Institutional Variables and Student’s Employability Skills Development in Public Universities in Cross River and Akwa Ibom States, Nigeria
Bibliographic record
Abstract
This study addresses institutional variables as determinants of employability skills acquisition among undergraduates in Cross River and Akwa Ibom States, Nigeria. Three research hypotheses were posed to guide the study. A descriptive survey research design was employed for the study. The population comprised of final year students in Faculty of Education at the University of Calabar numbered 904 and University of Uyo 939 respectively. Stratified random sampling technique was used to select data and a sample of 108 was drawn from University of Calabar and 112 drawn from the University of Uyo. A self-structured rating scale titled “Students’ Employability Skills Acquisition Scale (SEASAS). Face and content validity of the instrument was done by supervisor and experts, Cronbach alpha reliability coefficient range were .73-.92. Hypotheses were analyzed using t-test (population and independent t-tests) and one-way analysis of variances (ANOVA), hypotheses were tested at 0.05 level of significance. The result of the study revealed among others: institutional variables on the levels of employability skills after their years in various programmes were not significantly low. Based on the findings, it was however recommended among others that; employability skills studies should be embedded in the university curriculum, university authority should make programmes of study more elaborate and rich in content to equip students with skills. Academic programmes in the universities irrespective of the school-age and terms of conditions should also be given basic priorities.
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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 | 0.000 |
| 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".