“Its not a book; it’s a Bok”: social work students’ experience of using creative journaling practices as a pedagogical tool to develop transformative learning during the COVID-19 pandemic
Bibliographic record
Abstract
This paper reports on an international research project designed to explore the relevance and impact of creative journaling as a pedagogical tool during the COVID-19 pandemic. The project involved seven social work and social policy educators from eight countries: namely, Canada, India, Israel, Jersey Island, Spain, Sweden, the United Kingdom, and United States of America. Our work comes out of a larger mixed-method project that aimed to understand how creative journaling may help to facilitate transformative learning experiences and professional socialization processes of social work students. The data used for this article explicitly interpret conversations from two transnational focus groups, comprising 15 students from six participating countries (Canada, Spain, Jersey, India, UK, United States of America) in 2020–2021. Five significant themes emerged: Remote Learning during COVID-19, Self-care during COVID-19, Learning through the use of the Bok, Personal and Professional Identities, and Pathways toward Transformative learning. The findings revealed that creative journaling practices were important components of students’ professional development processes. Our intention with this paper is to contribute conceptual and practical insights into the implementation and impact of creative journaling practices.
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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 | 0.012 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.015 |
| Scholarly communication | 0.013 | 0.006 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 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".