The text-processing intervention significantly improved struggling middle school readers' performance on a proximal vocabulary measure¶
Claim · All claims
Evidence · 1 study · causalr2·q3·i2medium
Currency · newest study 2016 · not yet checked against its sources · 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.
q3 i2 Treatment students outperformed business-as-usual control students on the researcher-developed vocabulary measure after the intervention. → Amy E. Barth 2016
Evidence¶
Amy E. Barth 2016¶
Amy E. Barth, Sharon Vaughn, Philip Capin, Eunsoo Cho, Stephanie Stillman-Spisak, Leticia Martinez, and Heather Kincaid. (2016). Effects of a Text-processing Comprehension Intervention on Struggling Middle School Readers. Top Lang Disord. 2016; 36(4): 368–389. https://doi.org/10.1097/TLD.0000000000000101
q3 · i2 · causal · r2
One-way ANCOVA on the researcher-developed vocabulary matching measure with pretest as covariate, in a randomized trial with 83 treatment and 51 comparison students. The article reports "treatment students performed better than the control students" with F (1, 131) = 7.00, p = .009, ηp2= .051.
"For the vocabulary measure, treatment students performed better than the control students on the vocabulary, F (1, 131) = 7.00, p = .009, ηp2= .051"
Discussion¶
Related Claims¶
- The text-processing intervention significantly improved struggling middle school readers' identification of key words and main ideas on a proximal measure — related
- The multi-component intervention produced statistically significant advantages over business-as-usual on one decoding measure (ES = 0.58) and one fluency measure (ES = 0.46), but not on reading comprehension — related
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