Changes in self‐perceptions of competence and intrinsic motivation among elementary schoolchildren
Bibliographic record
Abstract
BACKGROUND: Children's perceived competence and intrinsic motivation are assumed to be very high at the outset of schooling. However, how they change and how they relate to each other and to academic achievement across early schooling years remain open to question. AIMS: This 3-year longitudinal study was aimed at examining the following questions. Do children's perceived competence and intrinsic motivation about reading and mathematics change across the first 3 years of schooling? Do their perceived competence and intrinsic motivation differ according to academic domains? Do their perceived competence and intrinsic motivation relate to their academic achievement in each academic domain? SAMPLE: A total of 115 elementary schoolchildren (63 boys and 52 girls) were examined in first grade (mean age = 84,5 months, SD =.67) and for the next 2 years. METHOD: Children responded to questionnaires about their perceived competence and intrinsic motivation in reading and mathematics. Year-end grades in these two subjects were used as a measure of performance. RESULTS: Changes in perceived competence and intrinsic motivation, and between-year intercorrelations, were observed to differ according to academic domains and gender. Intrinsic motivation did not make a significant contribution to academic achievement at either school grade or in any academic domain, whereas perceived competence was significantly related to achievement at each school grade in both reading and mathematics. CONCLUSIONS: Differences between boys and girls observed in this study were not linked to a specific domain and cannot be attributed to gender-role stereotypes. Girls appeared to be more precocious in differentiating their competence and intrinsic motivation according to academic domain, as well as in being able to process and integrate information about their ability from past performances in a domain to judge their competence in the same domain.
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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 | 0.001 | 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 | 0.001 |
| 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".