The SIGMAA on Statistics and Data Science Education hosted an insightful panel discussion at the 2025 Joint Mathematics Meeting (JMM) titled: “Navigating the Frontier: Statistics, Data Science, and AI in the First Two Years of College.” This session held on January 10 provided insights into the current state of intro stats and data science curricula and offered guidance for departments considering whether to modernize intro stats courses to include data science or to develop standalone courses.

Organizer/Facilitator

Dr. Helen Burn, Highline College (Slide Deck)

Dr. Burn opened the session and highlighted the impact of 15 years of mathematics reforms on intro stats enrollments and emphasized the importance of developing a change strategy related to the data science curriculum.

Panelists

  • Patti Frazer Lock, St. Lawrence University (Slide Deck)

    Dr. Lock provided updates on GAISE (Guidelines for Assessment and Instruction in Statistics Education), including content to omit from Intro Stats and draft Student Learning Outcomes. She shared revised GAISE recommendations for Statistics and Data Science courses, demonstrated ways to incorporate multivariate thinking in intro stats courses, and discussed the merits of offering standalone data science courses for different student audiences.

  • Jamie Perrett, Brigham Young University (Slide Deck)

    Dr. Perrett explored ways to integrate advanced data analysis techniques and computational skills into early college curricula. He discussed employer needs (Python, Cloud Tools, SQL, Dashboarding), current student programming and tech skills, and curriculum ideas for statistical methods and data science courses, sharing content from BYU’s Intro Stats and Data Science Ecosystems courses.

  • Kelly McConville, Bucknell University (Slide Deck)

    Dr. McConville advocated for combining intro stats and data science into a single course that teaches the data analysis workflow based on the assertion that most students take only a single course in this curricular area. She emphasized educating students to be both creators and consumers of data, addressed course design, content to omit, and assessment in the age of AI.

  • Victor Piercey, Ferris State University (Slide Deck)

    Dr. Piercey posed the question of integrating data science across all general education pathways (statistics, quantitative reasoning, and college algebra/STEM-prep) in the first two years. He shared results from the MAA CRAFTYs Taskforce on Data Science, including national survey findings on new courses, ethics, and collaboration between 2- and 4-year institutions. His slide deck includes a QR code to the ACM-ASA-MAA-SIAM Joint Taskforce on Undergraduate Data Science Competencies.

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