Individual differences in science competence among students are associated with ventrolateral prefrontal cortex activation
Bibliographic record
Abstract
Functional neuroimaging studies have revealed that, compared with novices, science experts show increased activation in dorsolateral and ventrolateral prefrontal brain areas associated with inhibitory control mechanisms when providing scientifically valid responses in tasks related to electricity and mechanics. However, no study thus far has explored the relationship between activation of the key brain regions involved in inhibitory control mechanisms, namely the ventrolateral prefrontal cortex (VLPC) and dorsolateral prefrontal cortex (DLPC), and individual differences in conceptual science competence, while controlling for scientific training. In the present study, 24 secondary school students (11 female participants, 13 male participants) were selected from a larger pool based on their performance on a conceptual science questionnaire and were divided into groups with low and high conceptual science competence. In an fMRI block design, participants had to verify the correctness (true or false) of congruent and incongruent statements. In congruent statements, both spontaneous and scientific conceptions about given natural phenomena lead to a scientifically appropriate judgment. However, in incongruent statements, commonly held spontaneous conceptions about natural phenomena lead to a scientifically inappropriate judgment. The interaction effect reveals that students with higher conceptual science competence display stronger activation of the left VLPC and DLPC in incongruent trials than in congruent trials. These findings show that activation of the VLPC and DLPC when reasoning in incongruent situations underlies individual differences in conceptual science competence, and suggests stronger recruitment of inhibitory control mechanisms in more competent individuals.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".