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Online Education · n8n Workflow Automation

Online Education — Enrollment and Progress Monitoring

Portfolio Demonstration

Enrollment, onboarding, module progress, assignment status, and quiz performance flow in a straight line, with a single risk gate near the end - combining inactivity days and quiz score - deciding between tutor intervention or an on-track milestone marker.

n8n canvas: Online Education — Enrollment and Progress Monitoring — full workflow canvas in n8n

Problem

Learners who stall mid-course or miss milestones often disengage completely without a timely nudge.

System Design

Course milestone timeline: the most compact and linear canvas in the portfolio, resembling a left-to-right course-progression timeline with a single branch point near the end.

Workflow Stages

  1. 01Enrollment & Onboarding
  2. 02Progress & Performance Tracking
  3. 03Support Risk & Tutor Intervention

Tools Used

  • n8n
  • Form Trigger
  • Code (JavaScript)
  • If
  • Set

Safety & Human Review

  • Workflow name begins with DEMO | and is inactive.
  • No credentials are attached to any node.
  • No enabled external send node exists anywhere in this workflow.
  • All data is fictional (example.com emails, invented names/addresses).
  • Uses only built-in n8n node types.

Implementation Evidence

Real screenshots of the working system — collapsed by default so this page stays readable.

What's Working

7 structural checks passed, including: Workflow JSON parses (local + server-returned copy); active is false; Name begins with DEMO |; No credentials attached to any node. Structural and logic validation completed. Live n8n execution pending manual safe test.

Limitations & Confidentiality

Classification and scoring logic is deterministic/rule-based rather than a live AI model, by design (provider-independent, fully inspectable, no credential required). No real system of record, messaging channel, or calendar is connected - every downstream action is simulated or drafted, never sent. Live n8n execution has not been triggered as part of this build.

Portfolio demonstration built for a fictional business with fictional data. It is not connected to any real client, system, or customer.

What I'd Improve Next

Replace deterministic classification with a real AI model behind the same confidence/human-review pattern where one exists. Connect the mock/simulated steps to real systems of record once reviewed and approved. Wire a real (approved) communication channel behind the draft-message steps.

Have a similar workflow to automate?

I'll tell you honestly whether automation is the right fix.