Do Thinking Styles Change With Task Complexity in Problem-Solving?
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Bibliographic record
Abstract
In this study, we analyzed the differences in the three types of thinking styles (i.e., analytical thinking, dichotomous thinking, and metacognitive thinking) between tasks of varying complexity.The participants consisted of 31 medical students who were asked to think aloud while diagnosing two virtual patients in an intelligent tutoring system.We applied text mining on the participants' think-aloud transcripts to extract the metrics of analytical thinking and dichotomous thinking.We manually coded monitoring and self-reflection activities from the think-aloud transcripts as indicators of metacognitive thinking.The results showed no significant differences in participants' analytical and dichotomous thinking between a difficult and an easy task.However, participants demonstrated a significantly higher level of metacognitive thinking in a difficult task than in an easy task.
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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 | 0.000 | 0.001 |
| 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) | 0.000 | 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