Behavioral-pattern exploration and development of an instructional tool for young children to learn AI

Abstract

This study aimed at developing an instructional tool for the artificial intelligence education of young students, and used learning analytics to identify the sequential learning behavioral patterns of students during the process of learning with the instructional tool. The instructional experiment took 9 weeks. The first stage of the course was 5 weeks spent on individual learning of MIT App Inventor and Personal Image Classifier. The second stage was 4 weeks spent on cooperative learning to make a robot car and play a computational thinking board game. In the second stage, the students worked in pairs to make the robot car. Finally, they played the computational thinking board game with the personal image classification application they developed in the first stage and the robot car they made in the second stage. The innovative studies found meaningful behavioral patterns when the young students learned the application of artificial intelligence with the instructional tool developed and proposed in the study.