Strategies for Facilitating Athletic Training Clinical Instruction
Bibliographic record
Abstract
Purpose: Athletic training education programs ensure the training of clinical instructors through annual workshops designed to familiarize them with athletic training clinical standards and guidelines. An opportunity exists for these workshops to enhance education related to instructional strategies and development. Unfortunately, many clinical instructors lack sufficient time to attend workshops and classes. This research integrates on-line discussion boards as a supplemental tool with in-class workshop sessions. The purpose of this study was to investigate the interaction of clinical instructors through on-line discussion boards. Methods: This research component, in conjunction with a larger project incorporating an in-class clinical instructor workshop, utilized on-line discussion boards to present a unique method of data collection. Qualitative methods from this research included gathering discussion board transcripts from a group of clinical instructors enrolled in an on-line WebCT course. Results: Data collected from the discussion boards identified themes that developed from the content analysis. Themes revealed through the transcripts of each discussion board linked issues presented in the in-class sessions. In addition, these discussion boards provided supplemental interactions supporting the need for increased interactions between clinical instructors. Conclusions: Additional time outside of the clinical setting allows the clinical instructors to interact with a variety of topics including their personal experiences with athletic training students, insight into these experiences, and instructional strategies used with these students. These on-line discussions created a supplemental time for these clinical instructors to communicate their ideas after attending the in-class sessions.
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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 | 0.007 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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".