How Should We 'Explain in Plain English'? Voices from the Community

Max Fowler, Binglin Chen, Craig Zilles

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

"Explain in plain English"(EipE) questions are seen as an important developmental activity and assessment tool in the research community studying how people learn to program, but they aren't widely used in practice because of difficulty of grading and workload issues. In this paper, we interviewed eleven members of the introductory programming education research community about their thoughts on EipE questions as a whole and how individual borderline student answers should be graded. Through inductive coding of the interview transcripts, we identify: (1) themes relating to how EipE questions should be used in class, (2) the importance of training students to complete EipE questions, (3) standards for the selection and presentation of code in EipE questions, (4) the theoretical and practical considerations relating to grading EipE questions, and (5) English as a second language (ESL) concerns. In addition, we attempt to extrapolate from our observations what the underlying grading process is that faculty are using to grade EipE questions.

Original languageEnglish (US)
Title of host publicationICER 2021 - Proceedings of the 17th ACM Conference on International Computing Education Research
PublisherAssociation for Computing Machinery, Inc
Pages69-80
Number of pages12
ISBN (Electronic)9781450383264
DOIs
StatePublished - Aug 16 2021
Event17th ACM Conference on International Computing Education Research, ICER 2021 - Virtual, Online, United States
Duration: Aug 16 2021Aug 19 2021

Publication series

NameICER 2021 - Proceedings of the 17th ACM Conference on International Computing Education Research

Conference

Conference17th ACM Conference on International Computing Education Research, ICER 2021
Country/TerritoryUnited States
CityVirtual, Online
Period8/16/218/19/21

Keywords

  • EipE
  • explain in plain English
  • interviews
  • qualitative

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Education

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