In this paper, we extend existing research on using geometric features extracted from trajectory data to understand student behavioral patterns and learning outcome. We analyzed 910,661 trajectories data from 390 students who played the KitKit School, a mathematics educational game. As a result of factor analysis, three behavioral patterns are computed: conflict, wavering, and locomotion. A conflict pattern is the degree of curvature of trajectory and implies the degree of decision conflict. A wavering pattern is the number of times when the directions of a trajectory change and refers to the level of confusion a user may feel between choices. Locomotion pattern is the trajectory length of a user's movement while making a choice. The correlation analysis results show that conflict (r=-0.145, p=0.004) and wavering (r=-0.100, p=0.049) negatively correlated with the learning outcome. There is no significant correlation between locomotion and learning outcome (r=0.076, p=0.133). The contributions of this paper are (1) Identification of three types of student behavioral patterns using geometric features of trajectories: conflict, wavering, and locomotion (2) Findings on a negative relationship between learning outcome and the two types of behavioral patterns, conflict and wavering.