A small team. An open horizon.
Open ENA brings together learning science, quantitative ethnography, artificial intelligence, and educational technology.
We are building a transparent and approachable path into Epistemic Network Analysis—one where methods, interface decisions, and future capabilities can be inspected rather than hidden.
Openness is more than access.
It means making the path from evidence to interpretation visible: what the model receives, what the computation does, what the figure shows, and what it cannot claim.
Open ENA is a non-commercial platform for educational and research purposes and will remain free forever.
The Education University of Hong Kong
Educational researcher · Application developer
His work spans technology-enhanced learning, learning analytics, artificial intelligence in education, network analysis, and content and language integrated learning.
EdUHK profile
3D ENA Research Group · Hong Kong
ENA variants · Dimensionality-reduction algorithms
He has played a pioneering role in advancing ENA variants such as 3D ENA and dimensionality-reduction algorithms for ENA. As the key developer of 3D ENA 1.0, he combines computer science and psychology to develop interactive research tools.
3D ENA team profile
National Taiwan University of Science and Technology
Assistant Professor · Graduate Institute of Digital Learning and Education
Her work spans artificial intelligence in digital learning, cognitive and social networks, data literacy, data visualization, and graph analysis.
Taiwan Tech profile
Meredith College, North Carolina, USA
Open ENA team
A member of the Open ENA team affiliated with Meredith College, North Carolina, USA.
Forthcoming conference paper · 2026
Hu, D., Hamilton, E., Tu, Y. F., & Xu, Q. (2026, November). Design and development from rENA to jENA: Accelerating the creation of web-based Open ENA tools. [Conference paper]. International Conference on Quantitative Ethnography.
ICQE 2026 · Publication details forthcoming
Journal article · 2025
Tu, Y. F., Hwang, G. J., & Hu, D. (2025). Effects on the learning achievement, approaches to learning, and multi-stage reflection quality of students with different levels of digital self-efficacy in a data literacy course: An ARCS-based self-reflective online learning model. Computers & Education, 238, 105397. https://doi.org/10.1016/j.compedu.2025.105397
View journal article
Conference paper · 2024
Yu, J., Hu, D., & Wang, C. H. (2024). Development of ENA 3D: A tool for epistemic network analysis in three-dimensional space. In Y. J. Kim & Z. Swiecki (Eds.), Advances in quantitative ethnography (Communications in Computer and Information Science, Vol. 2278, pp. 152–165). Springer. https://doi.org/10.1007/978-3-031-76335-9_11
View conference paperOpen ENA builds on the theory and methods of Quantitative Ethnography (QE) and Epistemic Network Analysis (ENA). We gratefully acknowledge the University of Wisconsin–Madison, Professor David Williamson Shaffer, and the researchers, software developers and collaborators of the Epistemic Analytics Lab at the Wisconsin Center for Education Research for their foundational and continuing contributions to QE, ENA and the webENA tool.
QE combines contextual, qualitative understanding of human activity with quantitative analysis. (Shaffer, 2017)
ENA models connections by analyzing the co-occurrence of coded elements in meaningful contexts, supporting both network visualization and statistical comparison. (Shaffer et al., 2016)
Grounded in this research, Open ENA brings coded data, model settings and network comparisons into a browser-based research workflow. Researchers must interpret results in relation to their research questions, coding decisions and original qualitative evidence. (Shaffer & Ruis, 2017)
The Open ENA team used and referred to the webENA tool when establishing this platform's initial visual appearance and layout. We explicitly acknowledge that this initial interface reference originated with the original ENA research team and its webENA design work in Madison, Wisconsin, USA.
ENA network visualization is also informed by research on visual design and interpretation. (Tan et al., 2022)
Open ENA is an independent platform maintained by the Open ENA team.