A Framework for Supporting Non-Native English Speakers in Programming Education

Since the majority of programming languages, documentation, and instructional materials are in English, learning programming can be particularly difficult for non-native English speakers. Although previous research has highlighted these problems, little is known about the most effective pedagogical approaches for teaching programming to non-native English speakers. By examining the experiences of Japanese university students learning Python and concentrating on how language competency and programming experience influence their learning requirements, this study used clustering analysis to divide the students into three groups: intermediate learners (moderately proficient in programming with a dependence on translation tools), advanced learners (higher proficiency but difficulties with debugging and code optimization), and beginners (low programming experience and fluency in English). Based on our findings, we developed a framework for improving programming education that incorporates multilingual resources, instructional methodologies, adaptive learning technologies, and mentorship programs.