Abstract
Programming skills (PS) are indispensable abilities in the information age, but the current research on PS cultivation mainly focuses on the teaching methods and lacks the analysis of program features to explore the differences in learners’ PS and guide programming learning. Therefore, the purpose of this study aims to explore horizontal differences and vertical changes in PS of learners aged 18 to 25 and facilitate the discovery of programming features and behaviors to guide the acquisition of PS through an experiment of statistical analysis and cluster analysis of 2,400 Python programs in four programming tasks. The research found the characteristics and main differences of PS reflected in the function call, interactive loop and several structures nesting. Simple programming task to medium-difficulty programming task is the most important link in programming learning. Furthermore, the research also showed that the difference in program structure is the core and foundation. The difference in type and quantity in simple structure, nested structure and mixed-use of structures is regular, which is an important factor to determine whether the program runs efficiently and whether the programming task can be solved. Finally, some heuristic ideas were put forward to help learners optimize programs and solve programming difficulties, which was of great guiding significance to PS learning.
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This study was funded by the National Natural Science Foundation of China (Grant Number 61977031).
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Zhang, W., Zeng, X., Wang, J. et al. An analysis of learners’ programming skills through data mining. Educ Inf Technol 27, 11615–11633 (2022). https://doi.org/10.1007/s10639-022-11079-4
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DOI: https://doi.org/10.1007/s10639-022-11079-4