Investigating young children's algorithmic thinking in robot programming activities from embodied cognition perspective

Educational robots have been increasingly used in early childhood settings to introduce young children to programming and computational thinking (CT). However, less is known about how algorithmic thinking (AT), a core CT skill, develops through children’s embodied interaction with such tangible tools. Using multimodal analysis on approximately 30 hours of video recordings of task-based interviews with five pairs of 5-6-year-old children, this study examines how their bodily actions and interactions with the physical environment shape their AT during Bee-Bot programming activities. The findings identify three embodied forms of early AT—incremental, transitional, and systematic—which unfold dynamically through young children’s use of tapping, manipulating, and tracing actions to support algorithm construction and intertwined mathematical reasoning. From a child-centred, non-deficit lens, we also interpret young children’s encounters with recurrent challenges as meaningful embodied sense-making rather than cognitive deficits, as they draw on familiar sensorimotor experiences to understand turn commands and navigate step-counting difficulties by reorganising the environment to reduce cognitive demands. This study contributes to the literature by enriching our understanding of the embodied nature of early AT and offering pedagogical implications for its integration into early mathematics education through embodied approaches.