Running head: ReView ReView: A Digital Video Player to Support Music Practice and Learning
Bibliographic record
Abstract
Thanks to the emergence of digital video, producing and distributing video is now possible in ways that were previously limited to video production companies. Yet the functions of current digital media players differ little from the VCR’s play, rewind, fast-forward, and pause functions, which may not support learning tasks appropriately. Therefore, we designed an enhanced digital media player, ReView, to better support video-based learning. To test ReView’s usefulness, advanced music students in the Young Artists Programme of the National Arts Centre of Canada were given the opportunity to use the media player to review a video recorded lesson. In this paper, we present the students ’ ratings of the usefulness of ReView’s features, and the frequency with which the features were used. We discuss these findings with respect to technological support for browsing video content. Additionally, we present findings related to the content of the video that the students chose to watch. Specifically, we found that students prefer to watch themselves play rather than review instructions received from a coach.
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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 | 0.004 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.060 | 0.018 |
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".