Gpt-4.1 mini-powered learning management automation
Ready for 3.0Ready for 3.0. This template uses no nodes that n8n 3.0 removes. No removed nodes, versions or helpers found. Static check, last run 2026-10-19.
Nodes used (9)
- Schedule Trigger
n8n-nodes-base.scheduleTrigger - Edit Fields (Set)
n8n-nodes-base.set - HTTP Request
n8n-nodes-base.httpRequest - AI Agent
@n8n/n8n-nodes-langchain.agent - Structured Output Parser
@n8n/n8n-nodes-langchain.outputParserStructured - OpenAI Chat Model
@n8n/n8n-nodes-langchain.lmChatOpenAi - If
n8n-nodes-base.if - Gmail
n8n-nodes-base.gmail - Code
n8n-nodes-base.code
What it does
How It Works Automates daily learner engagement monitoring, progress analysis, and personalized feedback delivery for training programs. Target audience: learning and development teams, corporate training managers, and online education platforms scaling instructor workload. Problem solved: manual progress tracking consumes instructor time; AI analysis identifies struggling learners early for intervention. Workflow runs daily checks on learner activity, retrieves course data and progress, analyzes engagement with OpenAI models, evaluates quiz scores, generates performance summaries, sends progress reports to learners, emails instructors on at-risk cases, generates learning paths, and triggers manager notifications. Setup Steps 1. Configure daily schedule trigger. 2. Connect learning management system APIs (LMS). 3. Set OpenAI keys for progress analysis. 4. Enable Gmail for multi-recipient notifications. 5. Map learner risk thresholds and escalation rules. Prerequisites LMS platform credentials, OpenAI API key, learner database, email service for notifications, manager contact lists. Use Cases Corporate onboarding programs tracking employee progress, online learning platforms identifying struggling students Customization Adjust AI analysis criteria for your curriculum. Integrate Slack for instructor alerts. Benefits Reduces instructor workload by 70%, identifies at-risk learners 2 weeks early