Programming education for the mechanisms of image recognition through a data science perspective

Abstract

Artificial intelligence (AI) has been developing rapidly. Demand in Japan and abroad for the development of human resources who can utilize data science and AI is growing. Technology and home economics topics in junior high school are central in compulsory education, but the practice of teaching AI as a subject has just begun. Therefore, this study developed a seven-hour instructional process for experiential learning of the mechanism of AI and incorporated a data science perspective using image recognition, an AI technology, as the subject.

The program was implemented, and its effectiveness was verified. In the class, students learned the process of image recognition, the relationship between network and AI, and the advantages and disadvantages of AI using the Teachable Machine, Proguru, and teacher-developed sample applications, respectively. The students were taught to acquire knowledge and skills related to AI through experiential learning. Consequently, it was confirmed that the students understood the mechanism of AI through firsthand activities, considered their own relationship with AI, and speculated the advantages and disadvantages of AI in the future society.