Impact-Based Training Evaluation Model (IBTEM) For School Supervisors in Indonesia
Bibliographic record
Abstract
This article represents a study aiming at developing: (1) an IBTEM which is capable to promote partnership between training providers and their client institutions, easy to understand, effective, efficient; and (2) an IBTEM implementation guide which is comprehensive, coherent, easy to understand, effective, and efficient. The method used in the study was Research and Development (R & D) suggested by D. Gall, P. Gall, and Borg (2007) that was simplified into three phases: pre-development, development, and validation phases. The pre-development phase was used to review related theories, interview resource persons, and collect relevant documents. The result of this phase was an IBTEM draft. The development phase was used to organize a focus group discussion (FGD) attended by participants from the Yogyakarta Education Quality Assurance Institute, Regional Offices of Education, school supervisors, principals, and teachers. The result of this phase was a revised IBTEM draft. The validation phase consisted of internal and external validations. The internal validation was done through a Delphi technique. The team in the Delphi involved experts in educational evaluation, educational management, and vocational education. The result of the internal validation phase was a theoretical IBTEM that was then validated externally. The external validation was conducted by carrying out limited field testing of the theoretical IBTEM involving three institutions: the Center for Development and Empowerment for Arts Teachers, Center for Development and Empowerment for Mathematics Teachers, and the Yogyakarta Education Quality Assurance Institute. The external validation phase resulted in a final IBTEM. The study results confirm that: (1) the developed IBTEM is capable to promote partnership between training providers and their client institutions, easy to understand, effective, and efficient; and (2) the developed IBTEM implementation guide which is comprehensive, coherent, easy to understand, effective, and efficient.
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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 | 0.017 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".