Oral narratives, dialogical intervention and reading comprehension: A study of 5-to-8 years old French children.
Bibliographic record
Abstract
The acquisition of narrative skills is a developmental process that spans several years. Although children as young as 4-5 years can produce descriptive narratives, they have difficulties to produce coherent and causally-motivated plots. Previous studies have shown that from 6-7 years on, children produce more coherently structured and mind-oriented narratives after participating in conversations that solicit children's attention on the reasons of the events of the story. We believe that promoting narrative skills is not only an important achievement in itself but also a useful approach for improving children's reading comprehension, more useful then concentrating on lower level units of written text like phonological awareness or letters. The aim of this study is to present the progression of children's oral narratives in the construction of a story from a set of pictures and in the recall of a story read by the experimenter, and how such a progression relates to measures of emergent reading and writing skills and to two theory of mind tasks. To this effect, 100 children between the ages of 5 to 8 (25 children per age group) participated in the different phases of the study. Preliminary results show that the dialogical intervention procedure promotes in some children more structured and evaluative narratives, a progression that correlates with children's emergent reading and writing measures. These results confirm the importance of the conversational intervention procedure for improving narratives and its usefulness as an evaluative tool for understanding the relation between oral narratives and reading comprehension.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".