College graduation rates vary significantly across high schools among students with the same HSGPA, and about one-fourth of that school-level variation is induced by comparing students with similar HSGPAs¶

Claim · All claims
Evidence · 1 study (2 entries) · associational r3 · q2
Currency · newest study 2019 · not yet checked against its sources · not reviewed by a person · overdue for a recheck since 2024: baselines and conditions change

Subclaims¶

q2 i? There is significant high school variance in six-year college graduation rates for students in every HSGPA band, controlling for background and college characteristics. → Allensworth 2019 q2 i? School-level variance is larger when HSGPA is included (0.603) than in a controls-only model (0.447), consistent with frogpond effects suppressing grades at schools with more positive school effects. → Allensworth 2019 (2)

Evidence¶

Allensworth 2019¶

Allensworth, Elaine M., & Clark, Kallie. (2019). Are GPAs an Inconsistent Measure of College Readiness across High Schools? Examining Assumptions about Grades versus Standardized Test Scores. University of Chicago Consortium on School Research. https://consortium.uchicago.edu/publications/are-gpas-inconsistent-measure-achievement-across-high-schools-examining-assumptions

q2 · i? · associational · r3

Non-parametric binned HSGPA models with school-level random effects on graduation, controlling for student background and college institutional variables. The article reports "significant high school variance in college graduation rates for students in each HSGPA bin".

"There is significant high school variance in college graduation rates for students in each HSGPA bin. For example, among students with HSGPAs between 3.25-3.5, a two-standard deviation range of high school effects is 0.144 ± 0.575 in log-odds in the conditional model."

Allensworth 2019 (2)¶

Allensworth, Elaine M., & Clark, Kallie. (2019). Are GPAs an Inconsistent Measure of College Readiness across High Schools? Examining Assumptions about Grades versus Standardized Test Scores. University of Chicago Consortium on School Research. https://consortium.uchicago.edu/publications/are-gpas-inconsistent-measure-achievement-across-high-schools-examining-assumptions

q2 · i? · associational · r3

Comparison of the continuous-HSGPA model's intercept variance (0.603) against a controls-only model (0.447). The authors interpret the 26% extra variance as consistent with "frogpond" effects wherein HSGPAs are suppressed at schools with more positive school effects.

"About one-fourth of the school-level variation in Model 2 ((0.603-0.447)/0.603 = 26%) is “extra” variation that is induced by comparing students with similar HSGPAs."

Discussion¶

Related Claims¶

• ACT scores show significant subgroup misprediction by race, ethnicity, and gender that HSGPA models do not, and school-level variance is smaller among students with the same ACT score than the same HSGPA — related
• Both HSGPA and ACT scores leave large high school effects on college graduation unexplained, which the study recommends measuring and publishing directly — a broader claim this one bears on
• Students with the same HSGPA or the same ACT score graduate from college at different rates depending on which high school they attended — a broader claim this one bears on
• School average ACT scores predict college graduation for students with the same individual HSGPA and ACT score, reducing between-school variance by 42 percent, while school poverty is not significant once average ACT is included — a narrower finding that bears on this claim
• Adding ACT scores to models with HSGPA contributes little to the prediction of college graduation and does not reduce between-school variability — related