Using Nursery Rhymes to Foster Phonological and Musical Processing Skills in Kindergarteners
Bibliographic record
Abstract
The aim of this study was to assess the efficiency of four learning conditions to develop phonological and musical processing skills through a set of 10 nursery rhymes. According to the analysis of the teachers’ practices, eight kindergarten classes (n = 100 kindergarteners) were paired and assigned to one of the following conditions: 1) music, 2) language, 3) combined [music and language], and 4) passive listening (control classes). Participants in conditions 1, 2, and 3 were met for 40 minutes per week over a ten-week period. In condition 1, the nursery rhymes were supplemented by musical activities and in condition 2 by language activities. Condition 3 was a combination of activities from conditions 1 and 2. In condition 4, children listened to a recording of the same nursery rhymes for 15 minutes daily during free exploration periods. No intervention was proposed for this control condition. All participants were evaluated using the same phonological and musical processing measures prior to and after the implementation of the program. Results indicated that children in conditions 1, 2 and 3 significantly improved their phonological awareness and their invented spelling skills at post-test. However, only the two conditions in which the music component was integrated enhanced significantly their results at the verbal memory task. Children in conditions 1, 3 and 4 enhanced tonal and rhythm perception skills. This study demonstrated that supplementing nursery rhymes with language activities is an efficient manner to develop emergent literacy skills, but the addition of musical activities could also boost phonological processing skills.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".