Improvement of Teacher Competence in Special Schools for Deaf and Intellectually Disabled Children to Enhance the Quality of Inclusive Education
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 research aims to analyze the human resource management (HRM) strategy at Fadhilah Special School for children with hearing impairment and intellectual disabilities in an effort to improve the quality of inclusive education. Fadhilah Special School serves 17 special needs students consisting of 8 hearing-impaired students and 9 intellectually disabled students, but it only has 5 educators, some of whom do not yet possess special competencies or certification in Special Education (PLB). This research employs a descriptive qualitative approach with a case study method and data collection techniques through interviews, observations, and documentation. The findings indicate that HRM still faces several challenges, such as: a lack of professional teachers, irregular training, an evaluation system that is not yet based on measurable performance indicators, and limitations in learning support facilities. Nevertheless, there is an initiative from the school principal to improve the work climate and internal communication. The main focus of this research is to formulate a systematic human resource management strategy, starting from recruitment, training, mentoring, to evaluation, as a foundation for enhancing the quality of inclusive education. This research is expected to provide theoretical and practical contributions to strengthening human resource management in special needs schools that have similar characteristics
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 | 0.001 | 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 | 0.000 | 0.001 |
| 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