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The approach lays out prototypical institutions based on a collection of best practices. The prototype is not the median college, but it is also not a baseline institution which has only those characteristics shared by all colleges. That approach would tend to understate the important local context of rural and urban colleges, and obscure one of the purposes of the Real Cost Project—to capture the unique cost structure associated with the diverse student population of the California Community Colleges.

So while the prototype does not describe any actual college perfectly, it is a reasonable representation of typical demographics, generally as reflected in statewide enrollment patterns. As a result, the prototype college looks like California in its relative composition of academic preparation, ethnicity. In addition, the resources prescribed for the prototype were driven by a set of quality indicators, albeit not necessarily outcome measures:.

These Quality Indicators represent an integrated approach to quality student learning and achievement. Group learning, team teaching, learning communities, intensive writing across the curriculum, and individualized interaction between faculty and students are possible at the prototype college because of the combination of smaller classes, a shift in faculty time allocation toward students, extensive professional development and training in pedagogical strategies, and a substantial change in the curriculum.

Every student desiring to transfer to a baccalaureate university would have a meaningful transfer and educational plan—more than merely a ministerial signature on a form. These are essential attributes of a quality education for the broad diversity of students at the California Community Colleges. In a analysis, Bruce Baker and Christopher Morphew developed the conceptual thinking around applying cost modeling to higher education by tackling an important complexity: that unlike K—12 education, where course taking is largely prescribed, college students have greater choice in course selection.

Cost estimates must take into account student pathways to program completion by considering all of the costs associated with providing access to those specific pathways and associated resources. The authors point out that if we are to look at outcome measures such as program or degree completion, one must consider not only the way in which institutions organize their resources, but also the varied ways in which students access those resources toward degree completion.

For example, students completing a program in mathematics navigate their way through general education courses as well as math courses, drawing on resources across units within institutions, not merely the higher-level unit offering the degree or credential. Among those students pursuing degrees in math, there may be a handful of most common pathways which represent resource consumption patterns to completion. Students may also access varied additional supports—academic, residential, and so on—as they navigate their way toward program completion.

A comprehensive and precise estimate of the costs associated with program completion must account for the ways in which students access resources along the way.

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That is, cost estimates must take into account student pathways to program completion by considering all of the costs associated with providing access to those specific pathways and associated resources. The study provided an important advance in how K—12 techniques could apply to the very different world of higher education. The earlier efforts at costing out a college education provide a basis upon which researchers can build in order to try something that is unprecedented: a full-fledged study to estimate the costs of an adequate community college education.

Our goal is to advance the thinking on this question by providing a framework for applying cost estimation methods from elementary and secondary education to community colleges, recognizing the distinctions between the two. Below, we identify eight key decision points that researchers will face in applying well-established K—12 analysis principles to the community college sector. For each challenge, we make recommendations providing our best advice on how to proceed. Issue 1: In beginning to define goals, how should researchers address the non-mandatory nature of attendance in higher education?

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Because students are not required by law to attend community college, how do we define goals in a way that incorporates access? In K—12 education, schooling is typically compulsory for students through age sixteen, so an outcome metric—such as high school completion—starts with a base of students that is universal.

In the community college sector, by contrast, attendance is not mandatory, so a measure that looked at completion rates would not tell us whether a college is doing a good job of providing access to students by recruiting them, offering courses that are in demand at convenient times, and so on. Indeed, a system that defined outcomes strictly in terms of proportion of beginning students who complete could provide a perverse incentive of encouraging community colleges to recruit only the most prepared students, screening out those with less preparation.

Recommendation 1: Any evaluation to determine the costs of providing an adequate system of community colleges must include, as one of many outcome measures, indicators of the population served, and ideally should capture the breadth and equity of access. And one might evaluate the extent to which the population served sufficiently represents disadvantaged student populations in the relevant service region.

To calculate the cost associated with a particular goal requires that researchers define the outcome measures and the levels denoting accomplishment of the goal. In this case, to determine the types and quantities of resources necessary to successfully recruit and serve a particular population of students requires that one first define the target population.

To this end, a key step would be to perform a descriptive analysis of the composition of enrollment with respect to student characteristics for example, low-income status, first-generation college enrollee, ethnic minority, and so on across college campuses throughout the state. Recruitment targets would then be set across the groups, which would be included as part of the goal definition.

Note that results of the descriptive analysis would be used as a baseline. That is, the chosen targets may not be simply to achieve the average composition of enrolling students, but rather to significantly improve recruitment among student groups who are currently underrepresented. Costs of the efforts involved in an expanded targeted recruitment effort, as well as the different and possibly additional supports necessary to adequately serve the new composition of enrolling students, could then be calculated through an input-oriented method, such as professional judgment. Issue 2: In further defining goals, should researchers consider intermediate metrics, such as completion, or ultimate goals, such as labor market outcomes, or some combination of the two?

Among the thorniest issues researchers face in applying K—12 costing-out techniques is articulating a clear set of goals for adequate outcomes. K—12 cost analyses have the convenience of falling back on short-run academic outcomes as their goal, as those outcomes are predictive of success at the next stage of their education. Many community college programs are career-specific, and thus the desired outcomes are employment and income. Should researchers consider labor market outcomes as the appropriate measure, intermediate measures such as retention and completion and transfer, or some combination of the two?

In their background report for the working group, Anthony Carnevale, Jeff Strohl, and Artem Gulish of Georgetown University make the argument that economic adequacy is a necessary condition to achieve educational adequacy. In making this argument, they suggest that labor market outcomes are the most appropriate metric. Because delivering economic self-sufficiency is critical, they argue, a community college education should help students attain skills that will enable them to earn a living.

In American society, where government provides few supports to those not in the labor market, human flourishing requires that individuals be economically self-sufficient. Merely providing resources to allow students to complete a community college certificate or degree is an insufficient measure of success, Carnevale and colleagues argue, because completion does not guarantee adequate labor market outcomes.

What level of labor market success is necessary to allow for human flourishing in contemporary American society? Carnevale and colleagues argue this two-part standard provides the minimum economic self-sufficiency necessary for human flourishing because it allows for entry into the bottom rungs of the middle class. They further note that because there are so many different costs associated with achieving completion outcomes in different programs, it is not possible, using a completion metric, to estimate a single cost for a community college education.

We think this approach has many strengths. Monitoring these data makes sense, and the use of the measures as minimal thresholds could be appropriate in some circumstances. But as Carnevale and colleagues themselves note, a number of complications arise with operationalizing a stand-alone labor market outcome goal. For one thing, the ability to achieve these economic targets is not in the control of the community colleges alone. Linking employment and income to program quality is complicated by regional labor market variations, employment supply and demand, and temporal cycles.

These outcomes depend on economic conditions, and labor markets that can fluctuate more rapidly than institutions can adapt. It is questionable whether we would want our community colleges to try to adapt to every cyclical shift in employment demand.

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Moreover, it is questionable whether we would want our community colleges to try to adapt to every cyclical shift in employment demand. Specifically, while earnings growth might be one measure upon which to judge community college performance, it would be undesirable to structure goals such that community colleges are put in the position of determining program offerings based only on their expected labor market returns. In addition, the ten-year lag between the observed goal and the programmatic investment complicates the application of this standard.

Indeed, it is based only on those who currently complete community college credentials, who constitute less than 40 percent of all those currently enrolled—and only two-thirds of that group now achieve this standard.


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See issue 3 below, discussing appropriate rates of success for which policymakers should strive. Exactly what these alternative standards should be, and for how many students each standard is appropriate, could be determined by further research. We are also concerned about the effect of predicating the goals of community colleges on a single result—labor market outcomes. Public opinion research suggests individuals have a wide variety of rationales for pursuing community college.

In this way, education is similar to other public goods, such as parks, that public dollars regularly support. Furthermore, potential income varies by the program or degree sought, which in turn is a function of the interests and desires of individual students. It may well be that the expected income for a graduate of a computer technology training program exceeds that for the veterinary technician from the same institution. But the animal lover who truly desires to be a veterinary technician might find little life satisfaction in maintaining and troubleshooting a bank of computer servers in a corporate basement.

If the community college will not offer veterinary programs, she may seek that program elsewhere, perhaps through a private online provider who will offer an inferior program. At the very least, the outcome measures must be sensitive to student choices, and must vary by program, degree, certificate, or academic trajectory. In part for these reasons, as Baker and Levin point out, most existing mechanisms of accountability for community colleges—such as performance-based funding—use proximal measures, such as completion, rather than distal measures, such as labor market outcomes.

At the same time, we agree with Carnevale and colleagues that proximal measures by themselves are not sufficient, because completion of a degree that does not support adequate earnings cannot be considered a benchmark of success.


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We therefore suggest a third path that brings together proximal and distal outcome measures. Recommendation 2: Proximal measures such as successful completion of a program should serve as the primary goal. In other words, we recommend bringing together the recommendations in the two previous reports by Carnevale, Gulish, and Strohl and by Baker and Levin.

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Given practical concerns, preliminary attempts to estimate the cost of adequate community college programs should focus on intermediate measurable outcomes, such as access, persistence, and completion toward degrees, certificates, or successful transfer followed by completion. However, degree and certificate completion measures can be validated by their relation to longer-term economic outcomes. Researchers would provide an estimate for what it costs to achieve a reasonable level of completion in a particular program.

That information is important given that completion, whatever the labor market outcomes, can have independent value. Separately—looking at labor market outcomes for graduates of this program across a variety of community colleges over time—researchers would provide an estimate of what it costs to make it likely that graduates in the program will also meet a labor market wage test. Policymakers would have information about costs associated with meeting the completion standard on the one hand, and the labor market standard on the other, and individual states could decide the relative weight to be accorded to each factor at any given point in time.

Issue 3: In defining goals even further, how should researchers assess the appropriate level of success to be costed out? Not everyone in a state is likely to complete a community college degree or certificate or higher, for example, so how should the appropriate degree of success sought be determined? How should such goals be set? Similar percentages would need to be calculated for those earning certificates with reasonable labor market returns.

Alternatively, policymakers could conduct surveys of stakeholders to determine acceptable success rates.

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As outlined below, we recommend a combination of approaches. Recommendation 3: Researchers should cost out not a single success rate, but instead focus on a range of possible levels of success, guided by research on community needs and public engagement of stakeholders. In addition, this question can be greatly informed through authentic public engagement where individuals with a stake in community college success rates are able to provide input as to what they perceive as an appropriate goal. Public engagement of this sort has been undertaken in K—12 cost studies.

For example, in the adequacy studies for New Mexico and New York, researchers held public engagement forums throughout the state to promote input from parents, teachers, business leaders, taxpayers, and other citizens as to what constitutes an adequate education that is, how the goals should be defined. For the New Mexico study, two surveys were administered to all legislators, superintendents, and principals in the state, and to the general public, respectively. Issue 4: How should researchers capture costs across different educational units: at the program level, institutional level, or some combination?

As discussed earlier, in K—12 costing-out studies, the unit of analysis is typically a school district or an individual school because there are common outcome goals and roughly common cost structures for programs.