하이브리드 러닝 환경에서의 CT-EL 기반 AI 교육 체제 설계 전략

Abstract

We propose an educational design strategy to enhance the effectiveness of experiential learning-based artificial intelligence education to improve computer thinking skills in a hybrid learning environment. We present four learning experiences (real life problem solving experience, reflective thinking experience, collaborative problem solving experience, AI education experience) that fit the principles of experiential learning (the principle of continuity and the principle of interaction) were developed based on the 4P-based AI education system. We also present four detailed functions for each hybrid learning element (subject knowledge, interaction, hybrid map design and hybrid class management) presenting a teaching strategy on how to apply hybrid learning elements at each stage of 4P-based AI education. Compared to general AI education and CT-EL AI education, CT-EL AI education in hybrid learning environment is more suitable education method for learning experience selection and learning performance evaluation. Therefore, AI education is expected to be systematically operated based on learning experiences and the effectiveness of CT-EL AI education in a hybrid environment is expected to increase.