The Effect of Prior Programming Experience on the Use of Binary Tree Learning System for the Promotion of Computational Thinking

Abstract

This study examined how block-type programming experience and coding experience in a
programming language affect "Computational Thinking (CT)" experience using a binary tree learning
system useful for developing CT. The authors have developed a binary tree learning system using a figure
classification to foster computational thinking and show that it effectively fosters CT. Binary tree is also
used in learning programming and can be constructed using the same approach to solve a branching
Solid State Technology
Volume: 63 Issue: 1s
Publication Year: 2020
747
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programming problem. Therefore, the previous programming experience may affect CT training using the
binary tree. To confirm this, we examined the impact of block-type programming experience and
programming experience on CT scores before and after system experience. As a result, no effect of prior
programming experience on CT scores. Therefore, it is thought to be unnecessary to consider the prior
programming experience when conducting CT training using the binary tree. This indicates that the binary
tree learning system is adequate for novice learners, such as the primary students who have no programming
experience or are not good at programming.