How Teacher Moderates the Relationship between Democratic Classroom Environment and Student Engagement
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it