The role of stakeholders in building adequate competences in students for the job market
Bibliographic record
Abstract
Competency is the acquisition of appropriate knowledge, attitudes, personality traits and skills to efficiently perform work place roles in industry, commerce, management and administration. Job competency is so important that employers always seek for people with such qualities before they are employed. It is therefore incumbent on educational institutions to train graduates to acquire the needed knowledge and skills to make them fit for the job market. This paper looks at the role of stakeholders in building adequate competences in students for the job market. The paper focuses on four (4) key stakeholders namely; government, industries, academic institutions and teachers to provide the desired knowledge, skills and attitude in students. It outlines the role of these stakeholders in providing the desired competences to students, highlights their challenges and suggests strategies to overcome these challenges. Reference was also made to the training programme of Saskatchewan Institute of Applied Science and Technology, Canada; which if properly adopted could help in building the needed competences in students. The article was concluded with some suggested recommendations. Key words: Competency based training, stakeholders, practical skills, competency, job market and technology.
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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 | 0.018 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".