Value trace problems with assisting references for Python programming self-study

San Hay Mar Hay Mar Shwe, Nobuo Funabiki, Yan Watequlis Syaifudin, Phyu Phyu Tar, Htoo Htoo Sandi Kyaw, Hnin Aye Thant, Wen Chung Kao, Nandar Win Min, Thandar Myint, Ei Ei Htet

Research output: Contribution to journalArticlepeer-review

Abstract

Purpose: This study aims to present the value trace problem (VTP) for Python programming self-study, by extending the works for Java programming learning assistant system. In total, 130 VTP instances are generated using Python codes in textbooks and websites that cover basic/advanced grammar topics, fundamental data structures and algorithms and two common library usages. Besides, assisting references on Python programming topics related to the VTP instances are introduced to assist novice learners in solving them efficiently. Design/methodology/approach: PyPLAS offers the VTP to study grammar topics and library usage through code reading. A VTP instance asks a learner to trace the actual values of important variables or output messages in the given source code. The correctness of any answer is checked through string matching. Findings: The applications to 48 undergraduate students in Myanmar and Indonesia confirm the validity of the proposal in Python programming self-studies by novice learners. Originality/value: The applications to 48 undergraduate students in Myanmar and Indonesia confirm the validity of the proposal in Python programming self-studies by novice learners.

Original languageEnglish
Pages (from-to)287-299
Number of pages13
JournalInternational Journal of Web Information Systems
Volume17
Issue number4
DOIs
Publication statusPublished - 2021

Keywords

  • Coding reading
  • Grammar concepts
  • Library usage
  • NumPy
  • Offline answering function
  • Pandas
  • Python programming
  • Value trace problem

ASJC Scopus subject areas

  • Information Systems
  • Computer Networks and Communications

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