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Table 1.

Potential sequence of classroom activities that advance in the complexity and sophistication of students' interactions with authentic messy data.

Data CharacteristicsPotential Focal Topics
Activity type A. Simplified second-hand data, summarized, curated to display a clear trend Easily illustrate a specific scientific concept (e.g., NGSS Disciplinary Core Idea) and how scientific results are disseminated 
Activity type B. Second-hand data that include some level of messiness (e.g., variation, outliers, does not follow predictions) or curation by student Introduce students to statistical concepts, curation, how to interpret data with variation and unexpected results, how data can be modified and displayed in different ways 
Activity type C. First-hand data collected from classroom labs or inquiry projects Asking scientific questions, how to quantify variables, importance of experimental design (e.g., replicates, controls); give students ownership and a personal connection to data 
Activity type D. Large, second-hand online data sets with guided instruction Introduction to computational tasks and data visualization techniques, examine variability at a larger scale 
Activity type E. Large, second-hand online data sets open to student inquiry investigation Organizing data, finding and selecting appropriate variables, building knowledge from multiple sources 
Data CharacteristicsPotential Focal Topics
Activity type A. Simplified second-hand data, summarized, curated to display a clear trend Easily illustrate a specific scientific concept (e.g., NGSS Disciplinary Core Idea) and how scientific results are disseminated 
Activity type B. Second-hand data that include some level of messiness (e.g., variation, outliers, does not follow predictions) or curation by student Introduce students to statistical concepts, curation, how to interpret data with variation and unexpected results, how data can be modified and displayed in different ways 
Activity type C. First-hand data collected from classroom labs or inquiry projects Asking scientific questions, how to quantify variables, importance of experimental design (e.g., replicates, controls); give students ownership and a personal connection to data 
Activity type D. Large, second-hand online data sets with guided instruction Introduction to computational tasks and data visualization techniques, examine variability at a larger scale 
Activity type E. Large, second-hand online data sets open to student inquiry investigation Organizing data, finding and selecting appropriate variables, building knowledge from multiple sources 
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