Autistic children often face limited access to early intervention due to shortages of trained professionals, linguistic diversity, and inconsistent service availability. Digital learning tools offer scalable opportunities to address these challenges; however, many lack evidence-based instructional design and fail to sustain engagement for young learners. This project examined whether these gaps could be addressed through an AI-powered, gamified learning platform informed by the principles of applied behavior analysis (ABA), an evidence-based approach to autism intervention. The platform was designed to translate core ABA instructional processes into structured digital activities, including clear task sequences, prompting hierarchies, positive reinforcement, and planned opportunities for generalization. Artificial intelligence features included speech, pose, and eye-gaze detection with automated accuracy tracking, integrated to support adaptive feedback and autonomy. Gamified elements were designed to promote motivation and independent responding. Early feasibility was evaluated through clinician review, caregiver interviews, and a preliminary individual-use trial, focusing on engagement, clarity of task structure, usability, and early indicators of learning progress. Clinicians noted strong alignment between learning objectives and foundational developmental and communication skill areas. Caregivers reported high usability, while children demonstrated strong engagement with gamified and AI-supported activities. Identified challenges included variability in internet quality and the need for guided onboarding. Overall, early feasibility findings suggest that AI-powered, ABA-informed gamified learning tools may enhance accessibility and engagement for autistic children across diverse contexts, highlighting the potential of integrating technology and behavioral science to support early learning.

Anastasia Trofilova is a Board Certified Behavior Analyst (BCBA) and clinical lead working at the intersection of Applied Behavior Analysis (ABA), autism intervention, and AI-enabled learning technologies. She currently serves as Clinical Subject Matter Expert at Cognitivebotics Technologies, where she leads the clinical design of gamified digital learning tools for autistic children grounded in evidence-based instructional principles. She is currently pursuing a PhD in Behavior Analysis at Capella University and contributes to interdisciplinary projects integrating clinical science with digital innovation.