John Fritz's video shows a perfect confirmation of one of the basic
pieces of knowledge in learning psychology: if you spend more time on a
learning task you'll do better (upto a certain maximum). Why is it so
difficult to convince students of this obvious truth? Not so difficult:
students choose between study and sport or the pub every day. Some
students make wise choices, others succumb to temptations. What
interests me most in this context is: how do we seduce students to spend
more time? The classic solution was to use force: force them to sit in a
classroom for hours, force them to hand in products or to do exams...
We all agree that we would prefer not to use force; can force be
replaced by a tool that allows students to inspect how much time they
spend?
Possible..... It sounds too simple to me, but who knows?
I think I have higher expectations of something like the traffic lights
at Purdue, though, where teachers are involved in specifying what kind
of behaviour and performance they expect from students in the course of
there unit.
Daniëlle's Course blog Learning Analytics #LAK12
donderdag 8 maart 2012
#lak12 OLA o yeah!?
I have enjoyed this week's talk by Simon Buckingham. It is refreshing to hear people talk optimistically about improving education, collaborating over borders, and -very important- empowering learners and teachers. None of that moaning of students are lazy and stupified by games, teachers aren't educated well enough and are only interested in lots of holidays, or there's no money for innovation anyway.....
Inspiring enthusiasm. Thanks!
Last night, awake in bed, I was thinking about using OLA communities to improve education. What is puzzling me is the role of local context.... My fundamental problem is that I just do not think that one way of learning or teaching is better than another, what works for us will not necessarily work for you and vice versa and there are many possible reasons: content, student population, capacity of teachers, available resources, you name it. We do PBL in Maastricht, but I would be the last to say that PBL is the best option everywhere. Taking that thought further I am wondering whether anyone can sensibly interpret an analysis of data without knowing the local context. One of the difficulties of educational research is that research articles almost never contain enough information about the context or concrete implementation of an educational design. Lack of space, but also lack of awareness, probably. Over the last 10 years I have heard quite a number of people trying to bridge that gap by developing educational ontologies.... As far as I know, they've all failed. We just can't get a grip on this. More and more I am inclined to think that it is qualitative research that we need to solve this and not quantitative... Not to say that no quantitative research can be useful, of course.
Will OLA also work for qualitative research data?
Inspiring enthusiasm. Thanks!
Last night, awake in bed, I was thinking about using OLA communities to improve education. What is puzzling me is the role of local context.... My fundamental problem is that I just do not think that one way of learning or teaching is better than another, what works for us will not necessarily work for you and vice versa and there are many possible reasons: content, student population, capacity of teachers, available resources, you name it. We do PBL in Maastricht, but I would be the last to say that PBL is the best option everywhere. Taking that thought further I am wondering whether anyone can sensibly interpret an analysis of data without knowing the local context. One of the difficulties of educational research is that research articles almost never contain enough information about the context or concrete implementation of an educational design. Lack of space, but also lack of awareness, probably. Over the last 10 years I have heard quite a number of people trying to bridge that gap by developing educational ontologies.... As far as I know, they've all failed. We just can't get a grip on this. More and more I am inclined to think that it is qualitative research that we need to solve this and not quantitative... Not to say that no quantitative research can be useful, of course.
Will OLA also work for qualitative research data?
dinsdag 28 februari 2012
#lak12 Side effect or main effect?
I'm enjoying the examples of how visualisation of student data is used to let teachers improve their course...
The software is good at presenting data in a way that makes it easy to get an overview, and the teachers are good at understanding their course content, their students, their context and, thus, good at coming up with measures to improve their education.
A positive side effect is that visualizing student data lures the teachers into thinking more carefully about questions like: what am I trying to achieve? what kind of student behaviour would I like to see? and how can I make that happen? It lures teachers into spending more time at carefully designing their education...
Thinking on further, I'm starting to wonder whether this is a side effect or a main effect. When I teach instructional design this is the behaviour that I would like to see in my students: that they spend time and effort (over and over again) on carefully thinking about what they are trying to achieve, monotoring whether these goals are reached, and keep on trying to improve their education....
In practice, a teacher can never pay attention to all problems and never try out all solutions. I am satisfied with teachers that just pick out one or two points and work on those, and pick one or two other points next time. My experience is, that it is often not that relevant which problems you start with, as long as you keep on trying to improve something.
So once I have lured teachers into spending that time and effort, I don't mind if we switch the software off :-)?
The software is good at presenting data in a way that makes it easy to get an overview, and the teachers are good at understanding their course content, their students, their context and, thus, good at coming up with measures to improve their education.
A positive side effect is that visualizing student data lures the teachers into thinking more carefully about questions like: what am I trying to achieve? what kind of student behaviour would I like to see? and how can I make that happen? It lures teachers into spending more time at carefully designing their education...
Thinking on further, I'm starting to wonder whether this is a side effect or a main effect. When I teach instructional design this is the behaviour that I would like to see in my students: that they spend time and effort (over and over again) on carefully thinking about what they are trying to achieve, monotoring whether these goals are reached, and keep on trying to improve their education....
In practice, a teacher can never pay attention to all problems and never try out all solutions. I am satisfied with teachers that just pick out one or two points and work on those, and pick one or two other points next time. My experience is, that it is often not that relevant which problems you start with, as long as you keep on trying to improve something.
So once I have lured teachers into spending that time and effort, I don't mind if we switch the software off :-)?
donderdag 23 februari 2012
#lak12 contradicting trends...
I have just realized that there are two contradicting trends in educational research:
- analzing big data in pursue of Evidence-Based Education
- small-scale qualitative studies where researchers consciously abolish striving for objectivity and generalizability in favour of deep understanding.
Interesting...
- analzing big data in pursue of Evidence-Based Education
- small-scale qualitative studies where researchers consciously abolish striving for objectivity and generalizability in favour of deep understanding.
Interesting...
#lak 12 week 5 - part 2
I'm splitting this up, so as not to confuse myself :-)
Six provocations of big data (Boyd & Crawford):
1. Automating Research Changes the Definition of Knowledge.
2. Claims to Objectivity and Accuracy are Misleading - all analysis means interpretation
3. Bigger Data are Not Always Better Data - they can be incomplete, biased, noisy
4. Not All Data Are Equivalent - Context matters!
5. Just Because it is Accessible Doesn’t Make it Ethical
6. Limited Access to Big Data Creates New Digital Divides
This summarizes about all my concerns, I think.
Why didn't we read this earlier on?
Six provocations of big data (Boyd & Crawford):
1. Automating Research Changes the Definition of Knowledge.
2. Claims to Objectivity and Accuracy are Misleading - all analysis means interpretation
3. Bigger Data are Not Always Better Data - they can be incomplete, biased, noisy
4. Not All Data Are Equivalent - Context matters!
5. Just Because it is Accessible Doesn’t Make it Ethical
6. Limited Access to Big Data Creates New Digital Divides
This summarizes about all my concerns, I think.
Why didn't we read this earlier on?
#lak12 Week 5
I'm catching up on the readings of week 5 and started of with the big Aspen report.
Nice and down to earth.... in some cases correlations can be useful, but be careful: correlations are not causal relations and they have limited value as predictors. If you want more, you still need to develop theories and test them purposefully. Yep.
In many cases you need to think carefully about what data you need, instead of just collecting everything just because you can... because otherwise you create more confusion and distractions.
I hadn't thought so much about the value of visualization of data (but good to be remembered that visualization techniques contain embedded judgements).
The privacy issues confuse me.... on the one hand I do feel powerless, because I don't know which data about me are collected by whom... and I dread the consequences for the less fortunate people: if you are illegal, you can already not go to a hospital any longer, but in future the police will track you down because of your mobile phone or your Facebook account?
On the other hand, I tend to think this is nothing new. Didn't we hate it when big companies were buying sets of addresses to send (paper) advertisements? well, nowadays I have the right to tell them to stop... And don't we already know much more about our risks to get diseases than 50 years ago? And we still have a reasonable insurance system (at least here in the Netherlands). So, we can expect new legislation to develop. Maybe along the lines of the 'information audit' proposed by Stefaan Verhulst.
Nice and down to earth.... in some cases correlations can be useful, but be careful: correlations are not causal relations and they have limited value as predictors. If you want more, you still need to develop theories and test them purposefully. Yep.
In many cases you need to think carefully about what data you need, instead of just collecting everything just because you can... because otherwise you create more confusion and distractions.
I hadn't thought so much about the value of visualization of data (but good to be remembered that visualization techniques contain embedded judgements).
The privacy issues confuse me.... on the one hand I do feel powerless, because I don't know which data about me are collected by whom... and I dread the consequences for the less fortunate people: if you are illegal, you can already not go to a hospital any longer, but in future the police will track you down because of your mobile phone or your Facebook account?
On the other hand, I tend to think this is nothing new. Didn't we hate it when big companies were buying sets of addresses to send (paper) advertisements? well, nowadays I have the right to tell them to stop... And don't we already know much more about our risks to get diseases than 50 years ago? And we still have a reasonable insurance system (at least here in the Netherlands). So, we can expect new legislation to develop. Maybe along the lines of the 'information audit' proposed by Stefaan Verhulst.
woensdag 22 februari 2012
#LAK12 Running a week behind...
I'm listening to the recording of the talk by Dragan Gasevic that I missed last week (when I'd missed the fact that it was at a different time :-))
I've been struggling to follow until he started talking about the concrete example of what they do in their own place. I can see how this is useful there, but I cannot link it to my own teaching... I've been thinking why.
It has something to do with the kind of course, which might have to be:
- large (with so many students that the teacher doesn't know them all)
- most interaction with learning material & other students online,
- a domain that can be modelled well (how else can we analyze the content of students' messages or contributions)
- a certain kind of content; some set of concepts or knowledge that is explained or 'delivered' in web resources...
The latter seems in contradiction with Dragan's claim that he does not believe in 'pizza delivery'.
My discovery of the week: I have realized that I do believe that learner analytics can be immensely useful to enable students to self-direct their learning. Big problem with that is that -even though we know that self-directed learning is good for retention and transfer- most students aren't interested in investing all that time and effort, they are interested in doing as little as possible to make their exam. Of course, there are exceptions... among which the participants of this course :-)
Some things I'm allergic to, though. Evidence-based education... measure whether some treatment works... hey guys, education and medicine cannot be compared so easily. For one thing, in medicine it doesn't matter which doctor prescribes the pills, in education that is not true. And if we know one thing from research it is that the teacher is an important success (or failure) factor. It would be more fair to compare education to psychotherapy really, where the bond between client and therapist has been identiefied as the main success factor. I'll stop moaning about one of my hobby horses now..
I've been struggling to follow until he started talking about the concrete example of what they do in their own place. I can see how this is useful there, but I cannot link it to my own teaching... I've been thinking why.
It has something to do with the kind of course, which might have to be:
- large (with so many students that the teacher doesn't know them all)
- most interaction with learning material & other students online,
- a domain that can be modelled well (how else can we analyze the content of students' messages or contributions)
- a certain kind of content; some set of concepts or knowledge that is explained or 'delivered' in web resources...
The latter seems in contradiction with Dragan's claim that he does not believe in 'pizza delivery'.
My discovery of the week: I have realized that I do believe that learner analytics can be immensely useful to enable students to self-direct their learning. Big problem with that is that -even though we know that self-directed learning is good for retention and transfer- most students aren't interested in investing all that time and effort, they are interested in doing as little as possible to make their exam. Of course, there are exceptions... among which the participants of this course :-)
Some things I'm allergic to, though. Evidence-based education... measure whether some treatment works... hey guys, education and medicine cannot be compared so easily. For one thing, in medicine it doesn't matter which doctor prescribes the pills, in education that is not true. And if we know one thing from research it is that the teacher is an important success (or failure) factor. It would be more fair to compare education to psychotherapy really, where the bond between client and therapist has been identiefied as the main success factor. I'll stop moaning about one of my hobby horses now..
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