A belated happy new year to anyone still out there in burble land.
And a brief explanation of the lack of burbling in recent months. Last term was the busiest and most stressful term I can remember in over fifteen years of teaching. For a variety of reasons, I became thoroughly disillusioned with teaching and lost all motivation to write up ideas in what little free time was available.
I cheered up a little when someone provided a link to this wonderful satirical blog on teaching https://robertpealhistory.wordpress.com/blog/ ( the blog article: “Keep it simple, stupid”).
But then I found out that far from being satirical, it was the real deal. Worse, it’s an approach to teaching that is endorsed by that great educational reformer Michael Gove AND the Daily Mail.
OK, Mr Peal is working in a completely different type of school. He’s teaching a different subject. He has challenges of classroom management and pupil behaviour that I rarely, if ever, encounter. I’m generally in agreement with his view that Powerpoint should be used to show images, not provide the backbone of a lesson (though he seems woefully ignorant of the potential for its interactive, non-linear use). And, of course, children like structure, reliability, the security of knowing that they’re learning.
But that doesn’t mean a lesson can’t also be fun, challenging, imaginative, varied, surprising…. The very last thing a teacher should be is….
So, in the interests of balance, The Burble Is Back.
And where better to start than with Excel spreadsheets.
Context – Year 9 Enzymes. They’ve covered the basics of enzyme kinetics, largely discovered by themselves, and are now looking at different ways of measuring enzyme activity (rate of substrate breakdown, rate of product formation, etc).
The investigation was this splendidly challenging Yeast Catalase and Temperature activity – pretty much the same design that I use with Year 12 when they try to demonstrate a Q10 effect and have to evaluate whether and why their data does not match the predicted pattern.
I’m not expecting Year 9 to get a Q10 curve, but it’s a self-differentiating, challenging activity that is exciting, different, fun, surprising…
Now you can see from the attached homework questions that I want them to analyse and evaluate their results. But there are lots of potential problems with this. Some groups only manage to cover 2 temperatures. Others have, shall we say, technical difficulties. Others have data that shows no coherent pattern at all. Students trying to work with this kind of data inevitably end up confused – and we’re back to that horrible question that negates scientific curiosity, “what’s supposed to happen?” We need to use ALL the data in some way.
So look what happens if you get them to enter it into a class Excel spread sheet (names have been changed…) which I’ve also projected on to the white board.
Why does this help? Well, firstly, it adds a level of interest, and dare I say it, competitiveness to the lesson. For some reason, they just love putting stuff on the board. It also helps keep them very busy and focussed (good test of a successful lesson, I think, is when the bell goes and the students looks surprised that it’s the end of the lesson – has the time really gone that quickly?). And, vitally, they still have ownership of the data – these are THEIR numbers – they become quite attached to them in a way that just can’t happen if you pick a problem out of a textbook.
Now with our current timetable, I use the entire double lesson to carry out the practical and collect the data, so we return to the numbers in the following single. I project the completed table on to the board and immediately lots of important learning outcomes start emerging.
First, despite all the best efforts of “Shall we do the fandango?”, much of the “noise” has disappeared from the data and the means show a clear, enzyme like pattern. The value of doing LOTS of repeats is immediately apparent.
But why else might we do repeats? What else can we see? Yes, some of the numbers seem out of place. What could we do with these numbers? A bit of discussion and they see that by looking at the overall mean, and then comparing it with individual numbers in the table, we might choose to eliminate some of the data. At which point I produce this version of the table as a handout…
… and get them to identify anomalies. I give them about 5 minutes to do this, and then it becomes a bit like evicting contestants from the Big Brother household. Or The Weakest Link. We discuss rigorous criteria for eliminating numbers (rather than just a vague sort of “well, it doesn’t look right) and then vote on which numbers are out.
And because the numbers can be removed, live, from the projected Excel spread sheet, it automatically recalculates the mean, far more quickly and accurately than they could ever do themselves. It means they’re focussing on the actual numbers, rather than fiddling round with calculators. The rate for 70’C now drops, correctly, to zero. We can discuss why two groups found activity at this temperature and we have an evaluation point – they fess up, admitting that they probably didn’t keep it in the water bath for long enough before mixing the reagents, so there wasn’t time for the enzyme to denature.
Once this is over – and the discussion and voting is much more fun than you might imagine – they can copy the new means into the Revised Mean Mean row and they’re set to plot the graph and answer the questions.
And there goes the bell…