OpenIntro was started with one goal in mind: create a free and open-source introductory textbook. The mission of OpenIntro is to make educational products that are free, transparent, and lower barriers to education. I am a co-author on the three textbooks developed as part of this project and I also work on developing supplementary materials such as R labs, lecture slides, answer keys for instructors. Find out more at openintro.org.
MOOCs - Course development:
I am currently teaching the Statistics with R Specialization on Coursera. This specialization contains content from my previous Data Analysis and Statistical Inference course as well as a new course on Bayesian Statistics and a capstone project.
I have developed and taught the popular MOOC Data Analysis and Statistical Inference on Coursera.
This course is part of the Reasoning, Data Analysis and Writing Specialization. My collaborators on this Specialization course are Denise Comer (Duke, Thompson Program in Writing), Ram Neta (UNC, Philosophy), and Walter Sinnott-Armstrong (Duke, Philosophy).
I am also involved with the Teaching Statistical Thinking, along with Dalene Stangl (Duke, Statistical Science) and Kate Allman (Duke, Program in Education). This project is supported by the Bass Connections - Education and Human Development.
MOOCs - Research: Coursera and the Future of MOOCs
With the rise of open, online, publicly available education, educators have begun to question the legitimacy and practicality of this new form of learning (research opportunities, cost effectiveness vs. quality of education, completion rates, etc.). Our Bass Connections team in the Education and Human Development theme has developed and launched two Coursera courses in introductory chemistry and statistics, developing modules, investigating alternative means of conveying information, and probing the future of online education through mixed-methods research. Student team members are involved with all components of the project as well as serving as Community TAs for the courses. My collaborator on the project is Dorian Canelas (Duke, Chemistry). Find out more on the project homepage.
W-ISE and STEM FoR ALL:
This project aims to assess the use of active-learning techniques in introductory STEM courses as a means of increasing retention of women and minorities. Our model is based on social cognitive career theory (SCCT). SCCT suggests that individuals are more likely to pursue and continue in a field of study when, among other conditions, the individual has a high level of self-efficacy (feelings of ``I can do it”). Previous research suggest that self-efficacy is an especially good predictor of retention rates for groups who are viewed as a marginalized group within a field, such as women and minority students in STEM. Motivated by these findings, this project explores whether and how active-learning techniques in introductory STEM courses affects students’ self-efficacy since an increase in self-efficacy would suggest an increase in retention rates. The project is funded by Bass Connections - Education and Human Development for the 2015-2016 Academic year and my collaborator on the project is Genna Miller (Duke, Economics).
Statistical education apps developed in R Shiny. Check out the gallery and let me know if you would like to contribute to this project.
This page is perpetually under development, check back again for an updated list of projects I’m working on.Share