A Dataset of Scratch Programs: Scraped, Shaped and Scored

Efthimia Aivaloglou, Felienne Hermans, Jesús Moreno-León, Gregorio Robles

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

29 Citations (Scopus)
18 Downloads (Pure)


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.
Original languageEnglish
Title of host publicationProceedings - 2017 IEEE/ACM 14th International Conference on Mining Software Repositories, MSR 2017
Place of PublicationLos Alamitos, CA
Number of pages4
ISBN (Electronic)978-1-5386-1544-7
Publication statusPublished - 2017
EventMSR 2017: 14th International Conference on Mining Software Repositories - Buenos Aires, Argentina
Duration: 20 May 201721 May 2017
Conference number: 14


ConferenceMSR 2017
Abbreviated titleMSR
CityBuenos Aires
Internet address


  • Scratch
  • dataset
  • computing education


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