Brief Growth Mindset and Mindfulness Inductions to Facilitate Task Persistence After Negative Feedback
Why this work is in the frame
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Bibliographic record
Abstract
Negative feedback in academic settings is often unavoidable, although it may directly interfere with the ultimate goal of education, as setbacks can diminish motivation, and may even lead to dropping out of school. Previous research suggests that certain predispositions, inductions, and interventions might mitigate the harmful effects of negative feedback. Among others, growth mindset beliefs and mindfulness meditation were proposed as the most promising candidates that may help students to retain motivation. In a pre-registered, randomized experiment, we gave a disappointing evaluation to 383 university students in a bogus laboratory IQ test situation. Half of the participants previously received a growth mindset induction referring to intelligence as a malleable characteristic, while the other half received a fixed mindset induction referring to intelligence as a stable characteristic that cannot be changed. Then participants had a brief mindfulness meditation session or a control condition. Subsequently, they could choose to complete practice tasks before the final IQ assessment. The number of completed optional tasks was used as a behavioral proxy for task persistence. The results showed no difference in task persistence for the growth mindset or the mindfulness induction groups, compared to the other conditions. However, those who reported having higher pre-induction growth mindset beliefs or dispositional mindfulness completed more optional tasks after the mindset or mindfulness induction, respectively. We concluded that our brief inductions may not be adequate for everyone to rectify the demotivating effects of negative feedback, but can enhance task persistence for people with a stronger disposition towards a growth mindset or mindfulness.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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 | 0.003 |
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