Examining Relations Between Parental Feedback Types and Preschool-Aged Children’s Academic Skills
Bibliographic record
Abstract
Prior research has shown associations between parent and teacher feedback and school-aged children’s academic outcomes. Specifically, studies have demonstrated that positive feedback (i.e., praise and/or affirmation) is beneficial for children’s academic outcomes, while corrective feedback exhibits more mixed associations with children’s academic outcomes. Little is known about the relations between parental feedback and younger children’s academic skills. The present study examines the frequency of positive and corrective types of feedback provided by parents of 4-year-old children during semi-structured interactions, as well as how these feedback types relate to children’s concurrent math and language skills and their change in math skills over a one-year period. Parent-child dyads (n=91) were observed interacting with a picture book, grocery store set, and magnet board puzzle for 5 to 10 minutes each, after which they completed math and language assessments. Parental affirmation was positively and corrective feedback was negatively associated with children’s concurrent math outcomes, but only corrective feedback was uniquely negatively associated with children’s math outcomes when controlling for affirmations. Parental praise was individually and uniquely positively associated with children’s expressive vocabulary and change in math outcomes from age 4 to age 5. This study suggests that the relations between parental feedback and young children’s academic outcomes depend on the type of feedback and the outcome of interest (i.e., math vs language), which can inform how parents may want to provide feedback to facilitate learning.
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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 | 0.002 | 0.011 |
| 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 | 0.000 |
| 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".