Situated cognition

Modularity and abstraction have become key features of program and system design. Inevitably, when computer scientists attempt to model the brain, such ideas tend to be thought of as relevant. The design of the computer itself, with its memory, processing unit and interface could be seen as a useful analogue to the functioning of humans.

Any model, by definition, is incorrect in some way. If it was not it would not be a model, it would be the real thing. To be useful, however, any model must have one or more features that reflect reality. Some researchers question the usefulness of models that compartmentalise concepts such as memory and knowledge. There seems to be little physical evidence for knowledge existing in the brain as a separate entity. Some neurological research (Rosenfield, 1 988) even calls into doubt the existence of memory

as a separate phenomenon.

Scientists remain puzzled about how the physiological activity in the brain relates to what we know of people's thought processes (via reflection and protocol analysis for instance) . One way of deducing the nature of thought processes would be to examine how people appear best to learn.

Humans have developed methods of teaching that emphasize abstraction and so it might be inferred that the brain stores information in an abstract form. Abstraction involves finding patterns in activities, extracting them and representing them in some formal way. For example, operations on numbers are used to teach children about buying and selling, weighing, measuring volumes, etc. Frequently, the actual tasks of purchasing, weighing and so on are taught later, as applications of the processing of numbers. At a later age, the same approach is used in topics such as electronics where the theory of electrical currents is taught before the student is exposed to electronic devices. Although these methods have been used for years and, in some cases, centuries, there are some experts who question the validity of this approach and the corresponding inferences about the nature of thought Among those who have adopted a different view are two prominent ITS researchers, John Seely Brown and Alan Collins.

In 1 9 89, Brown, Collins and Duguid provided support for the view that knowledge cannot be separated out from the context in which it is used. They believe that components of knowledge index the world and are 'inextricably a product of the activity and situation in which they are produced' (Brown et al. , 1 989, p33). This view on the nature of knowledge is termed situated cognition.

Given this premise, the authors argue that students will best learn by carrying out tasks rather than by first being given a theoretical model. A comparison is made with the learning of words divorced from their context. They claim that students who have . acquired vocabulary from dictionary definitions invariably use the words wrongly since the description in a dictionary can never be adequate. Only by observing others using a word, by reading it in the proper context or by trying to use it oneself can one come to

a proper understanding of its meaning over a period of time. Similarly, they suggest, knowledge of how to do a task cannot be obtained by starting with a theoretical description which is then applied. Thus some form of situated learning is required in order to best assimilate know ledge.

An analogy is drawn with the learning of crafts where the apprentice initially watches the expert at work and, after a while, takes over some of the operations (stealing moves). Eventually, the apprentice is allowed to carry out the complete task under the gradually reduced supervision of the teacher. Brown believes that a similar approach can be used with cognitive tasks as well as for manual ones. In fact, it is suggested that there is no clear distinction between physical and mental tasks since virtually all tasks require both faculties to some degree. This method of learning from the expert is termed cognitive apprenticeship.

In this initial paper, the ideas are not developed to any great degree and the authors admit that they are deliberatively speculative. For example, details of exactly how cognitive apprenticeship could work in the classroom or university environment are not given. Even so, the paper generated a great deal of debate. Much of the cognitive science view of knowledge seemed to be challenged. Certainly, Wenger's idea of knowledge being communicable in some direct way and almost palpable is regarded as mistaken.

The reaction of advocates of knowledge communication was awaited with interest. Much of the work by Clancey on GUIDON, for example, had assumed that the knowledge of the expert could be represented in rules and that the aim of teaching was to communicate these procedures to the student. In an address to the Annual Meeting of the Educational Research Association at Boston in April 1990 (later published in a set of IFIP collected papers) Clancey ( 1 99 1 ) gives his response. As Winograd had done, he had changed his view and decided that his earlier work had been based on false premises. He and others had previously believed the human memory contains representations that could be processed and that this was the essence of knowledge. However, it was now clear that this was not the case.

He admits that representations such as semantic nets, grammars, schemata and so on are useful and even necessary in some circumstances but that they should not be closely identified with what occurs in the human brain. These notations can be used to model how people interact with the: environment and provide a succinct description of obj ects and processes, but what goes on in the heads of humans is something completely different.

Previously, Clancey had assumed that the human memory was very much like a knowledge base containing some equivalent to if-then rules. He now believes that the brain does not contain such static information but constructs necessary internal representations as needed by processing the external representations (perceptions). We can consciously try to analyse what is going on and devise appropriate representations but these bear no relation to how we are thinking.

Like some earlier researchers, Rosenfield ( 1 988) for example, Clancey regards memory and knowledge not as having any physical properties but as abilities. Memory is seen as a 'capacity to directly reenact and compose previous ways of behaving' (Clancey,

1 99 1 , p6 1 ).

In an address to ITS '92, Clancey ( 1 992) further develops his ideas. Knowledge is perceived as a capacity to interact which comes into being during the interaction itself. This ability improves as more and more cases are considered of a similar type, but the evolution never stops since circumstances are always changing as are our perceptions of reality. Any attempt to model this phenomenon by rules or structures is doomed to failure since we deal with each new situation as it arises depending upon the circumstances. These circumstances may not have been met before or even anticipated but they must be considered. How people cope with new situations is generally explained by using such terms as judgment and common sense. Clancey claims that no systematic structures or algorithms can denote them - although we can describe them in this fashion well enough after the event.

One could attempt to generalise the rules and structures by having meta-rules for interpretation but this only transfers the problem to another level since a further set of rules would be needed to interpret the meta-rules and so on ad infinitum. S uch an approach would limit our actions in a way that does not reflect reality. As a final refutation of the schema model, Clancey states that this is not how the brain works since there is nowhere to store representational structures.

Clancey describes the implications of his beliefs for teaching and the development of ITSs. He suggests that the schemata view can prejudice methods of education if we believe that what we are attempting to do is to build up structures and matching processes in the student's mind. By attempting to impose set procedures and structures upon students we inhibit their learning and their capacity for innovation. Learning should take place in a �ommunity and involve interaction with other learners and with experts. Learning by doing becomes not just a good way but the only way of developing understanding. Not only this, but others should be involved too. For

example, medical students should learn about how hospitals work, what nurses do, patient care and so on, and not just about diagnosis of diseases.

In order to create more useful and usable systems Clancey now works with a wide range of groups particularly social scientists. He is taking what he calls a socio­ technical approach to system development where everyone who is relevant to the final system works together in a democratic fashion. This includes experts, teachers, users, designers, programmers, administrators and anyone else who may have a contribution to make.

Although some of the most prominent researchers in teaching by computer have advocated the situated cognition approach, no overall methodology for teaching has been developed. It is unclear to what extent learning by doing is seen as a necessary

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component of learning. For example, the Cognition and Technology Group at Vanderbilt University (CTGV, 1 993) cite the programmes that they have developed as examples of situated learning. These include the Jasper Woodbury S eries of videodisks for teaching mathematical principles. In each of these videos, Jasper is in some predicament or is trying to help someone and, in order to achieve his aim, he needs to apply some mathematical methods. So, in one story he has to work out whether a micro-light aircraft can reach an injured eagle. In order to help Jasper, the class has to find out the relationships between time, distance and speed. In another story various geometrical principles are useful. The authors argue that this is in line with situated cognition since realistic contexts are provided in which the users are encouraged to construct their own knowledge. They stress the importance of not using the videos to consolidate theoretical material but to use the stories to motivate the students to find out about the theory.

Critics have argued that these, and similar programmes, are not strictly in line with situated learning. For example, Tripp ( 1 993) believes that the Jasper programmes do not use the principles of situated cognition since users are not learning in the 'real world' from experts. He points out that the principles to be learned have already been abstracted out and have been embedded in an artificial scenario. What the students are exposed to is not the real world but a simulation. Certainly, if one accepts Tripp's view then situated learning becomes very difficult to provide since nothing but the real world provides the kind of experience that the student needs.

Tripp suggests that, in view of this, we should continue using traditional teaching methods. Not only are they the only currently feasible ones but they still have advantages . Principles c an be developed in a classroom situation where noise that may

distract students from learning can be eliminated . Since the nature o f what i s being taught is clearly delineated it can be tested by dependable means. Once the student has this knowledge c onsolidated it can then be tried out in practical situations and augmented as necessary.

The situated learning supporters would argue that it is precisely the separate manipulation of symbols in the classroom and their meaning in the real world that they wish to avoid. Brown ( 1 990) observes that symbols as developed in the classroom take on a meaning of their own, totally unrelated to what they are modelling in the real world. In the same paper, he cites work which shows that learning in an abstract situation may impair the ability to apply such knowledge in practical situations whereas students who learn during c arrying out tasks seem to be able to apply the knowledge they have acquired to different problems.

The views of supporters of situated cognition can be summarized as follows. Knowledge c annot be disembodied from the user and the context. It can be represented, perhaps in a diagram, by logic, or on the computer but in the translation process vital ingredients are lost which cannot be replaced. The models can be used in a restricted way for problem solving but do not equate in any way to the knowledge that a human would bring to bear on the same process. The computer representation is fixed, disembodied and cannot adapt to circumstances. User's knowledge is constructed as needed and is totally dynamic.

It might seem that the rift between the supporters of knowledge communication and situated cognition would mean that a system developer has to take one view or the other in order to produce a coherent piece of software. This does not have to be the case, however. There is common ground and the link between the views is the idea of modelling. If one considers models of the different aspects of the teacher/student interaction, such as a model of the domain and of the problem solving process, then the main point of debate is not what these artefacts should look like but how they are constructed. An advocate of knowledge communication would attempt to get the student to understand a computer model in a fairly direct way. A supporter of situated cognition would attempt to get the student to build up their own model. Brown ( 1 990), for example, sees the education process as facilitating the building of adequate mental models by the user. So, it would appear that modelling is a central concept in education.