Uncovering Patterns in Training Skills with ABA: Rule Extraction from the SYSABA Database

This study applies a refined methodological framework to extract association rules from the System for Applied Behavior Analysis (SYSABA) dataset, representing years of therapeutic preferences, course of treatment, and experience in developing and utilizing Individual Education Programs (IPET) in Polish therapeutic centers for children with developmental disorders. These IPETs comprise various elements, including targeted skills, teaching techniques, and recording methods. This study aims to uncover how IPETs are constructed and utilized by therapists in training new skills. Though utilizing a well-established Apriori algorithm, the study’s novelty stems from its tailored approach to a unique dataset, revealing uncovers salient patterns within IPETs, such as a pronounced preference for the Discrete Trial Training (DTT) technique, bi-monthly incremental task learning assessments, and customized reinforcement. The comprehensive examination of IPET patterns in Poland offers pivotal insights to enhance therapeutic decision-making strategies. This research contributes significantly to ABA-based treatments by understanding these patterns, ensuring more informed interventions and better patient outcomes.