Three Effective and Efficient Reasons for Reading in Science Lessons | BenRogers

Being a good reader correlates with good performance in science. Well, it would wouldn’t it? Reading scores correlate well with performance in most subjects. But it would be naive to think that improving reading ability would improve performance in science. 

It is hard to learn science through reading, which is presumably why we don’t do it often in class. If you want a learner to understand and learn a complex concept, you are unlikely to set a text. This isn’t what reading is good for, at least for most of us.

In this post I will describe three effective and efficient uses of reading in…

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Three Effective and Efficient Reasons for Reading in Science Lessons

The Impossibility of Reliable Setting by Ability | BenRogers

In principle, I don’t like the idea of setting by ability. It feels like segregation. But I also don’t like the idea of teaching wide ranges of ability in my classes. Except that I already do.

Despite all the warm words and passion on both sides, setting by ability isn’t really possible: you can’t measure ability precisely enough – the error bars you should be asking for when you get the results (Standard Error of Measurement) are surprisingly big.

We all know you can have a good test or a bad test – not about nerves, or lack of sleep, just they asked the right/wrong questions for you….

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Kasetsu – a highlight from ASE | BenRogers

One of my joys at the ASE conference is meeting up with Japanese science teachers. I admire their work tremendously – I was unable to attend the sessions this year, but was very happy to meet up (and I bought the much anticipated book containing Kiyonobu Itakura’s work translated into English – which is wonderful).

It explains the theory behind the technique developed by generations of Japanese science teachers called Hypothesis-Experiment or Kasetsu.

Explanation of Kasetsu by Professor Haruhiko Funahashi, Tomoko Hasegawa, and Mariko Kobayashi.
A super-short explanation of Kasetsu (or…

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Super-Quick Update to Refutation Texts | BenRogers

Brilliant ASE conference! Loads of curriculum thinking. Disciplinary and substantive knowledge very important (see Counsell here).

Charles Tracey (@physicsnews) suggested the use of ‘practice’ to describe the practices of scientists, including how scientists decide on what counts as evidence and knowledge. Disciplinary knowledge is all about our ‘practice.’

Charles suggested that writing explanations should include disciplinary knowledge as well as the more usual substantive knowledge. When another colleague mentioned misconceptions, I thought I’d make an addition to my refutation text…

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My ASE Slides – before I present them | BenRogers

This may be counter productive, but ASE conference time is precious. If you were thinking of coming to my presentation, please take a look at the slides (they’ll be tweaked obsessively as we get closer to Thursday). I hope someone out there is looking for this sort of thing – but I’m happy for it just to be me!

copy of ase problem solving (with bar-model) jan19

I’d love to see you there!


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How Knowledge Grows… | BenRogers

We are all now familiar with the idea of schema: the mind-map diagrams representing knowledge and the relationships between items of knowlegde.
A schema representing the relationships between knowledge
And we are familiar with how Cognitive Load Theory uses schemata to explain how richer schemata make us more creative and better problems solvers.
Working memory can draw on schemata to deliver knowlegde with very low effort. 
Finally, we probably all remember reading Daniel Willingham on chunking groups of knowlegde together to make a new single composite item of knowlegde (see here).


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My ASE Talk January 10th 2019 – How to Teach Problem Solving in Science (with added Bar-Models!) | BenRogers

I have planned the outline of my ASE Annual Conference talk (Thursday 12.00). It may develop a little, but the gist is:
Numerical Problems in Science
What does Cognitive load Theory teach us about problem solving?
The CLT model
Goal Free Effect
Worked Examples
Completion Problems
Expertise Reversal Effect

How can Efrat Furst’s models help us plan to develop problem solving in learners? (here and here)
The Bar Model: How can the Singapore Maths method of Concrete/Pictorial/Abstract help develop problem solving skills in science? (Download my bumper examples pack: Using Bar-Model to…

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