A Dataset of Scratch Programs

Scraped, Shaped and Scored

Conference paper (2017)

Authors

E.A. Aivaloglou Software Engineering - EEMCS
F.F.J. Hermans Software Engineering - EEMCS
Jesús Moreno-León King Juan Carlos University
Gregorio Robles King Juan Carlos University
Research Group
Software Engineering (EEMCS) (TU Delft)
Copyright: © 2017 E.A. Aivaloglou, F.F.J. Hermans, Jesús Moreno-León, Gregorio Robles
DOI
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https://doi.org/10.1109/MSR.2017.45
Dataset Scratch Computing education
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Published Date

2017

Language

English

Reuse Rights

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Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Software Technology

Research Group

Software Engineering

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.