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http://dx.doi.org/10.15267/keses.2020.39.1.117

A Study on the Application of Artificial Intelligence in Elementary Science Education  

Shin, Won-Sub (Seoul National University of Education)
Shin, Dong-Hoon (Seoul National University of Education)
Publication Information
Journal of Korean Elementary Science Education / v.39, no.1, 2020 , pp. 117-132 More about this Journal
Abstract
The purpose of this study is to investigate elementary school teachers' awareness of Artificial Intelligence (AI) and find out how to apply it in elementary science education. The survey was conducted online and involved 95 teachers working in the metropolitan area. The results of this study are as follows. First, teachers need to learn about the general characteristics of AI and how to apply it to education. Second, science classes had the highest preference for AI among elementary school subjects. Third, the preference for AI application by elementary science field was 68.4% for earth and space, 54.7% for exercise and energy, 32.6% for matter, 27.4% for life. Fourth, AI-based Science Education (AISE) teaching- learning strategies were developed based on AI characteristics and the changing perspective of elementary science education, AISE's teaching-learning strategies are five: 'automation', 'individualization', 'diversification', 'cooperation' and 'creativity' and teachers can use them in teaching design, class practice and evaluation stages. Finally, the creative problem-solving Doing Thinking Making Sharing (DTMS) model was devised to implement the creativity strategy in AISE. This model consists of four-steps teaching courses: Doing, Thinking, Making and Sharing based on the empirical learning theory. In the future, follow-up research is needed to verify the effectiveness of this model by applying it to elementary science education.
Keywords
artificial intelligence; elementary science education; AI-based science education (AISE); teaching-learning strategy; empirical learning theory; doing thinking making sharing (DTMS) model;
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