MIS40650 – Rethinking Knowledge and its ‘Management’

The session started with a discourse on Dreyfus’s five stage phenomenological model of skill acquisition. The argument given by Dreyfus is that expertise in general cannot be captured in a rule-based expert systems.

Dreyfus & Dreyfus

Dreyfus – Expertise in real world contexts.pdf (76.446 KB)

Dreyfus – Expertise in real world contexts

Dreyfus, Hubert L. and Dreyfus, Stuart E. (2005), ‘Expertise in real world contexts’, Organization Studies, 26 (5), 779-92.

Stage 1: Novice

In this stage of skill acquisition a novice user goes through rules for determining actions. In this stage the instruction process begins with instructor decomposing the task environment into context free features that beginner can recognise without desired skills. But merely following rules will produce poor performance in real world environment.

For example in case of learner driver, he starts this stage with the instructions given by driving instructor like to change gear once engines revs up.

Stage 2: Advanced Beginner

In this stage the user gets attuned to the relevant context as he gains experience with real situations. The user starts to recognise the new situational aspects as well as objectively defined non-situational features. 

For a learner driver, this stage is reached when he starts recognising the engine noise and automatically change the gears on hearing that noise. Why the learner driver did not recognise the engine noise earlier because he was not attuned to that aspect till that time though he had been into the car perhaps all his life. This is how the world is disclosed to us, once we start attuning to the situation aspects while acquiring a new skill, new insights are disclosed to us. Once we recognise these new insights these help us in performing better in that skill area. This is coming directly from Heidegger’s notion of world getting disclosed to us in stages.

Stage 3: Competence

This is the most crucial of all stages as this is the stage where finally the person starts to get emotionally attached or invested into the skill area. But as the person gets emotionally attached to the task at hand the performance because mentally exhausting as still the sense of what is important in any situation is missing. As a person becomes more proficient he learns to restrict himself to only a few of the vast number of possibly relevant features and aspects, understanding and slowly decision-making become easier. Naturally, to avoid mistakes, the competent performer seeks rules and reasoning procedures to decide which plan or perspective to adopt. The person therefore, must decide for themselves in each situation what plan or perspective to adopt without being sure that it will turn out to be appropriate.

Given this uncertainty, coping becomes frightening rather than merely exhausting. Prior to this stage, if the rules don’t work, the performer, rather than feeling remorse for his or her mistakes, can rationalize that he or she hadn’t been given adequate rules. But, since at this stage, the result depends on the learner’s choice of perspective, the learner feels responsible for his or her choice. Often, the choice leads to confusion and failure. But sometimes things work out well, and the competent student then experiences a kind of elation unknown to the beginner. Only at the level of competence is there an emotional investment in the choice of action. There is the possibility of taking the risk of proposing and defending an idea and finding out whether it fails or flies. But progress  is only possible if one starts taking risks, failure to take risks leads to rigidity rather than the flexibility we associate with expertise.

For example a competent driver leaving the freeway on an off-ramp curve learns to pay attention to the speed of the car, not whether to shift gears.

Stage 4: Proficiency

Proficiency seems to develop if, and only if, experience is assimilated in this embodied, atheoretical way. Only then do intuitive reactions replace reasoned responses. The proficient performer, after
spontaneously seeing the point and the important aspects of the current situation, must still decide what to do. And to decide, he or she must fall back on detached rule and maxim following.

For example, the proficient driver, approaching a curve on a rainy day, may feel in the seat of his pants that he is going dangerously fast. He must then decide whether to apply the brakes or merely to reduce pressure by some specific amount on the accelerator.

Stage 5: Expertise

The proficient performer, immersed in the world of skilful activity, sees what needs to be done, but decides how to do it. The expert not only sees what needs to be achieved; thanks to a vast repertoire of situational discriminations, he or she also sees immediately how to achieve the goal. A beginner calculates using rules and facts just like a heuristically programmed computer, but that with talent and a great deal of involved experience, the beginner develops into an expert who intuitively sees what to do without recourse to rules. Normally an expert does not calculate, or solve problems, or even think. He or she just does what normally works and, of course, it normally works. If one asks an expert for the rules he or she is using, one will, in effect, force the expert to regress to the level of a beginner and state the rules learned in school.


Next McDermott’s article was discussed, it started with a discussion around difference between a computer & human being. The conclusion was that computer can do perhaps most of the things a human can do, can even think like a human but it cannot experience  knowledge like we do. This again is coming straight from Heidegger’s notion that we experience world as we are in it and have a body.

McDermott – IT and KM.pdf (1.041 MB)

McDermott – IT and KM

McDermott, R. (1999), “Why information technology inspired but cannot deliver Knowledge Management”, California Management Review, Vol. 41, No. 4, pp. 103-117.

Knowledge is different from information and sharing it requires a different set of concepts and tools. The great trap in knowledge management is using information management tools and concepts to design knowledge management systems.

Six characteristics of knowledge distinguish it from information:

  1. Knowing is a human act
  2. Knowledge is the residue of thinking
  3. Knowledge is created in the present moment
  4. Knowledge belongs to communities
  5. Knowledge circulates through communities in many ways
  6. New knowledge is created at the boundaries of old

Leveraging knowledge involves a unique combination of human and information systems.


Walsham – KM – benefits and limitations of computers.pdf (121.697 KB)

Walsham – KM – Benefits and limitations of computers

Walsham, Geoff (2001) “Knowledge management: The benefits and limitations of computer systems”, European Management Journal, 19(6): 599-608.

Hansen et al

Hansen and Nohria – KM Strategy.pdf (4.999 MB)

Hansen and Nohria – KM Strategy

Hansen, M. T., N. Nohria, et al. (1999). “What’s your strategy for managing knowledge?” Harvard Business Review 77(2): 106-116.

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