Oral language skills intervention in pre‐school—a cautionary tale
Bibliographic record
Abstract
BACKGROUND: While practitioners are increasingly asked to be mindful of the evidence base of intervention programmes, evidence from rigorous trials for the effectiveness of interventions that promote oral language abilities in the early years is sparse. AIMS: To evaluate the effectiveness of a language intervention programme for children identified as having poor oral language skills in preschool classes. METHODS & PROCEDURES: A randomized controlled trial was carried out in 13 UK nursery schools. In each nursery, eight children (N = 104, mean age = 3 years 11 months) with the poorest performance on standardized language measures were selected to take part. All but one child were randomly allocated to either an intervention (N = 52) or a waiting control group (N = 51). The intervention group received a 15-week oral language programme in addition to their standard nursery curriculum. The programme was delivered by trained teaching assistants and aimed to foster vocabulary knowledge, narrative and listening skills. OUTCOMES & RESULTS: Initial results revealed significant differences between the intervention and control group on measures of taught vocabulary. No group differences were found on any standardized language measure; however, there were gains of moderate effect size in listening comprehension. CONCLUSIONS & IMPLICATIONS: The study suggests that an intervention, of moderate duration and intensity, for small groups of preschool children successfully builds vocabulary knowledge, but does not generalize to non-taught areas of language. The findings strike a note of caution about implementing language interventions of moderate duration in preschool settings. The findings also highlight the importance of including a control group in intervention studies.
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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 | 0.103 | 0.211 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.007 | 0.003 |
| Research integrity | 0.015 | 0.019 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".