DOI

The process of writing code and use of features in an integrated development environment (IDE) is a fruitful source of data in computing education research. Existing studies use records of students' actions in the IDE, consecutive code snapshots, compilation events, and others, to gain deep insight into the process of student programming. In this paper, we present a set of tools for collecting and processing data of student activity during problem-solving. The first tool is a plugin for IntelliJ-based IDEs (PyCharm, IntelliJ IDEA, CLion). By capturing snapshots of code and IDE interaction data, it allows to analyze the process of writing code in different languages-Python, Java, Kotlin, and C++. The second tool is designed for the post-processing of data collected by the plugin and is capable of basic analysis and visualization. To validate and showcase the toolkit, we present a dataset collected by our tools. It consists of records of activity and IDE interaction events during solution of programming tasks by 148 participants of different ages and levels of programming experience. We propose several directions for further exploration of the dataset.

Original languageEnglish
Title of host publicationSIGCSE 2021 - Proceedings of the 52nd ACM Technical Symposium on Computer Science Education
PublisherAssociation for Computing Machinery
Pages495-501
Number of pages7
ISBN (Electronic)9781450380621
DOIs
StatePublished - 3 Mar 2021
Event52nd ACM Technical Symposium on Computer Science Education, SIGCSE 2021 - Virtual, Online, United States
Duration: 13 Mar 202120 Mar 2021

Conference

Conference52nd ACM Technical Symposium on Computer Science Education, SIGCSE 2021
Country/TerritoryUnited States
CityVirtual, Online
Period13/03/2120/03/21

    Scopus subject areas

  • Computer Science(all)
  • Education

    Research areas

  • activity tracking, code tracking, ide instrumentation, programming education

ID: 78246208