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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Applying Efrat Furst’s Model of Building Long-Term Memory Representations | BenRogers

One of the challenges facing teacher is to know when to apply specific tasks to support long-term learning.

I have been using Efrat Furst’s model of long-term memory (here) to help new teachers sequence learning activities, and to build sequences of my own. The model begins with the first exposure of concept and builds up to mastery. Much of this post is also covered by Furst here).
Furst’s Model of Building Long-Term Memory Representations

The first encounter with a word or concept. Once the learner has been exposed to the concept, she may be able to recognise it again in the…

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Faded Support Terminal Velocity Writing Scaffolds | BenRogers

Explaining terminal velocity is a classic piece of GCSE writing. The cognitive demands are high:
recalling the sequence;
structuring the text;
phrasing the sentences.

I have designed this sequence of faded scaffolding to take place over several weeks (making use of spaced practice). It follows on from direct instruction style teaching.
Model response to task, demonstrating some tricky sentence structures.
A pdf of the full sequence is here: Terminal velocity frames (variation theory)



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