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. The frequencies of viewing course, completing feedback, adding discussion, adding posts, updating posts and viewing discussions on the forum in active group are much higher than those in inactive group. In each group, students’ learning behavior patterns, i.e., the association rules between activities are derived from the transaction data for the LMS. The cluster analysis shows that students in active group often view course, startcomplete feedback, view folder, add discussion forum, add post forum, update post  forum,  and  view  discussion  forum,  after  keep  in  touch  with  teachers  or classmates by writing messages. Students in the inactive group often remember to logout  from  the  system,  they  pay  more  attention  to  the  security  of  personal information than students in active group, and often up data their real-time status. 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.