Factors Affecting Compilable State at Each Keystroke in CS1

Steven Scott, A Hellas, J Leinonen, John Edwards

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

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Abstract

In this paper, we analyze keystroke log data from two introductory programming courses from two distinct contexts to investigate the proportion of events that compile, how this relates to contextual factors, the progression of programs, and academic outcomes. We find that, as students write their programs, frequency of compile and run events increases as does the proportion of events that compile. We also find a spike in the number of compile and run events as a program nears completion, that the proportion of events that compile varies by assignment, length of program, and programming context, that real-time IDE error diagnostics lead to higher proportion of events that are in compilable state, and that a student’s awareness of their compilable state is correlated with exam score while the amount of time they spend in an uncompilable state is not. Among the practical implications of our work are the fact that researchers cannot rely on frequency of compilation remaining constant through an assignment and a call to researchers and practitioners to design pedagogies that enhance student awareness of their compilable state.
Original languageEnglish
Title of host publication2023 IEEE/ACM 45th International Conference on Software Engineering: Software Engineering Education and Training (ICSE-SEET), 14-20 May 2023Engineering Education And Training, Icse-seet
PublisherIEEE
Pages314-323
Number of pages10
ISBN (Electronic)979-8-3503-2259-0
DOIs
Publication statusPublished - 2023
MoE publication typeA4 Conference publication
EventInternational Conference on Software Engineering: Software Engineering Education and Training - Melbourne, Australia
Duration: 14 May 202320 May 2023
Conference number: 45

Publication series

NameIEEE/ACM International Conference on Software Engineering: Software Engineering Education and Training
ISSN (Electronic)2832-7578

Conference

ConferenceInternational Conference on Software Engineering: Software Engineering Education and Training
Abbreviated titleICSE-SEET
Country/TerritoryAustralia
CityMelbourne
Period14/05/202320/05/2023

Keywords

  • Educational data mining
  • Keystroke analysis
  • Keystroke data
  • Predicting performance
  • Programming process data

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