Today I submitted an application for the Utah Conference on Undergraduate Research (UCUR), which will be meeting at Brigham Young University in Provo, Utah, on 28 February 2014. This will actually be a presentation by my two student assistants, David Anderson and Tanner Nackos, both of whom are going to the A2 Data Dive with me in two weeks.
Here is the actual application text:
Bringing Data Science to the Social Sciences: The UVU Data Lab
The quantity and variety of data that is potentially available to researchers has been growing explosively, leading to enormous changes in fields such as diverse as genetics, marketing, and sports. However, have been missing out on the “data deluge,” in part because of a lack of the necessary training. The UVU Data Lab at Utah Valley University is an attempt to help undergraduate students in the social and behavioral sciences understand the unique benefits of “big data” and “data in the wild,” and to give them the foundational skills necessary to use such data to form and test scientific hypotheses.
This presentation explores the promises and pitfalls of training undergraduates in data science. The UVU Data Lab is an ongoing project that began in fall of 2013 when the principal investigators and their faculty mentor received funding to participate in the University of Michigan’s A2 Data Dive (a2datadive.org), which is a two-day, high intensity exercise in data analysis as engaged service to local nonprofits. This experience led the PIs and faculty mentor to collaborate on developing an exploratory seminar on data science for undergraduate students in the behavioral sciences for spring 2014. That seminar will, in turn, help develop the Utah Data Dive (utahdatadive.org), which is planned for spring, 2015. This presentation explores the most promising developments and greatest challenges in this process, with the intention of helping other schools develop similar programs.
Conclusions and Significance
The benefits of data science training and the ability to use large, naturally occurring datasets within the social and behavioral sciences are potentially enormous, with the ability to test long-standing questions in novel ways and the level of detail necessary to find unexpected associations. This presentation helps lay the foundation for this important methodological and pedagogical development.
[As a side note, I also submitted an application for my art and technology piece, “Dance Loops.” Woo hoo!]