머신러닝 이해 및 활용을 위한 초등 AI 융합 수업 모형 및 설계원리 개발

Abstract

As AI is actively applied in primary and secondary education, AI-integrated classes that creatively solve subject-related problems by merging AI knowledge and subject knowledge have emerged. Therefore, it is necessary to systematically implement AI-integrated classes in elementary schools to understand and apply machine learning, a representative AI model commonly used for problem-solving. However, since elementary students require mathematical knowledge at the middle school level or higher to understand machine learning, there is a need for AI-integrated classes that help students intuitively grasp and apply machine learning. To design these AI-integrated classes, it is essential to integrate design principles by considering AI, integration, problem-solving, and the elementary context, and to apply them appropriately in the instruction procedure. However, teachers unfamiliar with AI-integrated classes lack standardized and concrete guidelines to refer for class design. Therefore, it is necessary to develop models and design principles to guide elementary teachers in effectively designing AI-integrated classes. This study developed an AI-integrated instruction model and design principles for understanding and applying machine learning in the elementary school context. To evaluate the applicability and effectiveness of the developed model and design principles, the study conducted pre- and post-surveys and interviews with fifth and sixth-grade students. As a result, it was confirmed that the model and design principles for AI-integrated classes significantly improved students' understanding of data, machine learning concepts, machine learning model development, and machine learning model application. This study provides practical guidelines on how to develop and implement AI-integrated classes in elementary schools to build the capacity to understand and utilize machine learning.