Learning analytics refers to the processes of generating, collecting, organizing, selecting, critically analysing, scrutinising and interpreting digital evidence (information and data) on learner activity, performance and progress, to inform and improve learning and teaching. Thus, interpreted evidence is used for feedback and recommendations for action to improve the learning experience and results of the learning processes.
Learning analytics relies on several digital techniques such as, for example, data mining, visual data analysis, machine learning, artificial intelligence, digital activity checklists, digital track records, discussion of track records in forums, collaboration track records in shared documents, achievement rubrics, etc.
The teacher can use learning analytics to better trace the learners’ performance, take targeted actions to improve the learners’ learning processes, and identify at-risk learners.