Mothers’ Educational Beliefs and Preschoolers’ English Learning Attitudes: The Mediating Role of English Experiences at Home
Bibliographic record
Abstract
This article analyzes the relationship between Korean mothers’ beliefs about early childhood English education and preschoolers’ attitudes toward English learning. English experiences in the home were also projected to be significantly related to the aforementioned factors. Participants consisted of 159 mother–child pairs in South Korea. This study yielded three main results. First, correlations were found between the mothers’ education level and all three factors, while the fathers’ education and family income levels correlated only with preschoolers’ English experiences at home. Second, the subfactors of the mothers’ beliefs, the preschoolers’ home English experiences, and their attitudes toward learning English were revealed to be partly related. Third, the study showed that preschoolers’ English experiences at home mediated the relationship between the mothers’ beliefs in the importance of English education and the preschoolers’ attitudes. In effect, while the mothers’ beliefs about early childhood English education did not directly affect their children’s attitudes, indirect effects were found to be mediated by English experiences at home. Based on these results, we propose that it is necessary for parents to create a rich language environment in the home that engenders in children positive foreign language learning attitudes.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".