TY - GEN
T1 - A Study of Grammar-Concept Understanding Problem for Python Programming Learning
AU - Htet, Ei Ei
AU - Shwe, San Haymar
AU - Aung, Soe Thandar
AU - Funabiki, Nobuo
AU - Fajrianti, Evianita Dewi
AU - Sukaridhoto, Sritrusta
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Python Programming has become commonly used among IT and non-IT engineers for a variety of applications such as data analysis, prototyping, web application systems, and embedded systems. It offers rich libraries and short coding capabilities. To further promote this useful language, a high-quality self-study tool has been strongly demanded, since it is still rare to open Python programming courses at universities. In this paper, we study the Grammar-concept Understanding Problem (GUP) for self-study of Python programming by novice students. A GUP instance consists a source code and a set of questions describing the definitions of grammar or library keywords appearing in the code. The correctness of the answer from a student is marked through string matching with the correct keyword. In this study, we selected 114 keywords and common functions, and made the corresponding questions for them. Then, we generated 24 GUP instances with 142 questions and assigned them to 9 students in Okayama University. The results confirmed the effectiveness of the proposal.
AB - Python Programming has become commonly used among IT and non-IT engineers for a variety of applications such as data analysis, prototyping, web application systems, and embedded systems. It offers rich libraries and short coding capabilities. To further promote this useful language, a high-quality self-study tool has been strongly demanded, since it is still rare to open Python programming courses at universities. In this paper, we study the Grammar-concept Understanding Problem (GUP) for self-study of Python programming by novice students. A GUP instance consists a source code and a set of questions describing the definitions of grammar or library keywords appearing in the code. The correctness of the answer from a student is marked through string matching with the correct keyword. In this study, we selected 114 keywords and common functions, and made the corresponding questions for them. Then, we generated 24 GUP instances with 142 questions and assigned them to 9 students in Okayama University. The results confirmed the effectiveness of the proposal.
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U2 - 10.1109/LifeTech53646.2022.9754882
DO - 10.1109/LifeTech53646.2022.9754882
M3 - Conference contribution
AN - SCOPUS:85129161970
T3 - LifeTech 2022 - 2022 IEEE 4th Global Conference on Life Sciences and Technologies
SP - 241
EP - 242
BT - LifeTech 2022 - 2022 IEEE 4th Global Conference on Life Sciences and Technologies
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 4th IEEE Global Conference on Life Sciences and Technologies, LifeTech 2022
Y2 - 7 March 2022 through 9 March 2022
ER -