Development of student self-efficacy in innovative fieldwork placements: A qualitative study
Bibliographic record
Abstract
Introduction: Self-efficacy plays an integral role in the development of occupational therapy students' clinical competency during fieldwork education. However, there is still a lack of knowledge surrounding this topic within the context of non-traditional fieldwork education. This study aims to investigate and make meaning of the experiences of occupational therapy students' and their perceived development of self-efficacy in non-traditional fieldwork placements, known as LEAP placements. Method: This qualitative phenomenology study, through a descriptive lens, explored sixteen occupational therapy students' experiences using thematic analysis. Findings: Self-efficacy during LEAP placements was shaped by several factors: a lack of role clarity detracted from development, while the opportunity for self-direction enhanced it. The level of support, preceptor role and availability, perceived value of the learning experience, and placement environment both enhanced and detracted from self-efficacy development. Conclusion: This study provides an increased understanding of self-efficacy development among occupational therapy students and innovative practices within LEAP placements. Students' perceptions of self-efficacy development is shaped by complex and nuanced factors.
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.
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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".