Claims

Students showed a large, statistically significant pre-to-post improvement in repeated reasoning (SMP 8) in the Mindsets program (d ≈ 1.19)

Claim · All claims
Evidence · 1 study · causal r1 · q2 · i3 large
Currency · newest study 2025 · checked against its sources 2026-10-17 (automated, 1 of 1 entry) · not reviewed by a person

Subclaims

Reading the evidence codes

q is the design tier, i the impact, n the sample, and the kind with its r the rigour judged within that kind: what each code means.

This claim: no standardized effect is recorded in observations/ for it yet, so no benchmark reading is possible.

q2 i3 Students were more likely to score in a higher Repeated Reasoning benchmark category at post compared to pre (b = 2.16, p = .012; d ≈ 1.19). → Gage 2025

Evidence

Gage 2025

Gage, N. (2025). The impact of the Mindsets mathematics program on student engagement, ability to reason, and repeated reasoning. WestEd. https://eric.ed.gov/?id=ED677579

q2 · i3 · causal · r1

Pre–post CLMM on the Repeated Reasoning dataset with a challenge random intercept (SD = 0.695). The report converted the log-odds effect using Chinn's (2000) method, "yielding an estimated d of 1.19, representing a large effect."

"The CLMM revealed a significant effect of time, b = 2.16, SE = 0.86, z = 2.51, p = .012, indicating that students were more likely to score in a higher Repeated Reasoning benchmark category at post compared to pre"

Discussion

Learner Variables

Page metadata
Field Value
type claim
id mindsets-smp8-pre-post-improvement
title Students showed a large, statistically significant pre-to-post improvement in repeated reasoning (SMP 8) in the Mindsets program (d ≈ 1.19)
description Students showed a large, statistically significant pre-to-post improvement in repeated reasoning (SMP 8) in the Mindsets program (d ≈ 1.19)
status review
evidence_strength moderate
newest_evidence 2025
source_checked 2026-10-17
generated by process:wiki-ingest on 2026-10-09
trust unverified — no one has confirmed this page's content
sources 1 — gage-2025

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