The impact of early reading interventions delivered by classroom assistants on attainment at the end of Year 2
Bibliographic record
Abstract
Previous research has shown that training teaching assistants to deliver early phonic reading interventions can have measurable effects at immediate post‐test. This study explored whether the effects of interventions delivered by classroom assistants (CAs) were still evident at the end of the first phase of schooling, 16 months after the early intervention finished. Children were divided into ‘treatment responder’ and ‘treatment non‐responder’ groups based upon post‐test decoding skills. The treatment responder group was significantly more likely to achieve average results in nationally administered tests (end of Key Stage 1 tests) and teacher ratings of attainment than the treatment non‐responders. Treatment responders were indistinguishable from national averages on the mathematics test, writing test and reading task performance, but differed on reading comprehension test and on teacher‐assessed attainment. Gains in reading delivered following early phonic reading interventions delivered by CAs are maintained for many children. Non‐responders and treatment responders with only modest decoding skill may require additional support to achieve national targets in literacy.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".