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http://dx.doi.org/10.22156/CS4SMB.2020.10.08.173

A Study on the Effectiveness of Algorithm Education Based on Problem-solving Learning  

Lee, Youngseok (KNU College of Liberal Arts and Sciences, Kangnam University)
Publication Information
Journal of Convergence for Information Technology / v.10, no.8, 2020 , pp. 173-178 More about this Journal
Abstract
In the near future, as artificial intelligence and computing network technology develop, collaboration with artificial intelligence (AI) will become important. In an AI society, the ability to communicate and collaborate among people is an important element of talent. To do this, it is necessary to understand how artificial intelligence based on computer science works. An algorithmic education focused on problem solving and learning is efficient for computer science education. In this study, the results of an assessment of computational thinking at the beginning of the semester, a satisfaction survey at the end of the semester, and academic performance were compared and analyzed for 28 students who received algorithmic education focused on problem-solving learning. As a result of diagnosing students' computational thinking and problem-solving learning, teaching methods, lecture satisfaction, and other environmental factors, a correlation was found, and regression analysis confirmed that problem-solving learning had an effect on improving lecture satisfaction and computational thinking ability. For algorithmic education, if you pursue a problem-solving learning technique and a way to improve students' satisfaction, it will help students improve their problem-solving skills.
Keywords
Problem-solving Learning; Computational Thinking; Software Education; Learning Satisfaction; Algorithm Education;
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Times Cited By KSCI : 13  (Citation Analysis)
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