Quantitative Learning Effect Evaluation of Programming Learning Tools accepted at TALE 2017 as full paper


Daisuke Saito, Ayana Sasaki, Hironori Washizaki, Yoshiaki Fukazawa, Yusuke Muto, “Quantitative Learning Effect Evaluation of Programming Learning Tools,” 6th IEEE International Conference on Teaching, Assessment, and Learning for Engineering (TALE2017), 12-14 December 2017, The Education University of Hong Kong, Tai Po, Hong Kong

Children can learn programming using different tools. Understanding how the characteristics and features of each tool impact the learning effect will enhance learning. However, the impact of specific tools on the learning effect is unclear. In this study, we conducted a workshop to evaluate the characteristics and features of six tools on the learning effect. Our study reveals that the learning effect clearly differs between the six tools.