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AICoFe: Implementation and Deployment of an AI-Based Collaborative Feedback System for Higher Education

◐ medium · 2026-05-14automated-grading, feedback-loop, higher-ed, llm, learning-analytics, human-in-the-loop-ai, rag

AICoFe: AI-Based Collaborative Feedback System for Higher Education

System Architecture

AICoFe orchestrates a multi-LLM pipeline using GPT-4.1-mini, Gemini 2.5 Flash, and Llama 3.1 to synthesize quantitative rubric data and qualitative observations into actionable feedback for higher education students. The key innovation is a teacher-in-the-loop mediation workflow: educators use specialized Learning Analytics dashboards to curate and refine AI-generated feedback drafts before delivery.

Technical Design

  • Multi-LLM orchestration: Three different models contribute complementary perspectives
  • Hybrid storage: SQL for traceability and structured metadata + MongoDB for semi-structured feedback versions
  • Learning Analytics dashboards: Dedicated educator interfaces for feedback curation

    • Connection to Broader AIED

    AICoFe extends prior work on AI Peer Feedback Systems from experimental prototypes to a deployed system with educator mediation. The multi-LLM approach addresses single-model bias concerns in Automated Grading. It sits at the intersection of Feedback Loop design and Learning Analytics — keeping educators as active curators through Human In The Loop AI principles.

    Connected Concepts

  • Automated Grading
  • Feedback Loop
  • Learning Analytics
  • Human In The Loop AI

    • Connected Articles

  • AI Peer Feedback Systems

    • Citation

    Becerra, A., Palma, A., & Cobos, R. (2026). AICoFe: Implementation and deployment of an AI-based collaborative feedback system for higher education. Proceedings of the Learning Analytics Summer Institute Spain 2026 (LASI Spain 2026). arXiv:2605.04740.