Competency Needs of Business Educators in Osun State Secondary Schools, Nigeria
Bibliographic record
Abstract
Competency is one of the essential elements in teaching. It also determines the effectiveness of teachers during the teaching and learning process and performance of students. The study therefore investigated the competency needs of business educators in Osun State with a view to know those competencies that are needed but not possessed. Descriptive research design of survey type was adopted for the study. The population was 613 business educators out of which 300 was sampled using simple and stratified random sampling techniques. A self-design 20-item questionnaire titled “Teachers’ Competency Assessment Questionnaire (TCAQ)” was used to collect data for the study. The instrument was constructed on 4-point scale. The instrument was validated by two experts. The reliability of the instrument was established using Cronbach alpha and this yielded reliability co-efficient of 0.78. The research questions raised were answered using the means scores. Any item with a mean score greater than or equal to 2.50 suggests moderate possession, item with mean score ranging from 1.50 to 2.49 suggests fairly possession while item with mean score of 1.49 or below suggests not possession. Findings of the study revealed that out four competencies assessed, two were moderately possessed (planning of instruction and classroom instruction skills) one was fairly possessed (practical demonstration skills) while the remaining one was not possessed (ICT skills). It was recommended among others that government and relevant agencies need to organize series of training for business educators to acquire the needed 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 | 0.002 |
| 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 | 0.001 |
| 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".