As I was heading off to lunch today (roast beef, couscous, roast vegetables and an apple, yeah, all good thank you), I was talking to a colleague about a recent National Geographic article. She mentioned her Dad had hauled out a NG from the dawn of time with an article they’d been discussing. Yes, they’re *that* kind of people…
I remembered back in my early computing days I’d laboriously entered in a magazine article index database program from a Compute! magazine, and having got the program finally debugged and working on my beloved Apple IIe. I then entered in a couple of years worth of NG issues. And then I clicked that the problem was in the searching. Was the article about big cats > in Africa > their impact > on ecosystems > and human geography > or was it about the photos > or what?
About 20 years goes past. Enter tiddlywiki. I figured they’d make a great way to teach wiki, database, data mining, tagging, and a host of other meaty goodness in geog/language/computing/et al classes. Tiddlywiki would also be a great tool to use because of its low demand, and it’s a free download.
My approach would be to grab a year’s worth of NGs (I sold about five year’s worth at a garage sale for $10 just before xmas – shop around). Get the students in teams and distribute the mags accordingly. They can read the articles, and start to tag them, using post-its. Once the students had teased the articles out, each group can tiddlywiki with a tag cloud plugin. When everyone has done the exercise, build an uber-tiddlywiki, and import the respective tiddlers to form a catalogue of the year’s editions. There’ll be a geek or two who can make it all work consistently, and an artist or two who can look at the css to be unique and beautiful – there’s room for everyone to come up with some input. And the tiddlywikis lend themselves to digging deeper into the information, while permitting links ‘out’ into the net – to other resources and information.
The next exercise would be to use a tiddlywiki in the same sort of way in a language class – analyse a Shakespeare play from different perspectives, and then slurp it into an uber-tiddlywiki, and then copy it to everyone so the notes were built by all, and shared by all. I’m usually not a big fan of collaborative work for assessment purposes, as my experience has been that the work load is not always evenly shared. But in the assembly and analysis of material for notes – there’s an opportunity for everyone to make a contribution, and the keen people are not penalised.