Concept maps can help students learn more meaningfully. According to test scores only, students were divided into three groups of high-score, middle-score and low-score, in the previous works, researchers then applied data mining association rule technique to analysis different student groups' assessment data to construct corresponding concept maps. However, for considering more accurate to evaluate students' performance states and various possible distributions of students' assessment data, in this research, we apply student-problem chart to obtain students response patterns for grouping purpose. We generate six response pattern groups for 30131 students. Using association rule data mining technique also, we will construct more precise concept maps for students of different groups individually.