Time Management Skills and Administrative Effectiveness of Principals in Nigerian Secondary Schools
Bibliographic record
Abstract
The study examined time management skills and administrative effectiveness of principals in Nigerian secondary schools. The descriptive survey design was used for the study. The population consisted of all the principals and teachers of secondary schools in Ondo, Ekiti and Osun states. The sample comprised of 200 principals and 600 teachers randomly selected from the three states. The data collected were analysed using frequency counts, simple percentage, mean and standard deviations. The study revealed that the time management skills as well as the level of administrative effectiveness of the principals were encouraging. However, the study revealed the factors that constitute impediments to the time management skills of the principals. These include the need to respond to emergency cases in the school, the need to respond to urgent calls from the ministry of education among others. The study further revealed the strategies that can be put in place for better time management among the principals. These include the need for the principals to identify their most consuming tasks and determine whether or not they have investing their time in the most important activities, and keeping a readily accessible record of their appointment and tasks among others. Based on the findings, it was recommended that the tempo of time management skills of the principals as well as their administrative effectiveness should be sustained while efforts should be directed towards avoiding those factors that constitute impediments to their time management skills.
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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 | 0.001 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".