Supervision Model Through Coaching and Mentoring for Enhancing Active Learning Instruction Competency of Elementary Teachers Under Office of the Basic Education Commission
Bibliographic record
Abstract
The study aimed to 1. investigate the components and indicators of active learning instruction competency among elementary school teachers, 2. examine the current state, desired state, and necessary requirements of active learning instruction competency among elementary school teachers, and 3. develop an educational supervision model based on instructional coaching and mentoring principles, aimed at enhancing active learning instruction competency among elementary school teachers under the jurisdiction of the Office of the Basic Education Commission. The study was divided into three phases: Phase 1 examine the components and indicators of active learning instruction competency. The target group comprised 7 qualified individuals selected through purposive sampling, with suitability assessed using an appropriateness assessment questionnaire. Phase 2 the current state, desired state, and necessary requirements of active learning instruction competency among elementary school teachers are investigated. The sample group consisted of 384 elementary school teachers selected through multi-stage random sampling, employing a proportional stratified sampling technique. A questionnaire with a 5-point Likert scale was utilized for data collection. Phase 3 the development of the supervision model involved input from a group of 9 qualified individuals selected through purposive sampling. These individuals were chosen based on their expertise and relevance to the research objectives. Research tools included interviews and assessments. The research findings revealed that: 1. there were 4 components and 24 indicators of active learning instruction competency among elementary school teachers. These components are categorized as follows: 1) Designing of active learning management: comprising 6 indicators, 2) Organization of learning activities focusing on higher-order thinking skills and practical application: consisting of 4 indicators, 3) Utilization of educational media, innovations, educational technology, and learning resources: encompassing 6 indicators, and 4) Measurement and evaluation based on actual conditions: including 8 indicators. Overall, the competency level is rated as the highest. 2. The current state was rated as moderate, while the desired state was rated as the highest. Upon disaggregating the components of the supervision model, it was found that the component with the highest level of necessity was Component 2, which pertains to organizing learning activities emphasizing higher-order thinking skills and practical application. 3. The results of developing the educational supervision model based on instructional coaching and mentoring principles to enhance active learning management competency among elementary school teachers, under the jurisdiction of the Office of the Basic Education Commission, revealed that the supervision model consisted of the following steps: 1) Planning, 2) Observation, 3) Reflection, and 4) Evaluation. These steps were deemed highly appropriate and feasible at the highest level.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".