Aligning AIED Systems to Embodied Cognition and Learning Theories

Embodied Learning involves the development of perceptuo-motor schemas as students manipulate physical objects that embody a concept, or when students move in domain-relevant ways, physically enacting solutions to problems, as well as gesturing as they interact with peers face-to-face. Teaching standards (e.g., for K-12 math education) align with such theories of learning. For instance, teachers are encouraged to have students “talk mathematics”, construct viable arguments and critique the reasoning of others, model with mathematics, and use tools with precision, among others. Yet most learning technologies and tutoring systems are not designed to facilitate embodied learning; instead, they tend to align with more traditional views of student learning. This paper explores possible ways AIED systems can reflect embodied learning theories, within K-12 STEM education. We present the WearableLearning platform as an example that intends to bring embodied learning to mathematics and computing education for students at the K-12 level, with implications and suggestions on how to use Artificial Intelligence to make embodied learning environments more effective.