Teaching Introductory Statistics with DataCamp

Benjamin S. Baumer et al.

Journal of Statistics and Data Science Education2020https://doi.org/10.1080/10691898.2020.1730734article
ABDC B
Weight
0.47

What the paper says

We designed a sequence of courses for the DataCamp online learning platform that approximates the content of a typical introductory statistics course. We discuss the design and implementation of these courses and illustrate how they can be successfully integrated into a brick-and-mortar class. We reflect on the process of creating content for online consumers, ruminate on the pedagogical considerations we faced, and describe an R package for statistical inference that became a by-product of this development process. We discuss the pros and cons of creating the course sequence and express our view that some aspects were particularly problematic. The issues raised should be relevant to nearly all statistics instructors. Supplementary materials for this article are available online.

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https://doi.org/https://doi.org/10.1080/10691898.2020.1730734

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@article{benjamin2020,
  title        = {{Teaching Introductory Statistics with DataCamp}},
  author       = {Benjamin S. Baumer et al.},
  journal      = {Journal of Statistics and Data Science Education},
  year         = {2020},
  doi          = {https://doi.org/https://doi.org/10.1080/10691898.2020.1730734},
}

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Teaching Introductory Statistics with DataCamp

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Evidence weight

0.47

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.31 × 0.4 = 0.12
M · momentum0.80 × 0.15 = 0.12
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.