In a hospital, clinical teachers must also care for patients, so there is less time for the teaching of clinical courses, or for discussing clinical cases with interns. However, electronic learning (e-learning) can complement clinical skills education for interns in a blended-learning process. Students discuss and interact with classmates in an e-learning collaborative environment. E-learning can assist clinical training and provides a collaborative environment, but every student has individual learning preferences on the e-learning platform. A typical platform, such as a learning management system (LMS) does not provide individual learning activities for every student. This paper clusters students into two groups: active and inactive groups. In each group, students' learning behavior patterns, i.e., the association rules for activities, are derived from the transaction data for the LMS. The cluster to which a student belongs defines the online learning behaviors, from the activity association rules. The method then provides individual preferred activities. Teachers instruct students in accordance with their aptitude, as derived from the learning behavior pattern. The cluster analysis shows that students in active group often view teaching videos after completing feedback. Students in the inactive group often view teaching materials after adding posts on a forum. [For the complete proceedings, see ED557189.]