For those with attention deficit hyperactivity disorder (ADHD), social interactions involving high levels of face-to-face interaction can raise stress levels and emotional dysregulation. Using animated avatar video models may mitigate potential emotional dysregulation while learning social skills in these populations. This study examined autonomic data of adolescents aged 7-13 diagnosed with attention deficit hyperactivity disorder (ADHD), n=5 during avatar animated video modeling (AAVM) of social and emotional skills. This was a replication study with the addition of biofeedback data collection and a change of population. Participants were given three Nearpod training modules with AAVM and multiple-choice quizzes on self-awareness, social awareness, and relationship skills. Using a multiple baseline design, we collected Social Emotional Learning (SEL) scores at baseline, and during each phase of intervention. During all phases, we collected heart rate and analyzed heart rate variability (HRV) metrics: standard deviation of N-N intervals (SDNN), high frequency (HF), low frequency (LF), and HF/LF ratio). We also collected real-time somatic data: muscle tension (EMG), skin conductance (SC), and skin temperature (temp). The somatic autonomic data were not analyzed as part of this thesis. Results suggest that persons with ADHD may benefit from avatar animated video modeling delivered instruction based on patterns in autonomic data, increases in scores on the targeted skills taught during instruction, and participant's expressions about this method of learning. In future research and practice the population for this content could be narrowed to age 8-12. Reliable but smaller and less obtrusive biofeedback devices are currently available, and having several accessible options is recommended.