Clustering, a machine learning technique within the domain of artificial intelligence, groups data based on similarities between samples. The process of learning analytics varies depending on an organization’s educational goals and the lesson’s objectives, making the selection of methods for collecting and analyzing learning logs important for both teachers and students. Although clustering software can assist in this process, careful consideration is required. In recent years, traditional statistical analysis has been complemented by the use of machine learning techniques in artificial intelligence. However, there are several machine learning methods, and if applied incorrectly, there is a risk of obtaining incorrect results. Therefore, it is important to select a strategy that is appropriate for the dataset. This chapter focuses on the use of unsupervised learning for learning analytics, emphasizing the responsibilities and precautions teachers should take when using clustering techniques to analyze learning patterns. It also provides examples of analyses conducted with actual learning logs.