SG-LOM as Metadata Description for Serious Games to Benefit from LMS Monitoring Features

Abstract

Compared to the conventional approach of e-learning, serious games are playing an increasingly important role in the educational sphere and reached a certain maturity to become a possible alternative to traditional methods of learning that is often seen as restrictive and boring sometimes by learners. This is due to the fact that young people today are familiar with new technologies and virtual worlds outside schools as part of their leisure. A habit that enable these young people to be immediately in the heart of the matter since they already have a video game culture (gameplay) that allows them to focus on the main message. However, the integration of serious games in the learning process still limited since they don’t provide efficient features for monitoring and assessing learner (player) interactions and decisions without breaking the nonlinearity of the game in order to show them the consequences of their decisions, a limit that has been proven in a previous comparative study [1].

In this paper we address the aspects of serious games (Robocode as example)  integration and deployment into LMS (Dokeos as example) based on the automatic packaging and exportation of serious games as reusable learning objects (LO) that can be easily distributed through any LMS. This integration uses the ADL SCORM data model that defines how content may be packaged as a Package Interchange File (PIF), and the IEEE LOM Application Profile “SG-LOM” [2] as metadata description to describe every level of SCORM since the standard LOM doesn’t meets the particular needs of serious games.