Over the past few days I've been reading what seems like hundreds of articles and blog posts about MOOCs. This is mostly because I've discovered a number of sites that aggregate these articles in convenient ways. I've given up trying to remember everything I read about MOOCs - I'm just letting the flood wash over me and seeing what might stick.
But I want to think a bit more about one article (or is it a blog?): MOOCs and exercise bikes: more in common than you'd think. Although some writers see the high attrition rate of MOOCs to be evidence of failure, I've been taking more of a toe-in-the-waters view - the barriers to signing up for a MOOC are so low that of course lots of enrollees will subsequently decide not to continue.
This article suggests a different perspective, that of the well-meaning learner who somehow loses motivation. Just like with that exercise bike, they feel bad about dropping out, and really wish they could have continued. Sometimes they will have stopped for a solid reason (bike equivalent - sprained ankle), but for many it was just lack of motivation. They know that they're missing a lot by not keeping up with the work, but their motivation fades and they're left with another failed attempt at learning.
So how can I build features into Useful Genetics that will help students stick with the course and get the full benefits of the course and the personal reinforcement of being a successful learner?
One part of the solution is course-specific - building relevance into every week's work. For Useful Genetics, week 1 is likely to be highly motivating (how people differ), but the next few
weeks material may be very dry (gene expression, how heredity
works), and I can see a lot of attrition happening here unless I make a special effort to prevent that.
Another other part of the solution is more general. What features of courses make them easier to stick with to completion? I haven't seen much discussion of this yet. Maybe this is one of the things that course-analytics can help with. (If any readers know of studies, please post them in the comments.)
The exercise-bike article mentions the motivational benefits of being part of a group. I don't think this motivation can come from the discussion forums; there are too many participants. Face-to-face study groups are great, and I can encourage students to form them, but these won't be an option for most people. But there might be a way to have people form interest-group-based online study groups, for genetic diseases or dog breeding or political concerns or whatever. Perhaps, once I see the feedback from the 'Why are you taking this course' part of the initial survey, I can encourage the formation of many small discussion groups focused on the specific motivations students describe.
Tuesday, October 09, 2012
Sunday, October 07, 2012
Doing for math what I want to do for genetics
Keith Devlin is teaching a Coursera course titled Introduction to Mathematical Thinking, and he's blogging about the experience here.
In his latest post he discusses the relationship between what his course aims to teach and what is usually taught in post-secondary mathematics courses. To paraphrase slightly, he contrasts the formalism of pure mathematics ("chess on steroids") with the role that abstract, pure reasoning plays in dealing with the more messy issues of the real world. Few students can really appreciate the former, but they all can benefit from the latter, so that's what his course teaches.
This is a lot like what I hope to do with genetics, since I want to replace much of the formalism of Mendelian analysis with reasoning how genetic effects play out in the world our students live in.
He's planning to use calibrated peer review for his final exam. I'll be very interested to see how this works in Coursera because I want to make extensive use of it in Useful Genetics. I've used the standard version of CPR in my BIOL 234 genetics course (see here and here), but Coursera describes their version as 'beta' so I don't know how good or solid it is.
In his latest post he discusses the relationship between what his course aims to teach and what is usually taught in post-secondary mathematics courses. To paraphrase slightly, he contrasts the formalism of pure mathematics ("chess on steroids") with the role that abstract, pure reasoning plays in dealing with the more messy issues of the real world. Few students can really appreciate the former, but they all can benefit from the latter, so that's what his course teaches.
This is a lot like what I hope to do with genetics, since I want to replace much of the formalism of Mendelian analysis with reasoning how genetic effects play out in the world our students live in.
He's planning to use calibrated peer review for his final exam. I'll be very interested to see how this works in Coursera because I want to make extensive use of it in Useful Genetics. I've used the standard version of CPR in my BIOL 234 genetics course (see here and here), but Coursera describes their version as 'beta' so I don't know how good or solid it is.
Saturday, October 06, 2012
Thinking about Peter Sloep's comments
Peter Sloep has some thoughtful comments in his Networked Learning Scoop-it on my MOOC-opalypse post. Here's his comments in purple, and my responses in black:
The line of argument followed in this essay is a familiar one: MOOCs are there to stay, there are all these apocalyptic predictions about the disappearance of colleges and universities as we know them, hence, to stay employed, I'd better make the student experience worth their money. Apart from the observation that it is a bit ironic that only now that jobs are on the line we start thinking about giving value for money, there are many problems with this kind of argument.
I was joking about being concerned about my job; I'll probably be over-the-hill by the time academia feels the big impacts of MOOCs.
First, Rosie argues from the assumption that MOOC-courses are bound to improve shortly. I am not so sure, I actually think that on the average, when more people jump on the MOOC bandwagon, the quality will go down. Yes, the better courses may be tweaked to offer a better learning experience, for instance by replacing the fora with more intelligent ones that help the learner find sensible stuff amongst the massive number of not-so-useful entries.
If most of the people who jump on the MOOC bandwagon are only doing so because it's trendy, we might see a decrease in average course quality. I don't think that's likely - I expect most institutions will try to produce good courses, and as more courses are out there, competition will motivate improvement. But even if the average course quality is no better, having more courses will mean we have more good courses.
Second, Rosie guesses that flipped classrooms, which provide tutoring next to a (free) MOOC, won't convince the students. That depends, I would say. Read Jonathan Marks' contribution, sitting next to this one. Also, she believes "nobody knows enough about how learning works to do a credible job of this". That simply isn't true. There is a long tradition of research on distance education which explains how to do this online and much research on learning in face-to-face settings other than classrooms and lecture halls which offers valuable insights (see my blog on Katie Vale's presentation, below). It is true, though, that this research has often been ignored by people used to and happy with ordinary lecturing.
I stand by the 'nobody knows enough...' statement. There's a fair bit of research and some valuable insights (including those that motivate flipped classrooms), but not nearly as much as we need.
Third, Rosie then concludes that "[...] one advantage a university gains by offering Coursera courses is that the enormous numbers of students and the online record-keeping make it possible to collect unprecedented amounts of data about student learning. But in practice most of the data will be worthless unless we carefully design our courses as learning experiments.' Under the label of learning analytics such data collection is already taking place and delivering insights. And, yes, it does make sense to carefully design courses as learning experiments. That is precisely what Harvard is doing with its EdX platform (again, see Kathie Vale). I would hope many more colleges start to do so, designing other learning environments than the default lecture hall and learn from the experience.
I couldn't find the Kathie Vale link, nor anything by Googling her. I read the Wikipedia entry on Learning Analytics, which reinforced my impression that this is primarily a set of tools we can use in our learning experiments. Learning analytics can be applied to 'found' data (e.g. any Coursera course) but is going to be most valuable in the context of carefully designed experiments.
In summary, I don't believe the apocalyptic predictions about MOOCs for one minute. The educational landscape, shaped by learning needs and wants on the one hand and forms and environments for learning on the other, is too vast and rugged to be surveyd to the full by a search party led by commercial MOOC providers alone. However, it is a good thing we start to question the traditional, much trodden roads to learning. If that is what they manage to achieve, we should thank them for that. (peter sloep, @pbsloep)
I don't really think that the rise of MOOCs will lead to the collapse of universities. Not because universities deserve to be preserved in their present form, but because the whole structure of higher education is so very very conservative that even apocalyptic forces will cause only slow incremental changes. But I'll save this for another post.
The line of argument followed in this essay is a familiar one: MOOCs are there to stay, there are all these apocalyptic predictions about the disappearance of colleges and universities as we know them, hence, to stay employed, I'd better make the student experience worth their money. Apart from the observation that it is a bit ironic that only now that jobs are on the line we start thinking about giving value for money, there are many problems with this kind of argument.
I was joking about being concerned about my job; I'll probably be over-the-hill by the time academia feels the big impacts of MOOCs.
First, Rosie argues from the assumption that MOOC-courses are bound to improve shortly. I am not so sure, I actually think that on the average, when more people jump on the MOOC bandwagon, the quality will go down. Yes, the better courses may be tweaked to offer a better learning experience, for instance by replacing the fora with more intelligent ones that help the learner find sensible stuff amongst the massive number of not-so-useful entries.
If most of the people who jump on the MOOC bandwagon are only doing so because it's trendy, we might see a decrease in average course quality. I don't think that's likely - I expect most institutions will try to produce good courses, and as more courses are out there, competition will motivate improvement. But even if the average course quality is no better, having more courses will mean we have more good courses.
Second, Rosie guesses that flipped classrooms, which provide tutoring next to a (free) MOOC, won't convince the students. That depends, I would say. Read Jonathan Marks' contribution, sitting next to this one. Also, she believes "nobody knows enough about how learning works to do a credible job of this". That simply isn't true. There is a long tradition of research on distance education which explains how to do this online and much research on learning in face-to-face settings other than classrooms and lecture halls which offers valuable insights (see my blog on Katie Vale's presentation, below). It is true, though, that this research has often been ignored by people used to and happy with ordinary lecturing.
I stand by the 'nobody knows enough...' statement. There's a fair bit of research and some valuable insights (including those that motivate flipped classrooms), but not nearly as much as we need.
Third, Rosie then concludes that "[...] one advantage a university gains by offering Coursera courses is that the enormous numbers of students and the online record-keeping make it possible to collect unprecedented amounts of data about student learning. But in practice most of the data will be worthless unless we carefully design our courses as learning experiments.' Under the label of learning analytics such data collection is already taking place and delivering insights. And, yes, it does make sense to carefully design courses as learning experiments. That is precisely what Harvard is doing with its EdX platform (again, see Kathie Vale). I would hope many more colleges start to do so, designing other learning environments than the default lecture hall and learn from the experience.
I couldn't find the Kathie Vale link, nor anything by Googling her. I read the Wikipedia entry on Learning Analytics, which reinforced my impression that this is primarily a set of tools we can use in our learning experiments. Learning analytics can be applied to 'found' data (e.g. any Coursera course) but is going to be most valuable in the context of carefully designed experiments.
In summary, I don't believe the apocalyptic predictions about MOOCs for one minute. The educational landscape, shaped by learning needs and wants on the one hand and forms and environments for learning on the other, is too vast and rugged to be surveyd to the full by a search party led by commercial MOOC providers alone. However, it is a good thing we start to question the traditional, much trodden roads to learning. If that is what they manage to achieve, we should thank them for that. (peter sloep, @pbsloep)
I don't really think that the rise of MOOCs will lead to the collapse of universities. Not because universities deserve to be preserved in their present form, but because the whole structure of higher education is so very very conservative that even apocalyptic forces will cause only slow incremental changes. But I'll save this for another post.
Friday, October 05, 2012
Preparing for the MOOC-ocalypse
MO-OCalypse? MOOC-apocalypse? (Oops, apocalypse is one of those words that, if you look too closely, always appears wrongly spelled.)
A UBC colleague who's also going to be producing a Coursera course got me thinking about the future of the university.
He starts with two reasonable assumptions: First, the diversity and quality of Coursera-like courses is going to increase rapidly over the next few years. Second, universities/faculty members/students are discovering that face-to-face lecturing in large classes is not the best use of student or faculty time and effort, and they will move toward 'flipped' classes where students use class videos and other online resources to learn the course content and then use classroom time for problem solving and interactive learning.
Creating the online resources for a flipped course is a big investment of technical resources and instructor time. So, for both instructors and administrators, it will make sense to instead use the resources of any appropriate Coursera courses. Contemplating this for very long leads one to various philosophical considerations, such as "Since Coursera courses are free, why would students pay to go to university?" and then "Yikes, what will become of my job??!!!"
For a university education to be perceived as worth the tuition, it won't be enough to supplement the free Coursera material with scheduled classroom peer-teaching experiences and a tutorial taught by a graduate student. The university needs to develop integrated programs with hands-on and face-to-face experiences that are seen as worth the cost.
Unfortunately, nobody knows enough about how learning works to do a credible job of this. So if the university is to avoid selling programs with little demonstrated value, it needs to gather the information that will let it create genuine value.
Ironically, the best way to prepare for this MOOC-opalypse may be to become part of the problem by teaching a MOOC. In principle, one advantage a university gains by offering Coursera courses or other MOOCs is that the enormous numbers of students and the online record-keeping make it possible to collect unprecedented amounts of data about student learning. But in practice most of the data will be worthless unless we carefully design our courses as learning experiments. That sentence makes it sound like designing a course to be a learning experiment is something I know how to do. It's not. And I'm not likely to have the time to do this even if I had the expertise.
On the other hand, my course is best-positioned to become an experiment, since it's the least developed of the three UBC Coursera offerings. UBC has offered Climate Literacy as a fully online Continuing Studies course (non-credit) for several years, and I think Introduction to Systematic Program Design is going to be an online version of CPSC 110. Although Useful Genetics will build on what I've taught in BIOL 234 - Fundamentals of Genetics, it's basically a new course. But if we're going to use Useful Genetics as an experiment in online learning we need to start now, because it will be too late once I've developed all the components.
So I'm emailing UBC's Centre for Teaching and Learning Technology (CTLT) to ask if they have a support person assigned to work on course-evaluation development for the Coursera courses.
Later: CTLT responded that this will be discussed at a meeting they're organizing with the Coursera instructors. I think this means "Not yet, but maybe..."
A UBC colleague who's also going to be producing a Coursera course got me thinking about the future of the university.
He starts with two reasonable assumptions: First, the diversity and quality of Coursera-like courses is going to increase rapidly over the next few years. Second, universities/faculty members/students are discovering that face-to-face lecturing in large classes is not the best use of student or faculty time and effort, and they will move toward 'flipped' classes where students use class videos and other online resources to learn the course content and then use classroom time for problem solving and interactive learning.
Creating the online resources for a flipped course is a big investment of technical resources and instructor time. So, for both instructors and administrators, it will make sense to instead use the resources of any appropriate Coursera courses. Contemplating this for very long leads one to various philosophical considerations, such as "Since Coursera courses are free, why would students pay to go to university?" and then "Yikes, what will become of my job??!!!"
For a university education to be perceived as worth the tuition, it won't be enough to supplement the free Coursera material with scheduled classroom peer-teaching experiences and a tutorial taught by a graduate student. The university needs to develop integrated programs with hands-on and face-to-face experiences that are seen as worth the cost.
Unfortunately, nobody knows enough about how learning works to do a credible job of this. So if the university is to avoid selling programs with little demonstrated value, it needs to gather the information that will let it create genuine value.
Ironically, the best way to prepare for this MOOC-opalypse may be to become part of the problem by teaching a MOOC. In principle, one advantage a university gains by offering Coursera courses or other MOOCs is that the enormous numbers of students and the online record-keeping make it possible to collect unprecedented amounts of data about student learning. But in practice most of the data will be worthless unless we carefully design our courses as learning experiments. That sentence makes it sound like designing a course to be a learning experiment is something I know how to do. It's not. And I'm not likely to have the time to do this even if I had the expertise.
On the other hand, my course is best-positioned to become an experiment, since it's the least developed of the three UBC Coursera offerings. UBC has offered Climate Literacy as a fully online Continuing Studies course (non-credit) for several years, and I think Introduction to Systematic Program Design is going to be an online version of CPSC 110. Although Useful Genetics will build on what I've taught in BIOL 234 - Fundamentals of Genetics, it's basically a new course. But if we're going to use Useful Genetics as an experiment in online learning we need to start now, because it will be too late once I've developed all the components.
So I'm emailing UBC's Centre for Teaching and Learning Technology (CTLT) to ask if they have a support person assigned to work on course-evaluation development for the Coursera courses.
Later: CTLT responded that this will be discussed at a meeting they're organizing with the Coursera instructors. I think this means "Not yet, but maybe..."
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