Implementing a Learning Record Warehouse for Different Interoperability Specifications in Moodle LMS
Resumen
Semantic interoperability is an important aspect in Learning Analytics systems, allowing data from various sources to be processed by a central application while preserving its original meaning. In this regard, there are two specifications that enable interoperability for Learning Analytics: Caliper Analytics and the Experience API (xAPI). This study presents the implementation of a Learning Record Warehouse (LRW) for storing Moodle logs, using the specifications Caliper Analytics and xAPI. OpenLRW was chosen as the platform to store data collected by plugins responsible for gathering Moodle logs in Caliper Analyzer and xAPI formats. Despite OpenLRW having an internal converter to convert data from xAPI to Caliper Analyzer format, some bottlenecks were identified during the experiments conducted within this study. © 2024 IEEE.
Colecciones
- Indexados Scopus [2005]
Ítems relacionados
Mostrando ítems relacionados por Título, Autor o Palabra clave.
-
School Clustering Through Machine Learning and Geospatial Analysis
(ANTACOM A.C.; SIP-IPN; UPIITA-IPNIngeniería de SistemasFacultad de Ingenierías, 2025)Schools and school population are prone to safety and health risks due to their proximity to hazardous features, either natural or infrastructural. In Mexico there is an official standard that points out which features to ... -
La tensión entre la justicia lega y la justicia letrada durante la primera mitad del siglo xix: el caso de Antioquia (Nueva Granada)
(Universidad del SalvadorDerechoFacultad de Derecho, 2010)El presente texto señala la tensión que existió, a inicios del siglo XIX antioqueño, entre la justicia lega (conformada por vecinos designados por el Ayuntamiento, que aplicaban preferentemente las costumbres locales) y ... -
Data Interoperability in Learning Analytics - Review of Literature
(Institute of Electrical and Electronics Engineers Inc.Ingeniería de SistemasFacultad de Ingenierías, 2024)Learning analytics (LA) and educational data mining (EDM) are two complementary approaches to modeling and understanding teaching-learning processes and, in general, data from academic environments. LA is applied to data ...