An NSF-funded initiative developing scalable instructional platforms that bring data science, computing, and statistical thinking to classrooms nationwide. Listed in the College Board's AP Statistics Course Description.
Stats4STEM is a research initiative dedicated to improving how students learn statistics, data science, and computational thinking. Through NSF-funded research, we develop evidence-based tools and curricula that make statistics education more engaging, accessible, and effective.
Our flagship platform, Key2Stats, is a free, open-access system featuring interactive lessons, auto-graded assessments, instant student feedback, real-time learning analytics, and an integrated R coding environment with 1,500+ real-world datasets. It enables differentiated instruction and supports equity-focused curriculum design.
Built from our research, Key2Stats brings statistics education to life with interactive tools used by thousands of educators and students nationwide.
Auto-graded with question-specific hints for struggling students
RDojo — a beginner-friendly R coding environment built right in
Curated from research institutions, ready for classroom use
Live analytics updating every 10 seconds as students work
OpenStax, OpenIntro, and community-shared resources built in
Canvas, Blackboard, Brightspace, Moodle — SSO & grade passback
Five National Science Foundation awards supporting over 15 years of innovation in statistics, data science, and STEM education.
The foundational grant — building a central repository for learning materials that bring R, real-world data, and statistical computing into STEM classrooms.
Integrating computing into high school statistics instruction through new features for teaching, learning, and assessment using RStudio on the Stats4STEM platform.
Developing Key2Stats and CodeR4Math platforms — 11 curriculum modules supporting computational thinking in statistics and mathematics classes.
A modular, scalable learning platform integrating R-based ecology datasets, assessment systems, and instructional building blocks for undergraduate ecology and data science education.
Educators, researchers, and developers working at the intersection of learning science and technology.
MS Statistics, UMass Amherst
MA Mathematical Finance, Boston University
BS Mechanical Eng., UIUC
13+ years teaching AP & regular statistics at Boston Latin School. Presented at USCOTS, ICOTS, AERA.
15+ years teaching statistics, mathematics, and physics.
University of Illinois, Tufts University, Harvard University
Leads the development team. Platform architecture, security, server & database management, and performance optimization.