Matthew Beckman

Associate Research Professor; CAUSE Director
Matt Beckman
Matthew
Beckman
Associate Research Professor; CAUSE Director
Interests
Statistics Education
Data Science Education
Educational Measurement
Address
Phone
(814) 863-1022
Website
Personal Site

Biography

Matthew Beckman is an Associate Research Professor of Statistics at Penn State and Executive Director of the Consortium for the Advancement of Undergraduate Statistics Education (CAUSE; www.causeweb.org).

He earned his PhD in Statistics Education and MS in Statistics from the University of Minnesota, and he earned a BS in Mathematics from Penn State University.

Beckman's research interests include Statistics & Data Science Education, especially post-secondary teaching, learning, and assessment. For example, he is currently PI of Project CLASSIFIES (NSF Award# 2236150) which seeks to develop and investigate tools that leverage Natural Language Processing to assist STEM instructors in large-enrollment classes with providing student feedback on short-answer tasks. 

Prior to joining Penn State, Beckman worked in the medical technology sector as a Sr. Statistician at Medtronic, and a Sr. Biostatistician at Nonin Medical. 

 

Honors and Awards

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

 

Selected Publications

  • Phadke, S., Beckman, M. D., & Lock Morgan, K. (2024). Examining the role of context in statistical literacy assessment.  Statistics Education Research Journal, 23(1).
  • Li, Z., Lloyd, S., Beckman, M. D., & Passonneau, R. J. (2023). Answer-state Recurrent Relational Network (AsRRN) for Constructed Response Assessment and Feedback Grouping.  Findings of the Conference on Empirical Methods in Natural Language Processing (EMNLP) 2023.
  • Lloyd, S. E., Beckman, M., Pearl, D., Passonneau, R., Li, Z., & Wang, Z. (2022). Foundations for AI-Assisted Formative Assessment Feedback for Short-Answer Tasks in Large-Enrollment Classes. In Proceedings of the eleventh international conference on teaching statistics. Rosario, Argentina.
  • Beckman, M. D., Çetinkaya-Rundel, M., Horton, N. J., Rundel, C. W., Sullivan, A. J., & Tackett, M. (2021). Implementing Version Control With Git and GitHub as a Learning Objective in Statistics and Data Science Courses.  Journal of Statistics and Data Science Education, 29(1). 
  • Beckman, M. D., delMas, R. (2018). Statistics students' identification of inferential model elements within contexts of their own invention. ZDM Mathematics Education 50(7). 
  • 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 200 - Elementary Statistics

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

STAT 300 - Statistical Modeling I

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