Improvements in Middle-Schoolers’ Performance and Motivation to Practice: An Experimental Investigation of Accurate Feedback in a Motor Task
Bibliographic record
Abstract
The present field experiment investigated the effects of accurate and non-accurate performance feedback on causal attributions, success expectancy, performance, and persistence on a motor task. Forty-six male middle-schoolers were randomly assigned to a Contingent (accurate) feedback, Non-contingent (non-accurate) feedback, or Control (no feedback) group and completed a challenging motor task. An initial treatment phase provided either accurate contingent feedback or yoked non-contingent feedback during the task, and measured task performance, attributions about performance, and success expectancy about future performance. A subsequent testing phase (same task) used the same measures and added a measure of motivation (persistence). Compared to the Contingent and Control groups, Noncontingent outcome feedback during the initial treatment phase led to more personally uncontrollable attributions, lower success expectancy, poorer performance, and lower persistence in the subsequent test phase. Despite a high rate of failure in the motor task for both feedback groups in the treatment phase, the Contingent group—getting accurate feedback about performance—had a higher sense of personal control and expectancy of success than the Non-contingent feedback group initially, and maintained these perceptions in the subsequent test phase where they also had better performance and higher levels of persistence than the Non-contingent group. Non-contingent feedback in an initial motor task appears to induce helplessness deficits in subsequent task performance and persistence. In contrast, providing accurate (contingent) feedback about achieved performance appears to protect against performance and motivational losses.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".