Physiotherapy students’ perception of their clinical learning environment and clinician teaching attributes in Nigeria
Bibliographic record
Abstract
Background: Feedback from students regarding their clinical learning environment and clinicians teaching attributes should be evaluated regularly to monitor students' learning experiences which can affect learning outcomes, the readiness for professional practice, and the level of satisfaction with the profession. Differences may exist in this feedback from students based on their institution, level of study, and characteristics of the clinicians. Aim: To evaluate physiotherapy students’ perception of their clinical learning environment and clinicians’ teaching attributes. Methods: This cross-sectional study utilised 258 participants from two academic institutions, which offer physiotherapy training in southeast Nigeria. A self-structured questionnaire, the McGill Clinical Teacher Evaluation tool (MCGill CTE) and the Dundee Ready Educational Environment Measure (DREEM) were used to collect the data. Descriptive statistics of mean and standard deviation were used to present the mean scores obtained on the DREEM questionnaire and McGill CTE tool. The Mann-Whitney U test was used to determine the difference in the students’ perception of their clinical learning environment and clinicians' teaching attributes based on their institution of learning and level of study. In addition, the Mann-Whitney U test also determined the difference in the students' perception of their clinicians teaching attributes based on the clinicians' gender, while the Kruskal Wallis test determined the difference in the students' perception of their clinician's teaching attributes based on their last clinical posting unit and the highest educational level of the clinicians. Results: The students perceived their learning environment to be “more positive than negative”. The highest-rated domain in the DREEM questionnaire was "perception of learning", while the lowest was "social perception". The highest-rated attribute for clinicians in the McGill CTE tool was "clinical interest in helping students to learn", while the lowest was "emphasises concept rather than factual recall". A significant difference was observed in the students rating of their clinical learning environment based on their institution and level of study. Conclusion: There is a need for regular evaluation of students' perception of their clinicians’ teaching attributes and the clinical learning environment to ensure the desired learning outcomes are attained and that students are ready for professional practice after training.
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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 | 0.003 |
| 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) | 0.003 | 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".