Naturalistic Parent Teaching in the Home Environment During Early Childhood
Bibliographic record
Abstract
Children's sociocultural experiences in their day-to-day lives markedly play a key role in learning about the world. This study investigated parent-child teaching during early childhood as it naturally occurs in the home setting. Thirty-nine families' naturalistic interactions in the home setting were observed; 1033 teaching sequences were identified based on detailed transcriptions of verbal and non-verbal behavior. Within these sequences, three domains of learning (knowledge, skills, and dispositions) and subtopics were identified and analyzed in relation to gender, child birth order, context, teaching strategies, and learner response. Findings show knowledge, skills, and dispositions were taught equally, marked by the most prominent subtopics taught within each domain, including cognitive (skill), game rule (knowledge), and social rule (disposition). Further, mothers and fathers were found to teach their children equally, however, fathers taught knowledge more than mothers, whereas mothers taught dispositions more than fathers. Differences between domains of learning and subtopics also existed between mother's and father's teaching based on child birth order and gender. This study also assessed the contrast between teaching knowledge, skills, and dispositions by context, parent teaching strategies, and child learner response. Results support the notion that family interactions in the home setting set a stage for children's rich informal learning experiences. Vygotskian sociocultural conceptions underpin this research and findings are discussed using this central theoretical lens.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".