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.
O Open ENA é uma plataforma não comercial para fins educacionais e de pesquisa e permanecerá gratuito para sempre.
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 paperO Open ENA se baseia na teoria e nos métodos de Quantitative Ethnography (QE) e Epistemic Network Analysis (ENA). Agradecemos à University of Wisconsin–Madison, ao professor David Williamson Shaffer e aos pesquisadores, desenvolvedores e colaboradores do Epistemic Analytics Lab, no Wisconsin Center for Education Research, por seu trabalho fundador e contínuo em QE, ENA e webENA.
Quantitative Ethnography (QE) combina a compreensão qualitativa da atividade humana em seu contexto com a análise quantitativa. (Shaffer, 2017)
Epistemic Network Analysis (ENA) modela as conexões entre elementos codificados que ocorrem juntos em contextos significativos. Essas conexões formam redes cujas estruturas podem ser visualizadas e comparadas estatisticamente. (Shaffer et al., 2016)
Com base nesses trabalhos, o Open ENA organiza dados codificados, configurações dos modelos e comparações de redes em um fluxo de trabalho no navegador. Os pesquisadores devem interpretar os resultados considerando a pergunta de pesquisa, os fundamentos da codificação e o material qualitativo original. (Shaffer & Ruis, 2017)
A equipe do Open ENA utilizou o webENA e o tomou como referência para estabelecer a aparência e a disposição iniciais desta plataforma. Reconhecemos expressamente que essa referência de design se originou na equipe original de ENA e em seu trabalho no webENA em Madison, Wisconsin, Estados Unidos.
A visualização de redes ENA também se baseia em pesquisas sobre design visual e interpretação. (Tan et al., 2022)
O Open ENA é uma plataforma independente mantida pela equipe do Open ENA.