Data dives with disaggregated course success data surfaced equity gaps previously invisible to faculty¶
Claim · All claims
Evidence · 2 studies · 2 designr2·q2
Currency · newest study 2023 · checked against its sources 2026-10-09 (automated, 2 of 2 entries) · 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 i? In some RPP courses, students of color and Pell-eligible students passed at lower average rates than their peers, which faculty had often not seen before disaggregation. → datadive-1
q2 i? Faculty had never before seen their own course success data disaggregated by student population, making data-dive insights actionable in new ways. → datadive-2
Evidence¶
datadive-1¶
Wiley, K., Neisler, J., & Means, B. (2023, February). Partnering to promote equity and digital learning. Digital Promise. https://doi.org/10.51388/20.500.12265/167
q2 · i? · design · r2
Report narrative on the summer 2021 data dive sessions in which Digital Promise researchers shared disaggregated grade data with course teams. The report states "students of color and Pell-eligible students were passing at lower average rates than their peers" in some courses, prompting discussions of targeted supports.
"in some courses, students of color and Pell-eligible students were passing at lower average rates than their peers, which led to discussions of additional targeted supports that could be provided."
datadive-2¶
Wiley, K., Neisler, J., & Means, B. (2023, February). Partnering to promote equity and digital learning. Digital Promise. https://doi.org/10.51388/20.500.12265/167
q2 · i? · design · r2
Report's equity-practice discussion of data access barriers: faculty lacked access to disaggregated student data until RPP researchers obtained it from institutional research offices, and the "data dives were actionable in new and meaningful ways" as a result.
"Many of the faculty had never before seen their own course success data disaggregated by student population, so insights from the data dives were actionable in new and meaningful ways."
Discussion¶
Related Claims¶
- Launching RPP work with disaggregated student data highlighted equity issues without assigning blame — possibly the same claim (merge candidate)
- In early online implementations of the Skyline Data Path course, Filipino students' success rates exceeded the course average while Latino students' fell below it — a narrower finding that bears on this claim
- Adaptive courseware in a corequisite statistics course was associated with improved course outcomes, particularly for Pell-eligible and corequisite students, but effects are confounded with instructor practices — related
- Courseware use did not disadvantage any student group and appeared especially promising for under-represented minority students, with grades independent of Pell, enrollment, age, gender, and first-gen status in 75% or more of analyses. — related
- Leaders caution that disaggregating data by student demographics is only the beginning of using continuous improvement for equity, not its entirety — a broader claim this one bears on
- Barriers to using equity visualizations included lack of classroom diversity and teachers' own equity beliefs — related
- Prior gateway course success rates averaged 66 percent with a 14-point gap for students of color — related
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
disaggregated-data-dives-surface-equity-gaps |
title |
Data dives with disaggregated course success data surfaced equity gaps previously invisible to faculty |
description |
Data dives with disaggregated course success data surfaced equity gaps previously invisible to faculty |
status |
review |
evidence_strength |
moderate |
newest_evidence |
2023 |
source_checked |
2026-10-09 |
generated |
by process:wiki-ingest on 2026-10-09 |
trust |
unverified — no one has confirmed this page's content |
sources |
2 — datadive-1, datadive-2 |
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