Teaching Introductory Statistical Classes in Medical Schools Using RStudio and R Statistical Language: Evaluating Technology Acceptance and Change in Attitude Toward Statistics

Henrique Alvarenga da Silva & Alexandre Sampaio Moura

Journal of Statistics and Data Science Education2020https://doi.org/10.1080/10691898.2020.1773354article
ABDC B
Weight
0.55

What the paper says

Biostatistics is a critical skill to physicians in an evidence-based medicine era, but teaching basic statistical concepts is challenging. Students often experience anxiety caused by the complexity of statistics and might express negative attitudes toward the subject. We aimed to analyze the effect of an introductory biostatistics course using RStudio on attitude toward statistics and assess its acceptance among medical students. Forty-three 1st-year medical students were included. Pre- and post-course attitudes toward statistics were assessed using the Survey of Attitudes Toward Statistics (SATS-28) scale and technology acceptance was assessed by a Technology Acceptance Model scale at the end of the course. There was a statistically discernible (significant) gain in the scores of three of the four SATS dimensions: affection (p = 0.006, Cohen’s d = 0.442), cognitive competence (p < 0.001, Cohen’s d = 0.605), and difficulty (p = 0.008, Cohen’s d = 0.421). Acceptance of RStudio was moderate to high in 93% of the participants, without statistical differences between genders. RStudio can be useful in the teaching of statistics to medical students, being well accepted and positively associated with students’ attitude toward statistics. Supplementary files for this article are available online.

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https://doi.org/https://doi.org/10.1080/10691898.2020.1773354

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@article{henrique2020,
  title        = {{Teaching Introductory Statistical Classes in Medical Schools Using RStudio and R Statistical Language: Evaluating Technology Acceptance and Change in Attitude Toward Statistics}},
  author       = {Henrique Alvarenga da Silva & Alexandre Sampaio Moura},
  journal      = {Journal of Statistics and Data Science Education},
  year         = {2020},
  doi          = {https://doi.org/https://doi.org/10.1080/10691898.2020.1773354},
}

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Evidence weight

0.55

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

F · citation impact0.51 × 0.4 = 0.21
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.