An integrated augmented reality (AR) and embedded electronics-based toolkit for improved visualization and understanding of network graphs

Network graphs are all-pervasive, and an in-depth understanding of networks is important for students and researchers across a variety of disciplines that involve analysis of multi-modal data. Networks can be challenging to conceptualize due to their complexity, and immersive technologies are needed to parse network graphs. This study introduces a novel immersive toolkit grounded in multimedia learning and embodied cognition theories to improve network graph comprehension in undergraduate STEM students. The toolkit integrates embedded electronics with Augmented Reality (AR) to create synchronized physical-virtual visualizations of complex networks featuring: (1) visual attributes to communicate network properties, (2) tactile interaction through physical network models, (3) local and global views of network graphs, and (4) contextual AR overlays. We present two implementations of this toolkit, one of which was implemented as a case study (intervention) in a senior-level undergraduate class ( N = 25) during finals week with statistically significant improvement (FDR adjusted p = 0.0018) in study outcomes post-intervention compared to pre-intervention. Notably, the improvement was pronounced among students that reported low confidence in subject matter pre-intervention. This study demonstrates how technology can be used to augment human cognition for complex mental tasks and demonstrates the utility of our toolkit to serve as a technology-enabled teaching aid.