Research Leader and Principal Investigator

Jennifer Noll

Program/Areas of Interest

  • Mathematics
  • Statistics
  • Data science
  • Applications of AI in mathematical tutoring

Biography

Dr. Jennifer Noll is a distinguished Research Leader and Principal Investigator at TERC, bringing over two decades of expertise in mathematics, statistics and data science education research. Her groundbreaking work spans from developing innovative curricula to leading multi-million dollar federal research initiatives, with a particular focus on transforming how students engage with statistical thinking and data science.

Her current research is in the exploratory stages of cutting-edge applications of AI in mathematical tutoring, particularly in probability and statistics education. She has also pioneered research on DataFest competitions revealing new opportunities for undergraduate statistics courses, focusing on team collaboration, research question design, and data ethics integration.

With extensive experience as a former Program Director at the National Science Foundation, Dr. Noll has managed over $10 million in research funding as lead of the Data Science Corps program where she worked to expand pathways to data science education.  She worked across multiple federal programs (ITEST, Computer Science for All, DRK12, and AISL programs).

National Science Foundation Awards

Principal Investigator on a National Science Foundation sponsored CAREER grant, titled: Transforming College Students’ Statistical Thinking: Data, Technology & Modeling. In this project I study the implementation of reform curricula (three different versions of the curriculum) and its subsequent impact on student learning of foundational topics in statistics. Five Year Award beginning September 2015-February 2021. Award Amount: $976,358.

Principal Investigator on a National Science Foundation sponsored TUES – type 2 project, titled, Collaborative Research: Process Oriented Guided Inquiry Learning (POGIL) Math – Guided Inquiry Materials for Gatekeeper Courses in Mathematics. In this project I work with chemists and mathematicians across several institutions to study the impact of new calculus materials on students’ understanding of limit, continuity and derivative. The research design uses pre/post assessment items, interviews, and classroom observations. Award amount: $399,600.

Co-Principal Investigator National Science Foundation DRK-12: Enhancing Mathematics Teaching and Learning in Urban Elementary Schools A Cluster randomized Efficacy Trial of a Novel Professional Development Approach Award to Teachers Development Group: $2,488,354.00
Sub-Award to Portland State University: $386,026
Grant Period: 9/2012 – 8/2016
Principal Investigators: Eva Thanheiser [Portland State University], Linda Foreman [Teachers Development Group and Grant PI],
Other Co-PIs: Julie Fredricks [Teachers Development Group], Mike Shaughnessy [PSU – Emeritus]

Education

  • Doctor of Philosophy – PhD, Mathematics Education & Applied Probability and Statistics
  • Bachelor’s degree, Mathematics

Associations

  • American Statistical Association

Honors/Awards

  • ACT Award from the National Science Foundation for contributions to the data science education portfolio
  • Statistics Teacher of the Year, Portland State University

Highlighted Publications

Noll, J., & Tackett, M. (2023). Insights from DataFest point to new opportunities for undergraduate statistics courses: Team collaborations, designing research questions, and data ethics. Teaching Statistics.

Noll, J., Kirin, D., Dolor, J., & Clement, K. (2021). Revealing students’ stories of inventing and using a statistical model in TinkerPlots for solving a comparing groups problem. Mathematical Thinking and Learning. DOI:10.1080/10986065.2021.1922858

Noll, J., Schnell, S., Gould, R., & Makar, K. (2021). New ways of interacting with data, context, and chance in statistical modeling processes. Mathematical Thinking and Learning, DOI:10.1080/10986065.2021.1922855

Noll, J., Clement, K., Dolor, J., Kirin, D., & Petersen, M. (2018). Students’ use of narrative when constructing statistical models in TinkerPlots. ZDM, 50(7), 1267-1280. https://doi.org/10.1007/s11858-018-0981-x.

Noll, J., Kirin, D. (2017). TinkerPlotsTM model construction approaches for comparing two groups: Student perspectives. Statistics Education Research Journal, 16(2), 213-243

Noll, J., & Kirin, D. (2016). Student approaches to constructing statistical models using TinkerPlotsTM. Technology Innovations in Statistics Education, 9(1), 1-24.