Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование
TaskTracker-tool : A Toolkit for Tracking of Code Snapshots and Activity Data during Solution of Programming Tasks. / Lyulina, Elena; Birillo, Anastasiia; Kovalenko, Vladimir; Bryksin, Timofey.
SIGCSE 2021 - Proceedings of the 52nd ACM Technical Symposium on Computer Science Education. Association for Computing Machinery, 2021. стр. 495-501.Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование
}
TY - GEN
T1 - TaskTracker-tool
T2 - 52nd ACM Technical Symposium on Computer Science Education, SIGCSE 2021
AU - Lyulina, Elena
AU - Birillo, Anastasiia
AU - Kovalenko, Vladimir
AU - Bryksin, Timofey
N1 - Publisher Copyright: © 2021 ACM. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2021/3/3
Y1 - 2021/3/3
N2 - 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.
AB - 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.
KW - activity tracking
KW - code tracking
KW - ide instrumentation
KW - programming education
UR - http://www.scopus.com/inward/record.url?scp=85103312858&partnerID=8YFLogxK
UR - https://www.mendeley.com/catalogue/7b09ccda-7550-3e1b-8cd4-725980196ebc/
U2 - 10.1145/3408877.3432534
DO - 10.1145/3408877.3432534
M3 - Conference contribution
AN - SCOPUS:85103312858
SP - 495
EP - 501
BT - SIGCSE 2021 - Proceedings of the 52nd ACM Technical Symposium on Computer Science Education
PB - Association for Computing Machinery
Y2 - 13 March 2021 through 20 March 2021
ER -
ID: 78246208