Craig Ortner

educe: bring out or develop (something latent or potential)

(math teacher turned lawyer turned math teacher again turned mostly school leader w/ a side of TOK)

[Craig Ortner @snortner]

1. Clarify what students must know and be able to do
2. Teach well
3. Read and write about the subject a lot

and most important, as much as possible, say "No" to doing everything else unless/until you are happy these are going really well, because of opportunity costs.

[SoL in the Wild @SoLInTheWild]

Here’s a key distinction I see missed in many of the framed for social media debates between inquiry-based learning and the science of learning.

The science of learning is not an instructional method. It is a body of evidence that helps us understand how learning occurs under different conditions. Inquiry-based learning, by contrast, is an instructional model—a particular way of organizing teaching and learning experiences.

Because of this, it makes little sense to place practices such as curiosity, questioning, or exploration into either an “inquiry” bucket or a “science of learning” bucket. Curiosity and questioning are not “inquiry methods” as claimed here. They are features of learning that can be leveraged through many different instructional approaches. If research shows that curiosity and questions can support learning, then those practices can absolutely be used within a science of learning, evidence-informed approach to teaching and learning.

Trying to frame these ideas as competing camps is often counterproductive. The real question is not whether we are using inquiry or the science of learning. Rather, it is how we use our understanding of human memory, attention, knowledge building, and learning processes to make evidence-informed instructional decisions. The science of learning should help us determine when, why, and how particular practices are most likely to be effective for the greatest number of students—not force them into opposing categories.

[Jack @tracewoodgrains]

I'm not sure this lands.

Take chess to see what it looks like at the limit. There is no skill in being an Engine Operator. Humans don't add to the engine by knowing how to turn it on just right. You run Stockfish and humans cannot even contribute.

Skill development changes you in concrete ways. A skilled chess player sees the board fundamentally differently, and better, than an unskilled one, memorizing positions in the blink of an eye, noticing patterns, spotting tactics. Yes, humans are obsoleted by machines there. But that does not make you equal to Magnus Carlsen.

So – school. Maybe we just want it all to be trade school, where the goal is to maximize earnings, and so humans should abandon every intellectual task obsoleted by AI. Maybe. And on that trajectory, perhaps we can abandon every intellectual task, full stop, because the train shows no signs of slowing down, and we're all about to be left behind.

Do we want to be slaves to minds greater than our own, masquerading as their masters because we know how to turn them on? Do we want to stop creating Terence Taos because Codex out-calculates us? Do we want every classroom to maximize the skill of flipping switches, accepting our own obsolescence by becoming eternal adolescents?

I do not. Skill-building matters as a good in itself. Training your mind matters. Becoming better and more knowledgeable, in concrete ways and in narrow topics, climbing skill pyramids ourselves rather than abandoning every intellectual skill, matters.

And any skill that is worth training, any subject that is worth learning, is worth training and learning right: in a way that actually improves the individual.

AI is not going away. But I'm not ready for human skill building to go away either. There are more chess classes worth preserving than "how to download Stockfish."

[Justin Skycak @justinskycak]

Achieve automaticity on foundational skills to free up mental resources for higher-level creative thinking.

[Nathan Whitaker @NathanWhitaker]

Every organization already has a culture.

The question is what it rewards, tolerates, protects, and repeats.

If you want to change a culture, don't start with slogans. Start by examining what behaviors get celebrated...and what behaviors get a pass.

[Craig Ortner @snortner]

@dylanwiliam @thisdudelikesAI Stealing an argument from https://t.co/FmVjWQxo4h

[Craig Ortner @snortner]

@dylanwiliam @thisdudelikesAI If you want to prove calc and understand it deeply you need limits. If you just want to use it then why belabor limits. Calc developed for centuries before algebra, much less limits.

[Ash Jogalekar @curiouswavefn]

Since everyone's talking about Erdős problems, I cannot recommend enough Paul Hoffman's biography of Erdős, the most prolific mathematician in history and a wholly singular and weird and wonderful character, even by mathematician standards. It's one of the best scientific biographies I have read.

https://t.co/jrd1pvdDCK

[Jon Hutchinson @jon_hutchinson_]

My latest instalment on belonging introduces “the belonging cycle’.

It’s based on a research review from Gregory Walton and explains what’s going on in a person’s brain when they are working out whether or not they belong.

Link below!

[Adam Boxer @adamboxer1]

The answer to this is simple, but implementing it is hard. To build a school or department approach, you need the below:

1. A systematic, workload friendly, programme of at-home retrieval practice*.

2. In-class accountability from the at-home retrieval practice.

3. Cumulative assessments (i.e., ones that test all content).

4. In-class interleaved practice.

*Systematic: covers all items in the curriculum

Workload friendly: self-explanatory, though it is about ratios. The most workload friendly solutions mean the teacher clicks a button and it all happens for them. This is unlikely to be effective. So there needs to be *some* input from the teacher in terms of setting and accountability, but you need to ensure the ratio of workload: impact is good.

At-home: unfortunately, there simply isn't enough curriculum time to do this kind of work in class.

[Gena Gorlin @Gena_I_Gorlin]

“Hey, you can see the map down there!”

[Jordan Adams @Jordan_C_Adams]

If even 10% of admins, teachers, and parents watched this, America would undergo an education renaissance.

[akhivae @akhivae]

Rich people be like I don't have a smartphone. I have a full-time secretary (she has four smartphones).

[Craig Ortner @snortner]

#IBTOK

[Jeremy Raper @puppyeh1]

This appears to confirm what everyone who interacts with AI should already know - they are sycophants dependent upon you (the user) for continued engagement, and since their well-being (training, intelligence, growth) depends on engagement they will agree aggressively with you far too often.

I notice this on even basic investing research tasks, and started telling ChatGPT wildly incorrect things - to see how or if it would push back. It really didn't. You essentially have to fight with the AI to get it to disagree with you and even then it keeps wheedling away at you.

AI is basically training the entire world to fall deeper into their own cognitive biases.

[Pengu @Penguxn]

if you think uncomfortable conversations are hard wait until you see the results of not having them

[George Mack @george__mack]

The high agency triangle

[Justin Skycak @justinskycak]

The easiest way to change behavior is to stop placing temptation an arm's reach away.

[Adam Boxer @adamboxer1]

Ok, for those who don't understand the word "correlation" and assume that I am a psychopath. I MADE A GRAPH

[alex peysakhovich @alex_peys]

got a framed copy to hang by the ai team

[Tom Bennett OBE @tombennett71]

Love it when a non-educator drops stone-cold wisdom about how to learn to be good at something: learn the basics, not the outcome. Learn the things that lead to the outcome.

[Justin Skycak @justinskycak]

If your study method hides mistakes until the test, then be prepared to make tons of mistakes on the test.