Welcome to my Research and Scholarship page! Below, you
will find links to project pages for some of my projects.
Note: to return to this site from any of the project pages, click on my name listed under project team.
My work applies theories and methods from the cognitive and learning sciences to investigate the act of learning and doing statistics, and critically examines statistics education research theories and methodologies.
Generally speaking, my work falls into one of two categories:
What computational thinking skills are needed in order to successfully utilize generative AI applications to complete statistical and data related tasks? How can these technologies help broaden participation in STEM? For more, visit link coming soon.
How do the statistically significant and not statistically significant category labels affect our cognition of statistical measures like p-values and Cohen’s d effect sizes? For more, visit RaoVNV.github.io/p-values/.
How do humans cluster sets of points? Is their clustering reliable? What individual and group differences are there in human clustering? What other cognitive processes is clustering related to? For more, visit RaoVNV.github.io/clustering/.
How do secondary teachers reason about aesthetic mappings linking complex data structures and modern data visualizations? For more, visit RaoVNV.github.io/Data-to-Graphs/.
What is biostatistical literacy, and how can we promote students’ biostatistical literacy skills? For more, visit RaoVNV.github.io/BiostatLiteracyProject.
How should we incorporate and discuss gender as an attribute in datasets used in instruction and practice in STEM courses? For more, visit https://raovnv.github.io/GenderInclusivity/.
The 2016 GAISE Guidelines call for the incorporation of multivariable thinking into introductory statistics curricula. How can we measure the efficacy of curricula in developing these skills, and how can we measure students’ multivariable thinking abilities? For more, visit link coming soon.
The Vedas and BhagavadGita contain essential lessons for all humanity. How can we borrow and apply pedagogical strategies from these timeless works to any subject we teach, including statistics? For more, visit link coming soon.