On Students' Ability to Resolve their own Tracing Errors through Code Execution

Mohammed Hassan, Craig Zilles

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

Abstract

When students attempt to solve code-tracing problems, sometimes students make mistakes as they read code that get in the way of correctly solving the problem. In this paper, we explore the degree to which students can correct their misunderstandings by executing the provided code on a computer. Specifically, we performed a qualitative between-subjects think-aloud study to compare what kinds of errors students can resolve by just executing the code versus which they can resolve by using a line-by-line debugger. From observing our participants, two factors appear to be necessary for them to independently resolve their misunderstandings. First, they need to be using a tool that provides visibility into the error itself. When using a tool that provided only the output of the code, our participants could only resolve dataflow-oriented errors. In contrast, when given the ability to step through the code, some of our participants could additionally resolve control-flow errors. Second, the error must affect the output. In all of the cases where students arrived at the correct answer in spite of having errors in their understanding of the code, none corrected their error independent of the tool they were using. Presumably, they were not forced to confront their error because of an incorrect answer. Finally, while necessary, these conditions appear not to be sufficient, as students still need to be able to correctly interpret the information that the tool provides.

Original languageEnglish (US)
Title of host publicationSIGCSE 2022 - Proceedings of the 53rd ACM Technical Symposium on Computer Science Education
PublisherAssociation for Computing Machinery
Pages251-257
Number of pages7
ISBN (Electronic)9781450390705
DOIs
StatePublished - Feb 22 2022
Event53rd Annual ACM Technical Symposium on Computer Science Education, SIGCSE 2022 - Virtual, Online, United States
Duration: Mar 3 2022Mar 5 2022

Publication series

NameSIGCSE 2022 - Proceedings of the 53rd ACM Technical Symposium on Computer Science Education
Volume1

Conference

Conference53rd Annual ACM Technical Symposium on Computer Science Education, SIGCSE 2022
Country/TerritoryUnited States
CityVirtual, Online
Period3/3/223/5/22

Keywords

  • debuggers
  • errors
  • tracing

ASJC Scopus subject areas

  • Computer Science(all)
  • Education

Fingerprint

Dive into the research topics of 'On Students' Ability to Resolve their own Tracing Errors through Code Execution'. Together they form a unique fingerprint.

Cite this