Epistemic Network Analysis (ENA) is a method for identifying and quantifying connections among elements in coded data and representing them in dynamic network models. A key feature of the ENA tool is that it enables researchers to compare different networks, both visually and through summary statistics that reflect the weighted structure of connections. The interface also lets users view the original data that contributed to each connection in the network representation. ENA can thus address a wide range of research questions.
This page gathers resources for learning and applying ENA: the introduction to the core ideas, key readings, tutorials and workshops, and the ENA Web Tool for implementation, with its help guide.
| Foundational ENA Papers | ||
|---|---|---|
| A Tutorial on Epistemic Network Analysis: Analyzing the Structure of Connections in Cognitive, Social, and Interaction Data | Shaffer, D. W., Collier, W., & Ruis, A. R. (2016) | The starting point: the theory behind ENA, how it builds network models, and worked examples in the ENA Web Tool. |
| Epistemic Network Analysis: A Worked Example of Theory-Based Learning Analytics | Shaffer, D. W., & Ruis, A. R. (2017) | A theory-based approach to learning analytics, walking from data to ENA visualizations. |
| Formatting Data for Epistemic Network Analysis | Shaffer, D. W. (2014) | Practical guidance on preparing and formatting data, with an explanation of stanzas. |
| ENA Web Tool Help | The Web Tool's own guide, kept current with each release: preparing and uploading data, building a model, ordered and transmodal networks, plots, and statistics. | |
| ENA Web Tool User Guide | Tan, Y. | This user guide demonstrates how to conduct an Epistemic Network Analysis (ENA) using the ENA web tool. It was written for an earlier version, so some screens and option names differ; for example, Conversations are now Horizons. |
| The Mathematical Foundations of Epistemic Network Analysis | Bowman, D., Swiecki, Z., Cai, Z., Wang, Y., Eagan, B., Linderoth, J., & Shaffer, D. W. (2021) | This article explains the mathematics behind ENA, showing how it transforms connections in discourse data into network visualizations and statistical comparisons that tell a consistent and interpretable story. |
| Tutorials and demos | |
|---|---|
| QE Tutorial: ENA Web Tool demo | A short introduction to the Epistemic Network Analysis Web Tool. |
| ENA Web Tool walkthroughs | Short how-to videos for specific Web Tool tasks, recorded with an earlier version. Tutorial mode is now the in-app tutorial and the setup wizard. |
| ENA demo: COVID press conferences | Compares COVID-19 press conferences by Jacinda Ardern and Donald Trump, and shows how ENA networks are constructed. |
| ENA demo: Law & Order: SVU | Compares how different detectives discuss a case and visualizes how the networks are built. |
For greater flexibility and more advanced analyses, try ENA in R. The rENA package supports the same core analytic process as the ENA Web Tool while allowing you to customize analyses and build more transparent and reproducible QE workflows.
Once your coded data is ready, you can use the rENA package to conduct your custom analysis from scratch, or continue from a model you built in the ENA Web Tool. To take your data to R, click Sets in the left sidebar, click the three-dot menu on your data file, and select Download CSV; then build the model in R with the same units, horizons, window, and codes. To take the model’s results instead, click Download Model above the comparison plot: it saves the plots and, optionally, the model data (nodes, point positions, line weights, and connection counts).
The rENA package provides functions for ENA. Step-by-step instructions can be found in this book chapter. You can also refer to the GitLab repository for a quick-start guide.
For a comprehensive description, see the documentation for the rENA package (an HTML version is available here).
| Documentation | ||
|---|---|---|
| QE R Package Repository | Index of QE R packages. | |
| rENA: Epistemic Network Analysis | Marquart, C. L., Swiecki, Z., Collier, W., Eagan, B. R., Woodward, R., & Shaffer, D. W. | CRAN official document page for rENA package. |
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