Trade-off between interoperability and data collection performance when designing an architecture for learning analytics

Abstract The heterogeneity of external systems that can be connected in an e-learning environment can impose interoperability and performance requirements for recording and storing the learning data. Web-based protocols have been developed to improve e-learning systems’ interoperability and capability to perform meaningful analytics. The present paper describes a web-based learning environment aimed at training how to command and control unmanned autonomous vehicles, provided with analytic capabilities. It integrates an external web content management system and a simulation engine that present different performance requirements for recording all significant events that occur during the learning process. Its record store construction, based on standard interoperability protocols, is explored here from the performance viewpoint. The tests that were conducted to assess regular data stores used for learning analytics show that performance should not be overlooked when constructing and deploying learning analytics systems.