthony P. Carnevale, Nicole Smith,
Michelle Melton, and Eric W. Precio, Learning While Earning: The New Normal (Lavar-
ington, CORRIENTE CONTINUA.: Center on Education and the Workforce Report, Georgetown Uni-
versity, 2015).

42 Benjamin Castleman, The 160-Character Solution (baltimore: Johns Hopkins Universi-

ty Press, 2015).

43 Robert Shireman and Joshua Price, “Prepare for Class, Attend, and Participate!” in
Decision Making for Student Success, ed. Benjamin Castleman, Saul Schwartz, and San-
dy Baum (Nueva York: Routledge Press, 2015), 124–142; y D. R. Marburger, “Ab-
senteeism and Undergraduate Exam Performance,” Journal of Economic Education 32
(2) (2001): 99–109.

44 For an overview of behavioral science insights and college course engagement, ver

Shireman and Price, “Prepare for Class, Attend, and Participate!"

45 Institute for Women’s Policy Research, “Fact Sheet.”
46 George D. Kuh, Jillian Kinzie, John H. Schuh, and Elizabeth J. Whitt, Student Success in

College: Creating Conditions That Matter (San Francisco: Jossey-Bass, 2005).

47 Peter Collier and David Morgan, “‘Is That Paper Really Due Today?': Differences in
First-Generation and Traditional College Students’ Understandings of Faculty Ex-
pectations,” Higher Education 55 (4) (2008): 425–446.

48 Annette Lareau, Unequal Childhoods: Carrera, Clase, and Family Life, 2y ed.. (Oakland: Uni-

versity of California Press, 2003).

49 Susan M. Dynarski and Judith E. Scott-Clayton, “The Cost of Complexity in Federal
Student Aid: Lessons from Optimal Tax Theory and Behavioral Economics,” Na-
tional Tax Journal 59 (2) (2006): 319–356.

50 Michael S.. Kofoed, “To Apply or Not to Apply: FAFSA Completion and Financial Aid

Gaps,” Research in Higher Education 58 (1) (2017): 1–39.
51 Bird and Castleman, “Here Today, Gone Tomorrow?"
52 Judith Scott-Clayton, “The Shapeless River: Does a Lack of Structure Inhibit Stu-
dents’ Progress at Community Colleges?” in Decision Making for Student Success, ed.
Castleman et al., 102–123.

53 Bird and Castleman, “Here Today, Gone Tomorrow?"
54 Ibídem.
55 Lauren Schudde and Judith Scott-Clayton, “Pell Grant as Performance-Based Schol-
arships? An Examination of Satisfactory Academic Progress Requirements in
the Nation’s Largest Need-Based Aid Program,” Research in Higher Education 57 (8)
(2016): 943–967.

56 Raj Chetty, John N. Friedman, Emmanuel Saez, et al., “Mobility Report Cards: El
Role of Colleges in Intergenerational Mobility,” NBER Working Paper No. 23618
(Cambridge, Masa.: National Bureau of Economic Research, 2017).

213

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148 (4) Fall 2019Benjamin Castleman & Katharine Meyer

57 Gregory M. Walton and Geoffrey L. cohen, “A Question of Belonging: Carrera, Social

Fit, and Achievement,” Journal of Personality and Social Psychology 92 (1) (2007).

58 Vincent Tinto, “Dropout from Higher Education: A Theoretical Synthesis of Recent

Investigación,” Review of Educational Research 45 (1) (1975): 89–125.

59 Claude M. Steele and Joshua Aronson, “Stereotype Threat and the Intellectual Test
Performance of African-Americans,” Journal of Personality and Social Psychology 69 (5)
(1995): 797–811; and Jean-Claude Croizet and Theresa Claire, “Extending the Con-
cept of Stereotype Threat to Social Class: The Intellectual Underperformance of
Students Low Socioeconomic Backgrounds,” Boletín de Personalidad y Psicología Social
24 (6) (1998): 588–594.

60 Kevin McClure, Andrew Ryder, and Andrew Mauk, “It All Adds Up: Examining and
Enhancing Campus Climate for Affordability at a Four-Year University," Diario de
Student Financial Aid 47 (2) (2017).

61 Krista M. Soria and Michael J. Stebleton, “Social Capital, Academic Engagement,
and Sense of Belonging among Working-Class College Students,” College Student Af-
fairs Journal 31 (2) (2013): 139–153; and Chetty et al., “Mobility Report Cards.”
62 Lareau, Unequal Childhoods; and Jenny Stuber, How Class and Culture Matter in Higher

Educación (Landham, Maryland.: Lexington Books, 2011).

63 Leasha M. Barry, Cynthia Hudley, Melissa Kelly, and Su-Je Cho, “Differences in
Self-Reported Disclosure of College Experiences by First-Generation College Stu-
dent Status,” Adolescence 44 (173) (2009): 55–68.
64 Stuber, How Class and Culture Matter in Higher Education.
65 Government Accountability Office, “Higher Education: State Funding Trends and
Policies on Affordability” (Washington, CORRIENTE CONTINUA.: Government Accountability Office,
2014), https://www.gao.gov/assets/670/667557.pdf.

66 State Higher Education Executive Officers, “State Higher Education Finance, año fiscal
2017" (Roca, Colo.: State Higher Education Executive Officers, 2017), https://
sheeo.org/wp-content/uploads/2019/02/SHEEO_SHEF_FY2017_FINAL-1.pdf.
67 John Bound, Michael Lovenheim, and Sarah Turner, “Why Have College Comple-
tion Rates Declined? An Analysis of Charging Student Preparation Collegiate Re-
sources,” American Economic Journal: Economía Aplicada 2 (3) (2010): 129–157.

68 Amy Li and Alec Kennedy, “Performance Funding Policy Effects on Community
College Outcomes: Are Short-Term Certificates on the Rise?” Community College
Revisar 46 (1) (2017): 3–39; and Nicholas Hillman and Daniel Corral, “The Equity
Implications of Paying for Performance in Higher Education,” American Behavioral
Scientist 61 (14) (2017): 1757–1772.

69 Vivian Liu, “The Impact of Year-Round Pell Grants on Academic and Employment
Outcomes of Community College Students,” Community College Research Center
Working Paper No. 95 (Nueva York: Teachers College Community College Research
Center, Columbia University, 2017).

70 For merit-based programs, see Timothy J. Bartik, Brad J. Hershbein, and Marta La-
chowska, “The Effects of the Kalamazoo Promise Scholarship on College Enroll-
mento, Persistence, and Completion,” Upjohn Institute Working Paper No. 15-229

214

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Dédalo, la Revista de la Academia Estadounidense de las Artes & SciencesFinancial Constraints & Collegiate Student Learning

(Kalamazoo, Mich.: W.. mi. Upjohn Institute for Employment Research, 2017),
https://doi.org/10.17848/wp15-229; and Lindsay C. Página, Jennifer Iriti, Danielle
Lowry, and Aaron Anthony, “The Promise of Place-Based Investment in Postsec-
ondary Access and Success: Investigating the Impact of the Pittsburgh Promise,"
Education Finance and Policy (próximo 2019). For “promise” programs, see Sue
Dinarski, “Building the Stock of College-Educated Labor,” Journal of Human Re-
sources 43 (3) (2008): 576–610.

71 Susan Scrivener, miguel j.. Weiss, Alyssa Ratledge, et al., Doubling Graduation Rates:
Three-Year Effects of CUNY’s Accelerated Study in Associate Programs (ASAP) for Devel-
opmental Education Students (Nueva York: MDRC, 2015), https://www.mdrc.org/
publication/doubling-graduation-rates.

72 Joshua Angrist, Daniel Lang, and Philip Oreopoulos, “Incentives and Services for
College Achievement: Evidence from a Randomized Trial,” American Economic Jour-
nal: Economía Aplicada 1 (1) (2009): 136–163; Barr and Castleman, “Advising Stu-
dents to and through College”; and Eric P. Bettinger, Bridget Terry Long, Philip
Oreopoulos, and Lisa Sanbonmatsu, “The Role of Application Assistance and In-
formation in College Decisions: Results from the H&R Block FAFSA Experiment,"
Revista trimestral de economía 127 (3) (2012): 1205–1242.

73 Scott-Clayton, “The Shapeless River.”
74 Dennis Kramer, Michael Holcomb, and Robert Kelchen, “The Costs and Conse-
quences of Excess Credit Hours Policies,” Educational Evaluation and Policy Analysis 40
(1) (2017): 3–28.

75 Ibídem.
76 Gregory M. Walton and Geoffrey L. cohen, “A Brief Social-Belonging Interven-
tion Improves Academic and Health Outcomes of Minority Students," Ciencia 331
(6023): 1447–1451.

77 David S. Yeager, Gregory M. Walton, Shannon T. Brady, et al., “Teaching a Lay The-
ory before College Narrows Achievement Gaps at Scale,” Actas del Congreso Nacional
Academy of Sciences of the United States of America 113 (24) (2016): E3341–E3348.

78 Nicole M. Esteban, Stephanie A. Fryberg, Hazel Rose Markus, et al., “Unseen Dis-
advantage: How American Universities’ Focus on Independence Undermines the
Academic Performance of First-Generation College Students,” Journal of Personality
and Social Psychology 102 (6) (2016): 1178–1197; and Nicole M. Esteban, Sarah S. METRO.
Townsend, Hazel Rose Markus, y yo. Taylor Phillips, “A Cultural Mismatch: En-
dependent Cultural Norms Produce Greater Increases in Cortisol and More Nega-
tive Emotions among First-Generation College Students,” Journal of Experimental So-
cial Psychology 48 (2012) (6): 1389–1393.

79 Nicole M. Esteban, MarYam G. Hamedani, and Mesmin Destin, “Closing the So-
cial-Class Achievement Gap: A Difference-Education Intervention Improves First-
Generation Students’ Academic Performance and All Students’ College Transi-
ción,” Psychological Science 25 (4) (2014): 943–953.

80 David S. Yeager and Gregory M. Walton, “Social-Psychological Interventions in Ed-
ucation: They’re Not Magic,” Review of Educational Research 81 (2) (2011): 267–300.

215

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148 (4) Fall 2019Benjamin Castleman & Katharine Meyer

81 Todd Pugatch and Nicholas Wilson, “Nudging Study Habits: A Field Experiment
on Peer Tutoring in Higher Education,” Economics of Education Review 62 (2018):
151–161.

82 Ibídem.
83 Angrist et al., “Incentives and Services for College Achievement”; and Pugatch and

wilson, “Nudging Study Habits.”

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Dédalo, la Revista de la Academia Estadounidense de las Artes & SciencesFinancial Constraints & Collegiate Student Learning
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