https://orcid.org/0000-0003-3332-4311The rich discussions and presentations at the May 2022 Electronic Conference on Teaching Statistics (eCOTS) got me thinking about the future of data science and statistics education. The conference, organized by Consortium for the Advancement of Undergraduate Statistics Education (CAUSE) and led by Program Chair Megan Mocko (University of Florida) focused on the theme of “Preparing the Modern Student.”
This was the sixth eCOTS gathering in a series of virtual conferences established before the global pandemic made online conferences de rigueur. Each one has provided an affordable and accessible way for a diverse group to engage with the community. The keynotes and posters are made freely available for all to view after the conference. (In the spirit of full disclosure, I have served on the planning committee for the last three conferences.)
Some general themes emerged for me over the week. The first one I noticed related to “what to teach.” Mine Çetinkaya-Rundel’s eCOTS keynote provided a compelling motivation for the “superpowers” that we can provide to our students to undertake shapeshifting (data wrangling), time travel (version control), and clairvoyance (predictive modeling), among other skills. Nathan Taback’s keynote shared ways that he teaches experimentation using “multiverse analysis.” Both challenged the community about what to teach to prepare students to make sense of the data around them.
A second theme that arose was “how to teach” the modern student. The pandemic and other longer-standing trends have demonstrated the importance of student-centered practices and active learning to support students for success. Talithia Williams’ keynote summoned the community to push past barriers and to create a “cultural mindset of data agency.” Many sessions at eCOTS explored important ways to make our classrooms and programs more diverse and inclusive. These included aspects of accessibility, culturally responsive teaching, and fostering sense of community.
The last theme, “when to teach,” was the focus of Rob Gould’s keynote, where he described the dramatic growth in data science education at the K-12 level. In recent years, students in elementary, middle, and high schools are now encountering statistics and data science in many ways that will hopefully provide them a foundation in data fluency that will prepare them to make sense of the data around them.
These themes are part and parcel of what the Journal of Statistics and Data Science Education hopes to provide to our readers. This issue features ten papers, including one interview. Two papers (“Opportunities for K-8 Students to Learn Statistics Created by States’ Standards in the United States” and “Reflections on the Current and Potential K-12 Impact of the Journal of Statistics and Data Science Education”) focus directly on pre-secondary education and relate to “when to teach.” Discussions of “what to teach” arise in “Developing Students’ Intuition on the Impact of Correlated Outcomes,” “Implementing a Senior Statistics Practicum: Lessons and Feedback from Multiple Offerings,” and a datasets and stories paper entitled “Regression, Transformations, and Mixed-effects with Marine Bryozoans.” Finally, a number of papers explore “how to teach,” including “Think-aloud interviews: A Tool for Exploring Student Statistical Reasoning,” “Teaching Statistics to Struggling Students: Lessons Learned from Students with LD, ADHD, and Autism,” and “An Evaluation of College Students’ Perceptions of Statisticians.” A brief communication entitled “Data Discovery Challenge Using the COVID-19 Data Portal from New Zealand” and an interview with University of Minnesota Professor Bob delMas (this year’s winner of the George Cobb Lifetime Achievement Award, conferred at eCOTS) round out the issue.
I hope that you find these papers to be insightful and stimulating as we all work to create courses and programs that both challenge and support the modern student. I look forward to seeing future submissions on all of these topics in future months and years.
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