Title
A New Evaluation Metrics for Block-based Python Code
Abstract
The programming education for the students set off a global enthusiasm. The Block-Python programming tools can fill the gap from block-based programming to language coding. However, there is little work focus on the evaluation metrics for block-based python code. The past block-oriented evaluation metrics based on Computational Thinking (CT) were not language-oriented, and program volume was often ignored. In this paper, we propose a new evaluation metrics for block-based python code, which combines the CT dimensions and program volume. The experimental results show that the correlations between the proposed metrics and Halstead, McCabe complexity algorithms are both above 0.7, which is higher than Dr. Scratch.
Year
DOI
Venue
2019
10.1109/ICCE-TW46550.2019.8991838
2019 IEEE International Conference on Consumer Electronics - Taiwan (ICCE-TW)
Keywords
DocType
ISBN
programming education,Block-Python programming tools,block-oriented evaluation metrics,program volume,block-based Python code,CT dimensions
Conference
978-1-7281-3280-8
Citations 
PageRank 
References 
0
0.34
1
Authors
3
Name
Order
Citations
PageRank
Liu Zheng14712.80
Hong Luo200.68
Xiaolin Chai300.34