This study explores the role of generative AI (GenAI) in providing formative feedback in children's digital learning experiences, specifically in the context of mathematics education. Using multimodal data, the research compares AI-generated feedback with feedback from human instructors, focusing on its impact on children's learning outcomes. Children engaged with a digital body-scale number line to learn addition and subtraction of positive and negative integers through embodied interaction. The study followed a between-group design, with one group receiving feedback from a human instructor and the other from GenAI. Eye-tracking data and system logs were used to evaluate student's information processing behaviour and cognitive load. The results revealed that while task-based performance did not differ significantly between conditions, the GenAI feedback condition demonstrated lower cognitive load and students show different visual information processing strategies among the two conditions. The findings provide empirical support for the potential of GenAI to complement traditional teaching by providing structured and adaptive feedback that supports efficient learning. The study underscores the importance of hybrid intelligence approaches that integrate human and AI feedback to enhance learning through synergistic feedback. This research offers valuable insights for educators, developers and researchers aiming to design hybrid AI-human educational environments that promote effective learning outcomes.