Social-Epistemic Nexus Analytics
An AI-assisted research platform for modeling collaborative discourse as social-epistemic networks.
Compare groups, trace learning processes, identify roles, and generate transparent, reproducible network-based reports.
A complete SENA research workflow
From raw discourse to transparent, reproducible social-epistemic evidence.
Data Import
Bring discourse, interaction, timestamp, role, and outcome data into a structured project.
Coding Studio
Create or import codebooks, manually code discourse, and review AI-assisted suggestions.
ENA Builder
Model epistemic networks where concepts, skills, discourse moves, or codes become connected nodes.
SNA Builder
Construct actor networks from replies, mentions, co-participation, editing, or turn-taking.
SENA Fusion Lab
Overlay social ties and epistemic positions to generate social-epistemic role and community profiles.
Group Comparison
Compare groups, conditions, stages, or high/low outcome communities with cautious statistical framing.
Temporal Analysis
Trace changes across phases such as studying, planning, teaching, reflecting, inquiry, or design cycles.
AI-Assisted Interpretation
Draft cautious interpretation paragraphs grounded in selected figures, parameters, and verified evidence.
Report Generator
Generate publication-ready method notes, figures, captions, and reproducible project summaries.
Export / API / Reproducibility
Export complete research artifacts so teams can audit, reproduce, extend, and publish analyses.
A nexus framework for people, ideas, roles, and time
SENA connects Social Network Analysis, Epistemic Network Analysis, and SENS into one theory-aligned workflow.
What is SENA?
SENA models collaboration as a dynamic nexus: people, discourse moves, roles, communities, stages, scaffolding, and outcomes are analyzed together.
Why SNA alone is insufficient
SNA reveals participation, centrality, brokerage, reciprocity, and communities, but it cannot explain the epistemic content of interaction by itself.
Why ENA alone is insufficient
ENA reveals connections among concepts, codes, or reasoning moves, but it does not inherently explain social position, brokerage, or communities.
How SENA integrates SNA + ENA + SENS
SENA extends SENS into an end-to-end research workflow where social structure and epistemic structure become jointly interpretable evidence.
Role = f(centrality, discourse)
SENA(t) = SNA(t) ⊕ ENA(t)
From discourse traces to SENA evidence
Enterprise research workspace preview
A serious dashboard for importing, coding, comparing, interpreting, and reporting social-epistemic evidence.
AI-Integrated Lesson Study Demo
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Coding scheme
Group comparison
ENA network
Social network
Temporal trajectory
The reflecting stage appears to integrate multivoiced talk, support-and-critique, and generative orientations more strongly than earlier phases. Treat this as a draft analytic interpretation, not an automatic conclusion.
AI-generated interpretation: please verify against the coding scheme, network parameters, statistical results, and research context.
Research cases
Built for educational research, discourse analysis, teacher collaboration, and knowledge-building studies.
MOOC collaborative learning
Analyze large-scale forum interaction as linked social and epistemic patterns.
Interdisciplinary lesson study
Trace how teachers and faculty negotiate roles, problems of practice, and solution generation.
Knowledge building and teacher scaffolding
Compare how scaffolding configurations shape interaction, discourse, and group artifacts.
Deep learning representation
Represent deep learning as connected cognitive, social, and self-regulatory processes.
Visual analytics gallery
Publication-ready network figures, comparison panels, and temporal views for social-epistemic research.
ENA network graphs
SNA actor graphs
SENA overlay graphs
Group A vs Group B difference networks
Temporal trajectory plots
Role dashboards
Community comparison panels
Scaffolding-response maps
Exportable publication figures
Ethics, privacy, and reproducibility
SENA treats AI as an assistant, not an authority. Every claim should remain auditable and human-reviewed.
Trustworthy by design
SENA should support rigorous interpretation rather than automate research judgment. Every figure, code, prompt, parameter, and conclusion should be traceable.
Anonymization tools
Mask names, IDs, institutions, and sensitive metadata before analysis or export.
Role-based access control
Separate project owners, coders, viewers, lab admins, and external collaborators.
Consent / IRB metadata
Record approval IDs, consent scope, data retention, and usage constraints.
Audit logs
Track changes to data, codes, parameters, reports, and AI-generated drafts.
AI coding transparency
Store confidence scores, prompts, versions, human review state, and uncertainty flags.
Bias warnings
Avoid interpreting centrality, performance, or discourse quality as automatic judgment.
Reproducibility exports
Export codebook, filtered data, window settings, model parameters, figures, and logs.
Human review required
AI can draft interpretations, but researchers must validate claims against context and evidence.
Docs and method library
Scholarly guides, templates, examples, and API-ready documentation for research teams.
SENA Framework
Theory, constructs, assumptions, and analytic layers.
SNA Guide
Tie extraction, centrality, reciprocity, communities, and roles.
ENA Guide
Units, stanzas, code co-occurrence, centroids, and difference networks.
SENS Background
How SNA and ENA combine to study collaborative learning.
Coding Schemes
Templates for PPT, knowledge building, design thinking, and custom discourse codes.
Reproducibility Guide
Export settings, project logs, captions, and transparent methods notes.
API Documentation
50 documented SENA route resources covering 83 HTTP methods, exported as JSON and OpenAPI 3.1.
Citation Guide
Suggested wording for methods, AI-use statements, and data availability.
Enterprise API contract
50 route resources, 83 method contracts, and coverage tests for the current Next API surface.