School Location and Academic Achievement of Secondary School in Ekiti State, Nigeria
Bibliographic record
Abstract
The study looked at the location of schools as it relates to academic performance of students in Ekiti state of Nigeria between 1990 and 1997. The study population was results of the West African School Certificate Examinations (WASCE) conducted between 1990 and 1997 in 50 secondary schools in both rural and urban areas of the state. One validated instrument “Student Location Questionnaire (SLQ)” was used for data collection. One hypothesis was formulated and answered. Data were analysed using mean and t – test. The results showed that there was a significant differences between students’ academic achievement of rural and urban secondary schools in senior school certificate examinations (t=2.73, p<0.05). The study has proven that students in urban areas had better academic achievement than their rural counterpart. It is recommended that Government should bridge the gap between the rural and urban locations by providing the rural dwellers the social amenities which will enhance better academic performance of students in their final examinations like the SSCE. The community should assist the government by providing taxis and buses to facilitate movement of teachers and students to their school. Adequate incentives should be provided to rural area teachers to encourage them to put in their best to remain in their duty stations.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".