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http://dx.doi.org/10.14352/jkaie.2019.23.6.639

Designing the Instructional Framework and Cognitive Learning Environment for Artificial Intelligence Education through Computational Thinking  

Shin, Seungki (Computer Science Education, Mary Lou Fulton Teachers College, Arizona State University)
Publication Information
Journal of The Korean Association of Information Education / v.23, no.6, 2019 , pp. 639-653 More about this Journal
Abstract
The purpose of this study is to design an instructional framework and cognitive learning environment for AI education based on computational thinking in order to ground the theoretical rationale for AI education. Based on the literature review, the learning model is proposed to select the algorithms and problem-solving models through the abstraction process at the stage of data collection and discovery. Meanwhile, the instructional model of AI education through computational thinking is suggested to enhance the problem-solving ability using the AI by performing the processes of problem-solving and prediction based on the stages of automating and evaluating the selected algorithms. By analyzing the research related to the cognitive learning environment for AI education, the instructional framework was composed mainly of abstraction which is the core thinking process of computational thinking through the transition from the stage of the agency to modeling. The instructional framework of AI education and the process of constructing the cognitive learning environment presented in this study are characterized in that they are based on computational thinking, and those are expected to be the basis of further research for the instructional design of AI education.
Keywords
AI Education; Computational Thinking; Computer Science Education; Cognitive Learning Environment; Framework;
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Times Cited By KSCI : 5  (Citation Analysis)
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