The Mediation Role of Intrinsic and Extrinsic Motivation in the Relationship between Creative Educational Environment and Metacognitive Self-Regulation
Bibliographic record
Abstract
This study investigated the mediation role of intrinsic and extrinsic motivation in the relationship between creative educational environment and metacognitive self-regulation. Participants were 300 girls, selected randomly from the girl hostel in university of Tehran. Participants completed Akoal’s creative educational environment questionnaire, AMS academic motivation questionnaire and self-regulated learning strategies questionnaire MSLQ. To examine reliability of measures, Cronbach alpha coefficient and to determine validity factor analysis were used. The path diagram of hypothetical model was tested. Findings revealed the relationship between the models variables. So, teachers who want their students have a high intrinsic motivation in addition to create a conditions for free choice, should be confide the students, support ideas and give time to the idea, consider duties that are challengeable, teach debate, conflict and risk to their students and also with regard to the vitality, joy, dynamism and humor, create education environment for the development of their creativity. By creating such an environment, intrinsic motivation and using meta-cognitive self regulation becomes more. Implications and suggestions for future studies are discussed.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".