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Summary Carl Bereiter: Situated Cognition and How to Overcome It

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A summary of an article by Carl Bereiter: Situated Cognition and How to Overcome It. This summary discusses the important information from the article and describes the situations that are used by Bereiter in a more abstract and understandable way.

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CARL BEREITER: SITUATED COGNITION AND HOW TO OVERCOME IT

Situated rat behavior: rats learn their environment. Change it up a little and they are completely lost

Humans need to transcend their animal heritage to overcome situated cognition:
 Transforming physical environments and creating new social structures and practices along with them.
 Acquire expertise  enabeling us to function in a novel environment much as if we had evolved within it.
 Create a world of immaterial knowledge objects and acquire expertise in working with them.

Karl Popper’s metaphoric schema of 3 worlds:
 World 1: material world of inanimate and animate things.
 World 2: subjective world of individual mental life.
 World 3: world of immaterial knowledge objects.
Through situated cognition, world 1 and world 2 are directly and intimately connected.

Formal education is our individual escape route from the confines of situated cognition.

Nonsituated cognition only exists in the world of machines, not in nature.

Human cognition: cognition is the individual or collective process by which people negotiate the adaptation to
constraints and affordances to their environment, according to their individual or collective purposes.
Machine intelligence cognition: cognition is an internal process of symbol manipulation. Interaction with the outside
world through transducers that take an input and turn it into symbols that the machine can manipulate or translate
into actions.

Rule-based artificial intelligence  nonsituated cognition.

Advantages of computers:
 Rule based programs  good at carrying out long chains of reasoning and exhaustively searching memory.
 Reasoning further ahead and along more paths than humans.

Advantages of humans:
 Recognizing patterns (eg. aged faces, handwriting).
 Associate retrieval: getting reminded of something similar during doing something else.
 Imaginative through the ability to recognize patterns and associate retrieval  analogies and metaphors.

Rule-based AI works very well when all the necessary information can be explicitly represented and indexed.
However, in the real world there are just too many situations  it cannot be represented this way.

The limitations of situatedness are problems of transfer: what is learned in one situation cannot be transferred to another.
The progress of situated learning consists of increasingly fine attunement to the constraints and affordances of the particular
situation  when proceeding to learn, it tends to become less generalizable to other situations.
Advanced stages of situated learning bring negative transfer: habits are acquired  need to overcome in a new situation.

During transfer of situated knowledge to a new situation, important parts can be transferred, but you will not be attuned to the
situation: only the basics may transfer.

To discover abstract relationships between situations (to increase nonsituatedness), one has to create symbolic representations of
situations and carry out operations on those symbols  act more like a computer.

Whilst transferring knowledge, it is important to note that the situation in which the knowledge itself was created, is key in the
ability to transfer it: if there was no need to have a conceptual understanding of the knowledge, transferring the knowledge to
another situation becomes relatively hard.
If the goal of a situation is to finish some exercises, it is necessary to be pursuing knowledge-building goals to make knowledge
better transferable  less situated.
Knowledge-building goals are weakly connected to the current situation  more abstract than task completion.
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