From Clicking to Moving: Embodied Micro-Movements as a New Modality for Data Literacy Learning
This addresses digital fatigue and health risks in data literacy education for learners, though it is incremental as it builds on existing embodied learning concepts.
The paper tackles the problem of sedentary, passive digital learning for data literacy by introducing Kinetiq, a system that integrates full-body micro-movements into data problem-solving, resulting in significantly higher affective valence, enjoyment, engagement, and motivation while maintaining comparable learning gains in a preliminary study.
Widespread digital learning has expanded access to education but has resulted in highly sedentary, click-based interaction, contributing to digital fatigue, reduced cognitive flexibility, and health risks associated with prolonged passive screen time. Meanwhile, data literacy has become an essential competency in a data-driven society, yet it is typically taught through passive, disembodied interfaces that offer little physical engagement. We present Kinetiq (Kinetic+IQ), a novel system that integrates fun, full-body micro-movements directly into data and numeracy problem solving. Instead of selecting answers with a mouse, learners interact through natural gestures such as reaching, dodging, heading, elbowing, or knee-raising, thus turning abstract data problem-solving into embodied experiences that integrate thinking with movement. In a preliminary within-subjects study comparing Kinetiq with conventional platforms, participants reported significantly higher affective valence, enjoyment, engagement, and motivation, while maintaining comparable learning gains. We contribute: (1) a task-integrated movement paradigm for data learning, (2) a cross-platform web and mobile app system enabling full-body learning in constrained everyday spaces, and (3) preliminary empirical evidence that embodied micro-movements can enrich the affective experience of data literacy learning.