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Washington State Institute for Public Policy
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Learning communities—linked developmental and student success courses (for 2-year college students)

Higher Education
Benefit-cost methods last updated December 2017.  Literature review updated July 2017.
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Linked learning communities co-enroll undergraduate students in two or more courses with the aim to improve academic achievement through increased social and curricular integration. Learning community instructors, sometimes with assistance from a coordinator, integrate curricula by creating lesson plans and shared assignments that facilitate collaboration among students and connections between courses.

In this meta-analysis, students were in their first year at a community college and required developmental education. Student cohorts were co-enrolled in a developmental math or reading course linked with a student success course, which provided lessons focused on time management practices, goal setting and planning, study skills, and using academic and campus resources. Students were enrolled in a learning community for one semester.
BENEFIT-COST
META-ANALYSIS
CITATIONS
The estimates shown are present value, life cycle benefits and costs. All dollars are expressed in the base year chosen for this analysis (2016). The chance the benefits exceed the costs are derived from a Monte Carlo risk analysis. The details on this, as well as the economic discount rates and other relevant parameters are described in our Technical Documentation.
Benefit-Cost Summary Statistics Per Participant
Benefits to:
Taxpayers $50 Benefits minus costs ($234)
Participants $210 Benefit to cost ratio $0.39
Others $105 Chance the program will produce
Indirect ($218) benefits greater than the costs 34 %
Total benefits $147
Net program cost ($381)
Benefits minus cost ($234)
1In addition to the outcomes measured in the meta-analysis table, WSIPP measures benefits and costs estimated from other outcomes associated with those reported in the evaluation literature. For example, empirical research demonstrates that high school graduation leads to reduced crime. These associated measures provide a more complete picture of the detailed costs and benefits of the program.

2“Others” includes benefits to people other than taxpayers and participants. Depending on the program, it could include reductions in crime victimization, the economic benefits from a more educated workforce, and the benefits from employer-paid health insurance.

3“Indirect benefits” includes estimates of the net changes in the value of a statistical life and net changes in the deadweight costs of taxation.
Detailed Monetary Benefit Estimates Per Participant
Benefits from changes to:1 Benefits to:
Taxpayers Participants Others2 Indirect3 Total
Labor market earnings associated with higher education $107 $236 $105 $0 $448
Costs of higher education ($57) ($26) $0 ($28) ($111)
Adjustment for deadweight cost of program $0 $0 $0 ($190) ($190)
Totals $50 $210 $105 ($218) $147
Detailed Annual Cost Estimates Per Participant
Annual cost Year dollars Summary
Program costs $381 2016 Present value of net program costs (in 2016 dollars) ($381)
Comparison costs $0 2016 Cost range (+ or -) 20 %
Costs are based on a weighted average of per-participant costs published in Weiss et al. (2010) and Weissman et al. (2011). Estimates include the direct cost to operate a linked learning community for one semester, including instructor time, coordinator time, student services, and additional student supports like tutors and/or materials.
The figures shown are estimates of the costs to implement programs in Washington. The comparison group costs reflect either no treatment or treatment as usual, depending on how effect sizes were calculated in the meta-analysis. The cost range reported above reflects potential variation or uncertainty in the cost estimate; more detail can be found in our Technical Documentation.
Estimated Cumulative Net Benefits Over Time (Non-Discounted Dollars)
The graph above illustrates the estimated cumulative net benefits per-participant for the first fifty years beyond the initial investment in the program. We present these cash flows in non-discounted dollars to simplify the “break-even” point from a budgeting perspective. If the dollars are negative (bars below $0 line), the cumulative benefits do not outweigh the cost of the program up to that point in time. The program breaks even when the dollars reach $0. At this point, the total benefits to participants, taxpayers, and others, are equal to the cost of the program. If the dollars are above $0, the benefits of the program exceed the initial investment.

^WSIPP’s benefit-cost model does not monetize this outcome.

Meta-analysis is a statistical method to combine the results from separate studies on a program, policy, or topic in order to estimate its effect on an outcome. WSIPP systematically evaluates all credible evaluations we can locate on each topic. The outcomes measured are the types of program impacts that were measured in the research literature (for example, crime or educational attainment). Treatment N represents the total number of individuals or units in the treatment group across the included studies.

An effect size (ES) is a standard metric that summarizes the degree to which a program or policy affects a measured outcome. If the effect size is positive, the outcome increases. If the effect size is negative, the outcome decreases.

Adjusted effect sizes are used to calculate the benefits from our benefit cost model. WSIPP may adjust effect sizes based on methodological characteristics of the study. For example, we may adjust effect sizes when a study has a weak research design or when the program developer is involved in the research. The magnitude of these adjustments varies depending on the topic area.

WSIPP may also adjust the second ES measurement. Research shows the magnitude of some effect sizes decrease over time. For those effect sizes, we estimate outcome-based adjustments which we apply between the first time ES is estimated and the second time ES is estimated. We also report the unadjusted effect size to show the effect sizes before any adjustments have been made. More details about these adjustments can be found in our Technical Documentation.

Meta-Analysis of Program Effects
Outcomes measured Treatment Age No. of effect sizes Treatment N Adjusted effect sizes (ES) and standard errors (SE) used in the benefit-cost analysis Unadjusted effect size (random effects model)
First time ES is estimated Second time ES is estimated
ES SE Age ES SE Age ES p-value
Persistence into 2nd year 21 1 709 -0.009 0.065 22 -0.009 0.065 22 -0.009 0.883
Persistence within 1st year 21 2 1470 0.054 0.043 21 0.054 0.043 21 0.054 0.211
Remedial credits earned^ 21 2 1470 0.031 0.059 22 0.031 0.059 22 0.031 0.604

Citations Used in the Meta-Analysis

Weiss, M.J., Visher, M.G., Wathington, H., & National Center for Postsecondary Research. (2010). Learning communities for students in developmental reading: An impact study at Hillsborough Community College. New York: National Center for Postsecondary Research.

Weissman, E., Butcher, K.F., Schneider, E., Teres J., Collado, H. Greenberg, D. & Welbeck, R. (2011). Learning Communities for Students in Developmental Math: Impact Studies at Queensborough and Houston Community Colleges. New York: National Center for Postsecondary Research.