The Relationship between Teachers’ Factors and Effective Teaching
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 aims to examine the relationship between three teachers’ factors that’s teaching experiences, type ofschool performing and attendance of professional development course towards effective teaching amongsecondary school teachers in Johor, Malaysia. A total of 322 secondary school teachers from Malaysia involvedin this study. The instrument used in this study was a set of questionnaire which combined Charlotte Danielson(2007) and James H Stronge (2007) models. This quantitative study utilized survey method with stratifiedrandom sampling. Teachers’ factors were tested through correlation and multiple regression analysis. Thefinding indicate that there are significant positive correlation between three teachers factors (teachingexperiences, type of school performing and attendance of professional development course) towards secondaryschool teachers’ effective teaching. Highest relationship towards effective teaching is attendance of professionaldevelopment course (r=.676, p< .05), following by teaching experience (r=.621, p< .05) and type of schoolperforming shows least relationship (r=.193, p< .05). Besides, the regression model indicates a predictivesignificance by teachers’ factors towards effective teaching. Hence, the findings support the conclusion that theselected factors are predictors of secondary school teachers’ effective teaching. This study revealed theimportances of professional development course and teaching experience compare with type of schoolperforming. Teacher needs to always continue upgrade ourselves for practising teaching effectively. Thesefindings also have implications for secondary school teachers and administrators to reflect and broaden the viewstowards effective teaching.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.006 | 0.002 |
| 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