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

The following autoethnography was completed by two graduate students at University A learning to enact teaching for social justice while building content underpinnings in statistics at University B. The authors present a research base for teaching for social justice followed by a description of their lesson, observations during enactment, and reflection of change in beliefs about teaching for social justice afterward. Findings in this study are shared from the authors' personal perspectives through the enactment of teaching a lesson for social justice in an undergraduate statistics course at University B. Implications provide encouragement that the inclusion of social justice topics in undergraduate and graduate level teacher educator coursework may improve teacher attention to equity in practice.