Training Insight Problem Solving Through Focus on Barriers and Assumptions
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
ABSTRACT Recent research has reported successful training interventions that improve insight problem solving. In some ways this is surprising, because the processes involved in insight solutions are often assumed to be unconscious, whereas the training interventions focus on conscious cognitive strategies. We propose one mechanism that may help to explain this apparent disconnect. Recognition of a barrier to progress during insight problem solving may provide a point of access to the tacit constraining assumptions that have misled the solution process. We tested this proposal in an experiment that examined the effects of different training routines on problem solving. The experiment compared four training routines, focusing either on barriers and assumptions combined, barriers alone, assumptions alone, or goals, with two control conditions. Outcomes were measured using eleven spatial insight problems. The results indicated that training that combined focus on barriers and assumptions was significantly more effective than all other conditions, supporting the proposition that recognizing and reinterpreting barriers may assist in surfacing the unwarranted assumptions that prevent problem solving.
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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 | 0.001 | 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