International Journal of
Information and Education Technology

Abstract—The increasing integration of Artificial Intelligence (AI) in higher education is transforming approaches to the design and development of digital learning environments. Moodle, as an open-source Learning Management System (LMS), offers a flexible architecture conducive to innovation, but the integration of artificial intelligence into software development processes remains poorly formalized, particularly concerning human oversight and ethical governance. This study aims to formalize and assess a structured paradigm for human-artificial intelligence collaboration within the framework of educational software engineering. It introduces the Collaborative Iterative Co-Authoring Process (CICAP), a methodological framework integrating a generative artificial intelligence model into the development of a Moodle plugin for managing internship and job opportunities. The process was conducted under continuous human oversight, according to ethics-by-design principles, to ensure transparency, accountability, and explainability at each stage. The experimentation resulted in a complete plugin exhibiting high technical quality, stability, and maintainability. The results provide preliminary evidence that a human-supervised, AI-assisted workflow can increase efficiency while adhering to ethical and production-quality standards. The CICAP paradigm thus proposes a reproducible and responsible model for ethical and sustainable co-creation in educational engineering.

Keywords—human-AI co-creation, generative artificial intelligence, Moodle, ethics by design, Collaborative Iterative Co-Authoring Process (CICAP) paradigm, plugin development, Learning Management Systems (LMS)

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Cite: Yassine Karroumi, Khalid EL Khattabi, Fatima Ou-zennou, and Souad Eddarouich, "CICAP: A Human-AI Co-creation Paradigm for Ethical and Efficient Plugin Development in Moodle," International Journal of Information and Education Technology, vol. 16, no. 7, pp. 1869-1880, 2026.

Copyright © 2026 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).