ECR: Assessing Complex Collaborative STEM Learning at Scale with Epistemic Network Analysis

In this project, researchers are developing a statistical analysis technique for measuring how people learn. With prior NSF funding, members of the team created epistemic network analysis (ENA), a technique for creating network models of complex and collaborative thinking in science, technology, engineering, and mathematics.

ENA is being used by more than 40 researchers at 19 universities to answer a wide range of research questions in learning sciences, cognitive neuroscience, engineering education, environmental science education, medical and surgical education, and history of science.

The proposed research and development will create an online toolkit that lets researchers upload audio, video, text, or log-file data, automatically transcribe the audio data, develop and validate automated codes using supervised natural language processing tools, and produce ENA models.

This will make it possible for researchers analyze data on how people learn without requiring simultaneous expertise in automated transcription, data segmentation, coding, and network modeling. It will also make it possible to conduct analyses of learning using the large volumes of data that are currently generated by online learning tools, significantly expanding capacity for research on learning.


Active through August 31, 2022

Contact Information

David Williamson Shaffer