The field of Data Science is a multidisciplinary field, with mathematics, statistics, and computer science forming the core topics. Data science education research was examined by several research methodologies that include citations analysis, examination of the syllabi, and student peer review.
Here is my publications on the subject:
2020 Friedman, A. “Visualizing protein data sets in R through a student peer-review rubric. Biochemistry and Molecular Biology Education.
2020 Friedman, A., Beasley, Z.J. “Teaching R with Peer Review and a New Rubric.” UseR! 2020.
2019 Friedman, A. “Data Science syllabi measuring its content.” Education and Information Technologies. 24(6).
2017 Friedman, A. “Measuring the Promise of Big Data Syllabi.” Technology, Pedagogy andEducation 26(5).
2016 Friedman, A. “Statistics for Library and Information Services: A Primer for Using Open Source R Software for Accessibility and Visualization.”Published by Rowman & Littlefield.
