Exploring the adaptability of TeachABI as an online professional development module for high school educators
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
Educators often lack the knowledge and resources to assist students with acquired brain injury (ABI). Teach-ABI, an education module, was created to help elementary school teachers support students with ABI in classrooms. This study examined the adaptability of Teach-ABI for high school educators. A qualitative descriptive study explored high school educators' (n = 9) experiences reviewing Teach-ABI and its adaptability for high school through semi-structured interviews. The interview guide was informed by implementation and adaptation frameworks. Transcripts were examined using directed content analysis. Teachers felt Teach-ABI was a good foundation for creating a high school-based education module. Adaptations were highlighted, such as streamlining content (e.g., mental health) and strategies (e.g., supporting test taking), to better meet educator needs. Using implementation science and adaptation frameworks provided a structured approach to explore the adaptive elements of Teach-ABI. The module was perceived as a suitable platform for teaching high school educators about ABI. Teach-ABI is an innovative, user informed education module, providing a multi-modal (e.g., case study, videos) and replicable approach to learning about ABI. Applying frameworks from different fields provides concepts to consider when tailoring resources to align with educator needs (e.g., grade, class environment) and facilitate innovation uptake.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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