Effect of Information Load and Time on Observational Learning
Bibliographic record
Abstract
We examined whether altering the amount of and moment when visual information is presented affected observational learning for participants practicing a bowling skill. On Day 1, four groups practiced a cricket bowling action. Three groups viewed a full-body point-light model, the model's bowling arm, or between-limb coordination of the model's left and right wrists only. Following retention tests on Day 2, all participants practiced after viewing a full-body display. Retention was again tested on Day 3. Bowling accuracy improved in all four practice groups. Kinematics of the bowling arm became more like the model for the full-body and intralimb groups only. All groups improved on measures of interlimb coordination. Visual search data indicated that participants mainly focused their gaze on the model's bowling arm. These data lead to the suggestion that viewing "end-effector" information (i.e., information pertaining to the bowling arm) is an important perceptual constraint early in observational learning. Implicit manipulations designed to increase attention to other sources of information did not facilitate the learning process.
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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 | 0.001 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".