The likelihood of being identified as significantly below benchmark in early literacy screening increases as historically underserved background characteristics intersect¶

Claim · All claims
Evidence · 1 study · associational r2 · q2
Currency · newest study 2024 · checked against its sources 2026-10-20 (automated, 1 of 1 entry) · not reviewed by a person

Subclaims¶

q2 i? Students who receive special education services, are English learners, or come from a low income background are more likely to be identified as at significant risk of reading difficulty, and the chances increase as these characteristics intersect. → Lemke 2024

Evidence¶

Lemke 2024¶

Lemke, M., Murphy, D., Soo Ping Chow, A., & Acuña, A. (2024). Intersections: Student background and early literacy performance. WestEd. https://eric.ed.gov/?id=ED663858

q2 · i? · associational · r2

Multilevel statistical model of 2022/23 district-provided screening assessment data estimating likelihood of being significantly below benchmark more than once. The model shows a base chance of "about an 11 percent" rising with each intersecting characteristic, to about 53 percent for students from low income backgrounds who receive special education services; the small number who are also English learners have "even higher likelihoods" (no figure given).

"On average, students have about an 11 percent chance of being identified as significantly below benchmark more than once. That likelihood increases by about 8 percentage points if students come from a low income background, about 17 percentage points if students are English learners, and about 28 percentage points if students receive special education services."

Discussion¶

Related Claims¶

• Students from low income backgrounds, English learners, students receiving special education services, and Black and Hispanic students were more often identified as at significant risk — related
• Formal early childhood experience reduces the likelihood of being identified as significantly below benchmark, most pronounced among English learner students and Black English learner students — related
• The likelihood of being identified as at risk increases as historically underserved background characteristics intersect, with variation by gender and race/ethnicity, and school characteristics also matter — possibly the same claim (merge candidate)
• School and district factors relate to risk identification: low income concentration correlates with repeated risk identification, and segregation modestly increases it, though some schools outperform model predictions — related
• Low income, English learner, special education, Black, and Hispanic students were more likely to be classified significantly below benchmark at each time period and more than once — related
• School characteristics—percentage of low income students, teacher retention, and attendance—are associated with students' likelihood of being identified as at significant risk in early literacy screening — related
• Students from low income, English learner, special education, and several racial/ethnic groups are more likely to be repeatedly identified as significantly below benchmark, with low income students 2.5 times as likely — related
• Historically underserved student groups show substantially lower shares meeting the 12th-grade reading benchmark, with gaps up to 30 percentage points — related
• On 2022 NAEP 8th- and 12th-grade reading and math exams, students who were both English learners and from low-income backgrounds scored lowest among four student groups, with less than one third scoring basic or above in reading and less than one quarter in math — related
• Among control students, AI platform use is lower among special education students and lower-achieving students — related