This is the first ever episode of the Teacher Ollie’s Takeaways podcast, the podcast in which I summarise my key takeaways from twitter, blogs, research papers, conversations, and even my own classroom, from the week just past.

If you have any thoughts or comments after listening to this podcast, please share them with me via twitter: @ollie_lovell

# Show Notes

## John Hattie on Direct Instruction

“John (Hattie, 2009) defines direct instruction in a way that conveys an intentional, well-planned, and student-centered guided approach to teaching. “In a nutshell, the teacher decides the learning intentions and success criteria, makes them transparent to the students, demonstrates them by modeling, evaluates if they understand what they have been told by checking for understanding, and re-tells them what they have been told by tying it all together with closure”(p. 206).”

“When thinking of direct instruction in this way, the effect size is 0.59. Dialogic instruction also has a high effect size of 0.82. This doesn’t mean that teachers should always choose one approach over another. It should never be an either/ or situation. The bigger conversation, and purpose of this book, is to show how teachers can choose the right approach at the right time to ensure learning, and how both dialogic and direct approaches have a role to play throughout the learning process, but in different ways.”

“Precision teaching is about knowing what strategies to implement when for maximum impact.”

Some comments on my Masters Project…

“This study shows that, for under-achieving students, the bridge from mathematical challenge and disengagement to success and motivation is a fragile one, and the journey across it becomes more perilous the older a student gets. The ongoing challenge for teachers is to shore up and scaffold this fragile bridge’s structure, and to ensure that the scaffolding provided is appropriate to both the ‘who’ that is crossing, and the ‘when’ of their traverse.”

*Tidbit*

“Factor Game ( http:// www.tc.pbs.org/ teachers/ mathline/ lessonplans/ pdf/ msmp/ factor.pdf ) in which an understanding of primes and composites was crucial to developing strategies to win”

## The Mr Barton Podcast with Dylan Wiliam

Original article here.

**Reciprocal Teaching**

Robert Slavin: When we encourage students to help each other, whilst there are great benefits to both students, the students who learn the most are the ones who do the most explaining.

**The Relevance of Problem Contexts**

Jo Boaler:

Q: ‘When do girls prefer football to fashion?’

A: When it’s the context of a maths question. Presented with a structurally identical maths question in two different contexts, girls do better than boys when the context is that of football (soccer). This is because they bring less irrelevant and confounding background knowledge into the solving process.

**What is learning?**

Paul Kirschner: Learning is a change in long term memory, Aka: if they don’t remember it in 6 weeks, they haven’t really learnt it.

Relatedly… John Mason: ‘Teaching takes place in time, but learning takes place over time.’

Ref: Jame’s Manion’s article, Learning is Meaningless.

**We don’t actually Know what Good Teaching Looks Like!**

Heather Hill: We need to stop kidding ourselves by thinking that we can pick a good or a bad teacher by observing them teach a class. Hill suggests they would need to be observed in 6 different classes by 5 different observers (a total of 30 observations) to obtain a reliable rating.

*Edit: I emailed Heather Hill about this, and this is what she said: “hanks for your question. For my own instrument, it originally looked like we needed 4 observations each scored by 2 raters (see attached paper). However, Andrew Ho and colleagues came up with the 6 observations/5 observer estimates from MET data:” Ho’s paper. *

Dan Goldhaber: Comparing two models of ‘good teaching’ (a fixed effect and a random effect model) based upon ‘value added’ metrics, the best 9% of teachers as rated by one model were classified as the worst teachers in the other!

Dylan concludes that we can only really comment in the extremes, i.e., ‘We can be pretty sure that a teacher who appears to be very very good is in fact not very very bad, and we can be pretty sure that a teacher who appears very very bad is in fact not very very good.’, but that’s about the extent of it.

So… where to? Dylan says that team leaders should focus on one question: ‘What do you want to get better at and how can we do it?’. I’m (Ollie) a bit dubious about this and I think that team leaders could help by guiding efforts to areas where we can be pretty sure that they’ll have a positive effect on learning (more frequent assessment and better feedback, distribution of practice, better modelling, etc).

**Thinking Hard and Distributed Practice**

Robert Bjork: The harder you think about something the better you remember it. Relatedly, the best time to study something is at the point just before you’ve completely forgotten it!

**Simple Hacks to improve Assessment**

The hypercorrection effect: You get two benefits of assessment, the first is when the testee is forced to recall the information in the first place, this strengthens the synaptic connections. The second benefit is when they see the answer. Thus, in order to maximise learning, the best person to mark a test

Synoptic testing: Testing shizzle up to the point that you’re now up to!

**Building habits (****NY Times article****)**

Charles Duhigg’s TED talk.

*“the core of every habit is a neurological loop with three parts: A cue, a routine and a reward.*

The summary of this article is that you want to get to a point where the reward is internal, i.e., you don’t need any external input from yourself (or your students), to feel good about the habit that you’re trying to establish. However, the interesting thing that this NY times article points out, is that you can start of with an external reward, and use this to build the neuro-associations in such a way that the external reward will eventually be no longer required. I’ll read an excerpt from the article that provides a good example.

*“If you want to start running each morning, it’s essential that you choose a simple cue (like always lacing up your sneakers before breakfast or always going for a run at the same time of day) and a clear reward (like a sense of accomplishment from recording your miles, or the endorphin rush you get from a jog). But countless studies have shown that, at first, the rewards inherent in exercise aren’t enough.*

*So to teach your brain to associate exercise with a reward, you need to give yourself something you really enjoy — like a small piece of chocolate — after your workout.*

*This is counterintuitive, because most people start exercising to lose weight. But the goal here is to train your brain to associate a certain cue (“It’s 5 o’clock”) with a routine (“Three miles down!”) and a reward (“Chocolate!”).*

*Eventually, your brain will start expecting the reward inherent in exercise (“It’s 5 o’clock. Three miles down! Endorphin rush!”), and you won’t need the chocolate anymore. In fact, you won’t even want it. But until your neurology learns to enjoy those endorphins and the other rewards inherent in exercise, you need to jump-start the process.*

*And then, over time, it will become automatic to lace up your jogging shoes each morning. You won’t want the chocolate anymore. You’ll just crave the endorphins. The cue, in addition to triggering a routine, will start triggering a craving for the inherent rewards to come”*