Learning analytics and governance of the digital learning process

E-learning platforms collect a large amount of data on online courses, which progressively evolve towards complex and increasingly heterogeneous educational models. It is then necessary to pass the training's verification as linked to the observable results (completion status and results of the test), in favor of a global representation of the phenomena that positively or negatively affect the user experience. For this reason, we developed a model of analysis of the tracking data starting from the experiences of digital learning operators to create a tool capable of synthesizing all aspects of training. The developed Macro Index (and sub-indexes) makes comparable (online, classroom, blended) courses through a unified analysis model. It can discriminate different experiences and indicate the expected outcomes based on previous similar data, guiding the tutors in the differentiated intervention methods to support and facilitate learning.