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A Dataset of Scratch Programs : Scraped, Shaped and Scored. / Aivaloglou, Efthimia; Hermans, Felienne; Moreno-León, Jesús; Robles, Gregorio.

Proceedings - 2017 IEEE/ACM 14th International Conference on Mining Software Repositories, MSR 2017. Los Alamitos, CA : IEEE Computer Society, 2017. p. 511-514.

Research output: Scientific - peer-reviewConference contribution

Harvard

Aivaloglou, E, Hermans, F, Moreno-León, J & Robles, G 2017, A Dataset of Scratch Programs: Scraped, Shaped and Scored. in Proceedings - 2017 IEEE/ACM 14th International Conference on Mining Software Repositories, MSR 2017. IEEE Computer Society, Los Alamitos, CA, pp. 511-514, MSR 2017, Buenos Aires, Argentina, 20/05/17. DOI: 10.1109/MSR.2017.45

APA

Aivaloglou, E., Hermans, F., Moreno-León, J., & Robles, G. (2017). A Dataset of Scratch Programs: Scraped, Shaped and Scored. In Proceedings - 2017 IEEE/ACM 14th International Conference on Mining Software Repositories, MSR 2017 (pp. 511-514). Los Alamitos, CA: IEEE Computer Society. DOI: 10.1109/MSR.2017.45

Vancouver

Aivaloglou E, Hermans F, Moreno-León J, Robles G. A Dataset of Scratch Programs: Scraped, Shaped and Scored. In Proceedings - 2017 IEEE/ACM 14th International Conference on Mining Software Repositories, MSR 2017. Los Alamitos, CA: IEEE Computer Society. 2017. p. 511-514. Available from, DOI: 10.1109/MSR.2017.45

Author

Aivaloglou, Efthimia ; Hermans, Felienne ; Moreno-León, Jesús ; Robles, Gregorio. / A Dataset of Scratch Programs : Scraped, Shaped and Scored. Proceedings - 2017 IEEE/ACM 14th International Conference on Mining Software Repositories, MSR 2017. Los Alamitos, CA : IEEE Computer Society, 2017. pp. 511-514

BibTeX

@inbook{26bc55fd284e4fc5bbca02857e84fbd7,
title = "A Dataset of Scratch Programs: Scraped, Shaped and Scored",
abstract = "Scratch is increasingly popular, both as an introductory programming language and as a research target in the computing education research field. In this paper, we present a dataset of 250K recent Scratch projects from 100K different authors scraped from the Scratch project repository. We processed the projects' source code and metadata to encode them into a database that facilitates querying and further analysis. We further evaluated the projects in terms of programming skills and mastery, and included the project scoring results. The dataset enables the analysis of the source code of Scratch projects, of their quality characteristics, and of the programming skills that their authors exhibit. The dataset can be used for empirical research in software engineering and computing education.",
keywords = "Scratch, dataset, computing education",
author = "Efthimia Aivaloglou and Felienne Hermans and Jesús Moreno-León and Gregorio Robles",
year = "2017",
doi = "10.1109/MSR.2017.45",
pages = "511--514",
booktitle = "Proceedings - 2017 IEEE/ACM 14th International Conference on Mining Software Repositories, MSR 2017",
publisher = "IEEE Computer Society",
address = "United States",

}

RIS

TY - CHAP

T1 - A Dataset of Scratch Programs

T2 - Scraped, Shaped and Scored

AU - Aivaloglou,Efthimia

AU - Hermans,Felienne

AU - Moreno-León,Jesús

AU - Robles,Gregorio

PY - 2017

Y1 - 2017

N2 - Scratch is increasingly popular, both as an introductory programming language and as a research target in the computing education research field. In this paper, we present a dataset of 250K recent Scratch projects from 100K different authors scraped from the Scratch project repository. We processed the projects' source code and metadata to encode them into a database that facilitates querying and further analysis. We further evaluated the projects in terms of programming skills and mastery, and included the project scoring results. The dataset enables the analysis of the source code of Scratch projects, of their quality characteristics, and of the programming skills that their authors exhibit. The dataset can be used for empirical research in software engineering and computing education.

AB - Scratch is increasingly popular, both as an introductory programming language and as a research target in the computing education research field. In this paper, we present a dataset of 250K recent Scratch projects from 100K different authors scraped from the Scratch project repository. We processed the projects' source code and metadata to encode them into a database that facilitates querying and further analysis. We further evaluated the projects in terms of programming skills and mastery, and included the project scoring results. The dataset enables the analysis of the source code of Scratch projects, of their quality characteristics, and of the programming skills that their authors exhibit. The dataset can be used for empirical research in software engineering and computing education.

KW - Scratch

KW - dataset

KW - computing education

U2 - 10.1109/MSR.2017.45

DO - 10.1109/MSR.2017.45

M3 - Conference contribution

SP - 511

EP - 514

BT - Proceedings - 2017 IEEE/ACM 14th International Conference on Mining Software Repositories, MSR 2017

PB - IEEE Computer Society

ER -

ID: 12908712