In this post, we show you how to make a dataset that you uploaded to Tuva available to students for their own exploration and use. We will work with the Boothbay Harbor sea surface temperature (SST) dataset that we uploaded in an earlier “how to” post. We also illustrate a few of the many things you can do with Tuva, including “filtering” the data so that you only see a part of the data. We will also show you how to change the range of the axes on a graph and how to save a particular graph for future use. As in our first post using Tuva, we will assume that you are using the basic, free version that Tuva makes available to teachers. Of course, what we show you here also works with the premium version. The premium version also provides with additional ways to make assignments available to students that you will probably want to use if you have access to that product.
Before we begin looking at the data once again in Tuva, we should review what is in the dataset. It contains the average monthly SST in Boothbay Harbor for each month from September 1969 through August 2018. We calculated these monthly averages by starting with the publicly available daily temperature data and calculating the mean for each month. We collected these monthly averages in a new dataset where we used the fifteenth of each month as the date for each month’s average. We used this arbitrary, mid-month date because we have encountered a number of tools that need an actual month, day, and year to treat data as a sequence of dates.
So, let’s dive back into the data using Tuva. The following video shows you change the range of the axes on a plot and how to save a plot for future use.
Once you have saved a plot, you may want to share it with students in support of some work that they are doing. This next video picks up where the last one left off, showing you how to provide students with access to a plot that you have created.
The final video in this post shows how students can use the plots that you provide them to answer a question. You might remember that in our post about green crabs, we noted that the data that we had about early stages of crab development was from a study that was done in Boothbay Harbor in 1979 and 1980. We observed that the timing of hatching and the length of the growing period are likely to have changed since the fall of 1979 because the water in Boothbay Harbor was, most years, warmer now than it was then. Well, how much warmer is it? The students could use the Boothbay Harbor data to answer that question. This video shows how they might do that by using “filters” and a trendline.
As we noted in the video, the students cannot save their changes to the graph on the Tuva system when we are just using the free version of Tuva. (The premium version does allow students to save their work.) However, they CAN save a graph that they have made by capturing a picture of their screen. How you do that is different depending on whether you are using a Mac, PC, Chromebook, or something else. Searching the Internet for “screen capture” will lead you to information about how to that. Or, you can get in contact with us and we can help.
Hi Bill and CSI teachers,
This is great — thanks for the nicely done videos.
Here’s another Tuva trick to make it even easier to find the difference between SST in 1979 (or whenever) and 2018: Click on Stats and click “Add Reference Line to Y”. A line appears that you can drag to where the temp is in 1979. Then click “Add reference line to Y” again to add a second one, and put it where the temperature is in 2018. Hovering over each line gives its value, and you can simply subtract them to compute the difference. Students can color their reference lines by highlighting the reference line, then click on the small dot beside the X and a small color palette appears.
Also, if you have any questions about Tuva or troubleshooting needs, they respond quite quickly — just send them your question at firstname.lastname@example.org
— Molly Schauffler
Thanks, Molly! That’s a much better way to compare the starting and ending averages.