“My goal is to make statistics and data science physically and cognitively accessible.”
Professor Mine Dogucu mainly works in statistics and data science education, focusing on curriculum development and modernization. “The advances in computing and the emergence of data science have not only brought up discussions of the data science curriculum but also led to a change in redefining the statistics curriculum and its delivery,” she says. Professor Dogucu considers what should be taught in these curricula and how that content should be delivered. “I also study the assessment of learning in data science classes including reasoning with data, classroom projects, and automated grading.”
Accessible Bayesian Statistics
For the data science curriculum, Professor Dogucu works at various levels, ranging from introductory to advanced. One advanced topic is Bayesian statistics — a theory that interprets probability differently from “frequentist statistics,” which is commonly taught in statistics courses. “Despite its importance and an increasing demand for it in the workforce, Bayesian statistics has not found its equivalent place in the undergraduate statistics curriculum,” she says. Luckily, UCI offers an undergraduate Bayesian course that is required for data science majors. “To make Bayesian statistics more accessible for undergraduate students elsewhere, I am cowriting a publicly available book, Bayes Rules! An Introduction to Bayesian Modeling with R, which is specifically geared toward novice learners.”
Open Access Education
One major barrier in learning data science or any other subject is the cost of textbooks and software, which is why Professor Dogucu develops educational materials that are freely accessible in the public domain. She also contributes to open source programming language R through teaching-oriented packages. “By contributing to open education, I aim to impact students looking for open access data science learning materials; instructors in search of teaching resources for their classrooms; and scientists interested in learning tools for open and reproducible science.” Through open education, she hopes to reach more learners around the world.
Ph.D., The Ohio State University, 2017
M.S., Secondary School Science and Math Education, Bogazici University, 2013
B.A., Mathematics and minor in Education, Smith College, 2009
Statistics and Statistical Theory
Developing and studying methods for collecting, analyzing, interpreting and presenting empirical data...
A probabilistic framework that integrates prior knowledge with new data to update and refine probability …
Developing learning and teaching tools for information and computer sciences.