Effective solutions for gait rehabilitation in children with cerebral palsy (CP) remain elusive. Wearable robotic exoskeletons offer the potential to greatly increase the dosage and intensity of gait training in this population, which may improve outcomes. We recently reported that a robotic exoskeleton significantly improved knee extension in children with crouch gait from CP. Longitudinal studies are necessary to fully understand long term biomechanical effects of exoskeleton gait training. Given that children's gait can change both as they develop and throughout their therapy, advanced control strategies which can adapt assistance over time may be beneficial. But, stride-to-stride variability makes it difficult to ascertain the effects of exoskeleton assistance and therefore complicates implementation of adaptable control algorithms. Here, we examine the use of the variance ratio (VR), a previously published measure, to assess the effect of exoskeleton assistance on knee extensor and flexor EMG variability in children with CP. Our results show that VR was significantly increased ($p<0.001)$ compared to baseline during walking with exoskeleton assistance. After five practice sessions, we found that VR was reduced though still greater than baseline levels. Given its sensitivity to exoskeleton assistance and ease of computation, VR may be a useful measure in the future for evaluating stride-to-stride variability in real time to inform algorithmic decision making for autonomous adaptable control.