I recently had my students use the infogr.am website to create infographics to accompany blog posts about an inquiry in to reaction time that they conducted. The students found the site to be very easy to use.  The utility of the graphics in conveying the information is up for debate.  I'm very interested in working to have students consider how to convey information in useful AND visually interesting formats.  This experience got at the later more strongly than it did the former.  Part of this was due to my own fault in constructing the guidelines.  I find that typically, I tend to introduce a new tool in a very open manner the first time, and then use that experience to create more detailed guidelines for future uses.  For this project, students were only asked to create three different graphics displaying their data, so it's not all that surprising that the results suffer from lack of context and conscious consideration as to whether or not the mode of presentation is appropriate for the data.  If I use it again, I'll most likely incorporate guidelines that detail these two aspects to help students better frame their usage.

The infogr.am tool is very user-friendly and did not present students with any major difficulty in usage.  It seems to demonstrate a larger trend in internet-based design platforms by restricting aesthetic choices to a palate of colors, fonts, etc. that play well together visually.  Things will tend to look good, even if they are meaningless.

Below are some examples, with brief comments afterward:

The above series is interesting, but the lack of context on the document precludes any real meaning about what it is showing.  This is dealt with in the original blog post, to some extent.  

This series (all from the same data set) is pretty illustrative of the larger notion that some forms of data representation are more appropriate than others.  To my own mind, the stacked column scheme in the first graphic is less useful than the x-y plot in the second.  The grouped bar chart seems to do the best job at "telling the story" of the data.