The Effects of Self-Observation When Combined With a Skilled Model on the Learning of Gymnastics Skills
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
In this experiment, we examined whether self-observation, via video replay, coupled with the viewing of a skilled model was better for motor skill learning than the use of self-observation alone. Twenty-one female gymnasts participated in a within design experiment in which two gymnastics skills were learned. One skill was practiced in conjunction with the self-observation/skilled model pairing and the other with only self-observation. The experiment unfolded over five sessions in which pre-test, baseline, acquisition, retention, and post-test scores were obtained. Analysis of the physical performance scores revealed a significant Condition ×Session interaction in which it was shown that there were no differences between the intervention conditions at baseline and early in acquisition; but, later in acquisition, those skills practiced with the self-observation/skilled model pairing were executed significantly better than those with only self-observation. Also, an error identification test showed that participants had significantly higher response sensitivity scores for those skills learned with the paired intervention compared to self-observation alone. These results suggest that pairing self-observation with a skilled model is better in a gymnastic setting than self-observation alone.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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