Tag: Stephen Downes
Over the last few days I’ve been working through Stephen Downes’ paper Learning Networks and Connective Knowledge. I often struggle to get through these longer works and actually pull anything relevant out of them, and this is definitely a longer work (over 12,000 words, just over 29 pages pasted in Word). I used Diigo to highlight and comment while reading.
Below are quotes from Stephen’s paper and my comments. Stephen’s words are in block quotes; my comments appear below each snippet. If you’d like to see my notes in context and don’t use Diigo, use this annotated link for the page.
This is a bit rough and pretty much my “thinking out loud” from when I was reading, so don’t expect a lot of polished thoughts here. It’s also still over 3000 words, so don’t expect a succinct summary either. This is more of “somewhere in the middle of the process,” and I have many questions remaining.
In other words, cognitivists defend an approach that may be called ‘folk psychology’. “In our everyday social interactions we both predict and explain behavior, and our explanations are couched in a mentalistic vocabulary which includes terms like ‘belief’ and ‘desire’.” The argument, in a nutshell, is that the claims of folk psychology are literally true, that there is, for example, an entity in the mind corresponding to the belief that ‘Paris is the capital of France’, and that this belief is, in fact, what might loosely be called ‘brain writing’ – or, more precisely, there is a one-to-one correspondence between a person’s brain states and the sentence itself.
I’ve never heard cognitivism compared to “folk psychology” before. I’m not totally convinced by this argument. Cognitivist methods do have some research support, after all. (Think multimedia learning, Clark & Mayer’s “ELearning and the Science of Instruction.”) But their methods could (at least sometimes) be right even if their explanation of the underlying mechanism is wrong.
We may contrast cognitivism, which is a causal theory of mind, with connectionism, which is an emergentist theory of mind. This is not to say that connectionism (see also) does away with causation altogether; it is not a ‘hand of God’ theory. It allows that there is a physical, causal connection between entities, and this is what makes communication possible. But where it differs is, crucially: the transfer of information does not reduce to this physical substrate. Contrary to the communications-theoretical account, the new theory is a non-reductive theory. The contents of communications, such as sentences, are not isomorphic with some mental state.
For example (and there are many we could choose from), consider Randall O’Reilly on how the brain represents conceptual structures, as described in Modeling Integration and Dissociation in Brain and Cognitive Development. He explicitly rejects the ‘isomorphic’ view of mental contents, and instead describes a network of distributed representations. “Instead of viewing brain areas as being specialized for specific representational content (e.g., color, shape, location, etc), areas are specialized for specific
computational functions by virtue of having different neural parameters…
For example, when I say, “What makes something a learning object is how we use the learning object,” I am asserting a functionalist approach to the definition of learning objects (people are so habituated to essentialist definitions that my definition does not even appear on lists of definitions of learning objects).
It’s like asking, what makes a person a ‘bus driver’? Is it the colour of his blood? The nature of his muscles? A particular mental state? No – according to functionalism, what makes him a ‘bus driver’ is the fact that he drives buses. He performs that function.
To illustrate this concept, I have been asking people to think of the concept ‘Paris’. If ‘Paris’ were represented by a simple symbol set, we would all mean the same thing when we say ‘Paris’. But in fact, we each mean a collection of different things and none of our collections is the same. Therefore, in our own minds, the concept ‘Paris’ is a loose association of a whole bunch of different things, and hence the concept ‘Paris’ exists in no particular place in our minds, but rather, is scattered throughout our minds.
As we examine the emergentist theory of mind we can arrive at five major implications of this approach for educational theorists:
– first, knowledge is subsymbolic. Mere possession of the words does not mean that there is knowledge;
the possession of knowledge does not necessarily result in the possession of the words (and for much more on this, see Michael Polanyi’s discussion of ‘tacit knowledge‘ in ‘Personal Knowledge‘).
– second, knowledge is distributed. There is no specific ‘mental entity’ that corresponds to the belief that ‘Paris is the capital of France’. What we call that ‘knowledge’ is (an indistinguishable) pattern of
connections between neurons. See, for example, Geoffrey Hinton, ‘Learning Distributed Representations of Concepts‘.
– third, knowledge is interconnected. The same neuron that is a part of ‘Paris is the capital of France’ might also be a part of ‘My dog is named Fred’. It is important to note that this is a non-symbolic interconnection – this is the basis for non-rational associations, such as are described in the recent Guardian article, ‘Where Belief is Born‘
– fourth, knowledge is personal. Your ‘belief’ that ‘Paris is the capital of France’ is quite literally different from my belief that ‘Paris is the capital of France’. If you think about it, this must be the case – otherwise Gestalt tests would be useless; we would all utter the same word when shown the same picture.
– fifth, what we call ‘knowledge’ (or ‘belief’, or ‘memory’) is an emergent phenomenon. Specifically, it is not ‘in’ the brain itself, or even ‘in’ the connections themselves, because there is no ‘canonical’ set of connections that corresponds with ‘Paris is the capital of France’. It is, rather (and carefully stated), a recognition of a pattern in a set of neural events (if we are introspecting) or behavioural events (if we are observing). We infer to mental contents the same way we watch Donald Duck on TV – we think we see something, but that something is not actually there – it’s just an organization of pixels.
If this is the case, then the concepts of what it is to know and what it is to teach are very different from the traditional theories that dominate distance education today. Because if learning is not the transfer of mental contents – if there is, indeed, no such mental content that exists to be transported – then we need to ask, what is it that we are attempting to do when we attempt to teach and learn.
we can identify the essential elements of network semantics.
First, context, that is, the localization of entities in a network. Each context is unique – entities see the network differently, experience the world differently. Context is required in order to interpret signals, that is, each signal means something different depending on the perspective of the entity receiving it.
Second, salience, that is, the relevance or importance of a message. This amounts to the similarity between one pattern of connectivity and another. If a signal creates the activation of a set of
connections that were previously activated, then this signal is salient. Meaning is created from context and messages via salience.
Third, emergence, that is, the development of patterns in the network. Emergence is a process of resonance or synchronicity, not creation. We do not create emergent phenomena. Rather
emergence phenomena are more like commonalities in patterns of perception. It requires an interpretation to be recognized; this happens when a pattern becomes salient to a perceiver.
Fourth, memory is the persistence of patterns of connectivity, and in particular, those patterns of connectivity that result from, and result in, salient signals or perceptions.
For example, in order to illustrate the observation that ‘knowledge is distributed’ I have frequently appealed to the story of the 747. In a nutshell, I ask, “who knows how to make a 747 fly
from London to Toronto?” The short answer is that nobody knows how to do this – no one person could design a 747, manufacture the parts (including tires and aircraft engines), take it off, fly it properly, tend to the passengers, navigate, and land it successfully. The knowledge is distributed across a network of
people, and the phenomenon of ‘flying a 747’ can exist at all only because of the connections between the constituent members of that network.
“What happens,” I asked, “when online learning ceases to be like a medium, and becomes more like a platform? What happens when online learning software ceases to be a type of content-consumption tool, where learning is “delivered,” and becomes more like a content-authoring tool, where learning is created?”
The answer turns out to be a lot like Web 2.0: “The model of e-learning as being a type of content, produced by publishers, organized and structured into courses, and consumed by students, is turned on its head. Insofar as there is content, it is used rather than read— and is, in any case, more likely to be produced by students than courseware authors. And insofar as there is structure, it is more likely to resemble a language or a conversation rather than a book or a manual.”
The idea behind the personal learning environment is that the management of learning migrates from the institution to the learner.
Learning therefore evolves from being a transfer of content and knowledge to the production of
content and knowledge.
In a distributed environment, however, the design is no longer defined as a type of process. Rather, designers need to characterize the nature of the connections between the constituent entities.
In effective networks, content and services are disaggregated. Units of content should be as small as possible and content should not be ‘bundled’. Instead, the organization and structure of content and services is created by the receiver.
An effective network is desegregated. For example, in network learning, learning is not thought of as a Separate Domain. Hence, there is no need for learning-specific tools and processes. Learning is instead thought of as a part of living, of work, of play. The same tools we use to perform day-to-day activities are the tools we use to learn.
Knowledge is a network phenomenon. To ‘know’ something is to be organized in a certain way, to exhibit patterns of connectivity. To ‘learn’ is to acquire certain patterns.
A good student learns by practice, practice and reflection.
A good teacher teaches by demonstration and modeling.
The essence of being a good teacher is to be the sort of person you want your students to become.
The most important learning outcome is a good and happy life.
In essence, on this theory, to learn is to immerse oneself in the network. It is to expose oneself to actual instances of the discipline being performed, where the practitioners of that discipline are (hopefully with some awareness) modeling good practice in that discipline. The student then, through a process of
interaction with the practitioners, will begin to practice by replicating what has been modeled, with a process of reflection (the computer geeks would say: back propagation) providing guidance and correction.
These environments cut across disciplines. Students will not study algebra beginning with the first principles and progressing through the functions. They will learn the principles of algebra as
needed, progressing more deeply into the subject as the need for new knowledge is provoked by the demands of the simulation. Learning opportunities – either in the form of interaction with others, in the
form of online learning resources (formerly known as learning objects), or in the form of interaction with mentors or instructors – will be embedded in the learning environment, sometimes presenting
themselves spontaneously, sometimes presenting themselves on request.
This does not mean that a ‘science’ of learning is impossible. Rather, it means that the science will be more like meteorology than like (classical) physics. It will be a science based on modeling and simulation, pattern recognition and interpretation, projection and uncertainty.
I’ve been blogging for just over 2 years now; my first posts were on December 26, 2006. Like many bloggers, I definitely had a slow start: only 44 views in all of January 2007. Now I’m averaging over five times that every day. My numbers aren’t nearly as impressive as someone like Stephen Downes, but I’m not doing this to set records. I’m still quite pleased with the growth I saw in 2008 over my first year of blogging.
Views and Subscribers
Take a look at these comparisons:
- Total number of views for the year
- 2007: 16799
- 2008: 61062
- That’s 3.6 time more views in 2008
- Average daily views
- 2007: 46
- 2008: 121
- Highest daily average in a month
- 2007: 91, in August
- 2008: 223, in September
It’s hard to do a comparison of feed statistics. WordPress quit providing statistics in June of 2007, instead recommending people switch to Feedburner. I’m approaching 300 subscribers on Feedburner now, plus another 200+ on my main WordPress feed. If I could consolidate my subscribers, I’d have over 500. My subscriber numbers have grown a little faster than my views; they don’t seem to dip the same way my views have a couple of times, as you can see in the chart above.
My growth hasn’t been steady, but 2008 was steadier than 2007. Some of the bumps are from external links. June 2007 is when I posted my series on Instructional Design Careers, which generated a link from Don Clark and a lot of great discussion. April 2008 is when I liveblogged the TCC 2008 conference. Stephen Downes linked to me then, and I posted more times in that month than any other month (42 total posts). Since then, I’ve been mostly gaining momentum.
The recent large dip you see in the chart is August 2008, when I only wrote one non-bookmark post. It’s possible there was a problem with tracking that month too, since the numbers seem out of line with the trend. I expect that December dipped because of a combination of less posting and the holidays. The last data point on this chart is January, and since we’re only a few days into the month it’s still pretty low.
My 2008 top posts by views:
- One Keyboard and Mouse, Two Computers (4,893)
- Instructional Design Skills (4,516)
- What does an instructional designer do? (4,306)
- Technology Skills for Instructional Designers (2,890)
- Telecommute Instructional Design Jobs (2,500)
- Getting Into Instructional Design (2,453)
- Is Instructional Design the Right Career? (2,315)
- Professional Organizations and Career Opportunities (1,569)
- New Features in Captivate 3 (1,567)
After that are the pages for Instructional Design Careers and About Me, and the views drop off significantly.
The top post on that list gets a lot of search engine traffic, but no comments. I don’t expect that gets me many long-term readers either. Other than that and the new Captivate features, everything in the top rank by number of views is about instructional design careers. Only 2 of those top 9 posts were written in 2008 (#1 & #5); maybe the more established posts actually have more links to them and therefore rank better in the search engines?
Top Search Engine Terms
These are the top searches which brought people to my blog:
- instructional designer (584)
- instructional design jobs (276)
- instructional design skills (186)
- instructional design career (167)
- cyber bullying quotes (167)
- what is an instructional designer (163)
- one keyboard two computers (163)
- christy tucker (142)
- instructional designer skills (118 )
- two computers one keyboard (110)
Many similar phrases turn up too, plus a few interesting ones like “dirty comments,” “ubiquitous learning,” and “birthday reflections.”
Google Reader and the Google custom home page are the top two referrers to my blog. Pageflakes and the WordPress dashboard also rank highly.
Here’s the top blog posts that send traffic to me. Cammy Bean gets the prize for being on this list twice:
- The Value of Instructional Designers by Cammy Bean
- Getting Started with Instructional Design by Manish Mohan
- Predictions for Learning in 2008 on the Learning Circuits Blog
- Getting Started in Instructional Design by Cammy Bean
- Clive on Learning (Clive Shepherd’s blog–referrals come from his home page, not a specific post)
What do the patterns tell me?
- Lots of people are interested in learning about instructional design as a career. My posts on getting into the field and the skills created an initial bump in traffic and are still getting traffic and comments 18 months later.
- When I post more regularly, I get more traffic–mostly. Sometimes my traffic still grows even when I don’t write as much as long as what I write is interesting. But, there’s a general correlation between number of posts and views.
- External links are critical to building traffic, especially early on. Maybe I should be doing more to link to new bloggers myself to pass that traffic along.
- Search engine traffic is getting to be a bigger driver of traffic for me. I’m not particularly doing anything to optimize my blog for search engines, so I think just writing good content is enough for the kind of traffic I’m getting.
These are my liveblogged notes from this morning’s live session for CCK08. Although I usually aim for a fairly complete transcript of live sessions, I spent more time paying attention to and participating in the backchannel chat today. Therefore, some of the questions and discussion near the end aren’t included in my notes. My comments are in italics. There are a few comments copied directly from the chat. The recording will be available at some point under Week 9.
Much of this discussion was about how to get change to happen, with (I think) a very practical and realistic acknowledgment of the barriers to change. The idea of iterative change came up several times. Where traditional project and change management follows a linear process, what may be more effective for emerging technology is to do lots of little projects, see how they go, and adjust as needed.
Nancy mentioned another idea that I thought was great: an appreciative approach to change. Basically, you look at what strengths you have and start there, building on what already exists. Extending this idea, I think when we build on those strengths and stretch people to grow more, we can iteratively build on the new strengths.
If you’re looking for the nuts and bolts of the ideas, skip down to the “Change Ideas” list near the bottom of this post. This was the collected brainstorming of the group on how to make change happen.
Love the intro here—a circle of clip art chairs, asking people to put their names under a chair. Not a perfect solution for huge groups, but nice for imagining community with smaller groups.
Tech + Social
“Technology has fundamentally changed how we can be together”
Understand the relationships between the me, the we, and the many. The boundaries aren’t always clear.
Me: The individual. Personal identity.
We: Communities. Group identity, bounded membership, shared interest.
Many: Networks. Boundaryless, fuzzy. “intersecting interests”
Networks are about value of weak ties; Obama’s win reflects that value
Not so interested in learning theories; more interested in emerging roles and practices
Enabling people to be stewards of online communities
Stephen: Teachers just trying to change current practice. “How can I apply this in my current practice”
Nancy: You can’t usefully apply the technology unless you understand the teaching. Understand the teaching, then look at why it’s important. BUT sometimes looking at the technology first can spark an idea.
Is it just change, or is it the scale of change?
Stephen: Can we do the change just partway?
Nancy: Value of networks is that we don’t all have to do everything. One teacher doesn’t have to do everything by him/herself. We need safe places for people to explore, and sometimes privacy to try things out.
bradley.shoebottom: “Change is acceptable for only the amount people are willing to allow change. Therefore change needs to be iterative”
Nancy: Different roles for different people within the network
Use an “appreciative approach”—build on the strengths that already exist rather than trying to jump the chasm
Stephen: So many technologies are blocked
Nancy: sometimes people need to be taken outside the firewall to see what’s possible, but sometimes we need to look at workarounds and not our first choice tools. Demonstrating with limited tools can help changes occur.
Jo Ann Hammond-Meiers: @Lisa and others– yes — then it is important to stimulate the right questions from the teacher/learners. What do they want to happen?
How do you get change to happen?
Money can be a pressure point.
Concrete purposes rather than wide solutions can get to a lot of people. What’s the tangible benefit?
Do lots of little experiments on multiple fronts to figure out what works
How do you find the time to make the connections?
Nancy: we connect to people all the time. It’s as natural as breathing. Create the conditions for change to move the direction we want, rather than pushing hard for our own position. Make building community and ties into your meetings and time together with groups, without labeling it as “community building.”
Traditional project management is very linear, but we need something more iterative. Iterative change is a recurring theme here
Change that happens at the edges instead of in the middle
- Skunkworks—under the radar
- Small, iterative projects
- Distributed learning
- Start with your personal practices because you have control there, then apply that to your work
- Get outside validation
- Find related projects outside and work together
- Nike Strategy: Just do it
- Put in the infrastructure people need to change your practice. Instead of trying to directly change what people do, make it easier for them to do it—sort of letting them choose the tools
- Give what they WANT in a nonthreatening way
- Listen carefully for needs, not just openings for your own agenda
- Do easy things in an easy way
- Openness: share what you do openly (network value)
It’s not just about technology; it’s about how you see the world and connections and how we interact with each other. It’s about asking the questions to get people to see the world differently.
How do you measure success? Benchmarks? Would another course modeled like CCK08 be a success?
Nancy: it depends on the goals and learning. Not sure how to answer the question. How do you measure success with iterative learning?
In Groups Vs Networks: The Class Struggle Continues, Stephen Downes makes this statement about assessment:
I want to change the system of assessment in schools because right now we have tests and things like that that are scrupulously fair, particularly distance learning where we outline the objectives the performance metrics and the outcomes and all of that. I want to scrap that system. I want testing to be done by at random by comments from your peers and other people and strangers based on no criteria whatsoever and applied unequally and unfairly.
I found this a little jarring at first. Don’t we want things to be fair, to apply the same rules to everyone?
But applying the rules uniformly to everyone isn’t fair. The rules of baseball require that people run between the bases. Would you ask someone in a wheelchair to get up and run though, just because the rules say so? No, of course not. It’s absurd, not fair.
Most of the time, our educational system is set up with equality held up as the ideal. Everyone should be treated equally; we should hold everyone to the same standards. No exceptions should be made for individuals to bend the rules. In the US, NCLB is a prime example of this: every child is expected to meet the grade level goals, regardless of learning or other disabilities. We start from the assumption that everyone will learn and be assessed equally.
A better ideal for the system would be equity. We can move the emphasis away from applying the rules consistently across the board to giving people what they need as individuals to be successful. We should recognize that people do have obstacles to overcome and provide support for them to get around those obstacles. Being in a wheelchair means someone won’t run, but it certainly doesn’t mean they can’t participate in any sports.
The ALA article Equality and Equity of Access: What’s the Difference? describes equality as “fairness as uniform distribution” and equity as “fairness as justice.”
It occurred to me as I read Stephen’s ideas about assessment that connectivism may be a better way to get to the ideal of equity. It’s better for equity and accessibility when you don’t start from the assumption that everyone will learn and be assessed in the same way. If we start with the assumption that individuals will find their own path in learning, and that our job is to give them lots of opportunities and ways to participate, we’re more likely to help people get past their obstacles.
The CCK08 class is modeling that approach of letting people find their own path and giving them a chance for equity. Everything Stephen talks about with valuing diversity over uniformity reinforces that idea. The 2000 people can figure out what works best for them–lots of time in the Moodle forums or none, multiple blog posts or just reading and lurking, concept maps or word clouds, live sessions or only asynchronous. It’s what allows me to still be a participant in this class even though I knew I’d be out for a few weeks while I moved. I could take that break when I needed and step back in now.
I don’t know whether anyone in the course is visually or hearing impaired, but I can’t see any reason why they couldn’t find ways to actively participate and learn. Not everything is accessible to everyone, but you don’t need to see every image or hear the audio presentations to find value in the course.
I do wonder though–with the course so open and flexible, and with so many people participating, how much diversity is actually represented by the participants of the CCK08 class?