Neural Epistemic Network Analysis: Combining Graph Neural Networks and Epistemic Network Analysis to Model Collaborative Processes

Zheng Fang, Weiqing Wang, Guanliang Chen, Zachari Swiecki

Abstract: We report on the design and evaluation of a novel technique for analysing the sociocognitive nature of collaborative problem-solving—neural epistemic network analysis (NENA). NENA combines the computational power and representational ability of graph neural networks (GNNs) to naturally incorporate social and cognitive features in the analysis with the interpretative advantages of epistemic network analysis (ENA). Comparing NENA and ENA on two datasets from collaborative problem-solving contexts, we found that NENA improves upon ENA’s ability to distinguish between known subgroups in CPS data, while also improving the interpretability and explainability of GNN results.