Integrating relational knowing and structured learning in social work placements – a framework for learning in practice
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Professional placements are integral to social work education and provide formative but variable learning opportunities for students. As social work programs expand and requirements for placements increase, settings where a social worker may not be employed are increasingly utilized, risking further variability of student experience. This paper reports on qualitative responses to two open-ended questions in a cross-sectional survey conducted with social work students from four universities on the island of Ireland. Questions included (1) what students found most helpful in assisting their learning, and (2) what would have improved their learning during placement. A six-step approach to thematic analysis was used to analyse qualitative data from 427 responses to question one, and 355 responses to question two. Four key pillars of practice learning were identified: enabling relationship(s); ‘real world’ practice opportunities; structured teaching and learning; and academic-practice alignment. Drawing on these findings, the paper presents a framework for integrated learning which promotes students’ capacity for active inquiry in practice. Linked processes of relational knowing and structured teaching and learning emerged as integral to knowledge acquisition and professional development on placement. Findings re-established the significance of the supervisory relationship and relationship-based learning.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.004 |
| Science and technology studies | 0.009 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it