Evidence‐Based Strategies for Reading Instruction of Older Students with Learning Disabilities
Bibliographic record
Abstract
Over a quarter of 8th‐grade students and more than one‐third of 4th graders do not read well enough to understand important concepts and acquire new knowledge from grade‐level text. For students with learning disabilities, the numbers are more troubling. This article describes features of evidence‐based instruction for students who continue to struggle with reading in late elementary, middle, and high school. Recommendations are organized into 5 areas that are critical to the reading improvement of older struggling readers: (1) word study, (2) fluency, (3) vocabulary, (4) comprehension, and (5) motivation. Much of the content in this article reflects our efforts with the Special Education and Reading Strands at the National Center on Instruction, funded by the Office of Special Education Programs and the Office of Elementary and Secondary Education. Two reports, both available at http://www.centeroninstruction.org/ , have particular relevance— Interventions for Adolescent Struggling Readers: A Meta‐Analysis with Implications for Practice and Academic Literacy Instruction for Adolescents: A Guidance Document from the Center on Instruction.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".