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Even though there were only 300 cases, I still felt I was awash in data. I think that's important for students.

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Multiple representations at the same time: Observing multiple features related to measures of center of the given data and also regression line at the same time

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Multiple representations at the same time: Observing multiple features related to measures of center of the given data and also regression line at the same time

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considering how the structure of the table helps or hinders your ability to make sense of relationships relating to fuel economy

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I started to say bivariate data..but then I realized it's really trivariate with the color

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It's useful to see links in data across graphs and the table - allows us to notice interesting cases or trends, which can further analysis

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Adding new or different variables, e.g., by coloring points

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different representations help you make sense of the date

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Opportunities for students to look at multiple representations of lots of data - to make co-constructed sense of...

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Opportunities for students to look at multiple representations of lots of data - to make co-constructed sense of...

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using overlay with dotplots

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Changing variable types from numerical to categorical

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Changing variable types from numerical to categorical

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I didn't like the numerical scale and how it related to the dataset

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Explore different kinds of variables and their corresponding visualizations

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Explore different kinds of variables and their corresponding visualizations

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e.g., Interesting to see relationships among 3 categoricals in one graph

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The sample of 300 showed many of the "data stories" just fine.

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Although I only explored one sample, I could see the potential to explore several samples and build understanding of a sample and sampling distribution

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Great scaffolded learning opportunity [after Option1]. Allows students to figure out the best way to answer their Qs e.g. which feature is important to look at or compare or to cluster for comparisons..

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Great scaffolded learning opportunity [after Option1]. Allows students to figure out the best way to answer their Qs e.g. which feature is important to look at or compare or to cluster for comparisons..

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At first I was meandering around without focus. Eventually I settled on "What makes gas guzzlers different aside from their poor fuel efficiency?"

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Had to change the file type of the downloaded file

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Had to change the file type of the downloaded file

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so that it could be accepted by CODAP

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I agree with the scaffold comment - I think this tool would help teachers push students to think about clumps of data instead of

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Building Curiosity about the tool (CODAP)

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Building Curiosity about the tool (CODAP)

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I noticed Number of Cylinders as a legend attribute...I was curious what CODAP was doing as the number in each of the 5 partitions were not the same. (It makes more sense to treat legend attribute as a categorical variable, but students often don't recognize how 'numeric' data can be categorical in nature.)

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You can "reverse-engineer" computed quantities

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You can "reverse-engineer" computed quantities

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For example, graph fuel cost against fuel efficiency. Fun!