Students as Data Scientists

Data Science is becoming an increasingly important topic in K-12 teaching and learning. To support students incorporating data into their science learning, MothEd features an online collaborative learning platform that young scientists can use to document their moth data, share their data and ideas, and engage with simple graphing tools and data cards to figure out what their data might be telling them. Both younger elementary students and more advanced middle school students can use our data science platform.

Gathering Data

With MothEd, students have their own moth collections that they can document on virtual data cards. Each card has a list of categories that the students create, depending on what they are investigating about moths. Students can explore their data in various ways, including graphing, making tables, and grouping into categories (“sorting”). 

A stack of moth data cards
A stack of moth data cards

Analyzing Data

As students sort their data cards, they might notice additional variables they want to track, for example they might notice different wingspans, or they might notice that their labeling needs to be cleaned up to be useful. If students use different date formats or spell words differently, these need to be corrected in order to be analyzed. Sorting data cards makes this cleaning easy– to unify the entries in a category, students simply drag cards from one sorted pile to the pile that has the correct format or spelling.   

A moth collection window with three stacks of moth data cards

Sorting data cards so they are grouped into categories is a way of making data “hierarchical,” similar to what data scientists do when exploring relationships among variables. Going from a single stack of cards to stacks that are sorted by moth color, for example, is a hierarchy by color. In the same way, a completely different hierarchy of cards would be made if moths were instead sorted by antenna type, or body length. If appropriate, younger students can initially be introduced to data sets with multiple variables using physical data cards. Physical cards can of course be sorted into categories manually as students think about their data, and this leads well into the creation and sorting of virtual cards.

Window showing the option to sort a stack by different variables.

Interpreting Data and Revealing Stories

With a single click, students can create a graph from their data cards. Then they can easily change the graph axes to explore different questions they may have about how different variables relate to one another, creating multiple visualizations of their data. 

As students “sort” data cards representing each of their moths and then choose categories to graph (e.g., number of spots on the moths wing, or moth color, or size, etc.) they are more likely to understand what each dot on the graph represents. At times, students expect certain patterns to emerge in their data. When alternative patterns emerge instead, students can form new understandings of the world around them. Working with data is an important skill for students to learn and cultivate, and can be applied across disciplines within science, and beyond!