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School-based mentoring for attendance

Pre-K to 12 Education
Benefit-cost methods last updated December 2024.  Literature review updated April 2026.
The studies in this analysis include mentoring programs in which supporting student attendance is a primary goal. Mentoring programs are school-based, and students meet with mentees generally one-on-one for an average of 18 months. Mentees were mostly trained school staff, but one study included college student mentors and one study included peer mentors. Most programs targeted elementary and middle school students, though one focused on high school students. Students were generally identified for mentoring services based on the number of absences, academic standing, and other factors like behavioral incidents or school attitude.

Two studies focused on the Check & Connect program, one study focused on the U.S. Department of Education’s Student Mentoring Program, one study focused on the Peer Group Connection-Middle School program, and one study examined a general program.
 
ALL
BENEFIT-COST
META-ANALYSIS
CITATIONS
For an overview of WSIPP's Benefit-Cost Model, please see this guide. The estimates shown are present value, life cycle benefits and costs. All dollars are expressed in the base year chosen for this analysis (2023).  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 $63 Benefits minus costs ($2,309)
Participants $147 Benefit to cost ratio ($0.33)
Others $78 Chance the program will produce
Indirect ($866) benefits greater than the costs 0%
Total benefits ($578)
Net program cost ($1,731)
Benefits minus cost ($2,309)

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

^^WSIPP does not include this outcome when conducting benefit-cost analysis for this program.

Meta-analysis is a statistical method to combine the results from separate studies on a program, policy, or topic to estimate its effect on an outcome. WSIPP systematically evaluates all credible evaluations we can locate on each topic. The outcomes measured are the program impacts measured in the research literature (for example, impacts on 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. See Estimating Program Effects Using Effect Sizes for additional information on how we estimate effect sizes.

The effect size may be adjusted from the unadjusted effect size estimated in the meta-analysis. Historically, WSIPP adjusted effect sizes to some programs based on the methodological characteristics of the study. For programs reviewed in 2024 or later, we do not make additional adjustments, and we use the unadjusted effect size whenever we run a benefit-cost analysis.

Research shows the magnitude of effects may change 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. 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 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
Dropout^
Leaves school for any reason before completing school with a high school diploma.
 9 1 276 0.119 0.128 12 n/a n/a n/a 0.119 0.353
Grade point average^
Non-standardized measure of student performance calculated across subjects.
9 1 1972 -0.017 0.029 11 n/a n/a n/a -0.017 0.567
High school graduation^^
On-time completion of high school with a diploma (excluding GED attainment).
 9 1 276 -0.010 0.103 12 -0.010 0.103 18 -0.010 0.925
Test scores^^
Standardized, validated tests of academic achievement.
9 2 3135 -0.030 0.025 10 -0.020 0.028 17 -0.030 0.226
Office discipline referrals^
Referrals of a student to an administrative office for disciplinary reasons.
9 1 16 -1.044 0.377 9 n/a n/a n/a -1.044 0.006
School absence
Number of school days missed in a given enrollment period.
 9 5 6865 -0.049 0.041 10 -0.049 0.041 10 -0.049 0.235
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
Affected outcome: Resulting benefits:1 Benefits accrue to:
Taxpayers Participants Others2 Indirect3 Total
School absence Labor market earnings associated with test scores $63 $147 $78 $0 $288
Program cost Adjustment for deadweight cost of program $0 $0 $0 ($866) ($866)
Totals $63 $147 $78 ($866) ($578)
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Detailed Annual Cost Estimates Per Participant
Annual cost Year dollars Summary
Program costs $1,731 2023 Present value of net program costs (in 2023 dollars) ($1,731)
Comparison costs $0 2023 Cost range (+ or -) 20%
Four of the five studies in the analysis report annual per-participant cost information. We use information in Lass et al. (2023) to estimate costs. For this program, we assume two teachers serve as advisors to the student mentors. The teachers participate in 80 hours of training. We apply average Washington State compensation costs (including benefits) for a 9-12th grade teacher as reported by the Office of the Superintendent of Public Instruction, divided by the total number of students served in the studies. We assume an additional $30 per student for materials, supplies, and operating costs. We then weight per-participant costs across the studies, based on sample sizes, and inflate dollars to 2023.
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.
Benefits Minus Costs
Benefits by Perspective
Taxpayer Benefits by Source of Value
Benefits Minus Costs Over Time (Cumulative 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 discounted dollars. 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.

Citations Used in the Meta-Analysis

Bernstein, L., Rappaport, C.D., Olsho, L., Hunt, D., & Levin, M. (2009). Impact evaluation of the U.S. Department of Education's Student Mentoring Program: Final report (NCEE 2009-4047). National Center for Education Evaluation and Regional Assistance.

Converse, N., & Lignugaris-Kraft, B. (2008). Evaluation of a school-based mentoring program for at-risk middle school youth. Remedial and Special Education, 30(1), 33–46.

Guryan, J., Christenson, S., Cureton, A., Lai, I., Ludwig, J., Schwarz, C., Shirey, E., & Turner, M. C. (2020). The effect of mentoring on school attendance and academic outcomes: A randomized evaluation of the Check & Connect program. Journal of Policy Analysis and Management, 40(3), 841–882.

Heppen, J.B., Zeiser, K., Holtzman, D.J., O'Cummings, M., Christenson, S., & Pohl, A. (2018). Efficacy of the Check & Connect mentoring program for at-risk general education high school students. Journal of Research on Educational Effectiveness, 11(1), 56–82.

Lass, K., Walsh, S., Demby, H., Snider, R., Burgess, K., & Jenner, E. (2023). Evaluation of peer group connection-middle school: Final impact evaluation report.