A few decision-tree splits identify very high-risk students, such as low-SES students who doubt they will reach college¶
Claim · All claims
Evidence · 1 study · associationalr2·q2
Currency · newest study 2017 · checked against its sources 2026-10-20 (automated, 1 of 1 entry) · not reviewed by a person · overdue for a recheck since 2020: tool and model accuracy changes quickly
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? Among the 712 students who did not think they would make it to college and were in the bottom quartile of SES, only 28 percent went to college and persisted. → James Soland 2017
Evidence¶
James Soland 2017¶
James Soland. (2017). Combining Academic, Noncognitive, and College Knowledge Measures to Identify Students Not on Track For College: A Data-Driven Approach. Research & Practice in Assessment, Volume Twelve, Summer 2017. https://www.nwea.org/research/publication/combining-academic-noncognitive-and-college-knowledge-measures-to-identify-students-not-on-track-for-college-a-data-driven-approach/
q2 · i? · associational · r2
The weighted decision tree (Figure 1) applied to the NELS sample; this branch combines a student expectation item with an SES split. The article also reports a less-obvious right-most branch with only a 50 percent chance of being college-ready.
"looking at the left-most branch of the decision tree, among the 712 students who did not think they would make it to college and were in the bottom quartile of SES, only 28 percent went to college and persisted."
Discussion¶
Learner Variables¶
- Socioeconomic Status — predictor: outcomes differ by group: a gap reflecting circumstances and treatment, not a cause
Related Claims¶
- Students not on track for college enrollment and persistence can be classified with about 90 percent accuracy using a small set of predictors — a broader claim this one bears on
- AI/AN youth dropout rates reach up to 50 percent, and college matriculation and retention rates remain very low compared to White peers — related
- The strongest college-readiness predictors measure four broad constructs: academic preparation, aspirations and expectations, socioeconomic status, and teacher perceptions — related
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
few-splits-identify-high-risk-students |
title |
A few decision-tree splits identify very high-risk students, such as low-SES students who doubt they will reach college |
description |
A few decision-tree splits identify very high-risk students, such as low-SES students who doubt they will reach college |
status |
review |
evidence_strength |
moderate |
newest_evidence |
2017 |
source_checked |
2026-10-20 |
recheck_by |
2020 |
generated |
by process:wiki-ingest on 2026-10-09 |
trust |
unverified — no one has confirmed this page's content |
sources |
1 — james-soland-2017 |
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