Resources for JEDI-Informed Teaching of Statistics
Pedagogy, research, and professional development
In the spirit of Gutiérrez (2009), access represents all of the opportunities available for student learning. These slides are a collection of resources for thinking about all of the dimensions of access. There is a particular emphasis on metacognition and unveiling the hidden curriculum.
Dr. Rochelle Gutierrez (2002) stated "equity is ultimately about the distribution of power - power in the classroom, power in future schooling, power in one's everyday life, and power in a global society." This presentation unpacks ways in which statistics classrooms can put power in students' hands.
Our recent research focuses on integrating Culturally Relevant Data into statistics and data science education. We’ve developed methods that connect coursework directly to students’ lived experiences, significantly enhancing engagement and understanding, particularly for those from historically marginalized groups. Our approach bridges the gap between theoretical data science and real-world application, making learning both accessible and impactful. Initial results from pilot courses are promising, and we are excited about the potential to further transform how data science is taught. Join us in making data science education more inclusive and effective for everyone
When done effectively, nontraditional grading methods can promote equity and help build an inclusive classroom. As with any shift in pedagogy, there are a number of questions to consider. This article summarizes four types of nontraditional grading and shares experiences from the authors who have applied them to a variety of courses in statistics.
In the college classroom, grades are the primary avenue by which we quantify and communicate student achievement. In setting up grading systems for our courses, we make countless decisions: Should the project be worth 25 or 30 percent of the final grade? Will I drop the lowest quiz score? What penalty (if any) should I implement for late work ? These seemingly small decisions can have a surprisingly large impact on the grades that we assign and the type of learning and understanding that we privilege. Thinking carefully about the way we grade is critical for JEDI-informed teaching of statistics. In recent years, I have been drastically and continually rethinking my approach to grading. At JSM 2023, I gave a talk about these efforts as part of the session "Power in the Classroom: From Helping Students Play the Game to Helping Students Change the Game." I am sharing the slides from this talk here.
In these slides, you will find: thoughts on the purpose of grades, the impact of grades, and why grading is an important consideration for JEDI-informed teaching; a brief discussion of the many problems with traditional grades (with suggested resources for further reading); three examples of changes I have implemented in introductory and advanced statistics courses at Macalester College; and reflections on what aspects of those changes worked... and what didn't. Additional resources and examples can be found at the "content resource" link.