Herein, we present two studies on how students’ Psychological State of Decision difficulty (PSD) relates to two aspects of learning, i.e., guessing behavior and learning achievement. To measure PSD, we extracted geometric features from trajectories of drag-and-drop touch interactions collected while students aged 7–10 played a math game on a tablet device. In the first study, we explored whether eight geometric features extracted from 97,303 trial trajectories could be grouped to understand students’ PSD. In the second study, we examined whether the two aspects of learning could be predicted using the data collected from 187 students with geometric features indicating their PSD. This work provides empirical evidence that geometric features can be grouped into two types of PSD in the context of learning, including conflict and uncertainty. Moreover, our results demonstrate that data on students’ PSD collected from drag-and-drop trajectories can be used to predict learning.

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.

There has been a growing concern over the huge increase in use of smart media by young children. This study explores the possibility of using augmented-reality(AR) for regulat-ing preschoolers' media usage behavior. With MABLE (mobile application for behavioral learning and education), parents can provide AR-assisted feedback by changing facial expressions and sound effects. When overlaying a smart media, which has MABLE running, in front of a QR marker on a puppet, a facial expression is displayed on top of the puppet's face. A two-week long experiment with 36 parent-child pairs showed that compared to using just the puppet, using MABLE showed higher amount of engage-ment among preschoolers. For the effectiveness of parental mediation in terms of self-control, our data showed mixed results. MABLE had positive effects in that the amount of rule-compliance increased and problematic behaviors de-creased, whereas the level of behavioral dependency on smart media was not influenced.

Acquiring simple arithmetic skills at the preschool level requires repetitive practices. One method for encouraging students to spend longer time practicing is by presenting the skills in an engaging game. As student retention on the game increases, the student will be more likely to acquire the practiced skill since she will have spent more time practicing. In this paper, we examine the relationship between internal locus of control and retention in game-based learning applications for young children using Todo Math, a mobile-based math learning application for children from Pre-K to 2nd grade. We examine 345,783 users' log data to show that when children prefer "free" mode, which has high internal locus of control, their retention on Todo Math is higher than children who prefer "daily" mode, which has high external locus of control. We present three analyses that support our findings using survival analysis, post-hoc analysis, and t-test.