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The internet has often been described as a "dumb network" with intelligence residing at the edges (meaning that the network only cares about distributing content - doing anything with the content is the task of protocols and devices at end points). I've been thinking about how this translates to the creation of a personal learning network. Connectivism presents "rapid knowledge growth" as the process of adding on or plugging into new networks (an example is a web programmer who is trying to learn a new programming language. Instead of taking a course, she might find it easier to join an existing development community, subscribe to list servs, read and modify code others have produced...in essence, she doesn't possess the knowledge, but competence in a knowledge economy isn't only about possessing something - it's about finding it when it is needed).
For the purpose of learning, I believe that we have to ascribe some level of intelligence to the network. The network primarily delivers content, but the network also carries a sense of learning (serendipity, aggregation). Learning (being defined as knowledge that can be or is actuated) can reside in non-human appliances. The creation and formation of a network then is an attempt on the part of the learner to create a structure that allows him to stay current in a certain field. Learning is not a state at which we arrive. Learning is a process. It could be argued that we know something once we connect with a network that enables us to continue to know more. Back to the web programmer example - if a web programmer leaves the community...and a new member joins, within several releases of new versions of the language, the new member is at that stage more knowledgeable than the experienced developer who has left. Why? Because she is able to function optimally within the existing environment with the existing tools. If the experienced programmer decides to rejoin the community to increase his understanding of changes to the programming language, he may be able to "get up to speed" very quickly. Again, the network, not what is known now, is what's important. Connecting to a new network results in instant access to know more...severing from a network results in immediate flow of new learning...
is a great example of the dangers of not accounting for fundamental shifts in the domain on which a corporation functions. The author's concluding comments are worth consideration: "I would argue that Microsoft used to know how to ship software, but the world has changed... The companies that "know how to ship software" are the ones to watch. They have embraced the network, deeply understand the concept of "software as a service", and know how to deliver incredible value to their customers efficiently and quickly."
Understanding, such as is required by Microsoft, cannot be gained through formal education. It can't be gained through utilizing solutions that have worked in the past. When we fail to stay connected to sources that provide feedback on our core foundation, we risk losing relevance. Microsoft's blunder, inferred by the author, is that it has failed to recognize larger, global changes. The same threat exists in our personal lives and in our corporations. The recording industry failed to understand how its end user was changing (evidenced by the success of Napster). The motion picture industry is making a similar error. As is traditional media (TV, newspapers). I'm afraid many higher education institutions are also failing to recognize the changed learner. We are still delivering learning to learners that no longer exist based on a model that is no longer valid.
"Connectivism" Interesting, Not Sure It's a Learning Theory
suggests that learning is a verb, not a noun. The author feels that clarity of terms is important (knowledge and learning in particular). I agree. Information is the "raw" concept that is personalized (or processed) to create knowledge. Knowledge is translated to learning when we actually do something. Knowledge that doesn't lead to a change in thought and action has limited value. Perhaps this is why corporate trainers are drawn to Kirkpatrick's four levels of training effectiveness
- the highest level focuses on results.
Marcy Driscoll defines learning as a "persisting change in performance or performance potential". I don't know how accurate that is in the context of what we need to do today. Perhaps we need to rethink the term "learning". So much of what I need to do today, I don't possess within myself at the point of need (I find many of my answers via other bloggers, Google, communities, my own personal digital knowledge base, etc.). For me, a change in performance potential is often only temporary - the core conditions change. What is needed is a change in performance right now
. This fits with the definition of "learning as actionable knowledge" - i.e. I find it when I need it. Am I missing something?
Learning (in today's era) isn't something that we necessarily possess. A few generations ago, fixing a tractor required knowing how to fix a tractor. Today, most of our challenges aren't physical in nature - they are knowledge based. This requires core skills of the field, augmented with knowing where to go to get the information needed for the task. Things are too complex. Effective workers (especially knowledge workers) need to create a personal network that enables access to answers when needed. Knowing how to do something now requires knowing where to go in order to do something. Learning isn't always possessed at the time of need.
How does the concept that learning is actuated knowledge relate to the notion that learning can reside in non-human appliances? In a connectivist sense, if knowledge can be used to "do something", then it can be classified as learning. I don't have to possess personal mastery in order to benefit from it. If I use a software tool, and I need help, I can use the in-program help. Knowing how to use the help tool requires that I don't have to know the contents of the help file. When I need assistance, I simply go to where I know I'll most likely receive my answers. Repetition of the same challenges may result in learning committed to memory...but knowing where to go is the real learning challenge. Learning in this manner can reside in objects in the sense that they ("the answer") are used for application.
Learning is usually viewed as something that happens to a person. A person learns how to solve a physics problem, how to skate, or how to communicate. The assumption is that we are fairly autonomous beings, and that we can acquire within ourselves what we need to know to do the things we want to do. This model works well in areas where one can know everything within a field of knowledge. The model breaks apart as complexity and abundance of knowledge increases. For many, this is a very real problem today. It feels that we simply can't stay on top of our own fields. Forget trying to stay aware of occurrences in other fields. How do we learn in such an environment? Abundance=dysfunctionality in a silo learning model. "Superman's Learning Theory" - the notion that I can know in myself what I need to know - is obsolete today.
Why? Designing elearning is a simple example. No one person can be subject matter expert, instructional designer, media specialist, and graphic designer. It takes a combination of specialized skills (connected specialization). Take that concept to more complex fields like medicine, astronomy, physics, or launching a space shuttle. It immediately becomes obvious that we need to create a network to hold the points of knowledge. The network is the learning. The aggregation of network nodes is the learning structure. If any critical nodes are removed from a learning network, the entire organism loses effectiveness. Learning is evolutionary. Learning is not an event or end goal. Learning is a process. Our personal network is continually being augmented and enhanced by new nodes and connections.
I'm very confident that this is the model that we need to use for successful learning in today's environment. We can't stand alone on our own knowledge. We have to aggregate with other nodes (people, content, knowledge) in order to meet the challenges of a complex information climate. Unfortunately, education (K-12, higher and corporate) are built on the model that we can fit what is important into one person's head. The network becomes valuable once we combine and connect separate nodes of knowledge.
One of the original points I assigned to connectivism was that "learning exists in diversity of opinions". The ability to formulate a network that provides diverse assessments of a problem (with potential solutions) requires multiplicity. A network can have seemingly contradictory points of information (something that is false today may be true tomorrow as the underlying foundations change). Exploring diverse opinions enables greater likelihood of making healthy decisions. Who knows, perhaps conservatives and liberals can recognize points of value in each other...:).
I've been reflecting on various definitions of learning and knowledge. Often, knowledge acquisition and learning are used interchangeably. I think they are very different terms (at least when used in the context of what it means to learn today). Acquiring knowledge leaves room for a dormant state (i.e. we know something, but we may not actually do what we know). In contrast, learning involves knowledge acquisition, but is defined by use/doing. When I learn, I'm growing in performance capacity based on acquiring knowledge. If acquired knowledge doesnt' lead to some type of use, I don't believe learning has occurred (a changed state of knowledge is only half the process. Our discussions of learning usually acknowledge this half, but fail to account for the equally important "doing").
Some clarification of terms:
- Data: raw facts, symbols
- Information: Data that has been organized, interpreted, processed and made useful (useful being defined as the criterion for which the data was originally collected).
- Knowledge: information in context (i.e. understanding the significance of information) or information with semantic meaning.
- Learning: actuated (or actionable) knowledge, doing something with knowledge
I've received some comments from readers challenging the notion that learning is actionable knowledge. Dwelling on organizational learning, personal knowledge management, social learning, and networked learning, I'm convinced that in today's environment, learning isn't learning unless there is an action component.
When we focus on learning, we usually focus on what we are including in our reasoning (learning and knowledge acquisition are often seen as similar concepts). Most often, we associate learning with gaining. Lately, I'm finding increased value in determining the role of exclusion in learning. What we choose to exclude in order to learn may provide as much information as what we actually include.
It's commonly accepted that our learning filters through some type of framework. This framework is an aggregation of personal beliefs, experiences, existing knowledge, and emotional intelligence. As an example, (if we can briefly utilize stereotypes for illustration purposes) conservatives are usually perceived as business focused, whereas liberals are perceived as people (or social issue) focused. These political worldviews shape and influence the type of information that penetrates into our active region of thinking and deliberation.
Often, we exclude from thought those concepts which are strongly antagonistic to views we already hold. Back to the stereotypes of conservatives/liberals - when these two groups engage in dialogue, they are largely speaking past each other. Instead of embracing each other in an attempt to understand what is really being said, the debate centers on what each party has included
in their thinking...while focusing on what the other party has excluded
in their thinking. The conservative promotes the value of business, the liberal the value of social structures. The conservative criticizes the liberal's lack of business focus; the liberal criticizes the conservative's lack of social focus. We argue our points of inclusion and criticize the points of exclusion in the reasoning of others.
Similarly, we are uniquely susceptible to logical fallacies in domains in which we have strong beliefs. The stronger our beliefs, the more susceptible we are to fallacies. Moving back to politics - we are often very forgiving of errors within our personal party. We are not very compassionate to errors in "the other party". This is particularly the case when we are espousing personal theories. When I'm discussing connectivism with colleagues, I'm aware of my willingness to forgive cognitive conflicts in my own theory. I'm much more critical of the shortcomings of behaviourism, cognitivism, or constructivism. Why is that? Why do our cognitive processes function in a domino fashion (see Ideas as Corridors
)? Why is it so hard for liberals to see value in conservative views (and vice versa)?
The process of exclusion is a vital learning process. We cannot possibly consider every facet of a new idea. We exclude in order to be able to move to the point of active cognitive interaction with an idea. Exclusion occurs during the filtering process. What we choose to ignore speaks to our larger worldview (beliefs and values). When we are trying to influence the values of others (for example, in helping students learn about other cultures), we spend our time trying to get the learner to acquire new mindsets. We need to take a step back and focus on what is happening during the filtering process.
By analyzing what we exclude in our own reasoning, we are able to gain a better understand of our own learning process. It's unrealistic to regularly evaluate our core beliefs and values, but a periodic evaluation may provide the ability for more effective learning in general. What we ignore in learning can be a valuable tool to ensure that our perspectives are properly balanced (and at minimum acknowledge the existence of other viewpoints contrary to our own). Sometimes, the ability to step out of our thought corridor, and into the corridor of an "opponent", can lead to deep insight and understanding. Not all learning (or cognitive activity) is logical. The choice to include/exclude information may be the point were emotional intelligence exerts its greatest influence. Thoughts?