Young Children’s Theory of Mind: Home Literacy Environment, Technology Usage, and Preschool Education
Bibliographic record
Abstract
Theory of mind (ToM) skills involve young children’s mentalizing ability to be aware of their own selves and other individuals’ thoughts, beliefs, desires, and intentions (mental states). The social cognition skills are essential for processing complex social relations and overcoming interpersonal difficulties in communication. Previous studies shed light on the relationship of parenting and demographics to children’s ToM skills, but do not examine the associations with both home environment and preschool education experiences. The goal of the present study is to investigate children’s preschool education experience, home literacy environment (HLE), and technology usage in relation to their ToM skills. Participants were 203 preschoolers and their parents. The study data were collected using a home literacy environment questionnaire (HLEQ), theory of mind scale, and a demographic information form. The findings revealed that (a) children’s ToM scores are not differentiated regarding gender, excluding the diverse belief tasks, b) children’s ToM performances were differentiated in favor of children who have internet access at home, c) HLE, child age, daily TV watching, household income, maternal education, preschool experience, and shared book reading explained 46% of the total variance of preschoolers’ ToM scores.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".