Effects were larger in intervention schools with a higher percentage of economically disadvantaged students or a lower percentage of White students¶

Claim · All claims
Evidence · 1 study (2 entries) · causal r3 · q3 · i0–i1
Currency · newest study 2023 · checked against its sources 2026-10-20 (automated, 2 of 2 entries) · not reviewed by a person

Subclaims¶

q3 i1 Students in intervention schools with a higher percentage of economically disadvantaged students benefited more than those in schools with a lower percentage (p = 0.045, g = 0.22). → Feng 2023 q3 i0 Students in intervention schools with a lower percentage of White students seemed to benefit more (p = 0.056, g = 0.19). → Feng 2023 (2)

Evidence¶

Feng 2023¶

Feng, M., Huang, C.-W., & Collins, K. (2023). Technology-based support shows promising long-term impact on math learning: Initial results from a randomized controlled trial in middle schools. WestEd. https://osf.io/exqpn

q3 · i1 · causal · r3

School-level moderator analysis splitting the 63 randomized schools into two groups by average percentage of economically disadvantaged students and estimating differential intervention effects (Hedges' g = 0.22).

"students in intervention schools with a higher percentage of economically disadvantaged students benefited more than those in intervention schools that had a lower percentage of students from economically disadvantaged backgrounds (p = 0.045, Hedges' g = 0.22)."

Feng 2023 (2)¶

Feng, M., Huang, C.-W., & Collins, K. (2023). Technology-based support shows promising long-term impact on math learning: Initial results from a randomized controlled trial in middle schools. WestEd. https://osf.io/exqpn

q3 · i0 · causal · r3

Companion school-level moderator analysis using average percentage of White students; the p value of 0.056 is marginally above conventional thresholds, and the authors hedge with "seemed to benefit more."

"Furthermore, students in the intervention schools with a lower percentage of White students seemed to benefit more than those in the intervention schools with a higher percentage of White students (p = 0.056, Hedges' g = 0.19)."

Studies bearing on this claim¶

Do instructional programmes help learners from low-income families as much as, or more than, their better-off peers? This table gathers the studies behind this claim and the 20 narrower claims that bear on it: 20 distinct studies (11 causal, 4 associational, 3 review, 2 quant-synthesis), q2–q3, 3 of 20 with an effect size coded. One row per study, codes as each entry records them; no effect is averaged and no verdict is drawn. Built by scripts/synthesize_claim.py from eval/synthesis/; a row that looks wrong is fixed on the claim it comes from.

Discussion¶

Learner Variables¶

• Socioeconomic Status — moderator: an instructional effect differs by group

Related Claims¶

• ASSISTments benefited students of color significantly more than White students, narrowing the ethnic achievement gap — related
• ASSISTments benefited Hispanic students more than non-Hispanic students — related
• The Exact Path evaluation sample was demographically diverse, including 42% African American, 47% economically disadvantaged, and 22% ESE students — related
• Active learning narrows achievement gaps for disadvantaged and underrepresented students — related
• Coursemojo use narrowed achievement gaps for students with disabilities and economically disadvantaged students in Tennessee — related
• Socially disadvantaged children do not differ in physical fitness but score significantly lower on academic performance than non-disadvantaged peers — related
• Most reviewed studies used samples composed of at least 40 percent economically disadvantaged students — related
• Socioeconomic status does not significantly moderate the mind-set–achievement correlation — related
• Early childhood education programs often yield larger benefits for children most in need, such as low-income children, children of color, and those with fewer educational resources — a broader claim this one bears on
• Benefits of CCSPP community schools were largest for Black students, English learners, and socioeconomically disadvantaged students — related
• Low-poverty schools benefited more from the evaluation pilot than high-poverty schools, in both math and reading — reports the opposite
• SimCalc treatment effects were not sensitive to school socioeconomic status or percentage of Hispanic students, and 91% of 7th-grade treatment classrooms exceeded the control-group mean gain — related
• No significant heterogeneity in pilot effects by school racial/ethnic composition was found — reports the opposite
• The study examines whether some early elementary school math curricula are more effective than others at improving math achievement in schools serving a high percentage of disadvantaged students. — a broader claim this one bears on
• Technology-enhanced stories (any digital addition, not multimedia alone) significantly improve expressive vocabulary for children disadvantaged by environmental factors such as low parental education — related
• An open classroom climate at school can partially compensate for the disadvantages of young people with low socioeconomic status — related
• No clear evidence that Medly's effect differed by Pupil Premium disadvantage status — related
• Mind-set interventions show weak overall effects on achievement, with some support that low-SES or academically at-risk students might benefit — related
• Field trip effects on science achievement are largest for Hispanic students and students qualifying for free or reduced-price lunch — related
• An adapted SimCalc linear-function unit in England produced significant posttest gains versus Texas-control predictions (ES = 0.57), with no significant gain differences by poverty or prior achievement — related
• The better-performing early math curricula raised achievement for several student subgroups, including students in low-scoring and high-poverty schools — related
• The intervention showed no meaningful differential effects for children facing socioeconomic disadvantage, EAL, SEN, or multiple overlapping challenges — related