Transmodal Analysis (TMA)

TMA is a computational framework for analyzing complex multimodal data. It extends state-dependent models such as Epistemic Network Analysis (ENA) to account for diverse data streams, addressing challenges such as varying temporal scales and learner characteristics to improve the robustness and interpretability of findings.

The package imports, preprocesses, and accumulates coded data across modalities with granular control over windows and weights, producing connection structures that downstream packages (e.g. rENA, ONA) can model and visualize.

For methodological details, see Shaffer, Wang, and Ruis (2025), "Transmodal Analysis," doi:10.18608/jla.2025.8423 .