Collaborating on a data analysis project: students do the math with the Google Docs spreadsheet program

For many years, I had my biotech students do projects where each group of students would analyze their own data, in addition to all of the data gathered by the class. I would draw a table on the white board and each group would enter their data. At the end of the class, all the groups would copy all the results into their notebooks, then analyze them in Microsoft Excel.

This worked pretty well, but it wasn't perfect. There were always cases where one group would be really slow, or someone had to leave early, or I needed to use the board and couldn't.

And, this method certainly wouldn't work for an on-line course. You don't want students to have to post lots of data to forums or e-mail spread sheets back and forth.

Google Docs spreadsheet program has solved this problem!

Students can gather data and collaborate on-line on the same document at the same time.

And I can control whether students are able to edit a document, or simply view the document and download the results.

I can even share the document with the world, if I so choose.

And when I tried this out in my class a couple of weeks ago, it worked really well!

Here's what we did:

1. Before class, I set up the table for data entry.
2. All my students went to www.google.com and signed up for a gmail account (if they didn't already have one).
3. I clicked the Share tab and entered a list of my students' gmail addresses.
4. Then, I clicked Invite Collaborators to send an e-mail to the students.

5. The students clicked the link in their e-mail to access the spread-sheet.
6. They entered their results in the spread sheet, simultaneously, as they worked on identifying their bacteria via blastn. This went on during and between class periods.
7. Then in the next class, I used the Sort function to sort data, show them what happened, and discuss some of the issues related to data analysis and bioinformatics, for example:

• being a good citizen and entering your data in community databases (I had never realized before this fall that so many of the information-poor entries in GenBank are that way because of the people who entered the information so poorly!)

• consistent data entry (it's hard to analyze your data when all the entries describe the same thing differently)

• the work that you have to do to clean up your data before you can analyze it, like fixing names, making all the entries consistent.

Then, all the students downloaded data to their own computers for analysis and graphing.  The students could have made some graphs in the Google document, but I wanted all the students to get practice. Second, I wanted to them to use PivotTables to analyze the results for the two different biomes (creek vs. forest) and that feature isn't available in Google Docs.

If you'd like to take a look at our results and see the table, I also published our data. You can find it at:  JHU_bacteria_2004