skip to main content
Washington State Institute for Public Policy
Back Button

Teacher professional development: Not targeted

Pre-K to 12 Education
Benefit-cost methods last updated December 2023.  Literature review updated June 2014.
Open PDF
Generally, professional development (PD) for K–12 teachers includes activities such as workshops, conferences, summer institutes, and time set aside during the school year for staff development. The evaluations included in this analysis examine impacts on student outcomes from providing more time and funding for teacher PD without directing how those resources are used.
 
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 (2022). 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 $7 Benefits minus costs ($124)
Participants $17 Benefit to cost ratio ($0.19)
Others $9 Chance the program will produce
Indirect ($52) benefits greater than the costs 39%
Total benefits ($20)
Net program cost ($105)
Benefits minus cost ($124)

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. See Estimating Program Effects Using Effect Sizes for additional information.

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
Standardized, validated tests of academic achievement.
10 12 461497 0.000 0.002 11 0.000 0.002 17 0.000 0.996
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
Test scores Labor market earnings associated with test scores $7 $17 $9 $0 $33
Program cost Adjustment for deadweight cost of program $0 $0 $0 ($52) ($52)
Totals $7 $17 $9 ($52) ($20)
Click here to see populations selected
Detailed Annual Cost Estimates Per Participant
Annual cost Year dollars Summary
Program costs $86 2013 Present value of net program costs (in 2022 dollars) ($105)
Comparison costs $0 2013 Cost range (+ or -) 10%
In the evaluations included in the meta-analysis, teachers received an average of 20 additional hours of non-targeted professional development (PD) in comparison with the usual amount of PD time. We calculated the value of PD time using average teacher salaries (including benefits) in Washington State as reported by the Office of Superintendent of Public Instruction. To calculate a per-student annual cost, we divided compensation costs by the number of students per classroom in Washington's prototypical schools formula and add per-student materials, supplies, and operating costs to account for the overhead (i.e. facility and administrative costs) associated with providing PD.
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

Angrist, J.D., & Lavy, V. (2001). Does teacher training affect pupil learning? Evidence from matched comparisons in Jerusalem public schools. Journal of Labor Economics, 19(2), 343-369.

Antoniou, P., & Kyriakides, L. (2013). A Dynamic Integrated Approach to teacher professional development: Impact and sustainability of the effects on improving teacher behaviour and student outcomes. Teaching and Teacher Education, 29(1), 1-12.

Cardelle-Elawar, M. (1995). Effects of metacognitive instruction on low achievers in mathematics problems. Teaching and Teacher Education, 11(1), 81-95.

Dalton, E.A. (2010). Relationship between professional development expenditures and student achievement. (Doctoral dissertation, Tarleton State University, 2010, UMI No. 3428757).

Duffy, G.G., Roehler, L.R., Meloth, M.S., Vavrus, L.G., Book, C., Putnam, J., & Wesselman, R. (1986). The relationship between explicit verbal explanations during reading skill instruction and student awareness and achievement: A study of reading teacher effects. Reading Research Quarterly, 21(3), 237-252.

Harris, D.N., & Sass, T.R. (2011). Teacher training, teacher quality and student achievement. Journal of Public Economics, 95(7-8), 798-812.

Jacob, B.A., & Lefgren, L. (2004). The impact of teacher training on student achievement: Quasi-experimental evidence from school reform efforts in Chicago. The Journal of Human Resources, 39(1), 50-79.

McGill-Franzen, A., Allington, R.L., Yokoi, L., & Brooks, G. (1999). Putting books in the classroom seems necessary but not sufficient. The Journal of Educational Research, 93(2), 67-74.

Siegle, D. & McCoach, D. (2007). Increasing student mathematics self-efficacy through teacher training. The Journal of Secondary Gifted Education, 18(2), 278-331.

Sloan, H.A. (1993). Direct instruction in fourth and fifth grade classrooms. Dissertation Abstracts International, 54(08), 2837A.