Enhancing the practice learning experiences of BME students: Strategies for practice education
Bibliographic record
Abstract
Practice learning, also known as field education or practicum is central to social work education not only in the UK, but also in countries such as the United States of America, Australia, New Zealand, Canada and South Africa. It presents students with opportunities to integrate academic learning and practice experience with people, their families, communities and environments, and enables the development and enhancement of key skills and social work values. In England, recent studies have highlighted the disparity between black students and white students in terms of progression and attainment on social work qualifying programmes, and practice placements are becoming notorious as sites of difficulty for many students from black and minority ethnic (BME) backgrounds. This paper focuses on a sub-group (black African students), an ethnic minority group with a unique set of characteristics which have been found to contribute to their specific experiences of practice education in the UK.This paper outlines some strategies which have been proposed by black African students as necessary and central to enhancing their practice learning experiences and outcomes on social work programmes. This article was developed from a paper presented to the International Conference on Practice Learning in Scotland (4-7 April 2014).
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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 | 0.009 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".