How Teacher Moderates the Relationship between Democratic Classroom Environment and Student Engagement
Bibliographic record
Abstract
This study investigates the relationship between democratic classroom environment and student engagement and its three dimensions: cognitive engagement, emotional engagement and behavioral engagement. Previous research has extensively reported about the positive relationship between democratic classroom environment and student engagement. However, these studies have evaluated only the relationship between democratic classroom environment and student engagement neglecting the three dimensions. This study contributes to this gap by examining the three dimensions as well. Thus, the paper had two aims: First to investigate the relationship between democratic classroom and the three dimensions of classroom engagement: behavioral engagement, emotional engagement and cognitive engagement and second, to examine the moderating role of teacher between democratic classroom and student engagement. A survey questionnaire was utilized to collect data from secondary school teachers. Since the study was based on correlation method, therefore, regression analysis were conducted to test the hypotheses of the study and to analyze the relationship between the variables. The findings of the study showed that there is a strong positive correlation between democratic classroom environment and student engagement and its three dimensions: behavioral, emotional and cognitive. The study also discovered that teacher moderates the relationship between democratic classroom environment and student engagement. On the basis of the results, the paper concludes that teacher plays an important role in the behavioral, emotional and cognitive engagement of students in the teaching and learning process.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".