In this paper, we combine dialogic and embodied theories of learning to create a unified analytic lens. Embodied cognition is a theoretical approach operating under the premise that thinking and communication are multimodal activities. Under this premise, dialogue between learners needs to be conceptualized using a multimodal lens. We identify multimodal voices as speech and movement bundles situated within a learning context and describe a phenomenon that we call Multimodal Dialogue – multimodal interaction between different multimodal voices. To demonstrate this phenomenon, we analyze a learning sequence by two third-grade students who participated in a mathematics lesson aimed to foster embodied learning of proportion. Our analysis zooms in on the phenomenon of a multimodal voice as a speech-and-movement bundle situated within a learning context. We further show how multimodal dialogic gaps – differences between multimodal voices within and between modalities – drive communication and eventual changes in voices.@en

Embodied learning and the design of embodied learning platforms have gained popularity in recent years due to the increasing availability of sensing technologies. In our study, we made use of the Mathematical Imagery Trainer for Proportion (MIT-P) that uses a touchscreen tablet to help students explore the concept of mathematical proportion. The use of sensing technologies provides an unprecedented amount of high-frequency data on students' behaviors. We investigated a statistical model called mixture Regime-Switching Hidden Logistic Transition Process (mixRHLP) and fit it to the students' hand motion data. Simultaneously, the model finds characteristic regimes and assigns students to clusters of regime transitions. To understand the nature of these regimes and clusters, we explore some properties in students' and tutor's verbalization associated with these different phases.@en