Single Subject

Single-subject design research focuses on understanding individual responses to interventions, offering detailed insights not always captured by group-level studies. Current research emphasizes optimizing experimental designs, particularly in adaptive experiments, using techniques like contextual bandit algorithms to balance efficient data collection with minimizing experimental regret. This approach is being applied across diverse fields, from evaluating educational interventions and biomedical treatments to analyzing user interactions with AI systems, facilitated by the development of ontologies for better organization and analysis of single-subject data. The resulting improvements in experimental design and data analysis promise more efficient and impactful research across various scientific disciplines.