In an earlier post today I said "I don't think educating for 'skills' is really very different than educating for 'knowledge'." In this item Tony Bates seems to go in the opposite direction, drawing distinctions between competencies, skills and learning outcomes. "Competence is the ability to do something successfully or efficiently." But it's only a first step. "A good sportsperson is not just competent but highly skilled" (now this seems to equivocated between the noun 'skill' and the adjective 'skilled', but I quibble). Finally, while both competencies and skills are possible learning outcomes, he says, "they need to be defined and measured if they are to become a learning outcome." And content is designed to produce learning outcomes. Thus, he says, "the balance in most higher education instruction is on mastery of content (a learning outcome) over the development of skills (or even competencies." All of which is fair enough - but which to me says they're all part of the same thing.
This article never actually lists then as six skills; we get three groups of two (something an AI will probably never do). Probably Hiroshi Tasaka is wrong on all six of these points. These are all recognition and response tasks. AI has for the most part already solved the recognition portion of the equation. The responses are in some cases presentation, and in other cases process orchestration. I list them here for your convenience (quoted):
You're probably wondering what I do think the job of humans will be in the future. Our job will be to train AI. We'll all be teachers in the future. Not teachers in the sense of giving instruction, but teachers in the sense of modelling appropriate behaviour. It will be a challenge, to be sure.
Alex Usher has an interesting theory to explain the lack of interest in post-secondary education funding in Canada: "It is not so much that higher education isn’t seen as an answer to the problem of growth (though that is part of the issue). No, the real issue is that few people care about growth anymore." What he means by 'growth' is "policies to increase collective wealth... To make the economy richer, more productive, more able to support higher private-sector salaries and higher public-sector spending." So what's the answer? Maybe a challenge: "something like being among the world’s most advanced and fairest economies by 2040." I could get behind that. But I think we'd need to look at the proposition more closely - our models of economic growth are broken, and divorced from concepts of equity and sustainability (both of which will be necessary to be an advanced and fair economy in 2040). But still. I like his thinking here.
The main news here is contained in the first sentence of the article: "IEEE are standing up a working group for Learning Metadata, to build on IEEE Std 1484.12.1 Standard for Learning Object Metadata while exploring new paradigms and technology practices in education." I don't see why IEEE wouldn't start with IEEE-LOM (ie., 1484.12.1) but then again I've never really understood the standards world. Phil Barker stuck a ™ on the title of this post, but as a matter of policy I don't litter headlines with such junk, and that by itself biases me against LRMI (petty, I know).
Clark Quinn opines, "My short (and admittedly cheeky) statement about education is that they’re wrong on two things, the curriculum and pedagogy, other than that they’re fine." More specifically, he says, "Most universities aren’t doing a good job of curriculum, focusing on knowledge instead of skills." And "Too often, it’s still the ‘information dump and knowledge test’. But even when that’s right, making it truly meaningful for the learners is sadly neglected." The thing is, they way most people think of skills, I don't think educating for 'skills' is really very different than educating for 'knowledge'. Indeed, 'skills training' is just as often rote as teaching for content knowledge.
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