Open ENA — Epistemic Network Analysis

Aprenda ENA tomando las decisiones del análisis.

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33 lecciones

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SecondGame ENA points, mean, and confidence interval. Original figure from the ENA and ONA tutorial by Tan and colleagues (2024).
InterpretaciónIntermedio35 min5 ago 2026
Lección de la Academia ENA 19

Report ENA Effect Sizes and Intervals

Use the shared synthetic design-talk dataset to practise reporting the magnitude and uncertainty of planned ENA coordinate contrasts alongside plots and p-values, document the decision, test a defensible alternative, and keep every interpretation tied to source evidence.

El cuerpo del tutorial revisado está disponible actualmente en inglés.

effect sizeconfidence intervalcoordinate comparison
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Tan et al. (2024), figure 6 · CC BY 4.0

Mean network comparison with both groups' ENA points. Original figure from the ENA and ONA tutorial by Tan and colleagues (2024).
Diseño de investigaciónIntermedio35 min6 ago 2026
Lección de la Academia ENA 20

Plan Multiple-Group ENA Contrasts and Multiplicity

Use the shared synthetic design-talk dataset to practise comparing three or more groups without forcing them into a two-group means rotation or reporting every favorable pairwise difference, document the decision, test a defensible alternative, and keep every interpretation tied to source evidence.

El cuerpo del tutorial revisado está disponible actualmente en inglés.

multiple groupsplanned contrastsmultiplicity
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Tan et al. (2024), figure 8 · CC BY 4.0

Novice networks projected into the expert space. Original figure from the ENA and ONA tutorial by Tan and colleagues (2024).
ModelizaciónIntermedio35 min7 ago 2026
Lección de la Academia ENA 21

Build Longitudinal ENA Trajectories in One Space

Use the shared synthetic design-talk dataset to practise representing successive network states as ordered paths while keeping every time point co-registered in one analytic space, document the decision, test a defensible alternative, and keep every interpretation tied to source evidence.

El cuerpo del tutorial revisado está disponible actualmente en inglés.

longitudinal trajectoryshared spacetime ordering
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Tan et al. (2024), figure 28 · CC BY 4.0

FirstGame mean ordered network (ONA). Original figure from the ENA and ONA tutorial by Tan and colleagues (2024).
ModelizaciónIntermedio35 min8 ago 2026
Lección de la Academia ENA 22

Choose Directed or Ordered Network Analysis When Sequence Matters

Use the shared synthetic design-talk dataset to practise deciding whether the research question concerns undirected association, directed ordering, or a stricter transition process, document the decision, test a defensible alternative, and keep every interpretation tied to source evidence.

El cuerpo del tutorial revisado está disponible actualmente en inglés.

ordered network analysisdirected edgessequence
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Tan et al. (2024), figure 14 · CC BY 4.0

RescuShell tutorial dataset: first three records. Original figure from the ENA and ONA tutorial by Tan and colleagues (2024).
Preparación de datosIntermedio35 min10 ago 2026
Lección de la Academia ENA 23

Prepare Multimodal Events for ENA

Use the shared synthetic design-talk dataset to practise aligning speech, action, sensor, screen, or spatial events on a defensible common timeline before modeling cross-modal connections, document the decision, test a defensible alternative, and keep every interpretation tied to source evidence.

El cuerpo del tutorial revisado está disponible actualmente en inglés.

multimodal dataevent alignmentsensor traces
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Tan et al. (2024), tutorial example · CC BY 4.0

Binary code columns in the tutorial dataset. Original figure from the ENA and ONA tutorial by Tan and colleagues (2024).
Preparación de datosIntermedio35 min11 ago 2026
Lección de la Academia ENA 24

Validate Automated Codes Before They Enter ENA

Use the shared synthetic design-talk dataset to practise evaluating whether model-generated labels are accurate enough for relational analysis and how classification errors propagate into edges, document the decision, test a defensible alternative, and keep every interpretation tied to source evidence.

El cuerpo del tutorial revisado está disponible actualmente en inglés.

automated codingclassifier validationerror propagation
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Tan et al. (2024), tutorial example · CC BY 4.0