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Matthew
Beckman
Assistant Research Professor; Chair of Undergraduate Studies
Matthew Beckman

Biography

Matthew Beckman is Director of Undergraduate Programs and Assistant Research Professor of Statistics at Penn State.

He received his PhD in Statistics Education from the University of Minnesota in 2015. He received his MS in Statistics from the University of Minnestoa in 2008, and a MS in Mathematics from Penn State University in 2006.

Beckman's research interests include undergraduate education in Statistics & Data Science. His focus is on assessment development. Other current research interests include undergraduate curriculum and instruction.

Beckman has previously worked in the private sector as a Sr Statistician at Medtronic Plc, and a Sr. Biostatistician at Nonin Medical Inc. He joined Penn State as faculty in 2016.

 

Honors and Awards

2017 Tombros Fellowship--Penn State Center of Excellence in Science Education

 

Publications

  • Beckman, M., Cetinkaya-Rundel, M, Horton, N., Rundel, C., Sullivan, A., Tackett, M. (in review). Implementing version control with Git as a learning objective in statistics courses. https://arxiv.org/abs/2001.01988.
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  • Kaplan, D., Beckman, M. (2020). Data Computing: an introduction to wrangling and visualization with R (2nd ed). https://dtkaplan.github.io/DataComputingEbook/.
     
  • Beckman, Guerrier, Lee, Molinari, Orso, & Rudnytskyi (2019). An Introduction to Statistical Programming Methods with R. https://smac-group.github.io/ds/.
     
  • Beckman, M. D., delMas, R. (2018). Statistics students' identification of inferential model elements within contexts of their own invention. ZDM Mathematics Education 50(7). DOI: 10.1007/s11858-018-0986-5.
     
  • Beckman, M.D., delMas, R. C. (2018). Cognitive transfer assessment in post-secondary statistics. Proceedings of the tenth international conference on teaching statistics. Kyoto, Japan.
     
  • Beckman, M. D., delMas, R. C., and Garfield, J. (2017). Cognitive transfer outcomes for a simulation-based introductory statistics curriculum. Statistics Education Research Journal 16(2).

 

Teaching

STAT 184 - Introduction to R programming

STAT 250 - Introduction to biostatistics STAT 380 - Data science through statistical reasoning and computing

STAT 470W - Problem solving and communication in applied statistics

STAT 501 - Regression analysis STAT 597 - Special topics in statistics education

PSU 016 - First-year seminar (statistics & data science)