Neuroeducation, Classroom Interventions and Reading Comprehension: A Systematic Review of the 2010-2022 Literature
Bibliographic record
Abstract
Reading comprehension is the cornerstone of human development, and consequently a fundamental and indispensable tool for communication and social interaction. In recent years, the field of reading comprehension research has been tightly connected with educational neuroscience, which has produced a growing number of interventions aimed at turning theoretical ideas of neuroeducation into practical efforts applicable to the classroom. The aim of the present systematic review was to analyze the state of neuroeducational research, to identify the main characteristics of the interventions developed, and to propose suggestions on the main findings that contribute to neuroeducation research on reading comprehension. Based on the guidelines of the PRISMA method, an exhaustive search was carried out in high impact databases. The selection process yielded 13 eligible studies and they were analyzed in terms of, for instance, theoretical focus, context and participants, and main findings. Results show that these studies most frequently addressed the emotional principle of self-regulation, the importance of the social principle of neuroeducation and its impact on the development of reading comprehension skills through activity breaks, holistic environment and physical exercise, and sensory cognitive development of attention and memory skills. Despite the homogeneity of the interventions presented in these studies, they showed significant effects on reading development, displaying higher research development concerning emotional and social aspects. The present study discusses the contributions of neuroeducational classroom interventions towards the development of reading comprehension skills, offering practical recommendations for teachers.
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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 | 0.006 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".