Data Science ARES: Mine Çetinkaya-Rundel
Join us at the Data Science Applied Research and Education Seminar (ARES) with:
Dr. Mine Çetinkaya-Rundel
Senior Lecturer, School of Mathematics, University of Edinburgh
Associate Professor, Department of Statistical Science, Duke University
Professional Educator and Data Scientist, RStudio
Free Event | Registration Required
The art and science of teaching data science
Modern statistics is fundamentally a computational discipline, but too often this fact is not reflected in our statistics curricula. With the rise of data science it has become increasingly clear that students want, expect, and need explicit training in this area of the discipline. Additionally, recent curricular guidelines clearly state that working with data requires extensive computing skills and that statistics students should be fluent in accessing, manipulating, analyzing, and modeling with professional statistical analysis software. In this talk, we introduce the design philosophy behind an introductory data science course, discuss in progress and future research on student learning as well as new directions in assessment and tooling as we scale up the course.
Mine Çetinkaya-Rundel is Senior Lecturer in the School of Mathematics at University of Edinburgh, Data Scientist and Professional Educator at RStudio, and Associate Professor of the Practice position at the Department of Statistical Science at Duke University. Professor Çetinkaya-Rundel’s work focuses on innovation in statistics and data science pedagogy, with an emphasis on computing, reproducible research, student-centered learning, and open-source education as well as pedagogical approaches for enhancing retention of women and under-represented minorities in STEM. Professor Çetinkaya-Rundel works on integrating computation into the undergraduate statistics curriculum, using reproducible research methodologies and analysis of real and complex datasets. She also organizes ASA DataFest, an annual two-day competition in which teams of undergraduate students work to reveal insights into a rich and complex data set. Professor Çetinkaya-Rundel works on the OpenIntro project, whose mission is to make educational products that are free, transparent, and lower barriers to education. As part of this project she co-authored three open-source introductory statistics textbooks. She is also the creator and maintainer of datasciencebox.org and she teaches the popular Statistics with R MOOC on Coursera. Professor Çetinkaya-Rundel is the past Chair of the ASA’s Section on Statistics and Data Science Education and an ASA and ISI Fellow.