Learning Recommendation Engine

Recommend optimal learning resources, activities, and pathways based on learner data and performance patterns.

When to Use

• Personalized content recommendations

• Next-best-action suggestions

• Resource matching

• Difficulty adaptation

• Intervention triggers

Recommendation Logic

• Collaborative filtering (learners like you learned X)

• Content-based (similar to what you've done)

• Performance-based (fill your gaps)

• Goal-oriented (towards your objectives)

• Engagement-based (what keeps you learning)

CLI Interface

/learning.recommendation-engine --learner-profile "profile.json" --context "struggling with calculus" /learning.recommendation-engine --next-best-action --performance "recent-scores.json"

Output

• Ranked recommendations with rationale

• Personalized learning queue

• Intervention triggers

• Resource suggestions

Composition

Input from: /learning.pathway-designer , /curriculum.analyze-outcomes

Output to: Personalized learning experience

Exit Codes

• 0: Recommendations generated

• 1: Insufficient learner data

• 2: Invalid profile format