In this paper, we describe a theoretically-grounded data mining approach to identify types of collaborative problem solvers based on students' interactions with an online simulation-based task about electronics concepts. In our approach, we developed an ontology to identify the theoretically-grounded features of collaborative problem solving (CPS). After interaction with the task, students' log files were tagged for the presence of 11 CPS skills from the ontology. The frequencies of the skills were clustered to identify four unique profiles of collaborative problem solvers--Chatty Doers, Social Loafers, Group Organizers, and Active Collaborators. Relationships among cluster membership, task performance, and external ratings of collaboration provide initial validity evidence that these are meaningful profiles of collaborative problem solvers. [For the full proceedings, see ED593090.]