Sometimes I feel that forgetting all I know seems to be expected when participating in Open Online courses. We should believe that learning in web differs so greatly from earlier knowledge and skills acquired that we begin almost from zero. These question are considered also by Rita in CritLit2010 Course blog. I haven’t stop my wondering.
In this post I try to conceptualize the development of expertise in ill-defined, open questions. My main source is a Doctor Dissertation: Eteläpelto A. The Development of Expertise in Information Systems Design. 1998 Jyväskylä Studies in Education, Psychology and Social Research 146, University of Jyväskylä. She presented scientific knowledge better than I could. I suppose that the basic concepts are still alive and help me. The main question is not online vs real life, it is the complexity of the domain, learning in changing contexts and trying to solve open and ill-defined demands.
Expertise is analysed as a consequence of domain-spesific experience arising out of practical problem-solving in real contexts. Practical domain knowledge can be captured via conceptual model construction, thinking aloud, qualitative and quantitative analyses are complementary in the assessment and description of various qualities of expertise. I have done this many times in my blog during connectivism courses 2008 and 2009 and critical literacies course 2010. What can I say today?
I try to capture the critical stages of my transition from psychology and adult education context to the open online studies context. One of the threats may be that I use heavily professionally-centred tools and methods and I tend to adopt these methods all the time even if my studies include better new notions. Another threat is to generalize from technical competence. I have a hunch that connectivism was easily called a learning theory because of developers’ technical perspective.
I have the right to use my expertise, I do not apologize it. But I have to proceed from professional centred to more interactive approaches, from context-free to more individualised solution models, from individual to network. I have to keep in mind whether a situated approach to learning and cognition would offer a more adequate framework for the redefinition of expertise.
Comparison of experts vs novices in terms of their metacognitive knowledge and awareness showed that experts were superior to novices in
1. domain spesific knowledge structures: experts tended to perceive information systems development from a more comprehensive perspective, adopting more the perspective of overall work organisation. Novices were more restricted in their scope and often failed to integrate end-user issues into their procedural working models. In their first project they had acquired strategic competence in using domain-spesific tools and methods, but were not able to consider users’ constraints comprehensively. 2. spesific components of metacognition, had better interconnections between the knowledge awareness and regulation components.
My CCK08 studies went for acquiring basic skills and strategic orientation, how to work online globally, in CCK09 I was more confident and in CritLit 2010 I tried to construct my way really, it is easier to say than do.
Human development happens in interactions between different knowledge qualities. Declarative knowledge encodes factual knowledge and procedural knowledge encodes much of cognitive skills including problem-solving in terms of production rules that are condition-action (if-then) pairs. Declarative knowledge is converted into procedural through memory systems. Long term memory and permanent memory are activated via semantic network. Temporary memory is network structure that has just been created.
Summary about expertise:
- experts are faster, make fewer errors than novices in their domain problem solving
- perceive large meaningful patterns in their own domain and focus on the relevant cues in the task
- represent their domain problems at a deeper level than novices
- knowledge is organized in a way that is relevant for problem solving
- use more time in problem analysing and constructing a detailed mental representation of the problem before they enter into the solution
- knowledge structures are hierarchically organized and have more depth in their conceptual levels
- categorize problems in their own domains according to abstract high-level principles and their knowledge structures are more coherent than those of novices
- have better self monitoring skills than novices
- high performance professionals spend more time on problem evaluation.
Some experiences are strong enough to be put in long-term memory, some visit only temporary memory. Declarative knowledge and procedural knowledge are connected to each other in very complex ways. Automatic responses may become very complex and hard to follow.
Because of limitations in human processing capacity, complex cognitive skills are learned through the acquisition of large integrated chunks of knowledge. Chunks take the form of larger, more detailed conditions and actions of production rules. Larger conditions provide more precise spesifications of the circumstances under which the action is appropriate. Reduction in the need to access declarative memory allows speedier rule-firing due to increase in the strengths of rules which are needed in each successful application.
I think our knowledge chunks are a problem in open online courses. We speak different languages and cannot always understand each other. A good example is Stephen Downes’ response to my blog post. I cannot follow his thinking – and this was my third course with him.
Now I am again confused, have to stop and publish this. I hope some day I will be wiser …