TY - GEN
T1 - Learning Programming for Non-Native English-Speaking Students
T2 - 56th Annual SIGCSE Technical Symposium on Computer Science Education, SIGCSE TS 2025
AU - Martono, Niken Prasasti
AU - Ohwada, Hayato
N1 - Publisher Copyright:
© 2025 Copyright held by the owner/author(s).
PY - 2025/2/18
Y1 - 2025/2/18
N2 - For non-native English speakers, learning programming presents unique challenges, particularly in languages like Python, which heavily rely on English syntax and documentation. This study explores the challenges faced by non-native English-speaking Japanese university students enrolled in introductory Python programming courses. A survey was held to examined various aspects of their learning experience, including their programming proficiency, English fluency, use of translation tools, and the impact of bilingual resources on their learning. Clustering analysis was employed to group the participants into three distinct clusters: beginners, intermediate learners, and advanced learners. Cluster 0 (beginners) had low programming experience and English fluency, relying on non-English materials and translation tools. Cluster 1 (intermediate) showed moderate skills, using bilingual resources and translation aids. Cluster 2 (advanced) had higher proficiency but faced challenges with debugging and code optimization. Our findings highlight the need for tailored resources to support students navigating English-based programming environments.
AB - For non-native English speakers, learning programming presents unique challenges, particularly in languages like Python, which heavily rely on English syntax and documentation. This study explores the challenges faced by non-native English-speaking Japanese university students enrolled in introductory Python programming courses. A survey was held to examined various aspects of their learning experience, including their programming proficiency, English fluency, use of translation tools, and the impact of bilingual resources on their learning. Clustering analysis was employed to group the participants into three distinct clusters: beginners, intermediate learners, and advanced learners. Cluster 0 (beginners) had low programming experience and English fluency, relying on non-English materials and translation tools. Cluster 1 (intermediate) showed moderate skills, using bilingual resources and translation aids. Cluster 2 (advanced) had higher proficiency but faced challenges with debugging and code optimization. Our findings highlight the need for tailored resources to support students navigating English-based programming environments.
KW - Python programming
KW - computer science education
KW - learning programming
KW - non-native English speakers
UR - http://www.scopus.com/inward/record.url?scp=86000252920&partnerID=8YFLogxK
U2 - 10.1145/3641555.3705211
DO - 10.1145/3641555.3705211
M3 - Conference contribution
AN - SCOPUS:86000252920
T3 - SIGCSE TS 2025 - Proceedings of the 56th ACM Technical Symposium on Computer Science Education
SP - 1539
EP - 1540
BT - SIGCSE TS 2025 - Proceedings of the 56th ACM Technical Symposium on Computer Science Education
PB - Association for Computing Machinery, Inc
Y2 - 26 February 2025 through 1 March 2025
ER -