Trauma-Informed Education in Open Online Courses: Lessons from Teacher Continuous Professional Development During COVID-19
Bibliographic record
Abstract
This study evaluates the feasibility and impact of the Open Online Course (OOC) aimed at enhancing teachers’ trauma-informed care practices during the onset of the COVID-19 pandemic. Educators from two public primary schools in Queensland, Australia, completed the course. Twenty-six educators were interviewed about their experience of the OOC. Thematic analysis revealed the feasibility of the OOC was influenced by participants’ ability to navigate the digital divide and allocate time for learning. The impact of the OOC was reflected in reports of the adoption of trauma-sensitive classroom management techniques amongst participants. The findings highlight that sustaining OOC-based teacher education on trauma-informed practice requires long-term access, integration of trauma-informed strategies, and ongoing support for hyflex and blended learning models. Findings are mapped onto a trauma-informed education framework and inform recommendations for future OOC design and delivery in post-pandemic educational settings.
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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 | 0.008 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| 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".