ABOUT THE ANNUAL DATA CHALLENGE EXPO
The Annual Data Challenge Expo is jointly sponsored by three American Statistical Association (ASA) Sections – Statistical Computing, Statistical Graphics, and Government Statistics. The 2026 Data Challenge Expo will be held in conjunction with JSM 2026 in Boston, Massachusetts from August 1 - 6, 2026.
PARTICIPATION
The challenge is open to students and professionals from the private or public sector. Using statistical and visualization tools and methods, contestants will analyze the given data set(s).
AWARD CATEGORIES
There will be two award categories:
- Professional (one level with a $500 award)
- Student (three levels with awards at $1,500, $1,000, and $500)
To enter, contestants must do the following by February 2, 2026.
- Submit an abstract for a contributed Speed Poster session to the JSM 2026 website. Specify the Statistical Computing Section as the primary sponsor.
- Note: The period for submitting contributed abstracts is December 2, 2025 to February 2, 2026.
- Forward the JSM abstract submission email with abstract number, title, and authors to Wendy Martinez (martinezw@verizon.net).
The abstract is a placeholder to ensure the contestant is included in the JSM 2026 program. Contestants will present their work in a speed poster session and judging will be based on the results of the analysis presented at the JSM in August 2026.
Presenters are responsible for their own JSM registration and travel costs, and any other costs associated with JSM attendance. Group submissions are acceptable. Following JSM, contestants may submit a paper describing their analysis and results to Chance Magazine.
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What works in education?
Participants in this 2026 Data Expo Challenge will develop a research question to explore, analyze, and visualize the What Works Clearinghouse (WWC) comprehensive research database. This dataset represents the U.S. Department of Education's historical commitment to transparency and evidence-based education policy. The dataset contains details about the design and findings from over 13,000 studies. The multi-level data structure provides individual findings nested within studies and intervention reports, accompanied by comprehensive research quality indicators including WWC standards ratings, evidence tiers, and effect sizes.
The dataset encompasses all major educational domains and grade levels, representing studies conducted across all U.S. states and regions with rich contextual data that helps answer the critical question of "what works for whom and under what conditions." This comprehensive coverage creates opportunities for multivariate analysis, longitudinal analysis, causal inference, and meta-analysis, among other possible methods.
This is your opportunity to contribute to evidence-based education policy and practice by using this gold-standard research database to uncover insights about how we design, implement, and evaluate educational interventions. Your analysis should aim to advance our understanding of educational effectiveness. Participants may enhance their analysis by incorporating additional datasets to provide broader educational, demographic, or policy context.
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