SIMVA: Serious Games Learning Analytics Based on Standards and Open Code
Résumé
Game Learning Analytics (GLA) collects game player interaction data that can be analyzed to offer insights into player behavior and support stakeholders such as developers and educators in understanding the learning process. However, current GLA methods are usually complex and costly to implement, with proprietary data formats and software, and too technology-dependent, limiting their applicability in real scenarios. To address these issues, we created SIMVA (SIMple VAlidator), an open-source, standards-based platform designed to simplify GLA applied to serious games. SIMVA uses the IEEE xAPI standard to collect and store data, facilitating player tracking and basic analysis/visualization. Our approach also allows for easy integration of various data storage systems (i.e. Learning Record Store) and different trackers, offering full data ownership to stakeholders. SIMVA also enables and simplifies game validation processes, supporting different experimental designs (e.g., control groups, A/B testing) and integrates pre-post questionnaires linked to player analytics data via anonymized codes. This integration supports the analysis of both quantitative and qualitative data, enhancing the assessment of the educational impact of games. Additionally, SIMVA is designed to simplify compliance with EU GDPR data privacy requirements. Overall, SIMVA offers a comprehensive open-code platform for both GLA and serious game validation. SIMVA will contribute to improving game effectiveness and to provide credible evidence of serious games educational value.
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