Learner-Controlled Self-Observation is Advantageous for Motor Skill Acquisition
Bibliographic record
Abstract
There were two main objectives of this research. First, we wanted to examine whether video feedback of the self (self-observation) was more effective for motor skill learning when the choice to view the video was provided to the learner (learner-controlled, LC) as opposed to an experimenter-controlled (EC) delivery. Secondly, we explored whether there were differences in the self-regulatory processes of self-efficacy and intrinsic motivation, as well as perceived choice between the LC and EC conditions. Two groups (LC and EC) of children (M age of 11.2 years; SD = 1.89) attempted to learn a progression of trampoline skills during a 2-day acquisition phase in which video self-observation was available. The second acquisition day was followed by a no self-observation retention test 1 day later. It was hypothesized that, during retention, the LC group would be more self-efficacious about their ability to progress through the trampoline skills, show greater intrinsic motivation and perceived choice, and go further in skill progression than the EC group. Analysis of the acquisition data showed the LC group had greater increases in self-efficacy as compared to the EC group. Results of the retention test showed that the participants in the LC group obtained higher scores on the intrinsic motivation and perceived choice measures and had higher skill progression scores as compared to the EC group. Regression analysis showed that group assignment and self-efficacy were significant predictors of the physical performance benefits noted in retention. These findings are discussed within Zimmerman's (2004) self-regulation of learning model.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.011 | 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 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".