A Systematic Review of MRI Neuroimaging for Education Research
Why this work is in the frame
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Bibliographic record
Abstract
This study aims to disclose how the magnetic resonance imaging (MRI) neuroimaging approach has been applied in education studies, and what kind of learning themes has been investigated in the reviewed MRI neuroimaging research. Based on the keywords "brain or neuroimaging or neuroscience" and "MRI or diffusion tensor imaging (DTI) or white matter or gray matter or resting-state," a total of 25 papers were selected from the subject areas "Educational Psychology" and "Education and Educational Research" from the Web of Science and Scopus from 2000 to 2019. Content analysis showed that MRI neuroimaging and learning were studied under the following three major topics and nine subtopics: cognitive function (language, creativity, music, physical activity), science education (mathematical learning, biology learning, physics learning), and brain development (parenting, personality development). As for the type of MRI neuroimaging research, the most frequently used approaches were functional MRI, followed by structural MRI and DTI, although the choice of approach was often motivated by the specific research question. Research development trends show that the neural plasticity theme has become more prominent recently. This study concludes that in educational research, the MRI neuroimaging approach provides objective and empirical evidence to connect learning processes, outcomes, and brain mechanisms.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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