“As an undergraduate humanities major, I struggled to learn statistics as a graduate student,” LeBlanc says. “The most difficult part for me was connecting the statistical procedures needed to specific research questions and hypotheses developed within my discipline.” I began teaching research methods to undergraduates at UTSA in 2001. I wanted to teach students how to connect theory and methodology more directly to specific applications.My first attempt was a two-page, two-dimensional decision tree that I distributed in class. ”
In the fall of 2014, LeBlanc began developing Stat Tree as an online interactive tool.
The following spring, he presented the tool at the Innovations in Online Learning conference.
This project received a $50,000 NSF grant to the NSF Innovation Corps (I-Corps™ program) in spring 2019. The software was made publicly available in August 2023.
As LeBlanc continued to develop the tool, he continued to present the concept at the Southwest Regional I-Corps Conference and later at the National I-Corps Conference.
“We asked our colleagues: What do you struggle with most when choosing a statistical test for your research question?” LeBlanc said.
UTSA researchers and their team found that some statisticians and data analysts spend up to six months training new employees. Interview participants also mentioned that learning new languages to perform different types of analysis was another major challenge. Organizations and educators tend to choose one language consistently. This means that researchers need to adapt to a new language when starting a new job or a new course. LeBlanc believes his tool will dramatically shorten that adjustment period and allow researchers to quickly translate their research questions into the language of their choice.
“This platform will benefit many learners and researchers who need direct instruction with statistical tools for analysis,” said UTSA College of Liberal and Fine Arts professor and professor of digital science. said Initiative Director Seok Kang. “The tools are open source and offer a variety of visualization options, giving students exposure to coding-based statistical analysis.”
