An Overview of Teachers’ Development and Secondary School Effectiveness in Ekiti State, Nigeria
Bibliographic record
Abstract
The study examined teachers’ development and secondary school effectiveness in Ekiti State, Nigeria. The study sought to establish the relationship between teachers’ development training and secondary school effectiveness in Ekiti State. Descriptive research design of survey type was adopted in the study. The population of the study comprised all the teaching staff (teachers and principals) numbered 5,908 in public secondary schools in Ekiti State. The total number of public secondary schools in Ekiti State was 202. The sample of the study was made up of 240 teachers and 24 principals selected from 24 public secondary schools in each of the three senatorial districts in Ekiti State. Multistage sampling procedures which involved simple random sampling and stratified random sampling techniques were used to select sample of the study. The instruments tagged Teachers’ Development Training Questionnaire (TDTQ) and Secondary School Effectiveness Questionnaire (SSEQ) were used to collect data. The instruments were validated and found reliable with the reliability coefficient of 0.84 and 0.86 respectively. Descriptive statistics of frequency counts, percentages scores, mean and standard deviation were used to answer the research questions and Pearson’s Moment Correlation was used to test the hypothesis at 0.05 level of significance. The findings of the study revealed that there is a significant relationship between teachers’ development and secondary school effectiveness in Ekiti State. Based on the findings and conclusions of the study, it was recommended that regular and relevant teachers’ development programmes should be organized for secondary school teachers in order to ensure continuous quality education delivery and secondary school effectiveness.
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.
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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".