Effect of Organizational Structure on the Delivery of Quality Education in Public Technical and Vocational Education Institutions in Kenya
Bibliographic record
Abstract
The purpose of the study was to investigate the effect of organizational structure on the delivery of quality education in public technical and vocational education institutions in Kenya. The study adopted Survey research design while target population was 689 employees in the Ministry of Educations’ Directorate of Technical Education, National Polytechnics and Technical Institutions. Simple random, stratified and purposive l sampling techniques were used to select 11 managers in Directorate of Technical Education, 15 administrators from National Polytechnics and other technical institutions, and 220 instructors from technical institutions. Data was collected using structured questionnaires and interview schedules. Data was analyzed both quantitatively and qualitatively using the statistical package for social science (SPSS) version 17.0. Descriptive and inferential statistics and content and analyses were used for specific data. The analysis was further amplified by subjecting selected results to graphical and tabular techniques. The study established that the structure of the institutions was both inclusive and bureaucratic with a few being described as flexible. The management of the institutions was responsible for the implementation of the educational reforms. However, special groups were charged with responsibility of spearheading the change process. The organizational structure was directly linked with the quality of education as was demonstrated by the regression analysis. This relationship was however, not very strong. The study recommended that technical educational institutions should be structured to suite the particular reform process for effectiveness and achievement of desired results so as to enhance the quality of technical education.
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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 | 0.005 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".