Neuroscience, Education and Cognitive Function

This study introduces a neural measure called neural alignment to predict learning outcomes by comparing students' brain activity to experts and peers in a computer science course.

This study shows brain-to-brain coupling during instruction correlates with learning outcomes and is influenced by scaffolding behaviors, not explanation approaches, and machine learning better decodes instructional methods from coupling data.

The paper examines brain function during physics problem solving in students, linking conceptual approaches to neural mechanisms and success in science reasoning.