License: Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/OASIcs.ICPEC.2022.7
URN: urn:nbn:de:0030-drops-166116
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2022/16611/
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Szydłowska, Justyna ; Miernik, Filip ; Ignasiak, Marzena Sylwia ; Swacha, Jakub

Python Programming Topics That Pose a Challenge for Students

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OASIcs-ICPEC-2022-7.pdf (0.6 MB)

Abstract

Learning programming is often considered as difficult, but it would be wrong to assume that all programming topics are equally tough to learn. In this paper, we make use of a gamified programming learning environment submission repository containing records of over 9000 attempts of solving Python exercises to identify topics which pose the largest challenge for students. By comparing students' effort and progress among sets of exercises assigned to respective topics, two topics emerged as especially difficult (Object-oriented programming and Classic algorithms). Also interesting are the identified differences between genders (indicating female students to fare better than male at the initial topics, and the opposite for the most advanced topics), and the scale of effort some students put to succeed with the most difficult exercises (sometimes solved only after tens of failed attempts).

BibTeX - Entry

@InProceedings{szydlowska_et_al:OASIcs.ICPEC.2022.7,
  author =	{Szyd{\l}owska, Justyna and Miernik, Filip and Ignasiak, Marzena Sylwia and Swacha, Jakub},
  title =	{{Python Programming Topics That Pose a Challenge for Students}},
  booktitle =	{Third International Computer Programming Education Conference (ICPEC 2022)},
  pages =	{7:1--7:9},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-229-7},
  ISSN =	{2190-6807},
  year =	{2022},
  volume =	{102},
  editor =	{Sim\~{o}es, Alberto and Silva, Jo\~{a}o Carlos},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2022/16611},
  URN =		{urn:nbn:de:0030-drops-166116},
  doi =		{10.4230/OASIcs.ICPEC.2022.7},
  annote =	{Keywords: learning programming, programming exercises, gamified learning environment, learning Python}
}

Keywords: learning programming, programming exercises, gamified learning environment, learning Python
Collection: Third International Computer Programming Education Conference (ICPEC 2022)
Issue Date: 2022
Date of publication: 11.07.2022

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