인공지능과 과학 교과의 체계적인 융합을 위한 교수 학습 모형 개발

Abstract

Objectives The purpose of this study is to develop a teaching-learning model that is the basis for designing and implementing teaching-learning for the systematic convergence of artificial intelligence and science subjects.
 Methods Richey and Klein (2007)'s design and development research method was applied to develop a teaching-learning model for learning that combines science and artificial intelligence modeling and to review its validity. Implications were drawn through comparison and analysis of modeling, a common learning element of the subject, and a teaching and learning model was developed based on this. The teaching-learning model was revised and supplemented several times by reflecting expert review opinions.
 Results In the teaching-learning model, learning is performed on K (knowledge), M (modeling), and B (personality) elements. Through the implementation of the teaching-learning model, an integrated teaching-learning design considering the characteristics of science and artificial intelligence subjects is possible. Because it was developed by reflecting the implications of in-depth comparison and analysis of science and artificial intelligence modeling, effective modeling learning can be executed. Modeling learning applied with the teaching-learning model can be used as a support strategy to solve the difficulties of existing science modeling teaching-learning. First, through teaching and learning to which converged modeling is applied, learners can participate in the entire modeling process relatively easily and conveniently, providing an opportunity to change the perception that the modeling process is difficult. Second, the use of artificial intelligence models and modeling results will be a specific support strategy that can support learners' thinking expression and hypothesis generation, which are pointed out as the biggest difficulty for learners in the process of model construction.
 Conclusions This study provides teaching-learning procedures, activities, detailed strategies, and examples necessary for teaching-learning situations for the effective design and implementation of science and artificial intelligence convergence education. Because of this, it is possible to clearly reveal how science and artificial intelligence convergence education can actually be done in the field. In addition, it is expected that it will be able to present a blueprint that can overlook the entire process of class design and execution for science and artificial intelligence convergence education.