## Using Mathematical Modeling to Disrupt Probabilistic

Misconceptions of Social Issues

Probabilistic decisions can be difficult to navigate in even the simplest of contexts. In the real world, situations are rarely simple, and robust probabilistic reasoning is needed to avoid drawing conclusions from statistical results that can be both mathematically incorrect and also socially detrimental. Mathematical modeling can offer a way forward when navigating the odds and oddities of real-world phenomena. |

## Research Objectives

This research will take a critical look at how computational modeling can support probabilistic understandings of aspects of social justice issues -- such as likelihoods, data analyses and inferences, proportions, and percentages. We will investigate and develop strategies for applying probabilistic reasoning and proportional representation to complex issues of social importance and will contribute new knowledge in the use of computational modeling to enrich probability teaching and learning. Informed by research in socially relevant mathematics, task design, and computational thinking.

**Principal Investigator:**Dr. Ami Mamolo

**Co-Investigators:**Dr. Robyn Ruttenberg-Rozen, Dr. Diane Tepylo

**Funding Agency:**Social Sciences and Humanities Research Council of Canada

Where to learn more

Upcoming activities and workshops:

Related Research:

Math in Social Issues:

- Coming this fall!

Related Research:

Math in Social Issues:

- Mamolo, A. (2018). Perceptions of social issues as contexts for secondary mathematics. Journal of Mathematical Behavior. Online first: https://doi.org/10.1016/j.jmathb.2018.06.007
- Mamolo, A., Thomas, K.*, Frankfort, M.* (2018). Exploring math through social justice problems. In (Eds.) A. Kajander, E. Chernoff, & J. Holm, Teaching and learning secondary school mathematics: Canadian perspectives in an international context (pp.377-392). Dordrechet: Springer.
- Mamolo, A. & Pinto, L. (2015). Risks worth taking? Social risks and the mathematics teacher. The Montana Mathematics Enthusiast., 12(1), 85-94.
- Mamolo, A., Deoraj, K.*, Dobson, J.*, Ruttenber-Rozen, R. (2019). Exploring food insecurity and social justice in the math classroom. Ontario Association for Mathematics Educators. Ottawa, ON

- Mamolo, A., Buteau, C., & Monaghan, M.* (2019). Prospective mathematics and sciences teachers’ views on coding & computational thinking. American Educational Research Association, Toronto, ON
- Tepylo, D., Mamolo, A., Ruttenberg-Rozen, R. (2019). Supporting mathematics through coding. Ontario Association for Mathematics Educators. Ottawa, ON
- Buteau, C., Mamolo, A., Muller, E., & Monaghan, M.* (2018). Computational thinking in mathematics :Undergraduate student perspectives. Research in Undergraduate Mathematics Education, San Diego, USA.
- Mamolo, A. & Lovric, M. (2017). Computational thinking in and for undergraduate mathematics: Perspectives of a mathematician. Research in Undergraduate Mathematics Education, San Diego, USA.
- Mamolo, A., Monaghan, M.*, & Muller, E., Buteau, C. (2018) Perceptions of computational thinking :Undergraduates, prospective teachers, and the experts weigh in. Fields MathEd Forum, Toronto, ON
- Mamolo, A., Tepylo, D., & Ruttenberg-Rozen, R. (2018). Educational coding for preservice teachers: Priorities, possibilities, and predicaments. Presentation for Fields MathEd Forum, Toronto, ON.

- Chernoff, E., Mamolo, A., & Zazkis, R. (2016). Representativeness in probabilistic decisions: The case of a

multiple choice exam. EURASIA Journal of Mathematics, Science and Technology Education, 12(4), 1009-1031. - Mamolo, A. & Pinto, L. (2015). Risks worth taking? Social risks and the mathematics teacher. The Mathematics Enthusiast, 12(1-3), 85-94.
- Chernoff, E. & Mamolo, A. (2015). Unasked but answered: Comparing the relative probabilities of coin flip sequences (attributes). Canadian Journal of Science, Mathematics, and Technology Education, 15(2), 186-202.
- Mamolo, A. & Zazkis, R. (2014). Contextual considerations in probabilistic situations: an aid or a hindrance? In (Eds.) E. Chernoff & B. Srirman, Probabilistic thinking: presenting plural perspectives (PT: PPP), (pp.641- 656). Dordrechet: Springer