Profiling and need assessment of third year bachelor of nursing sciences adult learners at the University of Namibia, Main Campus
Bibliographic record
Abstract
There is an increase of adult learners in higher education which can be challenging during their study period as they have to balance their social responsibilities with academic activities. The purpose of this study was to explore and describe the profile and need assessment of third year Bachelor of nursing sciences adult learners at the University of Namibia, main campus. A quantitative, descriptive cross sectional study design was utilized during this study. Data was collected through self-administered online questionnaire among 29 participants. The study found that most participants are aged 21 years, single with no children. Furthermore, most participants reside in the informal settlement with nonconductive learning environment due to noise and are using public transport to reach the campus. Most participants indicated that they are receiving study loan from the Namibia Financial Assistance Fund while few got financial assistance from the family members. Some students indicated having disabilities and most students indicated that they have used online teaching and learning before the outbreak of COVID 19 in March 2020 that cause shift in education. The study serves as the baseline information on student profiling and serve as a basis for further strategies to address the situation or for further research.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".