Unexpected improvement, decline, and stasis: A prediction confidence perspective on achievement success and failure.
Bibliographic record
Abstract
The authors hypothesized that reactions to performance feedback depend on whether one's lay theory of intelligence is supported or violated. In Study 1, following improvement feedback, all participants generally exhibited positive affect, but entity theorists (who believe that intelligence is fixed) displayed more anxiety and more effort to restore prediction confidence than did incremental theorists (who believe that intelligence is malleable). Similarly, when performance declined, entity theorists displayed more anxiety and compensatory effort than incremental theorists. However, when performance remained rigidly static despite a learning opportunity, incremental theorists evinced more anxiety and compensatory effort than entity theorists. In Study 2, this pattern was replicated when the entity and incremental theories were experimentally manipulated. Study 3 demonstrated that for both groups, theory violation impairs subsequent task performance. Taken together, these studies provide evidence that lay theory violation and damaged prediction confidence have significant and measurable effects on emotion and motivation. The authors discuss the implications of these findings for the literature on achievement success and failure.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".