Neural signatures of STEM learning and interest in youth.

Understanding the neural mechanisms underlying interest in Science, Technology, Engineering, and Mathematics (STEM) and learning is crucial for fostering creativity and problem-solving skills, key drivers of technological and educational growth. Traditional methods of assessing STEM interest are often limited by cultural and human biases, highlighting the need for more objective approaches. This study utilizes Electroencephalography (EEG) to identify neural markers linked to STEM interest and course-specific cognitive demands in young learners enrolled in a specialized private STEM program, including courses such as 3D Design, Programming, and Robotics. Specifically, Power Spectral Density (PSD) and Functional Connectivity (FC) were analyzed within theta, alpha, and beta frequency bands, which are associated with performance monitoring, creativity, and executive functioning. The findings reveal a significant negative correlation between STEM interest and brain activity in the frontal (F3, F4) and prefrontal regions (FP1, FP2) in the theta (r = -0.44, p = 0.2732; r = -0.77, p = 0.0268; r = -0.84, p = 0.0096; r = -0.62, p = 0.0990) and beta bands (r = 0.43, p = 0.2843; r = -0.56, p = 0.1524; r = -0.83, p = 0.0110; r = -0.75, p = 0.0328), indicating engagement in working memory and executive processing. Additionally, course-specific brain activity patterns reveal that Robotics is characterized by denser long-range FC networks, associated with problem-solving, while 3D Design exhibits more sparse yet efficient networks, indicative of creative ideation. A consistent beta band FC pattern between central and left-frontal areas reflects cognitive synchronicity and lateralization. These findings contribute to understanding the neurocognitive markers involved in STEM interest and learning, offering a framework for assessing and fostering engagement in STEM education through objective, neuroscience-based approaches.