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“The key is relationships”: Personalized learning at Learn4Life charter schools
It is a Wednesday afternoon in May, and for most students at Desert Sands Charter School, it is a pretty normal day—though it might not look normal compared to many other schools. A large, warehouse-like room that was originally designed to be an Office Depot makes up almost the entire schoolhouse, and several activities are happening at once. Some students work quietly on packet assignments at the rows of desks in the center of the space. Others meet individually with teachers at one of the many faculty desks that circle the room. Still others work in groups with a teacher in one of the small classrooms along the walls.
The activity suddenly pauses when one teacher stands and calls for everyone’s attention. Everyone looks toward the teacher and female student standing in front of him. Holding out a certificate, the teacher announces that Desert Sands has just produced its newest high school graduate. A chorus of cheers fills the air, and each teacher rings a bell to congratulate the girl as she receives her diploma.
Desert Sands is part of Learn4Life, a network of charter schools that uses a personalized learning model—driven by teachers who provide one-on-one instruction and build individualized learning plans—to help high school students who have dropped out, are at risk of dropping out, or are struggling in other ways with the public school system to reach graduation and postsecondary achievement.1
During a May visit to Learn4Life’s headquarters and two of its schools in Lancaster, California, the wide-open instruction spaces and small-group classrooms were a marked contrast to typically structured schools. The enthusiasm in the graduation celebration at Desert Sands was also reflected in interviews with administrators, faculty, staff, and students. Amid all the enthusiasm, the question remains: Is this enthusiastic environment and focused personalized learning model delivering the supports these mostly struggling students need for success?
While Learn4Life’s mission to lift students on the brink of failure to success through individualized instruction is exciting, it also involves some serious challenges. Those involved in this promising yet difficult approach deserve praise for their work, even if there is no guarantee that it works across the board. In the end, Learn4Life’s programs offer compelling insights about the potential for, benefits of, and hazards around this application of personalized learning.
Learn4Life also has a K–8 program, which it describes as its “home study program” that provides learning resources and lesson planning to parents who decide to homeschool their children. This program makes up a tiny portion of the Learn4Life organization, serving roughly 500 of its 47,000 students each year.
Learn4Life’s administrators said that while their schools offer the program on an “as-needed basis,” it is not their “core mission” of reengaging students who have or are at risk of dropping out of high school
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What consumer choice in higher education can teach about better serving K–12 students
If parts of the educational experience can be delivered more efficiently, then unused resources can be spent elsewhere. In high schools, newly available resources could be spent on needed student services. In colleges, prices could be lowered. Online learning and enterprise software enable more efficient service delivery. However, these efficiencies are usually captured by schools and colleges rather than enjoyed by students in the form of more services or lower prices.
In postsecondary education, the existence of a viable—even if often dysfunctional—consumer market is driving change. However, for high schools, driving efficiencies to students requires a new approach to internal resource allocation that integrates the price of services into school choice. If successful, high school students on the margins—dropouts, chronic absentees, working students, adults, and homeschoolers—will benefit from a market with more, and better, targeted services.
From a little over $7,000 in Utah to over $20,000 in Vermont, the per-student cost of K–12 education is well-known and varies widely across states and districts. However, ask what the price of a K–12 education should be, and the result is, rightly, a blank stare. When a public service is fully subsidized, the cost and price are both however much taxpayers are willing to provide.
Colleges are also subsidized, yet students pay to attend. Although the price varies depending on the student and college and is often opaque to the student, this crucial distinction ensures that a distorted, yet functional, consumer market exists in postsecondary education. Accordingly, over the past decade or so new models of internet-driven postsecondary education—both in and outside colleges—that lower price, lower student financial risk, increase speed to completion, and increase the likelihood of employment have started and are accelerating. Although sometimes threatening to accredited colleges, these models—often in partnership with unaccredited providers—are being adopted more broadly. Such innovation has not occurred in K–12.
Whether a wheel, pencil, car, computer, smartphone, administrative system, or online course, a new technology must create value for its users to become pervasive. Value can be defined as doing the same thing better, doing the same thing for less, or both. Often, a new technology will start by doing the same thing better for a small group of users or enabling new users to do something they could never do previously. Then, as the technology becomes more mature and widespread, it becomes cheaper, thereby accelerating its adoption, driving even greater value to consumers, and changing the market. The crucial element to widespread adoption is the customer’s ability to choose based on price and the associated ability to spend saved resources on something else of value. This drives the flywheel of competition, innovation, and market evolution.
Over the past 20 years, the internet has enabled students to access, and accredited schools and colleges to provide, a breadth of coursework in locations and on a schedule that would have otherwise been impossible. Over six million college students—roughly one-third of all students—took at least one class online in fall 2016.1 In K–12, about 2.7 million students took 4.5 million supplemental online courses in 2014–15.2 In other words, students are enrolling in online coursework from accredited schools and colleges to do the same thing “better.”
Online course delivery is also much cheaper than face-to-face delivery is. By relying on servers instead of buildings, digital content instead of print, courseware instead of lectures, and remote instructors instead of in-person instructors, distance education can reduce the fixed and marginal cost of delivery. By separating coursework from nonacademic functions, it can also unbundle the price-raising subsidies that support athletic teams, school security, student centers, dormitories, cafeterias, parking lots, some student support services, and the overhead to support it. Lastly, by amortizing what infrastructure costs do exist across a much-larger customer base, distance education further reduces the cost per course delivered. Despite this, over 90 percent of colleges charge the same or more for online courses as for face-to-face courses.3
When there are significant changes to any service’s delivery model, providers have a strong incentive to offer the new capabilities to their users but a strong disincentive to lower the price. In unsubsidized markets, new providers emerge that force price reductions across the market, thereby driving benefits to consumers. In heavily subsidized markets such as public K–12 and accredited colleges, new providers are at a competitive disadvantage, thereby slowing or prohibiting their emergence.
Without new providers, savings derived from the new, lower cost of delivery accrue to the school or college rather than the student. However, so long as consumers pay some portion of the cost, then eventually the market will adapt such that the “profit” flows to the student in the form of lower prices and new features. The postsecondary education market, of which accredited colleges are a subset, is undergoing such a change. The K–12 market is not, but it could.
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The surprising role of high-income families in student debt trends: Examining undergraduate borrowing by income, 1995–96 to 2015–16
Observers from across the ideological spectrum argue that the US is in the midst of a student debt crisis. This view is largely motivated by the fact that student debt now totals $1.5 trillion after rising rapidly in the past decade, particularly during the last economic recession.1 In 2003, outstanding debt was just $311 billion after adjusting for inflation.2
These trends have prompted several Democratic presidential candidates to propose that the federal government forgive most or all outstanding student debt (the vast majority of which was issued through federal programs).3 They argue that the debt is unaffordable for many and is the result of severe inequities in our higher education system. Concern about inequitable student debt extends beyond public policy. A growing number of private employers now repay a share of their employees’ student loans in part out of concern that students from disadvantaged backgrounds are the ones most likely burdened by debt.4
In light of these loan forgiveness proposals, employer-sponsored benefits, and the broader concerns about rising student debt, understanding who takes on student loans is important. A clearer picture of who borrows will help identify the beneficiaries of broad loan forgiveness proposals and the more limited employer repayment benefits, or any other policy aimed at reducing student debt and repayment obligations. It can also help gauge the extent to which student debt burdens reflect inequities in the US higher education system.
Prior analyses on this topic focus on the demographics of borrowers who currently hold the $1.5 trillion in outstanding debt. For example, researchers at the Urban Institute show that higher-income households hold a disproportionately large share of all student debt.5 Using different data, the Federal Reserve Bank of New York reports similar findings but also concludes that relative to household earnings, debt is higher among lower-income households.6
This report takes a different approach to understanding who holds student debt. It examines borrowers’ characteristics when the loans were originated, whereas the studies mentioned above capture borrowers at any point during repayment. Both perspectives are useful, but the former is less common in policy discussions. Moreover, previous research on income characteristics at loan origination appears at odds with data on borrowers in repayment. Some analyses focused on demographics at loan origination conclude that low- and middle-income students are “more than twice as likely as other students to have student loans” or that “high student debt goes hand in hand with low income.”7
To help fill the void in the research, this analysis focuses on borrowing patterns among students who enrolled in an institution of higher education in the 1995–96 and 2015–16 academic years. (It includes data points for the intervening years in an appendix.) The analysis is limited to two main statistics for undergraduates by family income: the share of students who took on debt and the amount they borrowed. These statistics are reported for two distinct groups of students at different points in their enrollment: first-year undergraduates and students who earned a bachelor’s degree in the years covered in this analysis 8 Data for the analysis come from the US Department of Education’s National Postsecondary Student Aid Study (NPSAS), which provides a representative sample of the undergraduate population for the 1995–96, 1999–2000, 2003–04, 2007–08, 2011–12, and 2015–16 academic years.9
While debt from graduate and professional students makes up a large share of all outstanding student debt (approximately 40 percent), this analysis excludes these students.10 The income information included in the NPSAS is difficult to interpret for these students because it reflects the student’s own income (and income from a spouse) while enrolled as a graduate student. The undergraduate data include parental income for dependent students or the student’s own income if he or she is an independent. This analysis includes both dependent and independent undergraduate students despite this difference because the overall findings are similar when only dependent students are included in the analysis.
Note that independent students, who tend to have low incomes and make up about half of undergraduates, skews the income distribution of the undergraduate population in this analysis (shown in Appendix C). Debt figures for this analysis include the amount of principal borrowed for all types of student debt (federal student and parent loans, private, state, etc.). They do not show unpaid interest. The 1995–96 and 1999–2000 data sets include loans that a student received from a family member in aggregated borrowing figures, but later data sets exclude these loans. To be consistent, this analysis excludes family loans from earlier data sets.11 Borrowers are grouped into five income categories that approximate the US household income quintiles for the last year in the analysis, 2015–16.12
The Congressional Budget Office estimates that 42 percent of annual loan disbursals measured in dollars are for students attending graduate and professional school. Federal budget tables do not include figures for the share of outstanding debt used to finance graduate and professional educations. An Urban Institute study finds that 48 percent of outstanding student debt is held by households that include someone with a master’s or professional degree. This debt, however, includes loans that financed an undergraduate education.
About 15 percent of undergraduates reported these family loans at an average of about $3,700 in 1995 dollars. See variables FAMLOAN and FAMOWE in the 1995–96 NPSAS at National Center for Education Statistics
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