Impact of COVID-19 on social work field education: Perspectives of Canadian social work students
Bibliographic record
Abstract
Summary: Social work field education has experienced major disruptions due to the COVID-19 pandemic, while also embracing new opportunities to grow. The Transforming the Field Education Landscape research partnership developed a cross-sectional web-based survey with closed- and open-ended questions to understand student perceptions of COVID-19's impacts on social work field education. The survey opened during the first wave of the pandemic from July 8 to 29, 2020 and was completed by 367 Bachelor of Social Work (BSW) and Master of Social Work (MSW) students across Canada. Quantitative and qualitative data were analyzed using descriptive statistics and thematic analysis. Findings: Respondents experienced reduced practicum hours and placements terminating early or moving online. Students were concerned about gaining adequate experience for future job prospects. They were generally positive about academic institutional responses to COVID-19 but described financial challenges with tuition costs and a lack of paid practica. Respondents were mostly satisfied with practicum supervision. They experienced negative impacts of COVID-19 on mental health with isolation and remote learning and described a lack of institutional mental health support. Students were concerned with missing direct practice skills, while some students reported more flexible hours, access to online events beyond their region, and increased research experience. They expressed a need for practicum flexibility and accommodation. Applications: Recommendations include an increase in flexibility and accommodations for practicum students, exchanges of promising and wise field education practices, and accessible postsecondary mental health supports. Professional development opportunities should support graduates who missed learning opportunities in their practicum.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.029 | 0.006 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".