Concept maps, visual representations of knowledge, are used in an educational context as a way to represent students' knowledge, and identify mental models of students; however there is a limitation of using concept mapping due to its difficulty to evaluate the concept maps. A concept map has a complex structure which is composed of concepts and their relationships that often have a weighted direction. This work explores the feasibility of the analysis of concept maps using data mining methods, and investigate the possibility of using concept maps as a research tool to understand college student's learning. A total of 111 college students participated in this study. The findings from frequent concept mining and sub-concept map mining suggest that students expect a traditional way of learning. The study also shows a promising area of further study in the area of data mining in education. (Contains 2 figures and 1 table.) [For the complete proceedings, "Proceedings of the International Conference on Educational Data Mining (EDM) (5th, Chania, Greece, June 19-21, 2012)," see ED537074.]