Perceptions of undergraduate allied health students of the clinical learning environment and clinical educators’ attributes at the University of Ghana
Bibliographic record
Abstract
Background. Clinical education is a vital aspect of the education of health sciences students and consists of two components, i.e. the clinical learning environment and supervision.Objectives. To determine the undergraduate allied health sciences students’ perceptions regarding clinical educators’ attributes and the clinical learning environment. Methods. This cross-sectional study included 169 undergraduate students, randomly recruited from various allied health professions programmes of the University of Ghana. The McGill clinical teacher evaluation tool and the clinical learning environment inventory were used to determine students’ perceptions of clinical educators’ attributes and the clinical learning environment, respectively. The Kruskal-Wallis test and independent t-tests were used to test for relationships between students’ level and programme of study and their perceptions. The level of significance was set at 95%. Results. Of the 169 participants, there were 99 (58.6%) male students, 79 (46.7%) third-year students and 82 (48.5%) medical laboratory science students. Only 16 (9.5%) participants indicated visits by lecturers during clinical rotations. The third-year students had a statistically significant perception of their clinical learning environment (p=0.000), while the differences between perceptions of clinical learning environment among the various programmes were also statistically significant (p=0.028), but not for clinical educators’ attributes (p=0.261). Conclusion. Allied health sciences students have positive perceptions of their clinical learning environment and clinical educators’ attributes. More frequent visits by lecturers to students during clinical rotations may ensure that student innovation is achieved in accordance with their classroom tuition.
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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 | 0.002 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".