In principle, I think that being able to customize your degree, across many institutions is a great idea. In practice though this is problematic.
I was reading yesterday that learners:
* know what they know
* know what they don't know
* don't know what they know
* don't know what they don't know
This last bullet is the most problematic one, and one that set curricula aim to remedy. If students don't know what they don't know, the problem with picking and choosing your own courses means that you might end up with a perpetual blind spot that you aren't even aware of.
I think that educational institutions can do A LOT with the first 3 bullets by allowing students to customize a set (but not set-in-stone) curriculum so that they don't have to repeat things they know, and they don't have to repeat things they know in order to know that they know them.
Good points.
The whole data thing is a very institutionally driven concept, wondering if we looked at it from another perspective if we'd see it differently.
I just thought of it as kind of like my personal learning records, almost like my personal learning network.
In my eclectic life, here are some perspectives that I draw upon:
I am very involved in my kid's schools (primary/middle years) and volunteer regularly. So much of what happens in any given school year is teacher dependent. Kids aren't empowered to own their own learning. As they move into higher ed, they have more control over what they learn, but not complete control.
If they move into workplaces (this is where I work), there is no interest in what/how they learned in schools, but many orgs do have their own system to classify your personality type/style. Even there, you are a worker who receives workplace learning. But, your learning records and even performance feedback could be part of your overall data portfolio.
If you are pursuing pro D of your own, THEN you get to be in the driver's seat, but you are likely to fall into your 3 bullets described.
Maybe a hunch like system with a rypple.com type addition could take your cumulative learning data - trending, pattern recognition - and give you suggestions based on more input sources than your own answers to questions.
Maybe I'm way off-base, but thanks for letting me pontificate anyway! Appreciate your response.
Holly
The whole data thing is a very institutionally driven concept, wondering if we looked at it from another perspective if we'd see it differently.
I just thought of it as kind of like my personal learning records, almost like my personal learning network.
In my eclectic life, here are some perspectives that I draw upon:
I am very involved in my kid's schools (primary/middle years) and volunteer regularly. So much of what happens in any given school year is teacher dependent. Kids aren't empowered to own their own learning. As they move into higher ed, they have more control over what they learn, but not complete control.
If they move into workplaces (this is where I work), there is no interest in what/how they learned in schools, but many orgs do have their own system to classify your personality type/style. Even there, you are a worker who receives workplace learning. But, your learning records and even performance feedback could be part of your overall data portfolio.
If you are pursuing pro D of your own, THEN you get to be in the driver's seat, but you are likely to fall into your 3 bullets described.
Maybe a hunch like system with a rypple.com type addition could take your cumulative learning data - trending, pattern recognition - and give you suggestions based on more input sources than your own answers to questions.
Maybe I'm way off-base, but thanks for letting me pontificate anyway! Appreciate your response.
Holly
I think this gets to the heart to one of the key problems with using recommender systems to help one to learn. There are two related issues here:
The first is that it is fiendishly hard to match paths of learners because a) there is no guarantee that others took the best path in the first place (because, unlike in matters of taste, they don't know what they don't know) and b) the combination of prior history and future goals is very difficult to model, so it is much harder to match people accurately. Most systems that have been built for this so far, including my own, are more to do with riding a wave than following a path, with sights set on the next thing rather than dealing with the complete learning trajectory.
The second (related) issue is that, unlike for questions of taste, where previous likes are a good predictor of future likes, once we have learned something we no longer have any need to learn the same thing (as a rule).
Just a couple of thoughts. I'm catching up with this conversation so will probably have more to say on the subject!
The first is that it is fiendishly hard to match paths of learners because a) there is no guarantee that others took the best path in the first place (because, unlike in matters of taste, they don't know what they don't know) and b) the combination of prior history and future goals is very difficult to model, so it is much harder to match people accurately. Most systems that have been built for this so far, including my own, are more to do with riding a wave than following a path, with sights set on the next thing rather than dealing with the complete learning trajectory.
The second (related) issue is that, unlike for questions of taste, where previous likes are a good predictor of future likes, once we have learned something we no longer have any need to learn the same thing (as a rule).
Just a couple of thoughts. I'm catching up with this conversation so will probably have more to say on the subject!
Jon - thanks for your response - I like the term fiendishly hard - hope to use that in conversation sometime.
Holly
Holly