Abstract: Students have incredibly different ways of learning, thinking, and processing information today. Traditional pedagogies that may be grounded in age, or contextually within curriculum, or course outline, are often inadequate to address the realities that many learners are faced with—especially children and youth struggling with educational learning challenges associated with disabilities such as dyslexia, ADHD, or in some cases conditions associated with auditory processing. The research introduced NeuroAI, an AI-supported personalized learning tutor designed to help support learners and students with a large variety of learning challenges. NeuroAI combines machine learning capabilities with brain-based education and learning strategies to help engage in lessons specifically for each child's pace, style, and understanding. NeuroAI relies on and integrates natural language processing, affective computing, and real-time analytics of performance data to allow for learning to become a closed loop relationship, ongoing feedback loops that occur between the learner's inputs to the instructional outputs. The affective computing capabilities of NeuroAI will, when a learner has engaged and input data into the system, identify engagement indicators for it to take into consideration, such as time to respond, error trending, and emotional cues, to help define the types and amount of content complexity, and how it is content is presented, and when to reinforce the information.The system will provide a hybrid recommendation engine to determine the most effective pathway to learning but will still offer options for students that encounter learning challenges due to conditions such as dyslexia, ADHD, or auditory processing. The findings highlight that NeuroAI provides not only the customized developed academic content but also an inclusive environment that allows learners with different neurological profiles to thrive. The research identifies a scalable opportunity based on credible research that connects cognitive science and education technology with an impact in schools for educators, developers and policy makers investigating equitable, impactful AI solutions in education. Keywords: NeuroAI, Personalized Learning, Adaptive Tutoring, Neurodiverse Learners, Affective Computing, Educational Technology, Explainable AI
Satyashree et al. (Tue,) studied this question.