Education for Practice in the UK and Ireland: Implementing Problem-Based Learning
Bibliographic record
Abstract
OBJECTIVE: This paper outlines the education of speech and language therapists in the UK and Ireland, and presents a preliminary study of student therapists' perceptions of problem-based learning (PBL) as a learning strategy in preparation for clinical work. PBL has been used extensively in medical and dental education in Europe, in Canada, and in the Middle East, and has been applied to speech and language therapist education in Sweden and in Australia. Its implementation in the UK and Ireland is relatively new. METHODS: A survey questionnaire was circulated to students in two centres via e-mail. Questions posed included student impressions of the most and least useful elements of PBL in their preparation for clinical practice, as well as how they considered improvements could be made; student reflections regarding PBL were also sought. RESULTS AND CONCLUSIONS: Findings support the implementation of PBL in the education of speech and language therapists, with more experienced students showing more positive support for PBL. Issues raised by the study include emphasis on clinical relevance of problems, particularly in the early years of the course. The majority of students regarded PBL as directly relevant for clinical preparation.
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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 | 0.010 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".