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With the increasing amount of digital learning offers, there is a high demand for individualized, adaptive learning pathways. The paper explores the role of learning analytics to improve qualification processes in educational institutions. E-learning, as a crucial component in educational and organizational learning, is examined for its role in enhancing learner success and motivation. Focusing specifically on Artificial Intelligence, the study aims to investigate how analysis approaches can provide valuable insights into the conceptualization and implementation of individualized learning pathways. In particular, the experimental environment, the use case for data provision and necessary data preparation are described. Furthermore, the application of different clustering methods to learners’ data gathered in the context of e-learning is presented and the findings are discussed.
