Una rigorosa alternativa ai test

Il primo di due articoli di un neoliberista... Questo è un articolo di un professore di economia con poca esperienza diretta nel campo dell'istruzione, ma che crede che i principi economici del libero mercato siano la risposta ai problemi dell'istruzione (e praticamente di tutte le altre società).

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febbraio 15

Una rigorosa alternativa ai test

Questo episodio è per gli abbonati a pagamento

		MICHAEL B. CORNO

How do we measure not how smart someone is, but how they are smart? That’s the question that Elliott Washor and Big Picture Learning have sought to answer with their innovation—the International Big Picture Learning Credential. Exactly how they have built this set of credentials and made it valid and reliable is the topic of my conversation with Elliott—and what it might portend for the future of learning. As always, you can listen to the conversation here or on your favorite podcast player (just search the Future of Education), watch the conversation at YouTube below, or read the conversation below in full if you’re a paying subscriber.

Michael Horn:                Welcome, welcome, welcome to the Future of Education where we are obsessed with helping all individuals build their passions and fulfill their human potential. And today’s guest has been doing that for a heck of a lot longer than I’ve been involved in trying to transform education and he’s been doing the work in a variety of ways, really by pushing the envelope or even ripping up that envelope and throwing out the playbook altogether and innovating. His name is Elliot Washor and among the many hats that he has worn and had, he’s the co-founder of Big Picture Learning. He’s the co-founder of the Met Center in Providence, Rhode Island. And we of course have had learners from Big Picture Learning schools on the show we’ve had Andrew Frishman on the show. But the topic that I really want to dive in with Elliot on is the international Big Picture Learning credential, which in the words of Elliot to me, “Changes the equation by measuring how an individual is smart, not just how smart they are.” And I think that’s a really profound flip and an exciting set of opportunities. So first, Elliot, welcome. It’s really good to see you. I assume you’re coming to us today from San Diego?

Elliott Washor:           Yeah, it’s not what people think. It’s raining and chilly here today. I got a sweater on even. I don’t mean to make anybody feel bad who’s in real cold weather, but not all is perfect in San Diego like people think.

Horn:                Well, still close enough to paradise I suspect. But before we really dive into the nuts and bolts here, let’s talk about this credential that you all have created. It was developed by Big Picture Schools, as I understand it in Australia, and then the University of Melbourne I think partnered on this to sort of vet and bless it if I understand. But tell us a little bit more about what it really is and why it’s unique.

Washor:           And I feel that over the five decades that I’ve been working that… And we’ve all in very good ways, many of us, struggle with assessment, constantly that our colleagues in Australia and the Viv White who’s the co-executive director of Big Picture Learning in Australia and her staff and we have about 40 schools there, have come up with something that contribute a lot to the field. So what happened was, is that Viv took Big Picture’s learning goals, which are basically pretty easy to understand by anybody in that we like to credit students around how they apply their academics in and outside of school with mentors and teaching staff as advisors in the real world and in school, once again in communities.

What they did was they took the learning goals and they went to the University of Melbourne to the psychometricians there, the head of whom is Sandra Milligan. And they said, “We want to credit teacher judgment, student self-assessment and mentor judgment and we need a warranting and validation entity to do that.” And Sandra and her team collaborated with our schools and developed an algorithm that as you put the information in, through once again teacher judgment, student self-assessment and mentor judgment, it spun out a validation that vetted and warranted that this was real, that what they actually said they did, they did. And then our students applied to universities, colleges, technical schools, and the workplace in Australia and it lo and behold it was accepted without using standardized test scores or GPAs.

Horn:                These areas now that they’re vetting are things like communication skills, empirical reasoning, quantitative reasoning as I understand it, personal qualities and sort of metacognition or knowing how to learn, I think. What are those artifacts that they’re feeding in or into that algorithm really look like?

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