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Washington State Institute for Public Policy
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Tutoring: By adults, one-on-one, structured

Pre-K to 12 Education
Benefit-cost methods last updated December 2019.  Literature review updated June 2014.
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The programs included in this analysis are structured, systematic approaches to tutoring struggling students in specific English language arts and/or mathematics skills. They include a variety of specific programs and curricula such as (in no particular order) Reading Recovery, Mathematics Recovery, Edmark Reading Program, Howard Street Tutoring, and Early Intervention Program. The programs typically serve early elementary school students and provide, on average, about 30 hours of tutoring time to an individual student each year. Tutors are typically certificated teachers or specially trained adults (e.g. instructional aides and community volunteers). Tutors receive approximately ten hours of training per year with a focus on the specific content and general tutoring strategies.
The estimates shown are present value, life cycle benefits and costs. All dollars are expressed in the base year chosen for this analysis (2018). 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 $3,692 Benefits minus costs $13,274
Participants $8,673 Benefit to cost ratio $6.43
Others $4,575 Chance the program will produce
Indirect ($1,222) benefits greater than the costs 95 %
Total benefits $15,719
Net program cost ($2,445)
Benefits minus cost $13,274
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 test scores $3,692 $8,673 $4,575 $0 $16,941
Adjustment for deadweight cost of program $0 $0 $0 ($1,222) ($1,222)
Totals $3,692 $8,673 $4,575 ($1,222) $15,719
Detailed Annual Cost Estimates Per Participant
Annual cost Year dollars Summary
Program costs $2,291 2013 Present value of net program costs (in 2018 dollars) ($2,445)
Comparison costs $0 2013 Cost range (+ or -) 10 %
In the evaluations included in the meta-analysis, the average structured one-on-one tutoring program provides 30 hours of intervention per student and ten hours of training time per tutor. The estimates assume that both certificated teachers and other adults (e.g. instructional aides) provide tutoring. To calculate a per-student annual cost, we used average Washington State compensation costs (including benefits) for K–8 teachers and instructional aides as reported by the Office of the Superintendent of Public Instruction.
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.

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
Test scores 7 23 2097 0.211 0.038 7 0.099 0.042 17 0.508 0.001

Citations Used in the Meta-Analysis

Allor, J., & McCathren, R. (2004). The efficacy of an early literacy tutoring program implemented by college students. Learning Disabilities Research and Practice, 19(2), 116-129.

Fuchs, L.S., Geary, D.C., Compton, D.L., Fuchs, D., Schatschneider, C., Hamlett, C. L., . . .Changas, P. (2013). Effects of first-grade number knowledge tutoring with contrasting forms of practice. Journal of Educational Psychology, 105(1), 58-77.

Iversen, S., & Tunmer, W. E. (1993). Phonological processing skills and the Reading Recovery program. Journal of Educational Psychology, 85(1), 112-126.

Jacob, R.T., Smith, T.J., Willard, J.A., and & Rifkin, R.E. (2014). Reading Partners: The implementation and effectiveness of a one-on-one tutoring program delivered by community volunteers (MDRC Policy Brief). New York: MDRC.

Mantzicopoulos, P., Morrison, D., Stone, E., & Setrakian, W. (1992). Use of the SEARCH/TEACH tutoring approach with middle-class students at risk for reading failure. Elementary School Journal, 92(5), 573-586.

Mayfield, L.G. (2000). The effects of structured one-on-one tutoring in sight word recognition of first-grade students at-risk for reading failure. Dissertation Abstracts International, 61(02), 481A.

McCarthy, P., Newby, R.F., & Recht, D.R. (1995). Results of an early intervention program for first grade children at risk for reading disability. Reading Research and Instruction, 34(4), 273-294.

Morris, D., Shaw, B., & Perney, J. (1990). Helping low readers in grades 2 and 3: An after-school volunteer tutoring program. Elementary School Journal, 91(2), 133-150.

Mostow, J., Aist, G., Burkhead, P., Corbett, A., Cuneo, A., Eitelman, S., . . . Tobin, B. (2003). Evaluation of an automated reading tutor that listens: Comparison to human tutoring and classroom instruction. Journal of Educational Computing Research, 29(1), 61-117.

Nielson, B.B. (1992). Effects of parent and volunteer tutoring on reading achievement of third grade at-risk students. Dissertation Abstracts International, 52(10), 3570A.

Pinnell, G.S., DeFord, D.E., & Lyons, C.A. (1988). Reading recovery: Early intervention for at-risk first graders. Arlington, VA: Educational Research Service. (ERIC Document Reproduction Service No. ED 303790)

Pinnell, G.S., Lyons, C.A., DeFord, D.E., Bryk, A.S., & Seltzer, M. (1994). Comparing instructional models for the literacy education of high-risk first graders. Reading Research Quarterly, 29(1), 9-39.

Pullen, P.C., Lane, H.B., & Monaghan, M.C. (2004). Effects of a volunteer tutoring model on the early literacy development of struggling first grade students. Reading Research and Instruction, 43(4), 21-40.

Rodick, J.D., & Henggeler, S.W. (1980). The short-term and long-term amelioration of academic and motivational deficiencies among low-achieving inner-city adolescents. Child Development, 51(4), 1126-1132.

Schwartz, R.M. (2005). Literacy learning of at-risk first-grade students in the reading recovery early intervention. Journal of Educational Psychology, 97(2), 257-267.

Smith, T.M., Cobb, P., Farran, D.C., Cordray, D.S., & Munter, C. (2013). Evaluating math recovery: Assessing the causal impact of a diagnostic tutoring program on student achievement. American Educational Research Journal, 50(2), 397-428.

Vadasy, P.F., Jenkins, J.R., Antil, L.R., Wayne, S.K., & O'Connor, R.E. (1997). The effectiveness of one-to-one tutoring by community tutors for at-risk beginning readers. Learning Disability Quarterly, 20(2), 126-139.

Vadasy, P.F., Jenkins, J.R., & Pool, K. (2000). Effects of tutoring in phonological and early reading skills on students at risk for reading disabilities. Journal of Learning Disabilities, 33(6), 579-590.

Vadasy, P.F., Sanders, E.A., & Tudor, S. (2007). Effectiveness of paraeducator-supplemented individual instruction: Beyond basic decoding skills. Journal of Learning Disabilities, 40(6), 508-525.