Wednesday, 5 September 2007

Just In Time

Just as I was starting to get a little bit fed up with the themes that seems to be emerging from this year's ALT Conference, Dylan William saved the day with a wonderfully refreshing, well-delivered keynote speech.

I'll blog more about this over-arching trends that have dominated this year once the conference has properly finished, but one of note has been this idea of putting the learning in charge or learning. This encapsulates the "we don't understand our students so should be more like them", "their attention span is only 5 nanoseconds therefore we can never expect them to be able to concentrate", "the students should decide what to learn even though they probably can't be bothered" and the "if we were more like Facebook and they'll want to learn more" concepts that we've touched on already and seen in other conference over the last year or so. (Indeed, as I write this while sciving the last session of the day, I can hear delegates performing the equivalent of penis envy with regard to Facebook!)

These ideas are not without merit, but I'm still not convinced that we should be tearing everything up to implement them. That's where Dylan's keynote was so interesting. One of his more memorable lines was forcing students to work using various learning styles, including those that they might not necessarily like. "School is where students go to watch teachers work." (I probably did not quite paraphrase this right!) This is at odds with current trends of aiming to get educators to accommodate students' individual learning styles.

Much of his talk was on using face to face contact time to improve "classroom aggregators". In a nutshell, this is data accumulated during classes in response to questions or other activities that all students are required to engage in. (Using clickers is an example of this.) He gave some useful examples of good questions to ask from the field of Mathematics and Physics, including traditional MCQ and MRQ questions through to more complicated examples that might elicit a relatively large but still finite set of responses. This gave instant feedback on the current state of the class' understanding, allowing a (good) educator to take the most appropriate next step. ("Just In Time" teaching!)

The refreshing thing about this, as we know from our previous low-tech "clickers" involving bits of coloured cardboard, is that you don't really need complex technology to try these ideas out as well. And, despite being "disruptive" technologies in many ways, educators do not have to completely redesign curricula in order to try them out, as we've seen with the gradual roll-out of clickers across the College of Science and Engineering. Of course, creating good diagnostic/feedback questions is not easy and requires skilled educators, and technology can't really help here so it's good to see pedagogy having to win over shiny new gadgets.

Where technology will really help here is in William's ideas for modeling student progress using data gathered from these aggregators and analysed alongside existing student data. Using clickers rather than coloured cards already makes student voting data ready for being mined so is a good start. But this is just the soft fluffy edge of a really complex (but interesting) problem which kind of falls outside the usual domain of learning technologists so it's maybe hard to see who'll be rising to the challange.

All in all, a good keynote delivered in an enjoyably dry style with a suitably loud tie!

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