Extracting typing game keystroke patterns as potential indicators of programming aptitude

Abstract

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This study attempted to determine whether individuals possess programming aptitude solely based on keystroke information from typing games where participants type computer programs. The participants were students enrolled in university programming courses. The results indicated that using typing speed alone as an indicator achieved an accuracy of 0.71, while employing a custom machine learning model achieved an accuracy of 0.83. Additionally, it was found that individuals with programming aptitude tended to type the enter key relatively slower compared to other keys.

Keywords

• typing game
• programming aptitude
• machine learning
• programming education
• keystroke analysis