- Computing education research (CER) is a rapidly advancing discipline, offering vast potential for data-driven, secondary research or replication studies. Although gathering and analyzing data for research seem straightforward, making research data publicly available to the community remains a challenge. Likewise, finding and reusing high-quality, prominent, and well-documented research data proves to be a daunting task. In this working group paper, the authors present their search for available datasets in the CER context (e.g., in databases and repositories). The available datasets are further analyzed using a newly developed metadata scheme and presented to the community as a resource. The second component of this work is a summary of the community’s perspective and concerns on publishing their research data, which has been gathered through a survey among 52 computing education researchers. Based on this status quo, this report presents recommendations for measures and future steps for the community to become more accessible andComputing education research (CER) is a rapidly advancing discipline, offering vast potential for data-driven, secondary research or replication studies. Although gathering and analyzing data for research seem straightforward, making research data publicly available to the community remains a challenge. Likewise, finding and reusing high-quality, prominent, and well-documented research data proves to be a daunting task. In this working group paper, the authors present their search for available datasets in the CER context (e.g., in databases and repositories). The available datasets are further analyzed using a newly developed metadata scheme and presented to the community as a resource. The second component of this work is a summary of the community’s perspective and concerns on publishing their research data, which has been gathered through a survey among 52 computing education researchers. Based on this status quo, this report presents recommendations for measures and future steps for the community to become more accessible and establish open data practices. We thus emphasize the potential of making research data available to enhance productivity, transparency, and reproducibility in the CER community.…


Metadaten| Author: | Natalie KieslerORCiD, John ImpagliazzoORCiD, Katarzyna BiernackaORCiD, Amanpreet KapoorORCiD, Zain KazmiORCiD, Sujeeth Goud RamagoniORCiD, Aamod SaneORCiD, Keith TranORCiD, Shubbhi TanejaORCiD, Zihan WuORCiD |
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| DOI: | https://doi.org/10.1145/3598579.3689378 |
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| Parent Title (English): | Working Group Reports on 2023 ACM Conference on Global Computing Education |
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| Publisher: | ACM |
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| Place of publication: | New York, NY, USA |
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| Document Type: | conference proceeding (article) |
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| Language: | English |
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| Date of first Publication: | 2024/09/24 |
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| Reviewed: | Begutachtet/Reviewed |
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| Release Date: | 2024/12/18 |
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| Tag: | open data, open science, datasets, reusing data, computing education, programming process data, secondary research, educational data mining |
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| Pagenumber: | 30 |
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| First Page: | 31 |
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| Last Page: | 60 |
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| institutes: | Fakultät Informatik |
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| Research Themes: | Digitalisierung & Künstliche Intelligenz |
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| Licence (German): | Creative Commons - CC BY-NC-ND - Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International |
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