Evidence map›Paper›PMID 42389714›Full record

ArticleAmerican journal of education (Chicago, Ill.)2024

Immigrant Optimism and Ever-English Learners' Journeys from Kindergarten to College in Texas.

Rebecca M Callahan, Lauren Schudde, Kimberly Pack-Cosme

Abstract read
In one paragraph

Article in American journal of education (Chicago, Ill.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Rebecca M CallahanUniversity of Vermont.ORCID 0000-0002-6928-4852
Lauren SchuddeUniversity of Texas-Austin.ORCID 0000-0003-3851-1343
Kimberly Pack-CosmeUniversity of Texas-Austin.ORCID 0000-0002-3504-130X

Funding

Scientific & Technical CoreP2CHD042849 · NICHD · UNIVERSITY OF TEXAS AT AUSTIN · PI MARK D. HAYWARD · 2017 to 2026
$5.2M
NICHD NIH HHS P2C HD042849
6 · The paper itself

Abstract

Purpose: Immigrant-origin English learners (ELs) are the fastest growing population in U.S. schools. Most EL research examines the college-going outcomes of this population by focusing on those who are EL-identified in high school; here, we capture both current- and former-EL identified students, or ever-ELs. A subset of bilingual, immigrant-origin students, ever-ELs may theoretically benefit from the high expectations of their foreign-born parents. In this study, we use an expanded analytic lens (ever-EL) to test whether an immigrant advantage exists with respect to high school graduation and college enrollment. Research Methods/ Approaches: We use multilevel models and longitudinal, statewide administrative K-12 and higher education data capturing kindergarteners in 1999 and 2000 (N=414,628) to examine how ever-EL status predicts five outcomes: high school graduation, application to a four-year college, any college enrollment, and type of college attended. Findings: Results show that ever-EL status is associated with a greater likelihood of graduating from high school, and, among high school graduates, ever-ELs are significantly more likely to enroll in college; however, this is due to the fact that they are significantly more likely to attend a two-year college and less likely to enroll in a four-year institution. Implications: We find limited evidence of an immigrant advantage among ever-ELs; instead, we suggest that systemic and structural challenges associated with the EL label may stand in ever-ELs' postsecondary pathways and impede full realization of their immigrant potential.

Indexed as

college enrollmentEver-ELfour-yearhigh school graduationtwo-year

Identifiers

PMID42389714
PMCPMC13322669

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.