TEACHERS BACKGROUND AS DETERMINANTS OF PRE-SCHOOL CHILDREN'S WRITING SKILLS IN SOUTHWESTERN NIGERIA
Bibliographic record
Abstract
Abstract The study examined teacher background training as determinants of pre-school children’s writing skills in Southwestern Nigeria. The study adopted mixed design that consisted of observation and correlational design. A self-designed instrument was used for this study. The population for the study consisted of all the pre-school children and their teachers in Southwestern Nigeria. The sample size for the study consisted of 120 pre-school teachers and 600 pre-school children. The study adopted a multi-stage sampling procedure. Three states were selected from six states in Southwestern Nigeria using simple random sampling technique through a ballot system. The instrument used was “Preschool Children Writing Skill Rubric” (PCWSR). Data for PCWSR was a administered by checking children’s’ note books. The data were analysed using Independent Sample T-test. Results indicated that teacher background training significantly influenced preschool children’s writing skills (df = 598; t = 11.476; p < 0.05). The study concluded that teachers’ training background was found to be the factor that could influence the writing skills of preschool children.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 teacher head, 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".