Inspired in part by a conversation from the Information Literacy Summit last week, and in part by this post from the awesome David Silver, we made tag clouds in my class this morning. U-Engage is a first-year experience class, providing an introduction to what a research university is in general and to OSU in particular. There are 100 students in the section I teach (actually, there are somewhere around 90) and the room is a classic, old-school lecture hall.
The size and the room make the course difficult in terms of planning engaging activities for the lecture time (the assignments and recitations are a different story – I think they’ve had lots of interactive activities there). This has been compounded by the fact that most of the course content in the middle of the term has been delivered by guest lecturers. I’m co-teaching the class and both of us have been feeling that we really wanted the last few weeks to be interactive and engaging because we have been kind of on the sidelines for so long.
My co-teacher had a brainstorm for last week’s activity, but we still didn’t have anything ready for this week – the final week before their group project presentations. The textbook wasn’t inspiring. There is some great information about the value of reflection (which has been a theme throughout the course), and on goal-setting but that stuff didn’t lend itself well to the kind of activity we had in mind. Reflection and goal-setting kind of needs to be personal to be meaningful the way these things are presented in the text, and we wanted something social and collaborative.
So at the IL Summit my husband Shaun talked about how he has an assignment requiring students to pull keywords out of the readings they do. It was fascinating to hear about that because his students’ difficulties finding keywords in many ways mirrors the difficulties we see students having in the library when it comes to choosing keywords. But because he is working from a known thing “what are the keywords that the author uses that capture the key ideas in THIS TEXT” he has an advantage we don’t – it seems like that would work way better as a first step than what we frequently have to do – “try and predict what words authors will use in this discourse that is entirely or almost entirely unfamiliar to you.”
In his presentation, Shaun mentioned that he is still working on ways to make the larger class discussion about the keywords work better, and I thought about David’s post above. But it wasn’t until I was working at the reference desk on Saturday that it all came together in my head – collaboration, social, keywords and tagclouds.
So here’s what we did – I demonstrated Wordle because, like David, I expected that most of the class wouldn’t know what a tag was and by extension, wouldn’t know what a tag cloud was. I wanted to get two ideas across: the idea that the tags needed to be single words or at most two-word phrases, and the idea that the tags would display larger if they were used more often.
(I also thought that Wordle would be of interest to some of the class, that it might come in useful for its own sake in their final projects, and that some of them might find it a useful study tool).
Then we asked them to come up with 5 keywords that described their first term/ transition to college and write a reflective paragraph about that. Once that was done, we go to do the social part. We had them get in groups of 4-5 and create a tag cloud out of all of their keywords. This is why it was important to me to make sure the concept of “more use = bigger text” was clear. To do that right, they would need to talk about their keywords, what they had in common, and if they maybe chose slightly different words to get at the same concept. These small groups also had to come to consensus on five “group” keywords.
Looking at the group keywords after the fact, I was surprised that a lot of the groups seemed to put together their five not by choosing the five most “popular” keywords (the ones used by most people) but instead that they tried to choose one of each group members’ keywords. I think this makes sense when the assignment is as personal as this – if they were trying to choose keywords that would reflect the meaning of another person’s text, I would expect this might be different. In addition, some groups used keywords for their “group” keywords that didn’t appear on any of the individual lists.
ETA – we took pictures –
Then, each group had to send one member to the chalkboard to come up with a group tagcloud, using the chalk that was available. On one level, this would ideally take a while as the groups compared their five words and decided how best to represent them. In practice, it didn’t work out that way, but I think that the way it did work out was better. As it turns out, there was very little overlap in terms – in fact, there was less overlap in the group terms than there was in the individual terms in one sense. So while there were a few terms that should probably have been bigger because lots of groups had them, there weren’t many like that.
ETA – more pictures –
Secondly, even though there were 14 or 15 people up at the board making the tagcloud (remember – there were about 75 people in class, and the small groups were only 4-5) that meant there were still WAY more people than that still sitting in the lecture hall seats. This means that every minute the representatives spent figuring out the “right” way to make a tagcloud was a minute the vast majority of the class had to be dis-engaged.
So instead, people talked some and made some words bigger because they were repeated. But they also made some words bigger because they were the words that the smaller group had felt were the most important. And there’s a validity to that, and a meaning to that, that I don’t think our original plan had captured.
ETA – last photo —
All in all, I was pretty happy with how the exercise turned out. I think this kind of exercise could have been especially effective earlier in the term, before the students knew each other as well as they do now – to humanize the 100-student classroom environment. And on that note, I think this kind of exercise would work really, really well in library instruction sessions as well. Combined with Shaun’s idea above about pulling keywords from a text, or perhaps using keywords generated another way – it’s a safe, collaborative way to talk about the connections between ideas and the terms we use to describe those ideas.
And isn’t that the big picture philosophy behind keyword searching – I mean, isn’t that the fun part?
Finally, I have to say that we could have just had each group representative put their terms into wordle – but I don’t think that would have worked as well. I think the physicality of the chalkboard and the actual social/cognitive act of having to do themselves what the computer does for us was important in making this engaging. In this case, the sheer number of people involved and the limited time we had meant that some got more out of it than others – and the chalkboard session had more of a free-for-all feel to it than a Deep Thoughts feel.
This also seems like a great way to connect class work/ reading with library session work. I think we all feel like the “teach how to drive the databases” one shot feels disconnected from the learning that goes on in class in a way we don’t like. We talked after the Summit about building in some keyword exercises in our beginning composition classes, at the start of the term in the non-researched papers, and using those keyword exercises to get at the critical reading piece that Shaun talked about with his assignment.
I think that’s a great idea on its own, but I also think that then building from keywords there to keywords while exploring ideas and finding your own sources might draw a connection between the idea of critical reading, writing and research — all of the pieces of the course. With the tagcloud exercise, it’s easy to think of ways to do that in the disciplines as well – a pre-library session assignment identifying keywords from a class text, a library session tag cloud of that text and another of the student keywords. And so on and so on and so on, leading up again to student-generated tag clouds representing ideas about research and suggesting pathways they can use to research about ideas.