Increasing In-Service Teachers’ Willingness to be Videoed to Support Professional Learning
Bibliographic record
Abstract
Increasing and compelling research demonstrates the affordances of personal video footage as an informative and transformational tool in teacher professional learning (PL), yet many in-service teachers avoid engaging in this practice. This Australian Research Council funded study tracked teacher willingness to use video to capture the application of PL over 12 months in a rural Australian primary school. Data from questionnaires, video-based learning conversations, and collaborative sharing sessions demonstrated a strong increasing trend in the number of teachers volunteering to be videoed across three iterations of research. Thematic analysis highlighted five key factors as catalysts for increased teacher participation in engaging with video as a professional learning (PL) tool. These factors include – safe relationships and the building of relational trust; personalized connection of PL to classroom practice; an effective video annotation repository system; teacher agency within an iterative structure; and time – the need for external support systems. This study found that when these factors were addressed, willingness to engage in using the power of video as a tool to support teacher PL increased.
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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 | 0.002 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".