Using wise interventions to motivate deliberate practice.
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
Deliberate practice leads to world-class excellence across domains. In the current investigation, we examined whether psychologically "wise" interventions targeting expectancies and values-stock antecedents of ordinary effortful behaviors-could motivate nonexperts to engage in deliberate practice and improve their achievement. As a preliminary, we developed and validated a novel task measure of deliberate practice and confirmed its association with (a) expectancy-value beliefs, and (b) achievement in the nonexpert setting (Study 1). Next, across 4 longitudinal, randomized-controlled, field experiments, we intervened. Among lower-achievers, wise deliberate practice interventions improved math performance for 5th and 6th graders (Study 2), end-of-semester grades for undergraduates (Study 3), and end-of-quarter grades for 6th graders (Study 4); the same pattern of results emerged in end-of-quarter grades for 7th graders (Study 5). Following the intervention, expectancy-value beliefs and deliberate practice improved for 1 month (Study 4), but not 4 (Study 5). Treatment proved beneficial over and above 2 control conditions: 1 that taught standard study skills (Studies 2 and 3), and 1 that discussed deep interests, generalized motivation, and high achievement (Studies 4 and 5). Collectively, these findings provide preliminary support for the heretofore untested hypothesis that deliberate practice submits to the same laws that govern typical forms of effortful behavior, and that wise interventions that tap into these laws can spur short-term gains in adaptive beliefs, deliberate practice, and objectively measured achievement. (PsycINFO Database Record
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 | 0.000 | 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) | 0.001 | 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