Not Too Late: Improving Academic Outcomes Among Adolescents
Open accessAbstract
There is growing concern that it is too difficult or costly to substantially improve the academic skills of children who are behind in school once they reach adolescence. But perhaps what we have tried in the past relies on the wrong interventions, failing to account for challenges like the increased variability in academic needs during adolescence, or heightened difficulty of classroom management. This study tests the effects of one intervention that tries to solve both problems by simplifying the teaching task: individualized, intensive, in-school tutoring. A key innovation by the non-profit we study (Saga Education) is to identify how to deliver "high-impact tutoring" at relatively low cost ($3,500 to $4,300 per participant per year). Our first randomized controlled trial (RCT) of Saga's tutoring model with 2,633 9th and 10th grade students in Chicago public schools found participation increased math test scores by 0.16 standard deviations (SDs) and increased grades in math and non-math courses. We replicated these results in a separate RCT with 2,710 students and found even larger math test score impacts-0.37 SD-and similar grade impacts. These effects persist into future years, although estimates for high school graduation are imprecise. The treatment effects do not appear to be the result of a generic "mentoring effect" or of changes in social-emotional skills, but instead seem to be caused by changes in the instructional "technology" that students received. The estimated benefit-cost ratio is comparable to many successful model early-childhood programs.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
0 of 36 cited sources checked · 0 supported · 0 flagged
- Findingreasoning
The treatment effects do not appear to be the result of a generic mentoring effect.
“The treatment effects do not appear to be the result of a generic “mentoring effect” or of changes in social-emotional skills, but instead seem to be caused by changes in the instructional “technology” that students received.”
Quote in the paperSubstantial claim - Findingown data
In a separate RCT with 2,710 students, math test score impacts were 0.37 standard deviations.
“We replicated these results in a separate RCT with 2,710 students and found even larger math test score impacts-0.37SD-and similar grade impacts.”
Quote in the paperSubstantial claim - Findingown data
In the first RCT with 2,633 9th and 10th grade students in Chicago public schools, participation increased math test scores by 0.16 standard deviations.
“Our first randomized controlled trial (RCT) of Saga's tutoring model with 2,633 9th and 10th grade students in Chicago public schools found participation increased math test scores by 0.16 standard deviations (SDs) and increased grades in math and non-math courses.”
Quote in the paperSubstantial claim - Findingown data
The treatment effects persist into future years.
“These effects persist into future years, although estimates for high school graduation are imprecise.”
Quote in the paperSubstantial claim - Findingown data
In the separate RCT with 2,710 students, grade impacts were similar to those in the first RCT.
“We replicated these results in a separate RCT with 2,710 students and found even larger math test score impacts-0.37SD-and similar grade impacts.”
Quote in the paperSubstantial claim
- Findingown data
After one year of program participation in study 1, the intention-to-treat effect on standardized math achievement test scores is 0.08 standard deviations.
“After one year of program participation the intention-totreat effect (ITT) on standardized math achievement test scores is 0.08 standard deviations (SD), and the treatment-on-the-treated (TOT) effect is 0.16 SD.”
Quote in the paperSubstantial claim - Findingown data
After one year of program participation in study 1, the treatment-on-the-treated effect on standardized math achievement test scores is 0.16 standard deviations.
“After one year of program participation the intention-totreat effect (ITT) on standardized math achievement test scores is 0.08 standard deviations (SD), and the treatment-on-the-treated (TOT) effect is 0.16 SD.”
Quote in the paperSubstantial claim - Findingreasoning
The treatment effects do not appear to be the result of changes in social-emotional skills.
“The treatment effects do not appear to be the result of a generic “mentoring effect” or of changes in social-emotional skills, but instead seem to be caused by changes in the instructional “technology” that students received.”
Quote in the paperSubstantial claim - Findingown data
There is no evidence consistent with classroom management being the key mechanism, in the sense that impacts are no larger in schools where disciplinary incidents in classrooms at baseline are more common.
“Nor do we find evidence consistent with the idea of classroom management being the key mechanism in the sense that the impacts are no larger in schools where disciplinary incidents in classrooms at baseline are more common.”
Quote in the paperSubstantial claim - Findingown data
There are no signs of increased effort in survey data.
“(This could simply reflect increased effort, but we see no signs of that in survey data.)”
Quote in the paperNot a substantial claim- Rests on an assumption: The survey measures of social-emotional skills and relationships with adults validly capture the constructs they are intended to measure.
- Findingown data
There is a decline in math course failures of 49%.
“and a decline in math course failures of 49%.”
Quote in the paperSubstantial claim - Findingown data
There is a treatment-on-the-treated effect on grades in regular classroom math courses equal to 0.56 points on a 0 to 4-point scale.
“we also see a TOT effect on grades in regular classroom math courses equal to 0.56 points (on a 0 to 4-point scale)”
Quote in the paperSubstantial claim - Findingcitation
Over the range of tutors hired, there is little difference between tutors at the top versus the bottom of Saga's ranked hiring list.
“We do not know how many tutors it would be possible to hire before effectiveness declines, but over this range there is little difference between tutors at the top vs. bottom of Saga's ranked hiring list (Davis et al., 2017).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Davis et al., 2017
Not checked in the free run.
- Findingown data
At 11th grade, a year or two after tutoring, there are persistent gains in math test scores of 0.22 SD pooling study 1 and 2.
“When we look at 11 th grade outcomes, a year or two after tutoring, we see persistent gains in math test scores of 0.22 SD (pooling study 1 and 2)”
Quote in the paperSubstantial claim - Findingown data
Survey data show no detectable effects on whether youth report feeling close to or supported by adults in school or out of school.
“But survey data show no detectable effects on whether youth report feeling close to or supported by adults in school or out of school”
Quote in the paperSubstantial claim- Rests on an assumption: The survey measures of social-emotional skills and relationships with adults validly capture the constructs they are intended to measure.
- Findingown data
In study 2, there are sizable positive effects on math grades similar to the findings for study 1.
“We also find sizable positive effects on math grades in study 2 similar to the findings for study 1.”
Quote in the paperSubstantial claim - Findingown data
There are gains in whether students like math and care about their math grades, mediators closely tied to math instruction and achievement specifically.
“We do find gains in whether students like math and care about their math grades-mediators closely tied to math instruction and achievement specifically.”
Quote in the paperSubstantial claim- Rests on an assumption: The survey measures of social-emotional skills and relationships with adults validly capture the constructs they are intended to measure.
- Findingown data
The gains in test scores do not appear to be the result of tutors narrowly teaching to the test.
“These gains in test scores do not appear to be the result of tutors narrowly teaching to the test”
Quote in the paperSubstantial claim - Findingown data
At 11th grade, there are improved math grades of 0.18 GPA points.
“and improved math grades of 0.18 GPA points.”
Quote in the paperSubstantial claim - Findingown data
About one-quarter of the sample have large gains in math grades but no gain in math test scores.
“About one-quarter of the sample have large gains in math grades, but no gain in math test scores, consistent with floor effects on the tests.”
Quote in the paperSubstantial claim - Findingown data
In study 1, the percentage of courses failed in non-math classes is cut by 23% (-0.056/0.22).
“Reading test scores do not show significant impacts but the TOT effect on grades in non-math courses was 0.20 points (relative to a CCM of 1.72) and percentage of courses failed in non-math classes are cut by 23% (-0.056/0.22).”
Quote in the paperSubstantial claim- The authors state this as an assumption: For the TOT IV estimate, treatment assignment has no effect on the outcomes of those assigned to treatment who do not participate.
- The authors state this as an assumption: The stable unit treatment value assumption (SUTVA) holds: treatment assignment has no spillover effects on control students' outcomes.
- Findingown data
The study does not see differential treatment effects for Black and Latinx students.
“We test the interaction of treatment with student race/ethnicity but do not see differential treatment effects for Black and Latinx students (Appendix Tables 21 and 22 present the pooled ITT and TOT results for this subsample of students, respectively).”
Quote in the paperNot a substantial claim - Findingown data
In study 1, the TOT effect on grades in non-math courses is 0.20 points, relative to a control complier mean of 1.72.
“Reading test scores do not show significant impacts but the TOT effect on grades in non-math courses was 0.20 points (relative to a CCM of 1.72) and percentage of courses failed in non-math classes are cut by 23% (-0.056/0.22).”
Quote in the paperSubstantial claim- The authors state this as an assumption: For the TOT IV estimate, treatment assignment has no effect on the outcomes of those assigned to treatment who do not participate.
- The authors state this as an assumption: The stable unit treatment value assumption (SUTVA) holds: treatment assignment has no spillover effects on control students' outcomes.
- Findingown data
Within the study schools, the specific students in the study have similar average test scores to the schoolwide averages of the schools they attend.
“Looking within the study schools, the specific students in the study have similar average test scores to the schoolwide averages of the schools they attend.”
Quote in the paperNot a substantial claim - Findingown data
In study 2, there are no statistically significant indications of spillovers on non-math courses once multiple testing is accounted for.
“There are no statistically significant indications of spillovers on non-math courses once we account for multiple testing.”
Quote in the paperNot a substantial claim - Findingown data
In study 2, the TOT effect is a 0.37 SD increase on the EXPLORE and PLAN math tests.
“The TOT effects are a 0.37 SD increase on the EXPLORE and PLAN math tests, a 0.42 point increase in math grades (relative to a CCM of 1.79), and a 44 percent decline (-0.082/0.187) of math courses failed.”
Quote in the paperSubstantial claim- The authors state this as an assumption: For the TOT IV estimate, treatment assignment has no effect on the outcomes of those assigned to treatment who do not participate.
- The authors state this as an assumption: The stable unit treatment value assumption (SUTVA) holds: treatment assignment has no spillover effects on control students' outcomes.
- Findingown data
The average test scores of students in the study schools are 9 to 12 percentile points lower than the CPS average.
“In comparison, the average test scores of students in our study schools are 9 to 12 percentile points lower than the CPS average.”
Quote in the paperNot a substantial claim - Findingreasoning
If there was no persistence in effects of year 1 participation on year 2 test scores, the effect of two years of Saga can be estimated as a TOT where participation is defined as receiving Saga tutoring in year 2, equal to 0.84 SD.
“This estimate is presented in the column labeled”
Quote in the paperSubstantial claim- The authors state this as an assumption: For the TOT IV estimate, treatment assignment has no effect on the outcomes of those assigned to treatment who do not participate.
- The authors state this as an assumption: The stable unit treatment value assumption (SUTVA) holds: treatment assignment has no spillover effects on control students' outcomes.
- Findingown data
In study 1, the TOT effect on math achievement test scores is 0.16 standard deviations.
“Table 3 shows the ITT effect in study 1 on math achievement test scores (EXPLORE and PLAN tests) equals 0.082 standard deviations (SD), with a TOT effect of 0.16 SD.”
Quote in the paperSubstantial claim- The authors state this as an assumption: For the TOT IV estimate, treatment assignment has no effect on the outcomes of those assigned to treatment who do not participate.
- The authors state this as an assumption: The stable unit treatment value assumption (SUTVA) holds: treatment assignment has no spillover effects on control students' outcomes.
- Findingreasoning
If there is no fade out of effects of year 1 participation, the effect of two years of Saga can be estimated by a TOT where participation is defined as receiving Saga tutoring in either year 1 or year 2, or both years, equal to 0.30 SD.
“This estimate is shown in table 6 in the column labeled”
Quote in the paperSubstantial claim- The authors state this as an assumption: For the TOT IV estimate, treatment assignment has no effect on the outcomes of those assigned to treatment who do not participate.
- The authors state this as an assumption: The stable unit treatment value assumption (SUTVA) holds: treatment assignment has no spillover effects on control students' outcomes.
- Findingown data
There are no detectable effects on the other measures in Table 7.
“There are no detectable effects on the other measures.”
Quote in the paperNot a substantial claim - Findingown data
In study 1, reading test scores do not show significant impacts.
“Reading test scores do not show significant impacts but the TOT effect on grades in non-math courses was 0.20 points (relative to a CCM of 1.72) and percentage of courses failed in non-math classes are cut by 23% (-0.056/0.22).”
Quote in the paperNot a substantial claim - Findingown data
In study 1, the ITT effect on math achievement test scores (EXPLORE and PLAN tests) equals 0.082 standard deviations.
“Table 3 shows the ITT effect in study 1 on math achievement test scores (EXPLORE and PLAN tests) equals 0.082 standard deviations (SD), with a TOT effect of 0.16 SD.”
Quote in the paperSubstantial claim - Findingown data
Even with pooled power, the proportionately large changes in measures like arrests and out-of-school suspensions are not quite significant.
“However even with this added power, the proportionately large changes in measures like arrests and out-of-school suspensions are not quite significant.”
Quote in the paperNot a substantial claim - Findingown data
In study 2, the TOT effect is a 0.42 point increase in math grades, relative to a control complier mean of 1.79.
“The TOT effects are a 0.37 SD increase on the EXPLORE and PLAN math tests, a 0.42 point increase in math grades (relative to a CCM of 1.79), and a 44 percent decline (-0.082/0.187) of math courses failed.”
Quote in the paperSubstantial claim- The authors state this as an assumption: For the TOT IV estimate, treatment assignment has no effect on the outcomes of those assigned to treatment who do not participate.
- The authors state this as an assumption: The stable unit treatment value assumption (SUTVA) holds: treatment assignment has no spillover effects on control students' outcomes.
- Findingown data
Results for female students are not so different from those of the full study 2 results that pool males and females together.
“Appendix Table 18 shows that the results for female students are not so different from those of the full study 2 results that pool males and females together.”
Quote in the paperNot a substantial claim - Findingown data
In the pooled sample, the TOT estimate is a 0.26 SD increase in math test scores.
“In the pooled sample, the TOT estimate is a 0.26 SD increase in math test scores, a 0.52 point increase in math GPA relative to a CCM of 1.67, and a decline of 0.09 in percentage of math courses failed, equal to 47% of the CCM.”
Quote in the paperSubstantial claim- The authors state this as an assumption: For the TOT IV estimate, treatment assignment has no effect on the outcomes of those assigned to treatment who do not participate.
- The authors state this as an assumption: The stable unit treatment value assumption (SUTVA) holds: treatment assignment has no spillover effects on control students' outcomes.
- Findingown data
In the pooled sample, the TOT estimate is a 0.52 point increase in math GPA relative to a control complier mean of 1.67.
“In the pooled sample, the TOT estimate is a 0.26 SD increase in math test scores, a 0.52 point increase in math GPA relative to a CCM of 1.67, and a decline of 0.09 in percentage of math courses failed, equal to 47% of the CCM.”
Quote in the paperSubstantial claim- The authors state this as an assumption: For the TOT IV estimate, treatment assignment has no effect on the outcomes of those assigned to treatment who do not participate.
- The authors state this as an assumption: The stable unit treatment value assumption (SUTVA) holds: treatment assignment has no spillover effects on control students' outcomes.
- Findingown data
In study 1, the TOT effect on the math tests administered by ISR is 0.19 standard deviations.
“we find TOT effects of 0.19 SD on the math tests we had ISR administer on our behalf (and which teachers, tutors and students did not know would happen in advance).”
Quote in the paperSubstantial claim- The authors state this as an assumption: For the TOT IV estimate, treatment assignment has no effect on the outcomes of those assigned to treatment who do not participate.
- The authors state this as an assumption: The stable unit treatment value assumption (SUTVA) holds: treatment assignment has no spillover effects on control students' outcomes.
- Findingown data
In study 1, there are no detectable spillovers to behavioral outcomes.
“There do not seem to be any detectable spillovers to behavioral outcomes, as shown in the final two panels of Table 3.”
Quote in the paperNot a substantial claim - Findingown data
In Table 7, there is a reduction in alcohol use that is statistically significant.
“We can see in Panel A that there is a reduction in alcohol use that is statistically significant.”
Quote in the paperNot a substantial claim - Findingown data
In study 2, the TOT effect is a 44 percent decline (-0.082/0.187) in math courses failed.
“The TOT effects are a 0.37 SD increase on the EXPLORE and PLAN math tests, a 0.42 point increase in math grades (relative to a CCM of 1.79), and a 44 percent decline (-0.082/0.187) of math courses failed.”
Quote in the paperSubstantial claim- The authors state this as an assumption: For the TOT IV estimate, treatment assignment has no effect on the outcomes of those assigned to treatment who do not participate.
- The authors state this as an assumption: The stable unit treatment value assumption (SUTVA) holds: treatment assignment has no spillover effects on control students' outcomes.
- Findingown data
In study 1, the decline in percent of math courses failed is 49% of the control complier mean (-0.087 / 0.179).
“We also estimate a decline in percent of math courses failed of 49% of the CCM (-0.087 / 0.179).”
Quote in the paperNot a substantial claim- The authors state this as an assumption: For the TOT IV estimate, treatment assignment has no effect on the outcomes of those assigned to treatment who do not participate.
- The authors state this as an assumption: The stable unit treatment value assumption (SUTVA) holds: treatment assignment has no spillover effects on control students' outcomes.
- Findingown data
In study 2 year 1, the participation rate was 36.9% for the treatment group and 7.8% for controls.
“The participation rate of study 1 youth in year 1 (defined as receipt of any Saga tutoring at all) was 40.2% for those assigned to treatment and 1.1% for controls, and for study 2 was 36.9% for the treatment group and 7.8% for controls.”
Quote in the paperNot a substantial claim - Findingown data
In Study 2 Year 1, there is no significant ITT effect on reading test scaled score (0.009, SE 0.046).
“SY 2015 Read Test Scaled Score (Z) 1415 -0.060 0.009 (0.046) 0.033 (0.113) -0.105 0.768”
Quote in the paperNot a substantial claim - Findingown data
In Study 2 Year 1, the ITT effect on math GPA is 0.168 (SE 0.046).
“SY 2015 Math GPA 1703 1.869 0.168*** (0.046) 0.431*** (0.12) 1.840 0.002”
Quote in the paperSubstantial claim - Findingown data
In Study 2 Year 1, the ITT effect on math courses failed (percent) is -0.034 (SE 0.014).
“SY 2015 Math Courses Failed (percent) 1703 0.147 -0.034** (0.014) -0.087** (0.035) 0.181 0.013”
Quote in the paperNot a substantial claim - Findingown data
In Study 2 Year 1, the ITT effect on ever arrested is -0.029 (SE 0.016).
“SY 2015 Ever Arrested 1848 0.191 -0.029* (0.016) -0.079* (0.043) 0.196 0.163”
Quote in the paperNot a substantial claim - Findingnone given
Our best estimate for the cost per participant during our study period is roughly $3,800, with a defensible range of $3,500 to $4,300.
“Our best estimate for the cost per participant during our study period is roughly $3,800, with a defensible range of $3,500 to $4,300.”
Quote in the paperSubstantial claim - Findingown data
In the pooled Study 1 and 2 sample at Year 1, the treatment improved non-math GPA (ITT = 0.077, p < 0.01; TOT = 0.185).
“Non-Math GPA 4354 1.825 0.077*** (0.024) 0.185***”
Quote in the paperSubstantial claim - Findingown data
In the first wave of the survey, there is a marginally significant increase in the share who say they like math (FDR q-value = .085).
“Panel A shows, in the first wave of our survey, that participants are more likely than controls to say it is important to get good grades in math, and a marginally significant increase in the share who say they like math (FDR q-value = .085).”
Quote in the paperNot a substantial claim - Findingown data
The only significant change in the collection of social-network measures is that Saga participants compared to controls think it is less likely their friends think studying is important.
“Panel E shows the only significant change in our collection of social-network measures is for Saga participants compared to controls to think it is less likely their friends think studying is important; whether this is due to an actual change in friends, or a new appreciation of what it means to take studying seriously, is not clear.”
Quote in the paperNot a substantial claim - Findingown data
In Study 2 Year 1, there is no significant ITT effect on non-math core courses failed (-0.012, SE 0.01).
“SY 2015 Non-Math Core Courses Failed (percent) 1730 0.139 -0.012 (0.01) -0.031 (0.026) 0.153 0.355”
Quote in the paperNot a substantial claim - Findingown data
In the pooled Study 1 and 2 sample at Year 1, the treatment had no statistically significant effect on reading test scaled scores (ITT = 0, SE = 0.028).
“Read Test Scaled Score (Z) 3716 0.003 0 (0.028) 0.007”
Quote in the paperNot a substantial claim - Findingown data
In the first wave of the survey, participants are more likely than controls to say it is important to get good grades in math.
“Panel A shows, in the first wave of our survey, that participants are more likely than controls to say it is important to get good grades in math, and a marginally significant increase in the share who say they like math (FDR q-value = .085).”
Quote in the paperSubstantial claim - Findingown data
In Study 2 Year 1, there is no significant ITT effect on violent crime arrests (-0.015, SE 0.02).
“SY 2015 Violent Crime Arrests 1848 0.115 -0.015 (0.02) -0.041 (0.055) 0.143 0.538”
Quote in the paperNot a substantial claim - Findingown data
In the pooled Study 1 and 2 sample at Year 1, the treatment reduced the percentage of non-math core courses failed (ITT = -0.02, p < 0.01; TOT = -0.048).
“Non-Math Core Courses Failed (percent) 4354 0.178 -0.02*** (0.007) -0.048***”
Quote in the paperSubstantial claim - Findingown data
In Study 2 Year 1, there is no significant ITT effect on disciplinary incidents (-0.073, SE 0.15).
“SY 2015 Disciplinary Incidents 1844 1.635 -0.073 (0.15) -0.243 (0.406) 1.860 0.877”
Quote in the paperNot a substantial claim - Findingown data
In the pooled Study 1 and 2 sample at Year 1, the treatment improved math test scaled scores (ITT = 0.113, p < 0.01; TOT = 0.264).
“Math Test Scaled Score (Z) 3717 0.004 0.113*** (0.026) 0.264***”
Quote in the paperSubstantial claim - Findingown data
In Study 2 Year 1, there is no significant ITT effect on other crime arrests (-0.051, SE 0.033).
“SY 2015 Other Crime Arrests 1848 0.250 -0.051 (0.033) -0.144 (0.09) 0.286 0.163”
Quote in the paperNot a substantial claim - Findingown data
There are enormous differences in estimated average effects for the quartile of students who benefit most (average PTE = 0.21 SD in ITT terms) versus the smallest-effect quartile (average PTE = 0.007 SD).
“We can see that there are enormous differences in the estimated average effects for the quartile of students who benefit the 41 We also recreate this plot for our predicted treatment effects on Math GPA in appendix figure 2. most (average PTE = 0.21 SD in ITT terms) versus the smallest-effect quartile (average PTE = 0.007 SD).”
Quote in the paperSubstantial claim - Findingown data
In Study 2 Year 1, there is no significant ITT effect on out-of-school suspensions (0.024, SE 0.113).
“SY 2015 Out-of-School Suspensions 1844 0.861 0.024 (0.113) 0.048 (0.307) 0.708 0.877”
Quote in the paperNot a substantial claim - Findingown data
In Study 2 Year 1, there is no significant ITT effect on drug crime arrests (-0.003, SE 0.016).
“SY 2015 Drug Crime Arrests 1848 0.054 -0.003 (0.016) -0.008 (0.042) 0.037 0.849”
Quote in the paperNot a substantial claim - Findingown data
In Study 2 Year 1, there is no significant ITT effect on non-math GPA (0.053, SE 0.037).
“SY 2015 Non-Math GPA 1730 1.950 0.053 (0.037) 0.136 (0.096) 2.031 0.355”
Quote in the paperNot a substantial claim - Findingown data
The difference in impacts on academic outcomes is not statistically significant across high-disruption and low-disruption schools.
“We find that the difference in impacts on academic outcomes are not statistically significant across highdisruption and low-disruption schools.”
Quote in the paperSubstantial claim - Findingown data
In-person observations of the Saga program suggest students were spending approximately 90% of their time on math.
“In-person observations we conducted of the Saga program suggest students were spending approximately 90% of their time on math.”
Quote in the paperNot a substantial claim - Findingown data
In Study 2 Year 1, there is no significant ITT effect on days absent (0.241, SE 0.953).
“SY 2015 Days Absent 1844 24.433 0.241 (0.953) 0.421 (2.561) 24.013 0.877”
Quote in the paperNot a substantial claim - Findingown data
In Study 2 Year 1, there is no significant ITT effect on property crime arrests (-0.033, SE 0.02).
“SY 2015 Property Crime Arrests 1848 0.089 -0.033 (0.02) -0.089 (0.054) 0.122 0.163”
Quote in the paperNot a substantial claim - Findingown data
In Study 2 Year 1, the ITT effect on math test scaled score is 0.145 standard deviations (SE 0.043).
“SY 2015 Math Test Scaled Score (Z) 1416 -0.018 0.145*** (0.043) 0.359*** (0.107) -0.100 0.002”
Quote in the paperSubstantial claim - Findingown data
The result on importance of math grades does not persist until the fall after the 2nd year of the program.
“Panel B shows this result does not persist until the fall after the 2 nd year of the program.”
Quote in the paperNot a substantial claim - Findingown data
The permutation test cannot reject the null hypothesis that the effect is the same for most items (p=.53).
“While this test is a bit under-powered and we cannot reject the null hypothesis that the effect is the same for most items (p=.53)”
Quote in the paperNot a substantial claim - Findingown data
In the pooled Study 1 and 2 sample at Year 1, the treatment reduced the percentage of math courses failed (ITT = -0.037, p < 0.01; TOT = -0.087).
“Math Courses Failed (percent) 4277 0.173 -0.037*** (0.009) -0.087***”
Quote in the paperSubstantial claim - Findingown data
In Study 2 Year 1, the ITT effect on total arrests is -0.101 (SE 0.054).
“SY 2015 Total Arrests 1848 0.507 -0.101* (0.054) -0.283* (0.146) 0.587 0.163”
Quote in the paperNot a substantial claim - Findingown data
In the pooled graduation outcomes, the treatment had no statistically significant effect on on-time graduation (ITT = 0.007, SE = 0.013; FDR Q = 0.876).
“Graduated On-Time | 3750 | 0.749 | 0.007 | (0.013) | 0.019 | (0.034) | 0.772 | 0.876”
Quote in the paperNot a substantial claim - Findingown data
The paper's results hold across different methods of variable calculation.
“Our results hold across different methods of variable calculation.”
Quote in the paperNot a substantial claim - Findingown data
In the Black and Latinx subsample pooled across both studies, the intent-to-treat effect on Math Test Scaled Score (Z) was 0.084 (SE 0.035), with N=3574, control mean -0.008, and Q-value 0.018.
“Math Test Scaled Score (Z) | 3574 | -0.008 | 0.084** | (0.035) | 0.018 | 0.029 | (0.052) | 0.946 | 0.001*** | 0.003”
Quote in the paperNot a substantial claim - Findingown data
In Study 2 at Year 1, the treatment reduced total arrests (ITT = -0.091, p < 0.05; TOT = -0.297, p < 0.05).
“SY 2015 Total Arrests 2710 0.452 -0.091** (0.045) -0.297** (0.15)”
Quote in the paperSubstantial claim - Findingown data
In the pooled 11th grade outcomes, the treatment had no statistically significant effect on 11th grade non-math GPA (ITT = 0.022, SE = 0.031; FDR Q = 0.782).
“11th Grade GPA: All Non-Math Courses 3339 | 1.944 | 0.022 | (0.031) | 0.057 | (0.072) | 1.794 | 0.782”
Quote in the paperNot a substantial claim - Findingown data
In the pooled analysis of both studies, for non-math core top 6 classes in that year, the intention-to-treat effect on non-math core course failures is -0.088 (SE 0.039).
“Non-math Core Course Failures | 4409 | 0.810 -0.088** | (0.039) | -0.211** | (0.094) | 0.916 | 0.051”
Quote in the paperSubstantial claim - Findingown data
In the pooled Year 1 sample (Studies 1 and 2), the intent-to-treat effect of the program on Days Absent was 0.767 (SE 0.582), with N=4968, control mean 23.581, and permutation p=0.313.
“Days Absent 4968 23.581 0.767 (0.582) 0.313”
Quote in the paperNot a substantial claim - Findingown data
In the pooled Year 1 sample (Studies 1 and 2), the intent-to-treat effect of the program on Math GPA was 0.219 points (SE 0.029), with N=4277, control mean 1.803, and permutation p<0.01.
“Math GPA 4277 1.803 0.219*** (0.029) 0***”
Quote in the paperSubstantial claim - Findingown data
The regression coefficient on the Z-score version of the outcome is -0.057 (SE 0.089) for the intention-to-treat effect.
“The regression coefficient on the Z-score version of the outcome is -.057 (se=.089) for the intention-to-treat effect.”
Quote in the paperNot a substantial claim - Findingown data
In the pooled analysis of both studies, the intention-to-treat effect on math GPA is 0.219 (SE 0.03).
“Math GPA | 4331 | 1.786 0.219*** | (0.03) | 0.521*** | (0.071) | 1.661 | 0.001”
Quote in the paperSubstantial claim - Findingown data
In the Black and Latinx subsample pooled across both studies, the intent-to-treat effect on Math Courses Failed (percent) was -0.032 (SE 0.014), with N=4133, control mean 0.178, and Q-value 0.018.
“Math Courses Failed (percent) | 4133 | 0.178 | -0.032** | (0.014) | 0.018 | -0.002 | (0.019) | 0.946 | 0.28 | 0.280”
Quote in the paperNot a substantial claim - Findingown data
In the pooled analysis of both studies, for non-math core top 3 classes each semester, the intention-to-treat effect on non-math core GPA is 0.067 (SE 0.025).
“Non-math Core GPA | 4409 | 1.916 0.067*** | (0.025) | 0.161*** | (0.06) | 1.805 | 0.025”
Quote in the paperSubstantial claim - Findingown data
In Study 2 at Year 1, the treatment reduced other crime arrests (ITT = -0.052, p < 0.1; TOT = -0.168, p < 0.1).
“SY 2015 Other Crime Arrests 2710 0.225 -0.052* (0.028) -0.168* (0.092)”
Quote in the paperNot a substantial claim - Findingown data
In the pooled Year 1 sample (Studies 1 and 2), the intent-to-treat effect of the program on Read Test Scaled Score (Z) was 0 (SE 0.028), with N=3716, control mean 0.003, and permutation p=0.758.
“Read Test Scaled Score (Z) 3716 0.003 0 (0.028) 0.758”
Quote in the paperNot a substantial claim - Findingown data
In the pooled analysis of both studies, for non-math core low grade by subject, the intention-to-treat effect on non-math core GPA is 0.079 (SE 0.024).
“Non-math Core GPA | 4409 | 1.746 0.079*** | (0.024) | 0.191*** | (0.059) | 1.626 | 0.019”
Quote in the paperSubstantial claim - Findingown data
In the pooled Year 1 sample (Studies 1 and 2), the intent-to-treat effect of the program on Non-Math Core Courses Failed (percent) was -0.02 (SE 0.007), with N=4354, control mean 0.178, and permutation p<0.1.
“Non-Math Core Courses Failed 4354 (percent) 0.178 -0.02*** (0.007) 0.066*”
Quote in the paperNot a substantial claim - Findingown data
In the pooled analysis of both studies, the intention-to-treat effect on math course failures is -0.07 (SE 0.017).
“Math Course Failures | 4331 | 0.308 -0.07*** | (0.017) | -0.166*** | (0.04) | 0.348 | 0.001”
Quote in the paperSubstantial claim - Findingown data
In the pooled analysis of both studies, the intention-to-treat effect on non-math core GPA is 0.076 (SE 0.024).
“Non-math Core GPA | 4409 | 1.809 0.076*** | (0.024) | 0.182*** | (0.059) | 1.689 | 0.019”
Quote in the paperSubstantial claim - Findingown data
In the pooled 11th grade outcomes, the treatment improved 11th grade math test scores (ITT = 0.096, p < 0.01; TOT = 0.222, p < 0.01; FDR Q = 0.003).
“11th Grade Math Test (z-score) | 2973 | 0.006 | 0.096*** | (0.029) | 0.222*** | (0.068) | -0.137 | 0.003”
Quote in the paperSubstantial claim - Findingown data
In the pooled analysis of both studies, the intention-to-treat effect on math course failures (percent) is -0.038 (SE 0.01).
“Math Course Failures (percent) | 4331 | 0.179 -0.038*** | (0.01) | -0.091*** | (0.023) | 0.191 | 0.001”
Quote in the paperNot a substantial claim - Findingown data
In the pooled analysis of both studies, for non-math core top 3 classes each semester, the intention-to-treat effect on non-math core course failures is -0.082 (SE 0.039).
“Non-math Core Course Failures | 4409 | 0.800 -0.082** | (0.039) | -0.197** | (0.093) | 0.919 | 0.051”
Quote in the paperSubstantial claim - Findingown data
In the pooled analysis of both studies, the intention-to-treat effect on number of non-math core courses is -0.061 (SE 0.044).
“Number of Non-math Core Courses | 4409 | 6.712 -0.061 | (0.044) | -0.144 | (0.105) | 6.905 | 0.210”
Quote in the paperNot a substantial claim - Findingown data
In the pooled analysis of both studies, for non-math core high grade by subject, the intention-to-treat effect on non-math core GPA is 0.071 (SE 0.025).
“Non-math Core GPA | 4409 | 1.864 0.071*** | (0.025) | 0.17*** | (0.059) | 1.751 | 0.025”
Quote in the paperSubstantial claim - Findingown data
In the pooled Year 1 sample (Studies 1 and 2), the intent-to-treat effect of the program on Non-Math GPA was 0.077 (SE 0.024), with N=4354, control mean 1.825, and permutation p<0.1.
“Non-Math GPA 4354 1.825 0.077*** (0.024) 0.093*”
Quote in the paperSubstantial claim - Findingown data
In the pooled analysis of both studies, for non-math core high grade by subject, the intention-to-treat effect on non-math core course failures is -0.076 (SE 0.038).
“Non-math Core Course Failures | 4409 | 0.838 -0.076** | (0.038) | -0.184** | (0.092) | 0.951 | 0.062”
Quote in the paperSubstantial claim - Findingown data
In the Black and Latinx subsample pooled across both studies, the intent-to-treat effect on Math GPA was 0.196 (SE 0.041), with N=4133, control mean 1.784, and Q-value 0.001.
“Math GPA | 4133 | 1.784 | 0.196*** | (0.041) | 0.001 | -0.004 | (0.061) | 0.946 | 0.006*** | 0.010”
Quote in the paperSubstantial claim - Findingown data
In the pooled graduation outcomes, the treatment had no statistically significant effect on ever graduating (ITT = 0.004, SE = 0.012; FDR Q = 0.876).
“Ever Graduated | 3770 | 0.823 | 0.004 | (0.012) | 0.008 | (0.032) | 0.859 | 0.876”
Quote in the paperNot a substantial claim - Findingown data
In the pooled Year 1 sample (Studies 1 and 2), the intent-to-treat effect of the program on Math Test Scaled Score (Z) was 0.113 (SE 0.026), with N=3717, control mean 0.004, and permutation p<0.01.
“Math Test Scaled Score (Z) 3717 0.004 0.113*** (0.026) 0.008***”
Quote in the paperSubstantial claim - Findingown data
In the pooled analysis of both studies, for non-math core top 3 classes each semester, the intention-to-treat effect on number of non-math core courses is 0.023 (SE 0.027).
“Number of Non-math Core Courses | 4409 | 5.656 0.023 | (0.027) | 0.057 | (0.065) | 5.793 | 0.400”
Quote in the paperNot a substantial claim - Findingown data
In the Black and Latinx subsample pooled across both studies, the intent-to-treat effect on Non-Math Core Courses Failed (percent) was -0.022 (SE 0.011), with N=4209, control mean 0.184, and Q-value 0.060.
“Non-Math Core Courses Failed (percent) 4209 | 0.184 | -0.022** | (0.011) | 0.060 | 0.012 | (0.015) | 0.663 | 0.444 | 0.940”
Quote in the paperNot a substantial claim - Findingown data
In the pooled Year 1 sample (Studies 1 and 2), the intent-to-treat effect of the program on Disciplinary Incidents was 0.047 (SE 0.086), with N=4968, control mean 1.532, and permutation p=0.284.
“Disciplinary Incidents 4968 1.532 0.047 (0.086) 0.284”
Quote in the paperNot a substantial claim - Findingown data
In the pooled Year 1 sample (Studies 1 and 2), the intent-to-treat effect of the program on Math Courses Failed (percent) was -0.037 (SE 0.009), with N=4277, control mean 0.173, and permutation p<0.01.
“Math Courses Failed (percent) 4277 0.173 -0.037*** (0.009) 0.001***”
Quote in the paperSubstantial claim - Findingown data
In the Black and Latinx subsample pooled across both studies, the intent-to-treat effect on Non-Math Core GPA was 0.092 (SE 0.034), with N=4209, control mean 1.797, and Q-value 0.019.
“Non-Math Core GPA | 4209 | 1.797 | 0.092*** | (0.034) | 0.019 | -0.053 | (0.049) | 0.663 | 0.757 | 0.940”
Quote in the paperSubstantial claim - Findingown data
In the pooled 11th grade outcomes, the treatment improved 11th grade math GPA (ITT = 0.075, p < 0.05; TOT = 0.179, p < 0.05; FDR Q = 0.037).
“11th Grade GPA: Math | 3086 | 1.980 | 0.075** | (0.037) | 0.179** | (0.086) | 1.843 | 0.037”
Quote in the paperSubstantial claim - Findingown data
In the pooled analysis of both studies, the intention-to-treat effect on math course failures (no selections) is -0.07 (SE 0.017).
“Math Course Failures (no selections) | 4210 | 0.297 -0.07*** | (0.017) | -0.163*** | (0.039) | 0.337 | 0.001”
Quote in the paperNot a substantial claim - Findingown data
In the pooled Year 1 sample (Studies 1 and 2), the intent-to-treat effect of the program on Out-of-School Suspensions was 0.136 (SE 0.089), with N=4968, control mean 1.161, and permutation p=0.196.
“Out-of-School Suspensions 4968 1.161 0.136 (0.089) 0.196”
Quote in the paperNot a substantial claim - Findingown data
In the pooled analysis of both studies, the intention-to-treat effect on non-math core course failures is -0.113 (SE 0.05).
“Non-math Core Course Failures | 4409 | 1.112 -0.113** | (0.05) | -0.271** | (0.121) | 1.296 | 0.051”
Quote in the paperSubstantial claim - Findingown data
In the pooled analysis of both studies, for non-math core low grade by subject, the intention-to-treat effect on number of non-math core courses is 0.024 (SE 0.029).
“Number of Non-math Core Courses | 4409 | 5.518 0.024 | (0.029) | 0.061 | (0.069) | 5.679 | 0.400”
Quote in the paperNot a substantial claim - Findingown data
In the pooled analysis of both studies, for non-math core top 6 classes in that year, the intention-to-treat effect on number of non-math core courses is 0.016 (SE 0.024).
“Number of Non-math Core Courses | 4409 | 5.713 0.016 | (0.024) | 0.041 | (0.058) | 5.835 | 0.479”
Quote in the paperNot a substantial claim - Findingown data
In the pooled analysis of both studies, the intention-to-treat effect on math GPA (no selections) is 0.225 (SE 0.03).
“Math GPA (no selections) | 4210 | 1.807 0.225*** | (0.03) | 0.525*** | (0.071) | 1.677 | 0.001”
Quote in the paperNot a substantial claim - Findingown data
In the pooled Year 1 sample (Studies 1 and 2), the intent-to-treat effect of the program on Arrests for Property Crimes was -0.018 (SE 0.01), with N=5343, control mean 0.066, and permutation p<0.05.
“Arrests for Property Crimes 5343 0.066 -0.018* (0.01) 0.035**”
Quote in the paperNot a substantial claim - Findingown data
In the pooled analysis of both studies, for non-math core low grade by subject, the intention-to-treat effect on non-math core course failures is -0.103 (SE 0.041).
“Non-math Core Course Failures | 4409 | 0.970 -0.103** | (0.041) | -0.248** | (0.098) | 1.140 | 0.032”
Quote in the paperSubstantial claim - Findingown data
In the pooled analysis of both studies, for non-math core high grade by subject, the intention-to-treat effect on number of non-math core courses is 0.024 (SE 0.029).
“Number of Non-math Core Courses | 4409 | 5.518 0.024 | (0.029) | 0.061 | (0.069) | 5.679 | 0.400”
Quote in the paperNot a substantial claim - Findingown data
In the pooled graduation sample (Studies 1 and 2), the intent-to-treat effect on Graduated On-Time was 0.007 (SE 0.013), with N=3750 and control mean 0.749.
“Graduated On-Time | 3750 | 0.749 | 0.007 | (0.013) | 0.019 | (0.034) | 0.772”
Quote in the paperNot a substantial claim - Findingown data
In the pooled analysis of both studies, for non-math core top 6 classes in that year, the intention-to-treat effect on non-math core GPA is 0.069 (SE 0.025).
“Non-math Core GPA | 4409 | 1.927 0.069*** | (0.025) | 0.165*** | (0.061) | 1.816 | 0.025”
Quote in the paperSubstantial claim - Premisenone given
A key innovation by Saga Education is to identify how to deliver high-impact tutoring at relatively low cost ($3,500 to $4,300 per participant per year).
“A key innovation by the non-profit we study (Saga Education) is to identify how to deliver “high-impact tutoring” at relatively low cost ($3,500 to $4,300 per participant per year).”
Quote in the paperSubstantial claim - Interpretationnone given
The estimated benefit-cost ratio is comparable to many successful model early-childhood programs.
“The estimated benefit-cost ratio is comparable to many successful model early-childhood programs.”
Quote in the paperSubstantial claim - Interpretationreasoning
The treatment effects seem to be caused by changes in the instructional technology that students received.
“The treatment effects do not appear to be the result of a generic “mentoring effect” or of changes in social-emotional skills, but instead seem to be caused by changes in the instructional “technology” that students received.”
Quote in the paperSubstantial claim - Premisecitation
Math skills for school-age children may be more responsive to school-based interventions than reading skills.
“and because math skills for school-age children may be more responsive to school-based interventions than reading skills (e.g.Fryer, 2014, 2017).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Fryer, 2014, 2017
Not checked in the free run.
- Premisenone given
Studies of educational interventions for teens tend to yield much more disappointing results than studies of interventions for young children.
“Studies of educational interventions for teens tend to yield much more disappointing results than of interventions for young children.”
Quote in the paperNot a substantial claim - Premisecitation
Long-term trends in test scores seem more encouraging for relatively younger than older students.
“Long-term trends in test scores seem more encouraging for relatively younger than older students (Hanushek et al., 2020).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Hanushek et al., 2020
Not checked in the free run.
- Premisecitation
The growing variability of academic achievement as children age means the variability of what students need within a given classroom is also heightened for older children.
“The growing variability of academic achievement as children age means the variability of what students need within a given classroom is also heightened for older children (Cascio and Staiger, 2012).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Cascio and Staiger, 2012
Not checked in the free run.
- Premisecitation
Failing core math classes is a driver of dropout in Chicago.
“We focused on math because failing core math classes is a driver of dropout in Chicago (Allensworth and Easton, 2005)”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Allensworth and Easton, 2005
Not checked in the free run.
- Study design and conductnone given
The two large-scale RCTs with thousands of teens essentially formed a representative sample of students enrolled in some of Chicago's most economically disadvantaged neighborhood schools.
“We carried out two separate large-scale randomized controlled trials (RCTs) with thousands of teens who essentially formed a representative sample of students enrolled in some of Chicago's (and hence America's) most economically disadvantaged neighborhood schools.”
Quote in the paperSubstantial claim - Premisecitation
Disparities in achievement test scores between students who are academically succeeding versus struggling grow rather than shrink as children progress through school.
“Furthermore, disparities in achievement test scores between students who are academically succeeding versus struggling seem to grow rather than shrink as children progress through school (Cascio and Staiger, 2012).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Cascio and Staiger, 2012
Not checked in the free run.
- Interpretationown data
There are suggestive findings consistent with better personalization of instruction as a relevant mechanism.
“We also present suggestive findings consistent with, although certainly not definitive proof for, better 'personalization' of instruction as a relevant mechanism.”
Quote in the paperNot a substantial claim - Interpretationreasoning
This insight enables Saga to expand the applicant pool to anyone who possesses strong math skills and is willing to devote one year to public service, without necessarily having extensive prior training or experience as teachers.
“This insight enables Saga to expand the applicant pool to anyone who both possesses strong math skills and are willing to devote one year to public service-for example, recent college graduates, retirees or career-switchers-but do not necessarily have extensive prior training or experience as teachers.”
Quote in the paperSubstantial claim - Premisecitation
As with Banerjee et al. (2007), Saga substitutes a very different teaching method for many dimensions of what previous studies call teacher skill or quality.
“As with Banerjee et al. (2007), Saga substitutes a very different teaching method for many dimensions of what previous studies call “teacher skill” or “quality” (such as teaching experience or extensive pedagogical training).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Banerjee et al., 2007
Not checked in the free run.
- Interpretationown data
The pattern of large math grade gains but no math test score gains is consistent with floor effects on the tests.
“About one-quarter of the sample have large gains in math grades, but no gain in math test scores, consistent with floor effects on the tests.”
Quote in the paperSubstantial claim - Interpretationown data
It is possible to perhaps double, or even triple, how much math students learn in a year, for something like one-fifth of the average cost of schooling per pupil per year.
“We find it is possible to perhaps double, or even triple, how much math students learn in a year, for something like onefifth of the average cost of schooling per pupil per year.”
Quote in the paperSubstantial claim - Premisereasoning
The importance of prior training and on-the-job learning is plausibly less for tutoring.
“But the importance of that prior training and on-the-job learning is plausibly less for tutoring.”
Quote in the paperNot a substantial claim - Premisecitation
Previous nonexperimental studies of SES tutoring in Chicago find little detectable effect on math scores.
“previous nonexperimental studies of SES tutoring in Chicago find little detectable effect on math scores.”
Quote in the paperNot a substantial claim - Study design and conductnone given
Treatment-control differences in missingness are not statistically significant.
“Treatment-control differences in missingness are not statistically significant.”
Quote in the paperSubstantial claim - Premisecitation
Fryer (2014) found that Saga tutoring did not appear to have large effects on test scores among 6th grade students beyond the effects of other charter practices.
“Saga tutoring did not appear to have large effects on test scores among 6 th grade students beyond the effects of the other charter practices”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Fryer, 2014
Not checked in the free run.
- Interpretationreasoning
The true effect of two years of Saga should be between the two bounds of 0.30 SD and 0.84 SD.
“The true effect of two years of Saga should be in between these two bounds.”
Quote in the paperSubstantial claim - Study design and conductnone given
Missingness of outcomes is balanced across treatment and control.
“While missingness of outcomes is balanced across treatment and control, as a sensitivity analysis we show results that use multiple imputation to fill in missing values.”
Quote in the paperNot a substantial claim - Interpretationown data
The effects on non-math grades suggest there is at least some spillover of the learning or behavioral changes induced by tutoring that affects learning in other areas.
“However, we find effects on non-math grades, suggesting there is at least some spillover of the learning or behavioral changes induced by tutoring that affects learning in other areas.”
Quote in the paperSubstantial claim - Interpretationreasoning
Even if Saga were not personalizing, the item-level results imply that personalizing (concentrating instructional time on where students are academically) would be an effective strategy.
“The implication is that even if Saga were not personalizing, the item-level results imply that personalizing (concentrating instructional time on where students are academically) would be an effective strategy.”
Quote in the paperNot a substantial claim - Interpretationown data
The differential shapes of the below- and above-median curves in Figure 4 suggest student learning is concentrated on the math topics close to their baseline levels of knowledge.
“But at the very least the differential shapes of the below-and above-median curves in Figure 4 suggest student learning is concentrated on the math topics close to their baseline levels of knowledge.”
Quote in the paperSubstantial claim - Premisecitation
Chetty et al. (2011) show that each one-percentile increase in 8th grade test scores is associated with $150 in additional annual earnings at age 27.
“Chetty et al. (2011) show that each one-percentile increase in 8 th grade test scores is associated with $150 in additional annual earnings at age 27.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Chetty et al. (2011)
Not checked in the free run.
- Interpretationown data
The present paper shows that substantial progress can be made by narrowing down the set of strategies adopted from 'no excuses' charter schools to just a single element that is easier to implement and hence scale: high-dosage tutoring.
“The present paper shows that substantial progress can be made by narrowing down even further the set of strategies adopted from 'no excuses' charter schools to just a single element that is easier to implement and hence scale: high-dosage tutoring.”
Quote in the paperSubstantial claim - Premisecitation
Fryer (2014) shows that identifying a handful of strategies from 'no excuses' charter schools and incorporating them into public schools can improve student achievement.
“Fryer (2014) shows that identifying a handful of strategies from 'no excuses' charter schools and incorporating them into public schools can improve student achievement.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Fryer (2014)
Not checked in the free run.
- Study design and conductown data
Even with the large sample, the study is barely powered if not slightly under-powered to detect heterogeneous treatment effects on math outcomes.
“But even with our large sample (relatively speaking from the perspective of social science experiments), we are barely powered if not slightly under-powered even to detect heterogenous treatment effects on math outcomes.”
Quote in the paperSubstantial claim - Interpretationown data
All else equal, the lack of significant difference across high- and low-disruption schools does not seem to support the hypothesis that improved classroom management is a key driver of the overall Saga impacts.
“All else equal, this would not seem to support the hypothesis that improved classroom management is a key driver of the overall Saga impacts.”
Quote in the paperSubstantial claim - Premisecitation
Reardon (2011) finds in the NAEP that the average high school student's scores in reading and math increase by around 0.6 to 0.7 standard deviations over 4 years, or approximately 0.15-0.18 standard deviations per year.
“Reardon (2011) finds in the NAEP that the average high school student's scores in reading and math increase by around 0.6 to 0.7 standard deviations over 4 years, or approximately 0.15-0.18standard deviations per year.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Reardon (2011)
Not checked in the free run.
- Study design and conductown data
In the pooled Study 1 and 2 sample, baseline characteristics did not differ significantly between treatment and control groups (p=0.828).
“Pooled Study 1 and 2: p=0.828”
Quote in the paperSubstantial claim
- May combine two claims. 99
- Classified as probably not a substantial claim. 65
- The quote only partly states this claim. 14
May combine two claims.
Findingown dataIn the first RCT, participation increased grades in math and non-math courses.
“Our first randomized controlled trial (RCT) of Saga's tutoring model with 2,633 9th and 10th grade students in Chicago public schools found participation increased math test scores by 0.16 standard deviations (SDs) and increased grades in math and non-math courses.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingnone givenEstimates for high school graduation are imprecise.
“These effects persist into future years, although estimates for high school graduation are imprecise.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataSurvey data show no detectable effects on grit, conscientiousness, or locus of control.
“or on grit, conscientiousness, or locus of control.”
Quote in the paperSubstantial claim- Rests on an assumption: The survey measures of social-emotional skills and relationships with adults validly capture the constructs they are intended to measure.
May combine two claims.
Findingown dataThe point estimate for graduation is positive, 1.9 percentage points, but imprecisely estimated; declines of up to 4.8 points or gains as large as 8.6 points cannot be ruled out.
“The point estimate for graduation is positive, 1.9 percentage points, but imprecisely estimated; we cannot rule out declines of up to 4.8 points or gains as large as 8.6 points.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataWhen items are rank-ordered by difficulty and effects are estimated for specific items, there are suggestive but imprecisely estimated indications that students with below-median baseline scores gain most on the easiest items, while above-median students gain most on harder items.
“When we rank-order items by difficulty and estimate effects for specific items we see suggestive (but imprecisely estimated) indications that students with below-median baseline scores gain most on the easiest items, while above-median students gain most on harder items.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataIn study 2, the treatment-on-the-treated effect on math scores after one year is 0.37 SD, roughly twice as large as in study 1.
“The TOT effect on math scores after one year is roughly twice as large as in study 1 (0.37 SD).”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataResults for 9th graders are similar to those from the pooled sample of 9th and 10th graders, consistent with findings suggesting the effects of CPS double dose algebra are limited.
“Appendix Table 16 shows results for 9 th graders are similar to those from the pooled sample of 9 th and 10 th graders, consistent with the findings of Nomi and Allensworth (2009) suggesting the effects of CPS double dose algebra are limited.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Nomi and Allensworth (2009)
Not checked in the free run.
May combine two claims.
Findingown dataIn study 1, some estimated effects on arrests are large relative to control means but are not statistically significant.
“However, some of the estimated effects on arrests are large relative to the control means, though they are not statistically significant.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataThe estimated TOT effect on graduating on time from high school, pooling study 1 and 2 samples, is positive 1.9 percentage points relative to a control complier mean of 77.2%, but it is imprecisely estimated.
“Table 9 shows that the estimated TOT effect on graduating on time from high school, pooling the study 1 and 2 samples again, is positive 1.9 percentage points relative to a CCM of 77.2%, but this is imprecisely estimated.”
Quote in the paperNot a substantial claim- The authors state this as an assumption: For the TOT IV estimate, treatment assignment has no effect on the outcomes of those assigned to treatment who do not participate.
- The authors state this as an assumption: The stable unit treatment value assumption (SUTVA) holds: treatment assignment has no spillover effects on control students' outcomes.
May combine two claims.
Findingown dataIn 11th grade, the TOT effect on math test scores is 0.22 SD, about the same size as the pooled impact measured at the end of one year of programming.
“We see TOT effects on math test scores in 11 th grade of 0.22 SD, about the same size as the pooled impact measured at the end of one year of programming, and the TOT on math grades is 0.18 GPA points, about 35% of the year one effect.”
Quote in the paperSubstantial claim- The authors state this as an assumption: For the TOT IV estimate, treatment assignment has no effect on the outcomes of those assigned to treatment who do not participate.
- The authors state this as an assumption: The stable unit treatment value assumption (SUTVA) holds: treatment assignment has no spillover effects on control students' outcomes.
May combine two claims.
Findingown dataThere are suggestive reductions in use of drugs other than marijuana and seriously hurting someone in a fight, but these are not statistically significant once multiple testing is accounted for.
“We also see suggestive reductions in use of drugs (other than marijuana) and seriously hurting someone in a fight, though these are not statistically significant once we account for the number of hypotheses being tested here.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataThe academic subject matter of the tutoring was specifically math, and the study finds significant positive effects on math test scores but no effects on reading test scores.
“The academic subject matter of the tutoring was specifically math, and we find significant positive effects on math test scores, but no effects on reading test scores.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataIn study 1, the TOT impact on math grades is 0.56 points on a 1-4 GPA scale, relative to a control complier mean of 1.63, representing a change of about C- to C+.
“So it is notable that we see changes in math grades as well, with a TOT impact of 0.56 points on a 1-4 GPA scale, relative to the control complier mean (CCM) of 1.63; this represents a change of about a C-to a C+.”
Quote in the paperSubstantial claim- The authors state this as an assumption: For the TOT IV estimate, treatment assignment has no effect on the outcomes of those assigned to treatment who do not participate.
- The authors state this as an assumption: The stable unit treatment value assumption (SUTVA) holds: treatment assignment has no spillover effects on control students' outcomes.
May combine two claims.
Findingown dataIn 11th grade, the TOT effect on math grades is 0.18 GPA points, about 35% of the year one effect.
“We see TOT effects on math test scores in 11 th grade of 0.22 SD, about the same size as the pooled impact measured at the end of one year of programming, and the TOT on math grades is 0.18 GPA points, about 35% of the year one effect.”
Quote in the paperSubstantial claim- The authors state this as an assumption: For the TOT IV estimate, treatment assignment has no effect on the outcomes of those assigned to treatment who do not participate.
- The authors state this as an assumption: The stable unit treatment value assumption (SUTVA) holds: treatment assignment has no spillover effects on control students' outcomes.
May combine two claims.
Findingown dataIn study 1 year 1, the participation rate was 40.2% for those assigned to treatment and 1.1% for controls.
“The participation rate of study 1 youth in year 1 (defined as receipt of any Saga tutoring at all) was 40.2% for those assigned to treatment and 1.1% for controls, and for study 2 was 36.9% for the treatment group and 7.8% for controls.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataFor study 1, about 25% of control students in the schools received SES tutoring, which involves 21 hours of writing tutoring per year and 20 hours of math tutoring.
“For example, for study 1 we estimate about 25% of control students in our schools received SES tutoring, which involves 21 hours of writing tutoring per year and 20 hours of math tutoring”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataIn the pooled sample, the TOT estimate is a decline of 0.09 in percentage of math courses failed, equal to 47% of the control complier mean.
“In the pooled sample, the TOT estimate is a 0.26 SD increase in math test scores, a 0.52 point increase in math GPA relative to a CCM of 1.67, and a decline of 0.09 in percentage of math courses failed, equal to 47% of the CCM.”
Quote in the paperSubstantial claim- The authors state this as an assumption: For the TOT IV estimate, treatment assignment has no effect on the outcomes of those assigned to treatment who do not participate.
- The authors state this as an assumption: The stable unit treatment value assumption (SUTVA) holds: treatment assignment has no spillover effects on control students' outcomes.
May combine two claims.
Findingown dataThe standard error of 3.4 percentage points means the study cannot rule out a decline in graduation rates as large as -4.8 percentage points or an increase as large as +8.6 points.
“The standard error of 3.4 percentage points means we cannot rule out a decline in graduation rates as large as -4.8 percentage points or an increase as large as +8.6 points.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataBaseline math scores are strikingly different across the PTE quartiles: the top quartile has scores 0.61 SD above the study sample average at baseline, and the bottom quartile 1.2 SD below average at baseline.
“But it's also the case that the baseline math scores are strikingly different across these quartiles as well, with those in the top quartile having scores 0.61 SD above our study sample average at baseline and those in the bottom quartile 1.2 SD below average at baseline.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataThe 90% time-on-math figure is high relative to other published figures for regular public school classrooms, but similar observations could not be carried out for the specific CPS classrooms that serve as the control condition.
“This figure is high relative to other published figures for regular public school classrooms, but we could not carry out similar observations for the specific CPS classrooms that serve as the control condition in this study.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataIn wave 1 of the survey, there are no statistically significant changes in measures of grit, conscientiousness, or, after multiple testing corrections, locus of control.
“Panels B, C, and D show there are no statistically significant changes in measures of”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataAround one-quarter of the study sample has estimated math test score gains in the neighborhood of zero or negative, but positive and sometimes substantially positive gains in math GPA.
“For present purposes the most relevant feature of Figure 3 is the fact that around onequarter of our study sample has estimated math test score gains in the neighborhood of zero or negative, but positive (and sometimes substantially positive) gains in math GPA.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingown dataMajority (over 97%) of study students for whom we have grade data only take one math class each semester after excluding Math Lab and double-dose Algebra.
“majority (over 97%) of study students for whom we have grade data only take one math class each semester after excluding Math Lab and double-dose Algebra.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataAbove-median students score higher than below-median students on every item, and in both groups the share who answer a question correctly increases with the P-score.
“Above-median students score higher than below-median students on every item, and in both groups, the share who answer a question correctly increases with the P-score (see appendix figure 3).”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataIn wave 1 of the survey, there are no statistically significant changes in the number of adults the student reports having available to talk to in school, the number of adults they think care about them, or their willingness to talk to adults in school.
“Panel A of Table 10 shows no statistically significant changes in the number of adults the student reports having available to talk to in their school, the number of adults they think care about them, or their willingness to talk to adults in the school.”
Quote in the paperNot a substantial claimThe quote only partly states this claim.
Findingown dataIn the pooled Study 1 and 2 sample at Year 1, the treatment improved math GPA (ITT = 0.219, p < 0.01; TOT = 0.518).
“Math GPA 4277 1.803 0.219*** (0.029) 0.518***”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataOn average, Saga increases student's test scores by six percentile points in study 1 and by 14 percentile points for study 2.
“We find that, on average, Saga increases student's test scores by six percentile points in study 1 and by 14 percentile points for study 2.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Findingown dataVisually, below-baseline-median students seem to benefit the most on items in the bottom or middle of the difficulty distribution while above-median students may benefit the most on more difficult items.
“visually it looks like below-baseline-median students seem to benefit the most on items in the bottom or middle of the difficulty distribution while the above-median may benefit the most on more difficult items.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataIn CPS administrative data, those students do not show particularly large gains or any gains in measures of effort such as school attendance or school disciplinary infractions; nor in survey data are there changes in measures like time spent on homework or share homework completed.
“But in the CPS administrative data we do not see those students showing particularly large gains (or any gains for that matter) in measures of effort such as school attendance or school disciplinary infractions.Nor in the survey data do we see any changes in measures like time spent on homework, or share homework completed.”
Quote in the paperSubstantial claimThe quote only partly states this claim.
Findingown dataIn the first wave of surveys, there is no statistically significant impact on the item asking if disruptions by others get in the way of learning.
“In addition, in the first wave of surveys we administered to students to measure mechanisms, we asked if”
Quote in the paperSubstantial claimThe quote only partly states this claim.
Findingown dataIn the pooled Study 1 and 2 sample at Year 1, the treatment had no statistically significant effect on total arrests (ITT = -0.048, SE = 0.029).
“Total Arrests 5343 0.414 -0.048 (0.029) -0.13”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataIn wave 2 of the survey, there are no detectable impacts on perceptions about supportive adults, grit, conscientiousness, locus of control, growth mindset, or social networks.
“Here again we see no detectable impacts on perceptions about supportive adults, grit, conscientiousness, locus of control, growth mindset, or social networks.”
Quote in the paperNot a substantial claimMay combine two claims. The quote only partly states this claim.
Findingown dataIn Study 1 at Year 1, the treatment improved math GPA (ITT = 0.274, p < 0.01; TOT = 0.561, p < 0.01).
“| Intent to | Treat | Estimate | 0.082** | 0.274*** | -0.043*** | 0.119** | 1.344** |”
Quote in the paperSubstantial claimMay combine two claims. The quote only partly states this claim.
Findingown dataIn Study 1 at Year 1, the treatment reduced the percentage of math courses failed (ITT = -0.043, p < 0.01; TOT = -0.087, p < 0.01).
“| Intent to | Treat | Estimate | 0.082** | 0.274*** | -0.043*** | 0.119** | 1.344** |”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Findingown dataIn Study 2, the 11th grade intent-to-treat effect on Math Test (z-score) was 0.017 (SE 0.041), with N=1445, control mean 0.000, and FDR Q-value 0.717.
“11th Grade Math Test (z-score) | 1445 | 0.000 | 0.017 | (0.041) | 0.046 | (0.126) | 0.046 | 0.717”
Quote in the paperNot a substantial claimMay combine two claims. The quote only partly states this claim.
Findingown dataIn Study 1 at Year 2, the treatment improved math test scaled scores (ITT = 0.163, p < 0.01; TOT for Year 2 = 0.839, p < 0.01).
“| | ITT | Estimate | | | 0.163*** | 0.14*** | -0.021 | 0.067 | 0.984* |”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataIn Study 1, the 11th grade intent-to-treat effect on Math Test (z-score) was 0.158 (SE 0.04), with N=1528, control mean 0.010, and FDR Q-value 0.001.
“11th Grade Math Test (z-score) | 1528 | 0.010 | 0.158*** | (0.04) | 0.3*** | (0.074) | -0.214 | 0.001”
Quote in the paperSubstantial claimMay combine two claims. The quote only partly states this claim.
Findingown dataIn Study 2, Year 1, the intent-to-treat effect on Math GPA was 0.15 (SE 0.043), with N=2062, control mean 1.859, and permutation p<0.05.
“ITT Estimate | 0.126*** | 0.15*** | -0.029** | | -0.007 | 0.065* | -0.011 | | -0.002 | 0.756 | 0.07 | | -0.013 | -0.026 | 0 | -0.052* | -0.019 | -0.091** | | |”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Findingown dataIn Study 1, the intent-to-treat effect on Graduated On-Time was 0.008 (SE 0.017), with N=1853, control mean 0.738, and FDR Q-value 0.74.
“Graduated On-Time | 1853 | 0.738 | 0.008 | (0.017) | 0.017 | (0.036) | 0.759 | 0.74”
Quote in the paperNot a substantial claimMay combine two claims. The quote only partly states this claim.
Findingown dataIn Study 1 at Year 1, the treatment improved math test scaled scores (ITT = 0.082, p < 0.05; TOT = 0.16, p < 0.05).
“| Intent to | Treat | Estimate | 0.082** | 0.274*** | -0.043*** | 0.119** | 1.344** |”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingown dataIn the pooled analysis of both studies, the intention-to-treat effect on number of math courses is 0.007 (SE 0.009).
“Number of Math Courses | 4331 | 1.900 0.007 | (0.009) | 0.017 | (0.021) | 1.942 | 0.423”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Findingown dataIn Study 2, the intent-to-treat effect on Graduated On-Time was 0.008 (SE 0.019), with N=1897, control mean 0.761, and FDR Q-value 0.919.
“Graduated On-Time | 1897 | 0.761 | 0.008 | (0.019) | 0.025 | (0.06) | 0.788 | 0.919”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataIn Study 1, Year 1, the intent-to-treat effect on Math GPA was 0.274 (SE 0.04), with N=2215, control mean 1.760, and permutation p<0.01.
“SY 2014 Math GPA 2215 1.760 0.274*** (0.04) 0***”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims. The quote only partly states this claim.
Findingown dataIn Study 2, Year 1, the intent-to-treat effect on Math Courses Failed (percent) was -0.029 (SE 0.013), with N=2062, control mean 0.149, and permutation p=0.159.
“ITT Estimate | 0.126*** | 0.15*** | -0.029** | | -0.007 | 0.065* | -0.011 | | -0.002 | 0.756 | 0.07 | | -0.013 | -0.026 | 0 | -0.052* | -0.019 | -0.091** | | |”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataIn the pooled Year 1 sample, the intent-to-treat effect on Drug Arrests was -0.013 (SE 0.009), and the interaction with whether the school was above median in CPS disciplinary incidents was 0.043 (SE 0.017), with N=5410.
“Drug Arrests | 5410 | 0.054 | -0.013 | (0.009) | 0.043** | (0.017)”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataIn the pooled Year 1 sample, the intent-to-treat effect on Out-of-School Suspensions was -0.09 (SE 0.075), and the interaction with whether the school was above median in CPS disciplinary incidents was 0.421 (SE 0.174), with N=5035.
“Out-of-School Incs | 5035 | 1.180 | -0.09 | (0.075) | 0.421** | (0.174)”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataA comparison of Saga Tutors SAT scores from AY2016-17 and AY2017-18 in Chicago reveals that average math SAT scores were 707 compared with the average math SAT scores for new NYC teachers of 613 reported in Rockoff, Jacob, Kane, and Staiger (2008).
“A comparison of Saga Tutors SAT scores from AY2016-17 and AY2017-18 in Chicago reveals that average math SAT scores were 707 compared with the average math SAT scores for new NYC teachers of 613 reported inRockoff, Jacob, Kane, and Staiger (2008).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Rockoff, Jacob, Kane, and Staiger (2008)
Not checked in the free run.
May combine two claims. The quote only partly states this claim.
Findingown dataIn Study 1 at Year 1, the treatment reduced the percentage of non-math core courses failed (ITT = -0.027, p < 0.05; TOT = -0.056, p < 0.05).
“| Intent to | Treat | Estimate | 0.082** | 0.274*** | -0.043*** | 0.119** | 1.344** |”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataIn the pooled Year 1 sample, the intent-to-treat effect on Disciplinary Incidents was -0.171 (SE 0.082), and the interaction with whether the school was above median in CPS disciplinary incidents was 0.379 (SE 0.166), with N=5035.
“Disciplinary incidents | 5035 | 1.549 | -0.171** | (0.082) | 0.379** | (0.166)”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataIn the pooled Year 1 sample, the intent-to-treat effect on Days Absent was -0.281 (SE 0.719), and the interaction with whether the school was above median in CPS disciplinary incidents was 2.252 (SE 1.157), with N=5035.
“Days Absent | 5035 | 23.932 | -0.281 | (0.719) | 2.252* | (1.157)”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingown dataIn Study 1, Year 1, the intent-to-treat effect on Math Test Scaled Score (Z) was 0.082 (SE 0.036), with N=1852, control mean -0.000, and permutation p=0.252.
“SY 2014 Math Test Scaled Score (Z) 1852 -0.000 0.082** (0.036) 0.252”
Quote in the paperNot a substantial claimMay combine two claims. The quote only partly states this claim.
Findingown dataIn Study 1 at Year 2, the treatment improved math GPA (ITT = 0.14, p < 0.01; TOT for Year 2 = 0.685, p < 0.01).
“| | ITT | Estimate | | | 0.163*** | 0.14*** | -0.021 | 0.067 | 0.984* |”
Quote in the paperSubstantial claimMay combine two claims. The quote only partly states this claim.
Findingown dataIn Study 2, Year 1, the intent-to-treat effect on Math Test Scaled Score (Z) was 0.126 (SE 0.036), with N=1865, control mean 0.008, and permutation p<0.05.
“ITT Estimate | 0.126*** | 0.15*** | -0.029** | | -0.007 | 0.065* | -0.011 | | -0.002 | 0.756 | 0.07 | | -0.013 | -0.026 | 0 | -0.052* | -0.019 | -0.091** | | |”
Quote in the paperNot a substantial claimMay combine two claims. The quote only partly states this claim.
Findingown dataIn Study 1 at Year 1, the treatment improved non-math GPA (ITT = 0.081, p < 0.05; TOT = 0.201, p < 0.01).
“| Intent to | Treat | Estimate | 0.082** | 0.274*** | -0.043*** | 0.119** | 1.344** |”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataIn Study 1, Year 1, the intent-to-treat effect on Math Courses Failed (percent) was -0.043 (SE 0.013), with N=2215, control mean 0.191, and permutation p<0.01.
“SY 2014 Math Courses Failed (percent) 2215 0.191 -0.043*** (0.013) 0.01***”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingown dataIn the pooled Year 1 sample (Studies 1 and 2), the intent-to-treat effect of the program on Total Arrests was -0.048 (SE 0.029), with N=5343, control mean 0.414, and permutation p=0.169.
“Total Arrests 5343 0.414 -0.048 (0.029) 0.169”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S4 (based). May combine two claims.
Premisenone givenBeing a successful tutor requires fewer specialized skills and less on-the-job learning than does classroom teaching.
“The key insight behind the specific educational intervention we study here, developed by Saga Education, is that being a successful tutor requires fewer specialized skills and less on-thejob-learning than does classroom teaching.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing), S4 (based).
PremisereasoningTeachers report that the two most challenging parts of their job are individualizing instruction and classroom management.
“No wonder teachers report that the two most challenging parts of their job are individualizing instruction and classroom management.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S4 (based).
Premisenone givenThe challenge to widespread implementation of tutoring has not been a pedagogical problem so much as an economic one, namely cost.
“The challenge to widespread implementation has not been a pedagogical problem so much as an economic one-that is, cost.”
Quote in the paperNot a substantial claimMay combine two claims.
PremisecitationMath is important for success in school and later earnings.
“because math is so important for success in school and later earnings (Duncan et al., 2007)”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Duncan et al., 2007
Not checked in the free run.
May combine two claims.
Premisenone givenMotivation becomes more challenging as students age, as reflected by increased prevalence of disruptive behaviors.
“Motivation becomes more challenging as students age, as reflected by increased prevalence of disruptive behaviors.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationThe failure to improve schooling outcomes at a pace to keep up with technological change has harmed economic growth, leading to a dramatic rise in the returns to schooling over time.
“The failure to improve schooling outcomes at a pace to keep up with technological change has harmed economic growth, leading to a dramatic rise in the returns to schooling over time (Goldin and Katz, 2008).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Goldin and Katz, 2008
Not checked in the free run.
May combine two claims.
InterpretationreasoningThe insight that tutoring requires fewer specialized skills expands the applicant pool and means tutors can be successful right away rather than after the usual three-year learning curve for classroom teachers.
“This insight expands the applicant pool, and also means that the people hired-tutors-can be successful right away (rather than the usual threeyear learning curve for classroom teachers”
Quote in the paperNot a substantial claimMay combine two claims.
InterpretationreasoningThe 0.16 SD gain is about what the average high school student learns in a year, so the intervention roughly doubles the annual math test score gain.
“This gain is about what the average high school student learns in a year, so the intervention (roughly speaking) doubles the annual math test score gain.”
Quote in the paperSubstantial claimClassified as probably not a substantial claim.
InterpretationreasoningThis substitution makes high-dosage tutoring more feasible from a cost perspective.
“This substitution makes high-dosage tutoring more feasible from a cost perspective.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationHired tutors have higher SAT scores than what other studies have reported for big-city public school classroom teachers.
“Hired tutors have higher SAT scores than what other studies have reported for big-city public school classroom teachers (Jacob et al., 2018).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Jacob et al., 2018
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationThe findings echo Banerjee et al. (2007)'s study in India of gains from substituting a simpler teaching task for teacher skill.
“Our findings echo Banerjee et al. (2007)'s study in India of gains from substituting a simpler teaching task for teacher skill.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Banerjee et al., 2007
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationDuflo et al. (2011) found that personalization by tracking improved learning outcomes for students in both the top and bottom halves of the achievement distribution.
“This suggestive result is consistent with Duflo et al.'s (2011) finding that personalization by tracking improved learning outcomes for students in both the top and bottom halves of the achievement distribution.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Duflo et al., 2011
Not checked in the free run.
May combine two claims.
PremisereasoningCompared to regular classroom instruction, one-on-one or two-on-one tutoring greatly simplifies the instructional task, expanding the set of people who can be successful instructors.
“Compared to regular classroom instruction, one-on-one (or two-on-one) tutoring greatly simplifies the instructional task, expanding the set of people who can be successful instructors.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Premiseown dataRoughly half of tutors hired were Black or Latinx, and approximately 50% were female.
“Roughly half of tutors hired were Black or Latinx, and approximately 50% were female.”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim.
Premisenone givenSaga Education's tutoring model was selected to study in part because of its low cost relative to the intensity of the intervention.
“We selected Saga Education's tutoring model to study in part because of its low cost relative to the intensity of the intervention.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationSome studies find classroom teachers orient material towards the top third of the classroom.
“Some studies find classroom teachers orient material towards the top third of the classroom (Bloom, 1984)”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Bloom, 1984
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
Premisenone givenSaga hired 139 total tutors across both study years out of an estimated pool of approximately 1,200 applicants.
“Saga hired 139 total tutors across both study years out of an estimated pool of approximately 1,200 applicants.”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim.
PremisecitationPast efforts to improve metacognition and social-emotional skills for adolescents and young adults have been more encouraging than efforts to improve academic skills.
“Given that past efforts to improve metacognition and social-emotional skills for adolescents and young adults have been more encouraging than efforts to improve academic skills (for example Blattman et al., 2017, Heller et al., 2017)”
Quote in the paperSubstantial claim0 of 2 sources checked- cites Blattman et al., 2017
Not checked in the free run.
- cites Heller et al., 2017
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationThe Saga intervention is similar in spirit to how charters often hire teachers with less experience and formal teaching credentials than normal public schools in exchange for smaller class sizes.
“The Saga intervention is similar in spirit to how charters often hire teachers with less experience and formal teaching credentials than normal public schools in exchange for smaller class sizes (Lake, Bowen, & Demeritt, 2012).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Lake, Bowen, & Demeritt, 2012
Not checked in the free run.
Classified as probably not a substantial claim.
PremisecitationTeachers learn how to individualize instruction or handle classroom management usually through extensive preservice pedagogical training as well as on-the-job learning over the first several years of classroom teaching.
“Teachers learn how to individualize instruction or handle classroom management usually through extensive preservice pedagogical training as well as on-the-job learning over the first several years of classroom teaching (Rockoff, 2004; Clotfelter et al., 2010; Henry et al., 2011).”
Quote in the paperSubstantial claim0 of 3 sources checked- cites Rockoff, 2004
Not checked in the free run.
- cites Clotfelter et al., 2010
Not checked in the free run.
- cites Henry et al., 2011
Not checked in the free run.
May combine two claims.
InterpretationreasoningExtrapolating the test score impacts to earnings gains based on the best estimates in the literature implies that the benefit-cost ratio of the program is comparable to exemplar early childhood model programs and larger-scale efforts to improve outcomes for younger children.
“Extrapolating these test score impacts to earnings gains based on the best estimates in the literature implies that the benefit-cost ratio of the program is comparable to both exemplar early childhood model programs, like the Abecedarian Project and the Perry Preschool Program, as well as larger-scale efforts to improve outcomes for younger children such as the Tennessee Star class size reduction”
Quote in the paperSubstantial claimClassified as probably not a substantial claim.
Study design and conductown dataIn summer 2014, the research team randomized a separate sample of 2,710 9th and 10th graders for study 2.
“Motivated in part to see if these results could be replicated at this large scale, in the summer of 2014 we randomized a separate sample of 2,710 9 th and 10 th graders (“study 2”).”
Quote in the paperSubstantial claimMay combine two claims.
Interpretationown dataThe intervention substantially improves learning of adolescents at a cost of $3,500 to $4,300 per year per student.
“One way to read this study is as a program evaluation of an intervention that substantially improves learning of adolescents, at a cost of $3,500 to $4,300 per year per student.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Premisenone givenSaga tutors neither had formal teacher training nor were licensed Illinois teachers.
“But Saga tutors neither had formal teacher training nor were licensed Illinois teachers.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).
Premisenone givenA school in which classroom teachers cycle in and out after just one year would face significant challenges.
“A school in which classroom teachers cycle in and out after just one year would face significant challenges.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S4 (based). May combine two claims.
PremisereasoningThe instructional technology of tutoring is quite different from that of a classroom, and so the set of skills and experiences required to be a successful tutor are plausibly different.
“One major innovation is the recognition that the instructional “technology” of tutoring is quite different from that of a classroom, and so the set of skills and experiences required to be a successful tutor are plausibly different.”
Quote in the paperNot a substantial claimMay combine two claims.
Interpretationown dataThe learning gains in study 1 are not statistical flukes or the result of unusually good program implementation that cannot be replicated, because the effects are at least as large in study 2.
“Table 4 suggests the learning gains experienced by students in study 1 are not statistical flukes, or the result of some unusually good program implementation that cannot be replicated, since the effects are at least as large in study 2.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductown dataPost-randomization missingness for grades equals 14.6% for controls and 14.8% for treatment.
“and somewhat higher for grades (14.6% vs. 14.8%)”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductown dataPost-randomization missingness for test scores equals 29.8% for controls and 29.5% for treatment.
“and test scores (29.8% vs. 29.5%)”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductreasoningRandom assignment was conditional on school-by-grade randomization blocks, and the probability of assignment to treatment varied across randomization blocks.
“we carried out random assignment conditional on school-by-grade “randomization blocks” and varied the probability of assignment to the treatment condition across randomization blocks.”
Quote in the paperNot a substantial claimMay combine two claims.
Study design and conductown dataThe treatment effect seems to increase with larger share of individuals within a block randomized to treatment, opposite to what would be expected if control students were benefiting from positive spillovers; under this test there is no evidence for violation of the SUTVA assumption.
“We see that the treatment effect actually seems to increase (rather than decrease) with larger share of individuals within a block who are randomized to treatment.This is the opposite relationship we would expect if control group students were benefitting from positive spillovers, and so at least under this test we do not see evidence for violation of the SUTVA assumption.”
Quote in the paperNot a substantial claim- The authors state this as an assumption: The stable unit treatment value assumption (SUTVA) holds: treatment assignment has no spillover effects on control students' outcomes.
May combine two claims.
Study design and conductreasoningFor year 2, the experiment cleanly identifies the ITT effect but cannot by itself tell how much of the ITT effect at the end of year 2 is due to gains among treatment youth who received tutoring just in year 1 versus in both years 1 and 2, because dosage duration was not randomly assigned.
“One challenge is that, for year 2, the experiment cleanly identifies the ITT effect, but cannot by itself tell us how much of the ITT effect at the end of year 2 is due to gains among treatment youth who received tutoring just in year 1 versus in both years 1 and 2. This challenge stems from the fact that we did not randomly assign dosage duration.”
Quote in the paperSubstantial claimMay combine two claims.
Study design and conductreasoningIn study 1 schools, students were independently randomized to receive the BAM program, and controlling or not controlling for BAM assignment has no impact on the estimates of Saga effects reported here.
“Because that randomization was independent of assignment to Saga tutoring, controlling or not controlling for BAM assignment has no impact on the estimates of Saga effects reported here.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductown dataPost-randomization missingness for school attendance equals 4.4% for controls and 6.2% for treatment.
“which for school attendance equals 4.4% for controls and 6.2% for treatment”
Quote in the paperNot a substantial claimMay combine two claims.
InterpretationreasoningThe results suggest the effects are at least additive in years of participation, and perhaps more-than-additive as models of dynamic complementarities in learning would suggest.
“The results suggest the effects are at the least additive in years of participation, and perhaps more-than-additive as models of dynamic complementarities in learning would suggest.”
Quote in the paperSubstantial claimMay combine two claims.
Interpretationown dataAn obvious interpretation of the pattern of results is that the academic subject matter of the tutoring sessions matters; tutoring students in math helps them to learn math.
“An obvious interpretation of this pattern of results is that the academic subject matter of the tutoring sessions matters; tutoring students in math helps them to learn math.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductown dataAnother wave of in-person surveys with 1,238 youth in the study 1 sample had effective response rates of 90.1% for the treatment group and 89.1% for controls.
“We carried out another wave of in-person surveys with 1,238 youth in the study 1 sample in the fall after the second intervention year (2014-15), with effective response rates of 90.1% for the treatment group and 89.1% for controls.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone givenAttrition rates are similar for study 2.
“Attrition rates are similar for study 2.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductown dataThe number of randomized students who showed up at study 2 schools comprised 36% of the 5,068 total 9th and 10th grade students enrolled in study 2 schools.
“The number of randomized students who showed up at these study schools comprised 36% of the 5,068 total 9 th and 10 th grade students enrolled in study 2 schools.”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim.
Study design and conductnone givenAll analyses control for randomization-block fixed effects.
“All analyses control for randomization-block fixed effects.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductown dataFor study 2, 2,645 students were randomized in 15 schools, 12 of which were also in study 1.
“For study 2, we randomized a sample of 2,645 students in 15 schools (12 of which were also in study 1).”
Quote in the paperNot a substantial claimMay combine two claims.
InterpretationreasoningThe implication is that the sample has scores below the CPS average, in contrast to many studies of no-excuses charters where applicants tend to have slightly better baseline scores than the host school system.
“The implication is our sample has scores below the CPS average, in contrast to many studies of 'no excuses' charters where applicants tend to have slightly better baseline scores than the host school system (e.g., Angrist et al., 2013).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Angrist et al., 2013
Not checked in the free run.
The quote only partly states this claim.
PremisecitationFryer (2014) found more pronounced effects on test scores among 9th grade students, on the order of 0.32 SD.
“but did appear to have more pronounced effects on test scores among 9 th grade students, on the order of 0.32 SD”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Fryer, 2014
Not checked in the free run.
Classified as probably not a substantial claim.
Study design and conductnone givenIn Fryer (2014), high schools could not be randomly assigned.
“although high schools could not be randomly assigned.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Fryer, 2014
Not checked in the free run.
May combine two claims.
Study design and conductown dataThe estimated effects on math outcomes are robust to a range of estimation decisions; the non-math GPA result, but not classes failed in non-math subjects, is somewhat more sensitive to these choices.
“The estimated effects on math outcomes we measure are robust to a range of estimation decisions; the non-math GPA result (but not classes failed in non-math subjects) is somewhat more sensitive to these choices.”
Quote in the paperNot a substantial claim- The authors state this as an assumption: The multiple imputation methods assume outcomes are missing at random, i.e. values are unrelated to missingness conditional on observed covariates.
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductown dataThe first wave of surveys selected a sub-sample of 881 youth and surveyed 663, with effective response rates of 88.2% for treatment students and 90.6% for control students.
“We selected a sub-sample of 881 youth and surveyed 663 for effective response rates of 88.2% for treatment students and 90.6% for control students.”
Quote in the paperNot a substantial claimMay combine two claims.
Study design and conductown dataRandomization appears to have been successful; baseline characteristics are jointly the same across treatment and control groups in study 1 (p=0.832) and study 2 (p=0.893).
“Randomization appears to have been successful.We carry out an F-test of the null hypothesis that baseline characteristics are jointly the same across treatment and control groups by regressing a treatment-group indicator against all variables in Table 2, separately for studies 1 and 2, controlling for randomization blocks.The p-value for study 1 is p=0.832, and for study 2 is p=0.893.”
Quote in the paperSubstantial claimMay combine two claims.
PremisecitationCPS already receives around $300 million in Title 1 grants each year, and existing research suggests for the average district how these funds are deployed leads to few detectable improvements in student learning.
“CPS already receives around $300 million in Title 1 grants each year, and existing research suggests for the average district how these funds are deployed leads to few detectable improvements in student learning (Deke, et al., 2012, Dragoset, et al., 2017).”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites Deke, et al., 2012
Not checked in the free run.
- cites Dragoset, et al., 2017
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
InterpretationreasoningThe pattern that below-median-at-baseline students benefit more on easier items and above-median students may benefit more on harder items would be consistent with the extra personalization built into the Saga program design.
“The fact that below-median-at-baseline students seem to benefit more on relatively easier items from Saga tutoring and above-median students may benefit more on harder items would be consistent with the extra personalization built into the Saga program design, where tutors are instructed to devote some time each session to working with students where they are academically as determined by frequent”
Quote in the paperNot a substantial claimMay combine two claims.
InterpretationreasoningWith per-student costs of $3,500 to $4,300, this implies the benefit cost ratio is 2.1 to 2.6 in study 1 and 4.9 to 6.0 in study 2.
“With per-student costs of $3,500 to $4,300, this implies the benefit cost ratio is 2.1 to 2.6 in study 1 and 4.9 to 6.0 in study 2.”
Quote in the paperSubstantial claimMay combine two claims.
InterpretationreasoningThe figure is at the very least consistent with, if not definitive proof for, floor effects with math tests.
“The figure is at the very least consistent with, if not definitive proof for, floor effects with math tests.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
InterpretationreasoningAs a thought exercise, that funding, if repurposed to Saga tutoring, would be enough to serve around 80,000 students per year, or 23% of the system's total enrollment of 355,000.
“As a thought exercise, that funding, if repurposed to Saga tutoring, would be enough to serve around 80,000 students per year, or 23% of the system's total enrollment of 355,000.”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim.
Study design and conductown dataTo account for individuals having multiple observations, standard errors are clustered on individuals.
“To account for individuals having multiple observations, standard errors are clustered on individuals.”
Quote in the paperSubstantial claimMay combine two claims.
InterpretationreasoningAssuming these gains persist from ages 25 to 59 and discounting at a 5% rate to age 15, the present discounted value of the gains is about $9,000 for study 1 and $21,000 for study 2.
“Assuming these gains persist from ages 25 to 59 and discounting at a 5% rate to age 15, the present discounted value of the gains is about $9,000 for study 1 and $21,000 for study 2.”
Quote in the paperSubstantial claim- The authors state this as an assumption: The gains from Saga tutoring persist from ages 25 to 59.
Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based). May combine two claims.
InterpretationreasoningThis stands in contrast with how tutoring services are often provided to school systems like Chicago's, where a tutoring provider hires former teachers at prevailing full-time teacher wages, which for a given level of spending per pupil means students get just a fraction of the number of instructional hours as they do with the intervention studied here.
“This stands in contrast with how tutoring services are often provided to school systems like Chicago's, where a tutoring provider hires (say) former teachers at prevailing full-time teacher wages, which then for a given level of spending per pupil means students get just a fraction of the number of instructional hours as they do with the intervention we study here.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Interpretationown dataFigure 4 provides suggestive visual evidence that reduced 'academic mismatch' could play a role.
“Figure 4 provides suggestive visual evidence that reduced 'academic mismatch' could play a role.”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim. May combine two claims.
PremisecitationBy way of comparison the benefit-cost ratios that have been estimated for model early childhood programs are on the order of 1.9 and 2.2 for the Abecedarian Project, and between 3.9 and 6.8 for the Perry Preschool Program, both estimated using a 5% discount rate.
“By way of comparison the benefit-cost ratios that have been estimated for model early childhood programs are on the order of 1.9 and 2.2 for the Abecedarian Project (Masse and Barnett, 2002), and between 3.9 and 6.8 for the Perry Preschool Program (Heckman et al., 2010), both estimated using a 5% discount rate.”
Quote in the paperSubstantial claim0 of 2 sources checked- cites Masse and Barnett, 2002
Not checked in the free run.
- cites Heckman et al., 2010
Not checked in the free run.
May combine two claims.
InterpretationreasoningThese studies have long been cited as arguments for investments in early childhood compared to later life stages; evidently, however, adolescence is not too late to also realize large social benefits from human capital investment.
“These studies have long been cited as arguments for investments in early childhood compared to later life stages; evidently, however, adolescence is not too late to also realize large social benefits from human capital investment.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductown dataWe report the smallest FDR q-value at which we could reject the null for each outcome using the method from Benjamini and Hochberg (1995); the results are qualitatively similar if we use the method from Benjamini, Krieger and Yekutieli (2006).
“We report the smallest FDR q-value at which we could reject the null for each outcome using the method from Benjamini and Hochberg (1995); the results are qualitatively similar if we use the method from Benjamini, Krieger and Yekutieli (2006).”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites Benjamini and Hochberg (1995)
Not checked in the free run.
- cites Benjamini, Krieger and Yekutieli (2006)
Not checked in the free run.
Probably not a substantial claim: may not pass S2 (checkable), S4 (based).
InterpretationreasoningGetting every student up to speed improves the degree to which regular classrooms are 'personalized.'
“That is, getting every student up to speed improves the degree to which regular classrooms are 'personalized.'”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductown dataSome students (N=65) were randomized into Study 2 twice, and both assignments are retained in the models.
“Some students (N=65) were randomized into Study 2 twice.Both assignments are retained in the models above.”
Quote in the paperNot a substantial claimMay combine two claims.
InterpretationreasoningThe benefit-cost ratio of Saga tutoring seems to be comparable in magnitude to that of the most successful early childhood programs, like the Abecedarian Project and the Perry Preschool Program, as well as interventions at scale to improve student outcomes such as the Tennessee STAR experiment.
“The benefit-cost ratio of Saga tutoring seems to be comparable in magnitude to that of the most successful early childhood programs, like the Abecedarian Project and the Perry Preschool Program, as well as interventions at scale to improve student outcomes such as the Tennessee STAR experiment.”
Quote in the paperSubstantial claimMay combine two claims.
InterpretationreasoningTogether, these two findings suggest Saga increases participants' adult earnings by $900 each year for study 1 and $2,100 each year for study 2.
“Together, these two findings suggest Saga increases participants' adult earnings by $900 each year for study 1 and $2,100 each year for study 2.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing), S4 (based). May combine two claims.
Premisenone givenFor non-math core courses, selecting the appropriate 'grade-level' course in each is less straightforward, and there is also possibility that including Saga in students' schedules affects which other 'core' courses they can take.
“For non-math core courses (that is, courses in science, social studies, and reading/English), selecting the appropriate 'grade-level' course in each is less straightforward, and there is also possibility that including Saga in students' schedules affects which other 'core' courses they can take.”
Quote in the paperNot a substantial claimMay combine two claims.
Interpretationown dataTaken together, the results suggest that the subject matter focus on math was important to generating the treatment effects on learning, and that tutoring seems unlikely to have boosted learning solely through a mentoring effect.
“Taken together, these results seem to suggest that the subject matter focus on math was important to generating the treatment effects on learning, and that tutoring seems unlikely to have boosted learning solely through a mentoring effect.”
Quote in the paperSubstantial claimMay combine two claims.
InterpretationreasoningIt is not too late or too difficult to substantially change the academic outcomes of children who are struggling academically even once they have reached adolescence.
“But there is another, perhaps more important way to read this study: As a demonstration that it is not too late or too difficult to substantially change the academic outcomes of children who are struggling academically even once they have reached adolescence.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductown dataThe personalization mechanism cannot be documented directly because the study lacks direct measures of the academic level at which tutors devoted their time and of classroom teaching.
“Unfortunately, we cannot document this mechanism directly because we do not have direct measures of the academic level at which tutors devoted their time, nor do we have that for classroom teaching.”
Quote in the paperNot a substantial claimMay combine two claims.
InterpretationreasoningIt is possible to improve academic skills by accounting for the challenges of individualizing instruction, and these strategies can be effective even when implemented in regular public high schools to broad, representative samples of students.
“The lesson may be that it is possible to improve academic skills by accounting for the challenges of individualizing instruction-among other things-and that these strategies can be effective even when implemented in regular public high schools to broad, representative samples of students.”
Quote in the paperSubstantial claimClassified as probably not a substantial claim.
Study design and conductown dataThe models include baseline covariates: randomization block, treatment assignment, gender, age, learning disability, free and reduced lunch recipient, race, baseline grade level, GPA, days absent from school, disciplinary incidents, including suspensions, and arrests.
“Baseline covariates: Randomization block, treatment assignment, gender, age, learning disability, free and reduced lunch recipient, race, baseline grade level, GPA, days absent from school, disciplinary incidents, including suspensions, and arrests.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductreasoningBecause randomization block fixed-effects fully explain school fixed-effects, the main effect for the 'above median per capita disciplinary incidents' dummy variable cannot be estimated and is not reported, but the interaction effect can be recovered and reported.
“Given that randomization block fixed-effects fully explain school fixed-effects, we cannot estimate the main effect for the 'above median per capita disciplinary incidents' dummy variable, so we do not report these estimates in the table.However, we can recover and report the interaction effect and see if impacts differ between these groups.”
Quote in the paperNot a substantial claim- The authors state this as an assumption: Randomization block fixed-effects fully explain school fixed-effects.
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductnone givenThe control condition for study 2 participants was overwhelmingly an elective course, while the control condition for study 1 9th-graders (the majority of the study 1 sample) was a second hour or 'double-dose' Algebra.
“It is important to note that while the control condition for study 2 participants was overwhelmingly an elective course, the control condition for study 1 9th -graders-i.e., the majority of the study 1 sample-was a second hour or”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductcitationThe smallest FDR q-value at which the null could be rejected for each outcome is reported using the method from Benjamini and Hochberg (1995).
“We report the smallest FDR q-value at which we could reject the null for each outcome using the method from Benjamini and Hochberg (1995)”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Benjamini and Hochberg (1995)
Not checked in the free run.
Classified as probably not a substantial claim.
Study design and conductown dataBaseline covariates and randomization block fixed effects are included in all models.
“Baseline covariates and randomization block fixed effects included in all models (see text).”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductown dataIn study 1, 15 students randomized to the control group received one or more session of Saga; in study 2, 88 students randomized to control (15 female and 73 male) participated in one or more session of Saga programming.
“In study 1, 15 students randomized to the control group received one or more session of Saga.In study 2, 88 students randomized to control (15 female students and 73 male students) participated in one or more session of Saga programming.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductcitationThe smallest FDR q-value at which the null could be rejected for each outcome was reported using the method from Benjamini and Hochberg (1995).
“We report the smallest FDR q-value at which we could reject the null for each outcome using the method from Benjamini and Hochberg (1995)”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Benjamini and Hochberg (1995)
Not checked in the free run.
Classified as probably not a substantial claim. May combine two claims.
Study design and conductnone givenRandomization was done using summer rosters of partner schools based on who they expected to enroll; a subset of these students showed up in these schools in the Fall of the study year. Students who do not show up are referred to as 'No Shows' and are included in the main analysis; main analyses excluding these students are also presented in the appendices.
“Randomization was done using summer rosters of partner schools based on who they expected to enroll; a subset of these students showed up in these schools in the Fall of the study year.We refer to the students who do not show up as 'No Shows', and we include them in the main analysis.We also present our main analyses excluding these students in the appendices (appendix tables 12 and 13).”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone givenFor randomization, gender and grade at the time of randomization (neither of which are necessarily time invariant) are used for blocking.
“For randomization, we use gender and grade at the time of randomization (neither of which are necessarily time invariant) for blocking.”
Quote in the paperNot a substantial claimMay combine two claims.
Study design and conductown dataThe compliance rate for Black students is 0.35 and the compliance rate for Latinx students is 0.43.
“The compliance rate for Black students is 0.35 and the compliance rate for Latinx students is 0.43.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductnone givenISR used two-phase sampling: after interviewing 70% of the survey sample frame they selected a random subsample for intensive follow-up, and the analyses employ sampling weights to account for this design.
“ISR used two-phase sampling: after interviewing 70% of the survey sample frame they selected a random subsample for intensive follow-up.Our analyses employ sampling weights to account for this design.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductown dataBoth assignments for the N=65 students randomized into Study 2 twice are retained in the models, and standard errors are clustered at the student level.
“Both assignments are retained in the models above and standard errors are clustered at the student level.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductnone givenWhere missing data was found, zeroes were imputed and variables identifying records as missing data were created and included.
“Where missing data was found, zeroes were imputed and variables identifying records as missing data were created and included.”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim.
Study design and conductown dataStandard errors are clustered on individuals to account for individuals having multiple observations.
“To account for individuals having multiple observations, standard errors are clustered on individuals.”
Quote in the paperSubstantial claimClassified as probably not a substantial claim. May combine two claims.
Study design and conductnone givenData are from a survey designed by DETAIL and given to a randomly selected subsample of Study 1 youth, proportional to overall treatment and control group size randomized during 2015.
“Data are from survey designed by DETAIL and given to a randomly selected subsample of Study 1 youth, proportional to overall treatment and control group size randomized during 2015.”
Quote in the paperSubstantial claim
The paper relies on this without support.
The survey measures of social-emotional skills and relationships with adults validly capture the constructs they are intended to measure.
“We draw on existing survey questions that have been used in previous studies of youth, including the Moving to Opportunity survey.”
The authors state this as an assumption.
For the TOT IV estimate, treatment assignment has no effect on the outcomes of those assigned to treatment who do not participate.
“The identifying assumption here is that treatment assignment has no effect on the outcomes of those assigned to treatment who do not participate.”
The authors state this as an assumption.
The multiple imputation methods assume outcomes are missing at random, i.e. values are unrelated to missingness conditional on observed covariates.
“These methods assume outcomes are missing at random (MAR), i.e. values are unrelated to missingness”
The authors state this as an assumption.
The stable unit treatment value assumption (SUTVA) holds: treatment assignment has no spillover effects on control students' outcomes.
“Below we discuss what evidence we have about one potential threat to this, the stable unit treatment value assumption (SUTVA).”
“Finally, the SUTVA assumption could be violated if tutoring has some spillover effects on control students, for example if control students see benefits of higher-achieving peers.”
The paper relies on this without support.
Many strategies from 'no excuses' charter schools are complicated to implement with fidelity and may be politically difficult to implement at large scale throughout urban public school systems.
“But many of those strategies are complicated to implement with fidelity and may be politically difficult to implement at large scale throughout urban public school systems.”
The authors state this as an assumption.
The gains from Saga tutoring persist from ages 25 to 59.
“Assuming these gains persist from ages 25 to 59”
The authors state this as an assumption.
The ratio of the TOT effects in study 1 and 2 is the same in standard deviations and percentiles.
“we estimate the percentile effect by assuming the ratio of the TOT effects in study 1 and 2 is the same standard deviations and percentiles.”
The authors state this as an assumption.
Randomization block fixed effects fully explain school fixed effects.
“Given that randomization block fixed-effects fully explain school fixed-effects, we cannot estimate the main effect for the 'above median' dummy variable, so we do not report this in the table.”
The authors state this as an assumption.
Randomization block fixed-effects fully explain school fixed-effects.
“Given that randomization block fixed-effects fully explain school fixed-effects, we cannot estimate the main effect for the 'above median per capita disciplinary incidents' dummy variable, so we do not report these estimates in the table.”
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Non-math course-failure reduction is miscalculated
MinorA decline of 0.056 relative to 0.22 is about 25.5%, not 23%.
Reported -23 · recomputed -25.454545
“percentage of courses failed in non-math classes are cut by 23% (-0.056/0.22).”
Math GPA scale is described with different lower bounds
MinorThe first passage describes the math GPA scale as starting at 1, while the earlier description says it starts at 0.
“with a TOT impact of 0.56 points on a 1-4 GPA scale”
“a TOT effect on grades in regular classroom math courses equal to 0.56 points (on a 0 to 4-point scale)”
Cites
Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482 · see citing works
An Introduction to the Bootstrap
Efron, B., & Tibshirani, R. J. (1994) · doi:10.1201/9780429246593 · Cited by 40,500 · see citing works
School readiness and later achievement.
Duncan, G. J., Dowsett, C. J., Claessens, A., Magnuson, K., Huston, A. C., Klebanov, P., Pagani, L. S., Feinstein, L., Engel, M., Brooks-Gunn, J., et al. (2007) · Developmental Psychology · doi:10.1037/0012-1649.43.6.1428 · Cited by 5,439 · see citing works
Applications of Item Response Theory To Practical Testing Problems
Lord, F. M. (2012) · Routledge eBooks · doi:10.4324/9780203056615 · Cited by 5,009 · see citing works
Teachers, Schools, and Academic Achievement
Rivkin, S. G., Hanushek, E. A., & Kain, J. F. (2005) · Econometrica · doi:10.1111/j.1468-0262.2005.00584.x · Cited by 4,501 · see citing works
From Neurons to Neighborhoods: The Science of Early Childhood Development
(2000) · doi:10.17226/9824 · Cited by 4,484 · see citing works
Identification of Causal Effects Using Instrumental Variables
Angrist, J. D., Imbens, G. W., & Rubin, D. B. (1996) · Journal of the American Statistical Association · doi:10.1080/01621459.1996.10476902 · Cited by 4,230 · see citing works
Selection on observed and unobserved variables: Assessing the effectiveness of Catholic schools
Altonji, J. G., Elder, T. E., & Taber, C. R. (2005) · Journal of Political Economy · doi:10.1086/426036 · Cited by 3,706 · see citing works
The 2 Sigma Problem: The Search for Methods of Group Instruction as Effective as One-to-One Tutoring
BLOOM, B. S. (1984) · Educational Researcher · doi:10.3102/0013189x013006004 · Cited by 2,734 · cited 4× · see citing works
“5 “the best learning conditions we can devise” (Bloom, 1984, p. 4).”
InfluentialEccles, J. S., Midgley, C., Wigfield, A., Buchanan, C. M., Reuman, D., Flanagan, C., & Mac Iver, D. (1993) · American Psychologist · doi:10.1037/0003-066x.48.2.90 · Cited by 2,616 · cited 1× · see citing works
“…learning outcomes for students in both the top and bottom halves of the achievement distribution.11 10 Previous research suggests there can be mismatches between the developmental needs of youth and their social environments, also called “stage-environment fit” (see Hunt, 1975; Eccles et al. 1993).”
The Role of Cognitive Skills in Economic Development
Hanushek, E. A., & Woessmann, L. (2008) · Journal of Economic Literature · doi:10.1257/jel.46.3.607 · Cited by 2,540 · see citing works
The Impact of Individual Teachers on Student Achievement: Evidence from Panel Data
Rockoff, J. E. (2004) · American Economic Review · doi:10.1257/0002828041302244 · Cited by 2,432 · see citing works
Athey, S. C., Tibshirani, J., & Wager, S. (2019) · The Annals of Statistics · doi:10.1214/18-aos1709 · Cited by 1,929 · see citing works
Recursive partitioning for heterogeneous causal effects
Athey, S., & Imbens, G. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1510489113 · Cited by 1,586 · see citing works
How Does Your Kindergarten Classroom Affect Your Earnings? Evidence from Project Star
Chetty, R., Friedman, J. N., Hilger, N., Saez, E., Schanzenbach, D. W., & Yagan, D. (2011) · The Quarterly Journal of Economics · doi:10.1093/qje/qjr041 · Cited by 1,514 · see citing works
Remedying Education: Evidence from Two Randomized Experiments in India
Banerjee, A. V., Cole, S., Duflo, E., & Linden, L. (2007) · The Quarterly Journal of Economics · doi:10.1162/qjec.122.3.1235 · Cited by 1,398 · see citing works
The rate of return to the HighScope Perry Preschool Program
Heckman, J. J., Moon, S. H., Pinto, R., Savelyev, P. A., & Yavitz, A. (2010) · Journal of Public Economics · doi:10.1016/j.jpubeco.2009.11.001 · Cited by 1,341 · see citing works
Carneiro, P. M., & Heckman, J. J. (2003) · doi:10.2139/ssrn.434544 · Cited by 1,325 · see citing works
(2005) · Medical Entomology and Zoology · Cited by 1,313 · see citing works
(2011) · Issue Lab (Candid) · Cited by 1,167 · see citing works
Early Childhood Education: Young Adult Outcomes From the Abecedarian Project
Campbell, F. A., Ramey, C. T., Pungello, E., Sparling, J., & Miller-Johnson, S. (2002) · Applied Developmental Science · doi:10.1207/s1532480xads0601_05 · Cited by 1,144 · see citing works
Duflo, E., Dupas, P., & Kremer, M. (2011) · American Economic Review · doi:10.1257/aer.101.5.1739 · Cited by 1,080 · see citing works
What does certification tell us about teacher effectiveness? Evidence from New York City
Kane, T. J., Rockoff, J. E., & Staiger, D. O. (2008) · Economics of Education Review · doi:10.1016/j.econedurev.2007.05.005 · Cited by 946 · see citing works
An Introduction to the Bootstrap.
Simonoff, J. S., Efron, B., Tibshirani, R. J., & Hjorth, J. S. U. (1994) · Journal of the American Statistical Association · doi:10.2307/2291020 · Cited by 855 · see citing works
Teacher credentials and student achievement: Longitudinal analysis with student fixed effects
Clotfelter, C. T., Ladd, H. F., & Vigdor, J. L. (2007) · Economics of Education Review · doi:10.1016/j.econedurev.2007.10.002 · Cited by 780 · see citing works
(2014) · Cited by 707 · see citing works
Self-citationYoung, A. (2018) · The Quarterly Journal of Economics · doi:10.1093/qje/qjy029 · Cited by 637 · see citing works
Accounting for No-Shows in Experimental Evaluation Designs
Bloom, H. S. (1984) · Evaluation Review · doi:10.1177/0193841x8400800205 · Cited by 532 · cited 4× · see citing works
“5 “the best learning conditions we can devise” (Bloom, 1984, p. 4).”
InfluentialThinking, fast and slow? Some field experiments to reduce crime and dropout in Chicago
Heller, S. B., Shah, A. K., Guryan, J., Ludwig, J., Mullainathan, S., & Pollack, H. A. (2017) · The Quarterly Journal of Economics · doi:10.1093/qje/qjw033 · Cited by 493 · cited 3× · see citing works
“…skills for adolescents and young adults have been more encouraging than efforts to improve academic skills (for example Blattman et al., 2017, Heller et al., 2017), one might wonder whether tutoring―which puts youth in close contact with a prosocial adult every day―is just operating…”
InfluentialSelf-citationThe High/Scope Perry Preschool Program
Belfield, C., Nores, M., Barnett, S., & Schweinhart, L. J. (2006) · The Journal of Human Resources · doi:10.3368/jhr.xli.1.162 · Cited by 485 · see citing works
The Race between Education and Technology
Burke, C. B., Goldin, C. D., & Katz, L. F. (2009) · Journal of American History · doi:10.2307/27694819 · Cited by 485 · see citing works
Clotfelter, C. T., Ladd, H. F., & Vigdor, J. L. (2007) · National Bureau of Economic Research · doi:10.3386/w13617 · Cited by 432 · see citing works
Explaining Charter School Effectiveness
Angrist, J. D., Pathak, P. A., & Walters, C. (2011) · American Economic Journal Applied Economics · doi:10.1257/app.5.4.1 · Cited by 422 · see citing works
Remedying Education: Evidence from Two Randomized Experiments in India
Banerjee, A., Cole, S. A., Duflo, E., & Linden, L. (2005) · National Bureau of Economic Research · doi:10.3386/w11904 · Cited by 414 · see citing works
Clotfelter, C. T., Ladd, H. F., & Vigdor, J. L. (2010) · The Journal of Human Resources · doi:10.1353/jhr.2010.0023 · Cited by 383 · see citing works
Comparative benefit–cost analysis of the Abecedarian program and its policy implications
Barnett, W. S., & Masse, L. N. (2006) · Economics of Education Review · doi:10.1016/j.econedurev.2005.10.007 · Cited by 373 · see citing works
Person-Environment Interaction: A Challenge Found Wanting Before it was Tried
Hunt, D. E. (1975) · Review of Educational Research · doi:10.3102/00346543045002209 · Cited by 360 · see citing works
Reducing Crime and Violence: Experimental Evidence from Cognitive Behavioral Therapy in Liberia
Blattman, C., Jamison, J. C., & Sheridan, M. (2017) · American Economic Review · doi:10.1257/aer.20150503 · Cited by 355 · see citing works
Fryer, R. G. (2014) · The Quarterly Journal of Economics · doi:10.1093/qje/qju011 · Cited by 295 · see citing works
Self-citationAngrist, J. D., Cohodes, S. R., Dynarski, S. M., Pathak, P. A., & Walters, C. R. (2016) · Journal of Labor Economics · doi:10.1086/683665 · Cited by 294 · see citing works
Duflo, E., Pascaline Dupas, Y., & Kremer, M. R. (2008) · National Bureau of Economic Research · doi:10.3386/w14475 · Cited by 292 · see citing works
What Does Certification Tell Us About Teacher Effectiveness? Evidence from New York City
Kane, T. J., Rockoff, J. E., & Staiger, D. O. (2006) · National Bureau of Economic Research · doi:10.3386/w12155 · Cited by 288 · see citing works
Board on Children, Y., Education, D. O. B. A. S. S. A., Division, H. A. M., & National Academies of Sciences, E. (2019) · National Academies Press eBooks · doi:10.17226/25388 · Cited by 282 · see citing works
Engel, M., Claessens, A., & Finch, M. A. (2013) · Educational Evaluation and Policy Analysis · doi:10.3102/0162373712461850 · Cited by 259 · see citing works
Preschool Programs Can Boost School Readiness
Gormley, W. T., Phillips, D. A., & Gayer, T. (2008) · Science · doi:10.1126/science.1156019 · Cited by 254 · see citing works
Everyone’s Doing It, But What Does Teacher Testing Tell Us About Teacher Effectiveness?
Goldhaber, D. D. (2007) · The Journal of Human Resources · doi:10.3368/jhr.xlii.4.765 · Cited by 242 · see citing works
A Benefit Cost Analysis of the Abecedarian Early Childhood Intervention.
Masse, L. N., & Barnett, W. S. (2002) · Cited by 237 · see citing works
Figlio, D., & Page, M. (2002) · Journal of Urban Economics · doi:10.1006/juec.2001.2255 · Cited by 230 · see citing works
The Long-Term Effects and Cost-Effectiveness of Success for All
Borman, G. D., & Hewes, G. M. (2002) · Educational Evaluation and Policy Analysis · doi:10.3102/01623737024004243 · Cited by 182 · see citing works
Heckman, J. J. (2017) · The MIT Press eBooks · doi:10.7551/mitpress/9781.001.0001 · Cited by 176 · see citing works
The Benefits and Costs of Head Start
Ludwig, J., & Phillips, D. (2007) · National Bureau of Economic Research · doi:10.3386/w12973 · Cited by 149 · see citing works
Self-citationGeneric machine learning inference on heterogenous treatment effects in randomized experiments
Chernozhukov, V., Demirer, M., Duflo, E., & Fernández‐Val, I. (2018) · RePEc: Research Papers in Economics · doi:10.1920/wp.cem.2017.6117 · Cited by 149 · see citing works
Research Design Meets Market Design: Using Centralized Assignment for Impact Evaluation
Abdulkadiroğlu, A., Angrist, J. D., Narita, Y., & Pathak, P. A. (2017) · Econometrica · doi:10.3982/ecta13925 · Cited by 144 · see citing works
The Rate of Return to the High/Scope Perry Preschool ProgramPreprint
Heckman, J. J., Moon, S. H., Pinto, R. R., Savelyev, P. A., & Yavitz, A. (2009) · SSRN Electronic Journal · doi:10.2139/ssrn.1501969 · Cited by 130 · see citing works
Randomization Tests Under an Approximate Symmetry Assumption
Canay, I. A., Romano, J. P., & Shaikh, A. M. (2017) · Econometrica · doi:10.3982/ecta13081 · Cited by 125 · see citing works
Inequality, Too Much of a Good Thing
Krueger, A. B. (2018) · Routledge eBooks · doi:10.4324/9780429494468-4 · Cited by 116 · see citing works
Does School Spending Matter? The New Literature on an Old Question
Jackson, C. K. (2018) · National Bureau of Economic Research · doi:10.3386/w25368 · Cited by 116 · see citing works
How Changes in Entry Requirements Alter the Teacher Workforce and Affect Student Achievement
Boyd, D. J., Grossman, P. L., Lankford, H., Loeb, S., & Wyckoff, J. (2005) · National Bureau of Economic Research · doi:10.3386/w11844 · Cited by 106 · see citing works
Evaluating the Benefits and Costs of the Job Corps
Long, D. A., Mallar, C. D., & Thornton, C. V. D. (1981) · Journal of Policy Analysis and Management · doi:10.2307/3324110 · Cited by 82 · see citing works
The Production of Human Capital in Developed Countries
Fryer, R. G. (2017) · Handbook of economic field experiments · doi:10.1016/bs.hefe.2016.08.006 · Cited by 78 · see citing works
Self-citationLong-run Trends in the U.S. SES—Achievement Gap
Hanushek, E. A., Light, J., Peterson, P. E., Talpey, L. M., & Woessmann, L. (2022) · Education Finance and Policy · doi:10.1162/edfp_a_00383 · Cited by 65 · see citing works
Knowledge, Tests, and Fadeout in Educational Interventions
Cascio, E., & Staiger, D. O. (2012) · National Bureau of Economic Research · doi:10.3386/w18038 · Cited by 64 · see citing works
Charter Schools and Labor Market Outcomes
Dobbie, W., & Fryer, R. G. (2019) · Journal of Labor Economics · doi:10.1086/706534 · Cited by 55 · see citing works
Self-citationLake, R., Bowen, M., Demeritt, A., McCullough, M., Haimson, J., & Gill, B. (2012) · RePEc: Research Papers in Economics · Cited by 48 · see citing works
Davis, J. M. V., Guryan, J., Hallberg, K., & Ludwig, J. (2017) · doi:10.3386/w23925 · Cited by 47 · see citing works
Self-citationTeacher Applicant Hiring and Teacher Performance: Evidence from DC Public Schools
Jacob, B. A., Rockoff, J. E., Taylor, E., Lindy, B., & Rosen, R. Z. (2016) · National Bureau of Economic Research · doi:10.3386/w22054 · Cited by 45 · see citing works
High-Dosage Tutoring and Reading Achievement: Evidence from New York City
Fryer, R. G., & Howard-Noveck, M. (2020) · Journal of Labor Economics · doi:10.1086/705882 · Cited by 36 · cited 2× · see citing works
“The contrast in math gains between grades that received tutoring (6th and 9th) versus did not (7th and 10th) was on the order of 0.09 to 0.40 SD. Separately, Fryer and Howard-Noveck (2020) study the effects of high-dosage reading tutoring for middle-school students and find statistically significant gains in attendanc…”
InfluentialSelf-citationResearch Design Meets Market Design: Using Centralized Assignment for Impact EvaluationPreprint
Abdulkadiroğlu, A., Angrist, J. D., Narita, Y., & Pathak, P. A. (2016) · SSRN Electronic Journal · doi:10.2139/ssrn.2889675 · Cited by 21 · see citing works
School Improvement Grants: Implementation and Effectiveness. NCEE 2017-4013.
Dragoset, L., Thomas, J., Herrmann, M., Deke, J., James‐Burdumy, S., Graczewski, C., Boyle, A., Upton, R., Tanenbaum, C., & Giffin, J. (2017) · National Center for Education Evaluation and Regional Assistance · Cited by 18 · see citing works
Impacts of Title I Supplemental Educational Services on Student AchievementPreprint
Deke, J., Dragoset, L., Bogen, K., & Gill, B. (2012) · RePEc: Research Papers in Economics · Cited by 16 · see citing works
A Blueprint for Scaling Tutoring Across Public Schools
Kraft, M. A., & Falken, G. T. (2020) · Brown Digital Repository · doi:10.26300/dkjh-s987 · Cited by 14 · see citing works
Cheng, A. A., & Peterson, P. E. (2017) · Education next · Cited by 7 · see citing works
Flagged first, then by citations
8 of the 80 references couldn’t be matched to a known paper.
Research works printed but not linked: 7
- [14]14. Benjamini, Y., Krieger, A. M., & Yekutieli, D. (2006). Adaptive linear step-up procedures that control the false discovery rate. Biometrika, 93(3), 491-507. https://doi.org/10.1093/biomet/93.3.49. Bhatt, M., Guryan, J., Ludwig, J., Shah, A., & the Chicago Youth Violence Project Team. (2021). Scope challenges to social impact (Working Paper No. 28406). National Bureau of Economic Research. http://www.nber.org/papers/w28406 · DOI
- [43]43. Gibbs, C., Ludwig, J., & Miller, D. L. (2013). Head Start origins and impacts. In M. J. Bailey & S. Danziger (Eds.), Legacies of the War on Poverty (pp. 39-65).
- [47]47. Grogger, J., Neal, D., Hanushek, E., & Schwab, R. (2000). Further Evidence on the Effects of Catholic Secondary Schooling [with Comments. In Brookings-Wharton Papers on Urban Affairs (pp. 151-201).
- [53]53. Henry, G. T., Bastian, K. C., & Fortner, C. K. (2011). Stayers and leavers: Early-career teacher effectiveness and attrition. Educational Researcher, 40(6), 271-280.
- [65]65. Nomi, T., & Allensworth, E. (2009). Double-dose Algebra as an alternative strategy to remediation: Effects on students' outcomes. Journal of Research on Educational Effectiveness, 2(2), 111-148.
- [70]70. U.S. Elementary and Secondary Schools: Equalizing Opportunity or Replicating the Status Quo? The Future of Children, 16(2), 99-123.
- [75]75. Wager, S., & S, A. (2018). Estimation and Inference of Heterogenous Treatment Effects using Random Forests. Journal of the American Statistical Association, 113(523), 1228-1242.
Cited by
Sorted by citations
Experimental evidence on learning using low-tech when school is out
Angrist, N., Bergman, P., & Matsheng, M. (2022) · Nature Human Behaviour · doi:10.1038/s41562-022-01381-z · Cited by 105 · see citing works
An astonishing regularity in student learning rate
Koedinger, K. R., Carvalho, P. F., Liu, R., & McLaughlin, E. A. (2023) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2221311120 · Cited by 78 · see citing works
“Recent research providing human tutoring to increase student motivation to engage in difficult deliberate practice opportunities suggests promise in reducing achievement gaps by reducing opportunity gaps (63, 64).”
BackgroundA Blueprint for Scaling Tutoring and Mentoring Across Public Schools
Kraft, M. A., & Falken, G. T. (2021) · AERA Open · doi:10.1177/23328584211042858 · Cited by 74 · see citing works
“Kraft and Falken high-dosage tutoring program cost between $3,500 and $4,300 per pupil, yielding a CER between 0.09 and 0.11 (Guryan et al., 2021).7 Vacation academy tutoring, administered by teachers over a short period, have a CER of 0.12 for the average effect of 0.07σ (Schueler, 2020).”
BackgroundMethodInfluentialThomas, D. R., Lin, J., Gatz, E., Gurung, A., Gupta, S., Norberg, K. A., Fancsali, S. E., Aleven, V., Branstetter, L. G., Brunskill, E., et al. (2023) · International Conference on Learning Analytics and Knowledge · doi:10.1145/3636555.3636896 · Cited by 73 · see citing works
“” A large number of review studies and meta-analyses suggest large learning gains can be achieved when students use these technologies [11], but there can be substantial variability in usage of educational technology, and such variability in usage can be correlated with differing learning outcomes.”
BackgroundInfluentialOnline Tutoring by College Volunteers: Experimental Evidence from a Pilot Program
Kraft, M. A., List, J. A., Livingston, J. A., & Sadoff, S. (2022) · AEA Papers and Proceedings · doi:10.1257/pandp.20221038 · Cited by 37 · see citing works
Educational Equity Through Combined Human-AI Personalization: A Propensity Matching Evaluation
Chine, D. R., Brentley, C., Thomas-Browne, C., Richey, J. E., Gül, A., Carvalho, P. F., Branstetter, L., & Koedinger, K. R. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-11644-5_30 · Cited by 37 · see citing works
Learning loss and learning recovery
Patrinos, H. A. (2022) · DECISION · doi:10.1007/s40622-022-00317-w · Cited by 18 · see citing works
“The impacts are large by comparison with other interventions, including early childhood programs (Fryer 2017; Guryan et al. 2021; Nickow et al. 2020).”
ResultBonesrønning, H., Finseraas, H., Hardoy, I., Iversen, J. M. V., Nyhus, O. H., Opheim, V., Salvanes, K. V., Sandsør, A. M. J., & Schøne, P. (2022) · Journal of Public Economics · doi:10.1016/j.jpubeco.2022.104765 · Cited by 14 · see citing works
Scenario-Based Training and On-The-Job Support for Equitable Mentoring
Chine, D. R., Chhabra, P., Adeniran, A., Kopko, J., Tipper, C., Gupta, S., & Koedinger, K. R. (2022) · Lecture notes in networks and systems · doi:10.1007/978-3-031-21569-8_54 · Cited by 9 · see citing works
Health Policies as Education Policies? A Review of Causal Evidence and Mechanisms
Gopalan, M., & Edara, R. (2023) · AERA Open · doi:10.1177/23328584231177616 · Cited by 9 · see citing works
“Finally, an educational intervention with one of the largest reported effect sizes of 0.23 SD pertains to the benefits of individualized tutoring (Guryan et al., 2021).”
BackgroundInfluentialUsing Generative AI to Provide Feedback to Adult Tutors in Training and Assess Real-Life Performance
Thomas, D. R., Gatz, E. E., Gupta, S., Lin, J., Tipper, C., & Koedinger, K. R. (2024) · Lecture notes in networks and systems · doi:10.1007/978-3-031-73427-4_21 · Cited by 9 · see citing works
Does Multiple Choice Have a Future in the Age of Generative AI? A Posttest-only RCT
Thomas, D. R., Borchers, C., Kakarla, S., Lin, J., Bhushan, S., Guo, B., Gatz, E. E., & Koedinger, K. R. (2025) · International Conference on Learning Analytics and Knowledge (LAK) · doi:10.1145/3706468.3706530 · Cited by 7 · see citing works
Cotton, C. S., Hickman, B. R., List, J. A., Price, J., & Roy, S. (2025) · Journal of Political Economy · doi:10.1086/738479 · Cited by 4 · see citing works
Abdelshiheed, M., Jacobs, J., & D’Mello, S. K. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-64299-9_11 · Cited by 4 · see citing works
Cotton, C. S., Hickman, B. R., List, J. A., Price, J., & Roy, S. (2020) · National Bureau of Economic Research · doi:10.3386/w27995 · Cited by 4 · see citing works
High dosage tutoring in pre-vocational secondary education: Experimental evidence from AmsterdamPreprint
de Ree, J., Maggioni, M. A., Paulle, B., Rossignoli, D., & Walentek, D. (2021) · doi:10.31235/osf.io/r56um · Cited by 4 · see citing works
Educación en la sombra en Latinoamérica: armando el rompecabezas
Bray, M., & Ventura, A. (2024) · Revista Española de Pedagogía · doi:10.22550/0034-9461.4059 · Cited by 2 · see citing works
“Guryan et al. (2021) argue that the impact of the mentoring part of the program they study seems to be less relevant than the academic portion by analyzing survey data.”
InfluentialBerg, J., Osher, D. M., Hubbard, D., Pardo, M., Somers, M., & Haider, Z. (2024) · Journal of Research on Educational Effectiveness · doi:10.1080/19345747.2024.2403995 · Cited by 1 · see citing works
“Guryan et al. (2021) demonstrated the powerful effects high-dosage math tutoring can have among struggling 9th and 10th grade students in Chicago with an approach that involved at least one class period of tutoring a day.”
Adolescence Development and the Math Gender GapPreprint
Borra, C., Iacovou, M., & Sevilla, A. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4122090 · Cited by 1 · see citing works
Sánchez-Coll, S. (2022) · SERIEs · doi:10.1007/s13209-022-00270-y · Cited by 1 · see citing works
“…in achievement test scores (Borghans et al. 2011), and thus interventions aimed at adolescents can still improve test scores through this channel (Guryan et al. 2021). labour supply (González 2013; Hernández Alemán et al. 2017; González and Trommlerová 2021a), health (González and Trommlerová…”
BackgroundSustained Effects of Small-Group Instruction in MathematicsPreprint
Finseraas, H., Nyhus, O. H., Salvanes, K. V., & Sandsør, A. M. J. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4783701 · Cited by 1 · see citing works
School interventions to reduce intergenerational inequality
Britton, J., & Sibieta, L. (2024) · Edward Elgar Publishing eBooks · doi:10.4337/9781800888265.00037
Crisis of Education Remediation Plans
Colvin, M. K., Reesman, J. L., & Glen, T. (2024) · doi:10.1093/9780197762660.003.0005
Lessons Learned From A Multi-Site Study Of An Algebra Support Curriculum
Spencer, D., Mark, J., Piecham, M. B., Zeringue, J. K., Klein, K., & O’Dwyer, L. M. (2024) · Emerald Group Publishing Limited eBooks · doi:10.1108/979-8-88730-711-420251030
Hamlin, D. E., Peltier, C. J., & Reeder, S. (2026) · American Educational Research Journal · doi:10.3102/00028312261450125
- Authors
- Guryan, J., Ludwig, J., Bhatt, M., Cook, P., Davis, J. M. V., Dodge, K., Farkas, G., Fryer, R., Mayer, S., Pollack, H., & Steinberg, L.
- Affiliations
- National Bureau of Economic Research (US)
- ORCID
- Venue
- National Bureau of Economic Research
- Publisher
- National Bureau of Economic Research
- Published
- 2021-03
- OpenAlex
- W3157580258
- Cited by
- 25
- References
- 80
- Citations by year
- 2026: 1 · 2025: 2 · 2024: 9 · 2023: 2 · 2022: 8 · 2021: 2 · 2020: 1
- Type
- report
- Language
- en
- Open access
- green
- doi.org
- Locations
- National Bureau of Economic Research (publishedVersion)
- Funders
- U.S. Department of Justice
- National Institutes of Health
- Office of Juvenile Justice and Delinquency Prevention
- Topics
- Social Sciences › Education › School Choice and Performance
- Social Sciences › Demography › Global Educational Reforms and Inequalities
- Social Sciences › Education › Early Childhood Education and Development
- Keywords
- academic intervention, adolescent students, mathematics scores, grade point average, low-cost education, Chicago Public Schools, benefit-cost ratio, educational inequality
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-11.
Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-11.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review