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Faculty of Science

Department of Mathematics & Statistics













Statistics Seminar | Samantha-Jo Caetano (University of Toronto)
	
 Mar 5, 2026 
 1:30PM to 2:30PM




































Date/Time

Date(s) - 05/03/2026
1:30 pm - 2:30 pm





Speaker: Samantha-Jo Caetano (University of Toronto)


Location: Hamilton Hall, Room 217


Title: Promoting Statistics and Data Literacy in and out of the Classroom


Abstract: Developing data literacy requires more than technical skill, it demands inclusive design, meaningful engagement, and opportunities to connect statistical thinking to the real world. In this talk, I examine how Universal Design for Learning (UDL) principles (CAST, 2018) can support inclusive teaching in large postsecondary statistics courses while also extending learning beyond the classroom through extracurricular and outreach initiatives.


First, I will describe the redesign of a large third-year statistics course to incorporate flexible assessment weighting, structured grace periods, and transparent generative AI policies. Grounded in UDL, these approaches aim to reduce unnecessary barriers while maintaining academic rigor. Student feedback and course outcomes suggest that flexibility can enhance motivation, autonomy, and equitable participation – aligning with broader calls for inclusive assessment practices in statistics education (Engel, 2017).




Second, I will discuss initiatives that engage learners with statistics outside formal coursework, including extracurricular competitions, consulting-style learning communities, data ethics case studies and outreach programs for K-12 students. These initiatives emphasize authentic data, storytelling, and collaborative problem-solving, responding to long-standing calls to cultivate statistical reasoning and real-world data literacy across educational levels (Ben-Zvi & Garfield, 2004; Ridgway, 2016).


Together, these efforts illustrate how flexibility inside the classroom and engagement beyond it can work in tandem to broaden participation in data-driven inquiry and foster a more confident, diverse generation of data-literate learners.


 


References




    

  1. Ben-Zvi, D., & Garfield, J. (2004). The Challenge of Developing Statistical Literacy, Reasoning and Thinking. Springer.
    2. 



    

  1. CAST. (2018). Universal Design for Learning Guidelines version 2.2. Retrieved from http://udlguidelines.cast.org
    2. 

  2. Engel, J. (2017). Statistical literacy for active citizenship: A call for data science education. Statistics Education Research Journal, 16(1), 44-49.
    3. 

  3. Ridgway, J. (2016). Implications of the Data Revolution for Statistics Education. International Statistical Review, 84(3), 528–549.
    4.