Health and Nutrition Issues Affecting Academic Involvement of Adult Learners in Literacy Programmes of Kogi State, Nigeria
Bibliographic record
Abstract
OBJECTIVE: This study investigated health and nutrition issues affecting academic involvement of Adult learners in literacy programme in Kogi State, Nigeria. The specific purpose of the study was: to ascertain the extent health and nutrition affect academic involvement of adult learners in literacy programmes in Kogi State Nigeria. MATERIALS & METHOD: The design for the study was a descriptive survey design. A structured questionnaire was used to collect data which wereanalysed using mean scores and standard deviation while t-test statistic was used to test the hypothesis that guided the study. RESULTS: Results of the analysis showed among others health and nutrition issues such as chronic illness, poor nutrition and hunger affect academic involvement of adult learners. The results also showed that unhealthy adult learners do not feel happy in class during lessons or learning activities. CONCLUSION: Based on the finding, it was concluded that health and nutrition have some level of relationship with adult learners’ academic involvement to a high extent.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".