Version 1.0 — Registered Research Software Release This release corresponds to the official registered version of the LOPathRecommenderProject, a software component developed and validated within the Horizon Europe project e-DIPLOMA (Grant Agreement 101061424). This software forms part of the scientific-technical contributions delivered in: Deliverable D3.4 — "AI Algorithms" WP3 — Piloting and Testing of Innovation Procedures and Technology Enhancement More information: https://e-diplomaproject.eu/results/ This version is permanently archived for citability and long-term preservation. 🔹 Scope of the software The LOPathRecommenderProject implements an adaptive learning-path recommendation engine for Moodle-based e-learning environments, relying exclusively on CSV log exports. The system integrates the following components: Full preprocessing pipeline for Moodle logs. Anonymization and filtering of student interactions. Extraction of structured Fact Tables (Users weights, LO weights, Sequential ratings, LO metadata). Construction of static and dynamic graph representations of user navigation. Recommendation algorithms based on: Cosine similarity, Weighted shortest-path computation (Dijkstra). A FastAPI service enabling real-time recommendation queries. UML class diagrams and communication workflows provided in /imgs/. 🔹 Purpose of this release This version is issued to: Provide an officially registered, citable version of the software. Ensure traceability of the implementation used in scientific-technical project outputs. Support future piloting and integration activities within the e-DIPLOMA project. Guarantee FAIR principles (Findable, Accessible, Interoperable, Reusable). Serve as evidence of software development contributions for research evaluation (AEI, ANECA, EU R&I). 🔹 Validation context This version has been: Implemented and validated as part of WP3 innovation and testing activities. Tested using real Moodle logs from multiple institutional courses. Integrated into a prototype architecture (Moodle plugin ↔ FastAPI backend). Verified for reproducibility using the provided preprocessing and recommendation scripts. 🔹 Technical notes Developed in Python 3.11.x. Uses widely supported scientific libraries (Pandas, NetworkX, Scikit-learn). Operates exclusively on Moodle CSV logs (no database access required). Modular design allowing future extensions and research adaptation. 🔹 Citation A DOI will be automatically generated by Zenodo upon archiving. Please cite this release when referring to its implementation or use.