College of Education and Human Development

Department of Educational Psychology

Andrew Zieffler

  • Teaching professor, Distinguished University Teaching Professor

  • Educational Psychology
    178 Education Sciences Bldg.
    56 East River Road
    Minneapolis, MN 55455

  • zief0002@umn.edu
Andrew Zieffler Headshot

Areas of interest

  • Teaching and learning of statistics
  • Measurement and assessment of statistics education research
  • Statistical computing and integration of computing into statistics curriculum
  • Data science education

Dr. Zieffler is currently accepting MA students who want to concentrate thesis work in statistics or statistics education.

Degrees

PhD, University of Minnesota

BS, St. Cloud State University

Biography

My research interests are in the teaching and learning of statistics and data science. I am also interested in measurement and assessment as it relates to statistics education and data science research. A further interest of mine is statistical computing and thinking about different ways to integrate computing into the statistics curriculum.

Courses I teach

  • EPSY 3264—Basic and Applied Statistics
  • EPSY 5261—Introductory Statistical Methods
  • EPSY 8251—Methods in Data Analysis for Educational Research I
  • EPSY 8252—Methods in Data Analysis for Educational Research II
  • EPSY 8264—Advanced Multiple Regression

Awards & Recognition

  • 2024 Outstanding Contributions to Graduate and Professional Education Award, University of Minnesota
  • 2022 CEHD Distinguished Teaching Award, College of Education + Human Development, University of Minnesota
  • 2019 MPA Award for Outstanding Graduate Faculty in Psychology, Minnesota Psychological Association
  • 2014 Waller Education Award, for outstanding contributions to and innovations in the teaching of elementary statistics, American Statistical Association, Section on Statistical Education
  • 2013 COGS Outstanding Faculty Award, University of Minnesota, Council of Graduate Students

Research Funding Grants

Current

 

Past
  • Collaborative Research: The Data Science WAV: Experiential Learning with Local Community Organizations. National Science Foundation funded October 1, 2019–September 30, 2022, $69,985, Zieffler, A. (PI). HDR DSC-1923700. https://dsc-wav.github.io/www/projects.html
  • Defining the quantitative and computational skills of incoming science students. A Science Education Program Award to Macalester College as a lead institution for a collaboration between Bryn Mawr, Oberlin, St. Olaf, Lewis and Clark, Harvey Mudd, Claremont-McKenna Colleges, and the University of Minnesota. Howard Hughes Medical Initiative funded 2013–2016, $250,000, Overvoorde, P. (PI). Grant #520076788.
  • Collaborative Research: Evaluation and assessment of teaching and learning about statistics (e-ATLAS).
  • National Science Foundation funded June 1, 2011–May 31, 2013, $91,970, Garfield, J., Pearl, D., delMas, R., & Zieffler, A. (PIs). DUE-1044812 & 1043141.
  • Collaborative research: The CATALST project, Change Agents for Teaching and Learning STatistics. Na- tional Science Foundation funded August 2008–July 2011, $299,974, Garfield, J., delMas, R., & Zieffler, A. (PIs). DUE-0814433.
  • National statistics teaching practice survey: Instrument development. National Science Foundation funded July 2008–June 2011, $71,887, Garfield, J., delMas, R., & Zieffler, A. (PIs). DUE-0808862.
Publications

Legacy, C., Le, L., Zieffler, A., Fry, E., & Vivas Corrales, P.* (2024). Results from the 2021 administration of the Statistics Teaching Inventory. Journal of Statistics and Data Science Education, 32(3), 232–240. https://doi.org/10.1080/26939169.2024.2333732

Rao, V. N. V.*, Legacy, C., Zieffler, A., & delMas, R. (2023). Designing a sequence of activities to build students’ reasoning about data and visualization. Teaching Statistics, 45(S1), S80–S92. https://doi.org/10.1111/test.12341

Legacy, C.*, Zieffler, A., Fry, E., & Le, L. (2022). COMPUTES: An instrument to measure introductory statistics instructors’ emphasis on computational practices. Statistics Education Research Journal, 21(1). doi: 10.52041/serj.v21i1.63

Legacy, C.*, Zieffler, A., Baumer, B. S., Barr, V., & Horton, N. J. (2022). Facilitating team- based data science: Lessons learned from the DSC-WAV project. Foundations in Data Science, 5(2), 244–265.​​ https://doi.org/10.3934/fods.2022003

Horton, N. J., Baumer, Benjamin S., Zieffler, A., & Barr, V. (2021). The Data Science Corps Wrangle- Analyze-Visualize program: Building data acumen for undergraduate students. Harvard Data Science Review, 3(1). doi: 10.1162/99608f92.8233428d

Zieffler, A., Justice, N.*, delMas, R., & Huberty, M.* (2021). The use of algorithmic models to develop secondary teachers’ understanding of the statistical modeling process. Journal of Statistics and Data Science Education, 29(1), 131–147. doi: 10.1080/26939169.2021.1900759

National Academies of Sciences, Engineering, and Medicine. (2018). [Contributing Author]. Data science for undergraduates: Opportunities and options. Washington, DC: The National Academies Press. https://doi.org/10.17226/25104

Garfield, J., Zieffler, A., & Fry, E.* (2017). What is statistics education? In D. Ben-Zvi, K. Makar, & J. Garfield (Eds.), The international handbook of research in statistics education (pp. 37–70). Cham, Switzerland: Springer International Publishing. doi: 10.1007/978-3-319-66195-7_2

* = Current or former graduate student

Presentations

Demirci, S., Dogucu, M., Rosenberg, J., & Zieffler, A. (2024, August). Crafting university experiences: Perspectives and practices in teaching introductory data science. Presentation at the Joint Statistical Meetings, Portland, OR.  https://sinemdemirci.github.io/jsm-24/

Peczuh, M.*, Weisen, S.*, Do, T.*, Zieffler, A., Maruyama, G., Morris, N., & Fergus, M. (2024, April). Sex differences in postsecondary education and employment pathways after high school. Paper presented at the American Education Research Association (AERA), Philadelphia, PA.

Le, L., Hayat, M., Green, J., Kaplan, J., Peters, S., & Zieffler, A. (2023, June). Demystifying the publishing process for statistics education journals. Presentation at the United States Conference on Teaching Statistics, State College, PA.

Erickson, J., McNaron, Toni, Zieffler, A., & Beaton, J. (2022, November). Impactful faculty-led professional development (PD) A discipline-specific framework to guide instructors’ investment in the field. Panel presentation at National Alliance of Concurrent Enrollment Partnerships (NACEP) annual conference, Minneapolis, MN.

Legacy, C.*, Rao, V. N. V.*, Zieffler, A., & delMas, R. C. (2022, January). Data to graphs and back: Secondary teachers' reasoning about the aesthetic mappings that link data and visualizations. Presentation at the 12th Statistical Reasoning, Thinking and Literacy (SRTL-12) Research Forum, online.

Baumer, B. S., Horton, N. J., Zieffler, A., & Legacy, C.* (2021, June). Facilitating team-based data science: Lessons learned from the DSC-WAV project. Presentation at the United States Conference on Teaching Statistics, Online.

Zieffler, A., Justice, N.*, delMas, R., & Huberty, M.* (2021, April). The use of algorithmic models to develop secondary teachers’ understanding of the statistical modeling process. Invited presentation for the CAUSE webinar series. Online.