A Systematic Literature Review of Undergraduate Data Science Education Research
Fuente:
arXiv
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| Autores principales: | , , , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| Acceso en línea: | |
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| _version_ | 1866917975290806272 |
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| author | Dogucu, Mine Demirci, Sinem Bendekgey, Harry Ricci, Federica Zoe Medina, Catalina M. |
| author_facet | Dogucu, Mine Demirci, Sinem Bendekgey, Harry Ricci, Federica Zoe Medina, Catalina M. |
| contents | The presence of data science has been profound in the scientific community in almost every discipline. An important part of the data science education expansion has been at the undergraduate level. We conducted a systematic literature review to (1) portray current evidence and knowledge gaps in self-proclaimed undergraduate data science education research and (2) inform policymakers and the data science education community about what educators may encounter when searching for literature using the general keyword 'data science education.' While open-access publications that target a broader audience of data science educators and include multiple examples of data science programs and courses are a strength, significant knowledge gaps remain. The undergraduate data science literature that we identified often lacks empirical data, research questions and reproducibility. Certain disciplines are less visible. We recommend that we should (1) cherish data science as an interdisciplinary field; (2) adopt a consistent set of keywords/terminology to ensure data science education literature is easily identifiable; (3) prioritize investments in empirical studies. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2403_03387 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | A Systematic Literature Review of Undergraduate Data Science Education Research Dogucu, Mine Demirci, Sinem Bendekgey, Harry Ricci, Federica Zoe Medina, Catalina M. Other Statistics The presence of data science has been profound in the scientific community in almost every discipline. An important part of the data science education expansion has been at the undergraduate level. We conducted a systematic literature review to (1) portray current evidence and knowledge gaps in self-proclaimed undergraduate data science education research and (2) inform policymakers and the data science education community about what educators may encounter when searching for literature using the general keyword 'data science education.' While open-access publications that target a broader audience of data science educators and include multiple examples of data science programs and courses are a strength, significant knowledge gaps remain. The undergraduate data science literature that we identified often lacks empirical data, research questions and reproducibility. Certain disciplines are less visible. We recommend that we should (1) cherish data science as an interdisciplinary field; (2) adopt a consistent set of keywords/terminology to ensure data science education literature is easily identifiable; (3) prioritize investments in empirical studies. |
| title | A Systematic Literature Review of Undergraduate Data Science Education Research |
| topic | Other Statistics |
| url | https://arxiv.org/abs/2403.03387 |