Video Annotation as a Supporting Tool for Video-based Learning in Teacher Training – A Systematic Literature Review
Bibliographic record
Abstract
Digital video annotation tools, which allow users to add synchronized comments to video content, have gained significant attention in teacher education in recent years. However, there is no overview of the research on the use of annotations, their implementation in teacher training and their effect on the development of professional competencies as a result of using video annotations as a supporting tool for video-based learning. In order to fill this gap, this paper reports on the results of a systematic literature review which was carried out to determine 1) how video annotations were implemented in studies in educational settings, 2) which professional competencies were investigated to be further developed with the aid of video annotations in these studies, and 3) which learning outcomes were reported in the selected studies. A total of 18 eligible studies, published between 2014 and 2022, were identified via database search and cross-referencing. A qualitative content analysis of these studies showed that video annotations were generally used to perform one or more of three functions, these being feedback, communication, and documentation, while they also enabled a deeper content knowledge of teaching, reflective skills, and professional vision, and facilitated social integration and recognition. The convincing evidence of the positive effect of using video annotation as a supporting tool in video teacher training prove them to be a powerful tool supporting the development of professional vision and other teaching skills. The use of video annotation tools in educational settings points towards further research as well.
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How this classification was reachedexpand
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".