An Early Literacy Program for Young Children with Down Syndrome: Changes Observed over One Year
Bibliographic record
Abstract
Abstract Although much individual variability exists, most persons with Down syndrome (DS) experience marked expressive language delays and challenges with speech production, hearing, and verbal memory that may negatively affect literacy development. There is, however, a paucity of research with respect to early intervention literacy programs with this population. The authors describe an early intervention literacy program that used a hybrid approach to reading instruction combining whole‐word (i.e., visual) and analytic (i.e., phonic or sound‐based) reading strategies. They also detail the changes observed in the literacy and language abilities of the participants over 1 year. The participants were 15 English speaking Canadian students with DS aged 3–6 years (M age 4;11, pretreatment) who took part in a 45‐week program. Weekly individual sessions with a certified teacher were augmented by regular homework. Each student's literacy and language abilities were assessed immediately pretreatment and posttreatment. Measures of letter name identification, letter sound identification, print concepts, and identification of taught sight words showed statistically significant changes. Letter name identification, letter sound identification, and number of sight words read pretreatment were all positively and significantly correlated with gains in word identification. There was also a clear difference regarding how many new sight words students were able to read posttreatment depending on whether they used abstract symbols to communicate (i.e., unprompted spoken words or signs) pretreatment. The authors note that this study provides support for literacy interventions that combine phonological awareness, word analysis, sight word training, and shared book reading with children with DS as young as 3 years of age with varying levels of language development.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".