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Cognitive Flexibility Theory

Spiro et al. (1991, 21) argue that there is a common basis for failure in many instructional systems and that these stem from basic problems with the design of the instructional materials. Spiro and Jehng (1990, 163) state that traditional instructional methods take a linear approach and while this is not a problem when the material is well structured and simple:

... as content increases in complexity and ill-structuredness, increasingly greater amounts of important information are lost with linear approaches and the unidementionality of organisation that typically accompanied them.

In response to this situation, Spiro et al. (1991, 24) "offer a constructivist theory of learning and instruction that emphasises the real-world complexity and ill-structuredness of many knowledge domains". They state that for instruction to be effective, several "highly intertwined topics" must be considered simultaneously. Among these topics they include:

the constructive nature of understanding;

the complex and ill-structured features of many, if not most, knowledge domains;

patterns of learning failure;

a theory of learning that addresses known patterns of learning failure.

Taking into account these topics, Spiro et al. (1991, 24-25) have devised a set of principal recommendations for the development of instructional hypertext systems "to promote successful learning of difficult subject matter". They argue that in particular:

Various forms of conceptual complexity and case-to-case irregularity in knowledge domains (referred to collectively as ill-structuredness) pose serious problems for traditional theories of learning and instruction.

Cognitive and instructional neglect of problems related to content complexity and irregularity in patterns of knowledge use leads to learning failures that take common, predictable forms. These forms are characterised by conceptual oversimplification and the inability to apply knowledge to new cases (failures of transfer).

The remedy for learning deficiencies related to domain complexity and irregularity requires the inculcation of learning processes that afford greater cognitive flexibility: this includes the ability to represent knowledge from different conceptual and case perspectives and then, when the knowledge must later be used, the ability to construct from those different conceptual case representations a knowledge ensemble tailored to the needs of the understanding or problem-solving situation at hand.

For learners to develop cognitively flexible processing skills and to acquire contentive knowledge structures which can support flexible cognitive processing, flexible learning environments are required which permit the same items of knowledge to be presented and learned in a variety of different ways and for a variety of different purposes (commensurate with their complex and irregular nature).

The computer is ideally suited, by virtue of the flexibility it can provide, for fostering cognitive flexibility. In particular, multidimensional and nonlinear hypertext systems, if appropriately designed to take into account all of the considerations discussed above, have the power to convey ill-structured aspects of knowledge domains and to promote features of cognitive flexibility in ways that traditional learning environments (textbooks, lectures, computer-based drill) could not (although such traditional media can be very successful in other contexts of for other purposes). We refer to the principled use of flexible features inherent in computers to produce nonlinear learning environments as Random Access Instruction.

Spiro et al. (1991, 25) present the following argument which encompasses these points:

Characteristics of ill-structuredness found in most knowledge domains (especially when knowledge application is considered) lead to serious obstacles to the attainment of advanced learning goals (such as the mastery of conceptual complexity and the ability to independently use instructed knowledge in new situations that differ from the conditions of initial instruction). These obstacles can be overcome by shifting from a constructive orientation that emphasises the retrieval from memory of preexisting knowledge to an alternative constructivist stance which stresses the flexible reassembly of preexisting knowledge to adaptively fit the needs of a new situation. Instruction based on this new constructivist orientation can promote the development of cognitive flexibility using theory-based hypertext systems that themselves possess characteristics of flexibility that mirror those desired for the learner.

This theory is called Cognitive Flexibility Theory (Spiro and Jehng, 1990, 163; Spiro et al. 1991, 25).

Ill-Structured Knowledge Domain

According to Spiro et al. (1991, 25-26), an ill-structured knowledge domain has two properties:

(1) each case or example of knowledge application typically involves the simultaneous interactive involvement of multiple, wide-application conceptual structures (multiple schemas, perspectives, organisational principles, and so on), each of which is individually complex (i.e., the domain involves concept- and case-complexity)

and

(2) the pattern of conceptual incidence and interaction varies substantially across cases nominally of the same type (i.e., the domain involves across-case irregularity),

Spiro et al. (1991, 26) suggest that the majority of knowledge areas, especially when they are applied, represent ill-structured domains.

Spiro et al. (1991, 26) state that there is often a difference in the objective of learning between beginning and more advanced learning. Teachers are often satisfied if learners who are new to a subject can gain a superficial knowledge of it and reproduce material in the same form as it was taught. More advanced learners, however, are expected to demonstrate mastery of complexity and/or the ability to transfer their knowledge to new situations.

Patterns of Advanced Learning Deficiencies

Spiro et al. (1991, 26-27) state that there has been little research conducted in the area of advanced knowledge acquisition which lies between knowledge acquisition of novice and expert. They claim, however, that their work in this area has produced a number of notable results. They summarise these as follows:

Failure to attain the goals of advanced knowledge acquisition is common. For example, when students are tested on concepts that are consensually judged by teachers to be of central importance and have been taught, conceptual misunderstanding is prevalent.

A common thread running through the deficiencies in learning is oversimplification. We call this tendency the reductive bias, and we have observed its occurrence in many forms. Examples include the additivity bias, in which parts of complex entities that have been studied in isolation are assumed to retain their characteristics when the parts are reintegrated into the whole from which they were drawn; the discreteness bias, in which continuously dimensioned attributes (like length) are bifurcated to their poles and continuous processes are instead segmented into discrete steps; and the compartmentalisation bias, in which conceptual elements that are in reality highly interdependent are instead treated in isolation, missing important aspects of their interaction. Of course, the employment of strategies of this kind is not a problem if the material is simple in ways consistent with the reductive bias. However, if real complexities exist and their mastery is important, such reduction is an inappropriate oversimplification.

Errors of oversimplification can compound each other, building larger scale networks of durable and consequential misconception.

The tendency towards oversimplification applies to all elements of the learning process, including cognitive strategies of learning and mental representation, and instructional approaches (from textbooks to teaching styles to testing). These various sources of simplification bias reinforce each other (e.g., one is more likely to oversimplify if an inappropriately easier learning strategy is also employed in textbooks or teaching because it is simple).

Spiro et al. (1991, 27) claim that the the strategies for advanced learning in ill-structured domains are frequently those suitable for introductory learning in structured domains. For example, compartmentalisation of knowledge components is effective in well-structured domains but blocks learning in ill-structured domains where a high level of knowledge interconnection is required. A focus on general principles works well in well-structured domains but leads to misunderstanding in ill-structured ones. Well-structured domains can be represented by a single unifying basis but ill-structured ones require multiple representations to obtain a full coverage. This can be illustrated by the use of analogies. It has been found that an analogy can be useful in introductory learning but later interferes with more advanced learning of the same topic.

Spiro et al. (1991, 27) claim that "There is much that appears to be going wrong in advanced learning and instruction" and that the cognitive theories and instructional practices that work well in introductory learning, not only do not work in advanced learning in more ill-structured domains, but may "produce impediments to further progress". They conclude that "a reconceptualisation of learning and instruction is required for advanced knowledge acquisition in ill-structured domains".

Spiro et al. (1991, 27) state that their interpretation of constructivism is complex:

We argue that there are different points in cognitive acts where constructive mental processes occur. First, we take it as an accepted cognitive principle that understanding involves going beyond the presented information. For example, what is needed to comprehend a text is not solely contained in the linguistic and logical information coded in that text. Rather, comprehension involves the construction of meaning: the text is a preliminary blueprint for constructing an understanding. The information contained in the text must be combined with information outside of the text, including most prominently the prior knowledge of the learner, to form a complete and adequate representation of the text's meaning.

However, our approach to constructivist cognition goes beyond many of the key features of this generally accepted view. The interpretation of constructivism that has dominated much of cognitive and educational psychology for the last 20 years or so has frequently stressed the retrieval of organised packets of knowledge, or schemas, from memory to augment any presented information that is to be understood or any statement of a problem that is to be solved. We argue that conceptual complexities and cross-case inconsistencies in ill-structured knowledge domains often render the employment of prepackaged ("precompiled") schemas inadequate and inappropriate. Rather, because knowledge will have to be used in too many different ways for them to be anticipated in advance, emphasis must be shifted from the retrieval of intact knowledge structures to support the construction of new understandings, to the novel and situation-specific assembly of prior knowledge drawn from diverse organisational loci in preexisting mental representations. That is, instead of retrieving from memory a previously packaged "prescription" for how to think and act, one must bring together, from various knowledge sources, an appropriate ensemble of information suited to the particular understanding or problem-solving needs of the situation at hand. Again, this is because many areas of knowledge have too diverse a pattern of use for single prescriptions stored in advanced, to cover enough of the cases that will need to be addressed (Spiro et al. 1991, 27-28).

In view of this, a new element of constructive processing, the flexible use of preexisting knowledge, has been added to Cognitive Flexibility Theory. Spiro et al. (1991, 28) claim that this "new constructivism" is doubly constructive because:

(1) understandings are constructed by using prior knowledge to go beyond the information given; and (2) the prior knowledge that is brought to bear is itself constructed, rather than retrieved intact from memory, on a case-by-case basis.

Spiro et al. (1991, 28) argue that cognitive flexibility theory "is an integrated theory of learning, mental representation, and instruction" and is aimed specifically at the special requirements "for attaining advanced learning goals, given the impediments associated with ill-structured features of knowledge domains" and with their findings about specific deficiencies in advanced learning.

Spiro and Jehng (1990, 168) state that the basic metaphor of Cognitive Flexibility Theory is the "criss-crossed" landscape. A landscape is a complex structure and one would be exposed only to a small amount of its detail in a single walk through it. If, however, the landscape was traversed a number of times in different directions, more and more information would be gathered about it. Spiro and Jehng use this metaphor in Cognitive Flexibility Theory, and state that:

One learns by criss-crossing conceptual landscapes; instruction involves the provision of learning materials that channel multidimensional landscape explorations under the active initiative of the learner (as well as providing expert guidance and commentary to help the learner to derive maximum benefit from his or her explorations); and knowledge representations reflect the criss-crossing that occurred during learning.

By criss-crossing the "conceptual landscape", a highly interconnected web-like knowledge structure can be constructed, and, Spiro and Jehng (1990, 170) claim that this structure has the potential to be used in problem solving or comprehension and "The likelihood that a highly adaptive schema can be assembled to fit the particular requirements for understanding or acting in the situation at hand is increased". This means that there is an increased range of situations to which this knowledge can be transferred. Spiro and Jehng argue that this flexibility is essential for learning in an ill-structured domain. They state that:

Because one cannot have a prepackaged knowledge structure for every situation that might be encountered, the emphasis must shift from intact schema retrieval to flexibility of situation-specific schema assembly. By criss-crossing a conceptual landscape in many directions, knowledge that will have to be used in many ways is taught in many ways (1990, 170-171).

As Cognitive Flexibility Theory emphasises the fact that material is continually represented in rearranged instructional sequences and from different conceptual view points, Spiro and Jehng (1990, 171) argue that the most appropriate delivery medium is a computer system which has random access delivery capabilities with a videodisc being an example. Cognitive Flexibility Theory can act as the "antidote" to the different types of learning failure associated with advanced learning in ill-structured domains when traditional instructional strategies are employed. Spiro and Jehng justify this claim by stating that:

If typical approaches have overlinearised, one can construct nonlinear presentations. If material has been presented from just one point of view, one can re-present it from different points of view. Cases that have been slotted in a rigid hierarchical structure can be repeatedly re-presented to attain heterarchical or montage-like structural representations. If partially overlapping exemplars have been indiscriminately lumped under one category in a way that causes important differences among them to be missed, one can demonstrate the diversity amongst the similarity. Or, if exemplars that partially overlap in important ways have been separated into different conceptual categories, the similarity amongst the diversity can be demonstrated. If aspects of knowledge have been overly compartmentalised, their insularity can be overcome by joint presentation. If decomposed elements are not additively assemblable, they can be reassembled with a more complex combinatory logic. If an old example/case is employed too monolithically as a precedent for a new one, you can decompose examples and then recombine aspects of different examples to achieve the most accurate (the most closely fitting) set of multiple precedents for understanding in a new situation (1990, 171).

Spiro and Jehng (1990, 171) call the computer based instructional materials based on Cognitive Flexability Theory Cognitive Flexibility Hypertexts.

To illustrate the use of such a hypertext, Spiro and Johng (1990, 173-180) describe "Exploring Thematic Structure in Citizen Kane" (or KANE for short). This is an experimental hypertext based on the film Citizen Kane. At the time of writing, it did not attempt to teach about the entire film, rather was concentrated on the characteristics of Kane. As this type of hypertext is designed for advanced learners, students are expected to be familiar with the film having viewed it one or more times and to have been thoroughly introduced to the main themes before using the hypertext.

The film is viewed from the perspective of ten different major themes. The video material itself is divided into 25 mini-cases or scenes which range in length from 30 to 90 seconds. Each of these scenes can be viewed in the context of the different themes. For example, Spiro and Jehng (1990, 177) describe a scene and then explain how it is interpreted from the perspective of some of the themes. The themes identified were:

The outsize Ambition theme and its Grandeur/Sweep and Egomania sub-themes.

Power theme ("Control others by their dependence on you" sub-theme).

The Fallibility/Morality sub-theme of Outsized Ambition theme.

The Hollow Man theme illustrating the Lifelessness sub-theme.

By viewing these different facets of Kane's character, students should obtain a much fuller picture of him than would have been gained by viewing the film in its original, linear form.

Spiro et al. (1991, 32) conclude by stating:

... we consider our work to be moving towards a systematic theory of hypertext design to provide flexible instruction appropriate for developing cognitive flexibility. ... We are encouraged so far about the robustness, systematically, and generality of our hypertext design principles, in that they have been applied in very similar ways to develop hypertext prototypes in domains as diverse as cardiovascular medicine, literary interpretations, and military strategy. Preliminary data on the effectiveness of these Cognitive Flexibility Hypertexts is also encouraging.

They state that research has indicated that Cognitive Flexibility Hypertexts promote superior transfer to new problem solving situations than did a design which emphasised the mastery of declarative knowledge.

Conclusion

A great advantage ofCognitive Flexibility Theory is that it has been devised especially to be used with hypertext.

From the point of view of constructing mental models, this theory would appear to be very appropriate as its use would result in the formation of a very complete, well linked model. The only difficulty with it is finding ways of 'criss-crossing' the subject material. In the example of KANE, this is done in a very logical way, but how could this be applied to a topic, for example, in science?

Server: http://scs.une.edu.au
Author: Tony Brown

Created: 25.6.97

© The University of New England, NSW, Australia

	Cognitive Flexibility Theory

	Spiro et al. (1991, 21) argue that there is a common basis for failure in many instructional systems and that these stem from basic problems with the design of the instructional materials. Spiro and Jehng (1990, 163) state that traditional instructional methods take a linear approach and while this is not a problem when the material is well structured and simple: ... as content increases in complexity and ill-structuredness, increasingly greater amounts of important information are lost with linear approaches and the unidementionality of organisation that typically accompanied them. In response to this situation, Spiro et al. (1991, 24) "offer a constructivist theory of learning and instruction that emphasises the real-world complexity and ill-structuredness of many knowledge domains". They state that for instruction to be effective, several "highly intertwined topics" must be considered simultaneously. Among these topics they include: the constructive nature of understanding; the complex and ill-structured features of many, if not most, knowledge domains; patterns of learning failure; a theory of learning that addresses known patterns of learning failure. Taking into account these topics, Spiro et al. (1991, 24-25) have devised a set of principal recommendations for the development of instructional hypertext systems "to promote successful learning of difficult subject matter". They argue that in particular: Various forms of conceptual complexity and case-to-case irregularity in knowledge domains (referred to collectively as ill-structuredness) pose serious problems for traditional theories of learning and instruction. Cognitive and instructional neglect of problems related to content complexity and irregularity in patterns of knowledge use leads to learning failures that take common, predictable forms. These forms are characterised by conceptual oversimplification and the inability to apply knowledge to new cases (failures of transfer). The remedy for learning deficiencies related to domain complexity and irregularity requires the inculcation of learning processes that afford greater cognitive flexibility: this includes the ability to represent knowledge from different conceptual and case perspectives and then, when the knowledge must later be used, the ability to construct from those different conceptual case representations a knowledge ensemble tailored to the needs of the understanding or problem-solving situation at hand. For learners to develop cognitively flexible processing skills and to acquire contentive knowledge structures which can support flexible cognitive processing, flexible learning environments are required which permit the same items of knowledge to be presented and learned in a variety of different ways and for a variety of different purposes (commensurate with their complex and irregular nature). The computer is ideally suited, by virtue of the flexibility it can provide, for fostering cognitive flexibility. In particular, multidimensional and nonlinear hypertext systems, if appropriately designed to take into account all of the considerations discussed above, have the power to convey ill-structured aspects of knowledge domains and to promote features of cognitive flexibility in ways that traditional learning environments (textbooks, lectures, computer-based drill) could not (although such traditional media can be very successful in other contexts of for other purposes). We refer to the principled use of flexible features inherent in computers to produce nonlinear learning environments as Random Access Instruction. Spiro et al. (1991, 25) present the following argument which encompasses these points: Characteristics of ill-structuredness found in most knowledge domains (especially when knowledge application is considered) lead to serious obstacles to the attainment of advanced learning goals (such as the mastery of conceptual complexity and the ability to independently use instructed knowledge in new situations that differ from the conditions of initial instruction). These obstacles can be overcome by shifting from a constructive orientation that emphasises the retrieval from memory of preexisting knowledge to an alternative constructivist stance which stresses the flexible reassembly of preexisting knowledge to adaptively fit the needs of a new situation. Instruction based on this new constructivist orientation can promote the development of cognitive flexibility using theory-based hypertext systems that themselves possess characteristics of flexibility that mirror those desired for the learner. This theory is called Cognitive Flexibility Theory (Spiro and Jehng, 1990, 163; Spiro et al. 1991, 25).

	Ill-Structured Knowledge Domain

	According to Spiro et al. (1991, 25-26), an ill-structured knowledge domain has two properties: (1) each case or example of knowledge application typically involves the simultaneous interactive involvement of multiple, wide-application conceptual structures (multiple schemas, perspectives, organisational principles, and so on), each of which is individually complex (i.e., the domain involves concept- and case-complexity) and (2) the pattern of conceptual incidence and interaction varies substantially across cases nominally of the same type (i.e., the domain involves across-case irregularity), Spiro et al. (1991, 26) suggest that the majority of knowledge areas, especially when they are applied, represent ill-structured domains. Spiro et al. (1991, 26) state that there is often a difference in the objective of learning between beginning and more advanced learning. Teachers are often satisfied if learners who are new to a subject can gain a superficial knowledge of it and reproduce material in the same form as it was taught. More advanced learners, however, are expected to demonstrate mastery of complexity and/or the ability to transfer their knowledge to new situations.

	Patterns of Advanced Learning Deficiencies

	Spiro et al. (1991, 26-27) state that there has been little research conducted in the area of advanced knowledge acquisition which lies between knowledge acquisition of novice and expert. They claim, however, that their work in this area has produced a number of notable results. They summarise these as follows: Failure to attain the goals of advanced knowledge acquisition is common. For example, when students are tested on concepts that are consensually judged by teachers to be of central importance and have been taught, conceptual misunderstanding is prevalent. A common thread running through the deficiencies in learning is oversimplification. We call this tendency the reductive bias, and we have observed its occurrence in many forms. Examples include the additivity bias, in which parts of complex entities that have been studied in isolation are assumed to retain their characteristics when the parts are reintegrated into the whole from which they were drawn; the discreteness bias, in which continuously dimensioned attributes (like length) are bifurcated to their poles and continuous processes are instead segmented into discrete steps; and the compartmentalisation bias, in which conceptual elements that are in reality highly interdependent are instead treated in isolation, missing important aspects of their interaction. Of course, the employment of strategies of this kind is not a problem if the material is simple in ways consistent with the reductive bias. However, if real complexities exist and their mastery is important, such reduction is an inappropriate oversimplification. Errors of oversimplification can compound each other, building larger scale networks of durable and consequential misconception. The tendency towards oversimplification applies to all elements of the learning process, including cognitive strategies of learning and mental representation, and instructional approaches (from textbooks to teaching styles to testing). These various sources of simplification bias reinforce each other (e.g., one is more likely to oversimplify if an inappropriately easier learning strategy is also employed in textbooks or teaching because it is simple). Spiro et al. (1991, 27) claim that the the strategies for advanced learning in ill-structured domains are frequently those suitable for introductory learning in structured domains. For example, compartmentalisation of knowledge components is effective in well-structured domains but blocks learning in ill-structured domains where a high level of knowledge interconnection is required. A focus on general principles works well in well-structured domains but leads to misunderstanding in ill-structured ones. Well-structured domains can be represented by a single unifying basis but ill-structured ones require multiple representations to obtain a full coverage. This can be illustrated by the use of analogies. It has been found that an analogy can be useful in introductory learning but later interferes with more advanced learning of the same topic. Spiro et al. (1991, 27) claim that "There is much that appears to be going wrong in advanced learning and instruction" and that the cognitive theories and instructional practices that work well in introductory learning, not only do not work in advanced learning in more ill-structured domains, but may "produce impediments to further progress". They conclude that "a reconceptualisation of learning and instruction is required for advanced knowledge acquisition in ill-structured domains". Spiro et al. (1991, 27) state that their interpretation of constructivism is complex: We argue that there are different points in cognitive acts where constructive mental processes occur. First, we take it as an accepted cognitive principle that understanding involves going beyond the presented information. For example, what is needed to comprehend a text is not solely contained in the linguistic and logical information coded in that text. Rather, comprehension involves the construction of meaning: the text is a preliminary blueprint for constructing an understanding. The information contained in the text must be combined with information outside of the text, including most prominently the prior knowledge of the learner, to form a complete and adequate representation of the text's meaning. However, our approach to constructivist cognition goes beyond many of the key features of this generally accepted view. The interpretation of constructivism that has dominated much of cognitive and educational psychology for the last 20 years or so has frequently stressed the retrieval of organised packets of knowledge, or schemas, from memory to augment any presented information that is to be understood or any statement of a problem that is to be solved. We argue that conceptual complexities and cross-case inconsistencies in ill-structured knowledge domains often render the employment of prepackaged ("precompiled") schemas inadequate and inappropriate. Rather, because knowledge will have to be used in too many different ways for them to be anticipated in advance, emphasis must be shifted from the retrieval of intact knowledge structures to support the construction of new understandings, to the novel and situation-specific assembly of prior knowledge drawn from diverse organisational loci in preexisting mental representations. That is, instead of retrieving from memory a previously packaged "prescription" for how to think and act, one must bring together, from various knowledge sources, an appropriate ensemble of information suited to the particular understanding or problem-solving needs of the situation at hand. Again, this is because many areas of knowledge have too diverse a pattern of use for single prescriptions stored in advanced, to cover enough of the cases that will need to be addressed (Spiro et al. 1991, 27-28). In view of this, a new element of constructive processing, the flexible use of preexisting knowledge, has been added to Cognitive Flexibility Theory. Spiro et al. (1991, 28) claim that this "new constructivism" is doubly constructive because: (1) understandings are constructed by using prior knowledge to go beyond the information given; and (2) the prior knowledge that is brought to bear is itself constructed, rather than retrieved intact from memory, on a case-by-case basis. Spiro et al. (1991, 28) argue that cognitive flexibility theory "is an integrated theory of learning, mental representation, and instruction" and is aimed specifically at the special requirements "for attaining advanced learning goals, given the impediments associated with ill-structured features of knowledge domains" and with their findings about specific deficiencies in advanced learning. Spiro and Jehng (1990, 168) state that the basic metaphor of Cognitive Flexibility Theory is the "criss-crossed" landscape. A landscape is a complex structure and one would be exposed only to a small amount of its detail in a single walk through it. If, however, the landscape was traversed a number of times in different directions, more and more information would be gathered about it. Spiro and Jehng use this metaphor in Cognitive Flexibility Theory, and state that: One learns by criss-crossing conceptual landscapes; instruction involves the provision of learning materials that channel multidimensional landscape explorations under the active initiative of the learner (as well as providing expert guidance and commentary to help the learner to derive maximum benefit from his or her explorations); and knowledge representations reflect the criss-crossing that occurred during learning. By criss-crossing the "conceptual landscape", a highly interconnected web-like knowledge structure can be constructed, and, Spiro and Jehng (1990, 170) claim that this structure has the potential to be used in problem solving or comprehension and "The likelihood that a highly adaptive schema can be assembled to fit the particular requirements for understanding or acting in the situation at hand is increased". This means that there is an increased range of situations to which this knowledge can be transferred. Spiro and Jehng argue that this flexibility is essential for learning in an ill-structured domain. They state that: Because one cannot have a prepackaged knowledge structure for every situation that might be encountered, the emphasis must shift from intact schema retrieval to flexibility of situation-specific schema assembly. By criss-crossing a conceptual landscape in many directions, knowledge that will have to be used in many ways is taught in many ways (1990, 170-171). As Cognitive Flexibility Theory emphasises the fact that material is continually represented in rearranged instructional sequences and from different conceptual view points, Spiro and Jehng (1990, 171) argue that the most appropriate delivery medium is a computer system which has random access delivery capabilities with a videodisc being an example. Cognitive Flexibility Theory can act as the "antidote" to the different types of learning failure associated with advanced learning in ill-structured domains when traditional instructional strategies are employed. Spiro and Jehng justify this claim by stating that: If typical approaches have overlinearised, one can construct nonlinear presentations. If material has been presented from just one point of view, one can re-present it from different points of view. Cases that have been slotted in a rigid hierarchical structure can be repeatedly re-presented to attain heterarchical or montage-like structural representations. If partially overlapping exemplars have been indiscriminately lumped under one category in a way that causes important differences among them to be missed, one can demonstrate the diversity amongst the similarity. Or, if exemplars that partially overlap in important ways have been separated into different conceptual categories, the similarity amongst the diversity can be demonstrated. If aspects of knowledge have been overly compartmentalised, their insularity can be overcome by joint presentation. If decomposed elements are not additively assemblable, they can be reassembled with a more complex combinatory logic. If an old example/case is employed too monolithically as a precedent for a new one, you can decompose examples and then recombine aspects of different examples to achieve the most accurate (the most closely fitting) set of multiple precedents for understanding in a new situation (1990, 171). Spiro and Jehng (1990, 171) call the computer based instructional materials based on Cognitive Flexability Theory Cognitive Flexibility Hypertexts. To illustrate the use of such a hypertext, Spiro and Johng (1990, 173-180) describe "Exploring Thematic Structure in Citizen Kane" (or KANE for short). This is an experimental hypertext based on the film Citizen Kane. At the time of writing, it did not attempt to teach about the entire film, rather was concentrated on the characteristics of Kane. As this type of hypertext is designed for advanced learners, students are expected to be familiar with the film having viewed it one or more times and to have been thoroughly introduced to the main themes before using the hypertext. The film is viewed from the perspective of ten different major themes. The video material itself is divided into 25 mini-cases or scenes which range in length from 30 to 90 seconds. Each of these scenes can be viewed in the context of the different themes. For example, Spiro and Jehng (1990, 177) describe a scene and then explain how it is interpreted from the perspective of some of the themes. The themes identified were: The outsize Ambition theme and its Grandeur/Sweep and Egomania sub-themes. Power theme ("Control others by their dependence on you" sub-theme). The Fallibility/Morality sub-theme of Outsized Ambition theme. The Hollow Man theme illustrating the Lifelessness sub-theme. By viewing these different facets of Kane's character, students should obtain a much fuller picture of him than would have been gained by viewing the film in its original, linear form. Spiro et al. (1991, 32) conclude by stating: ... we consider our work to be moving towards a systematic theory of hypertext design to provide flexible instruction appropriate for developing cognitive flexibility. ... We are encouraged so far about the robustness, systematically, and generality of our hypertext design principles, in that they have been applied in very similar ways to develop hypertext prototypes in domains as diverse as cardiovascular medicine, literary interpretations, and military strategy. Preliminary data on the effectiveness of these Cognitive Flexibility Hypertexts is also encouraging. They state that research has indicated that Cognitive Flexibility Hypertexts promote superior transfer to new problem solving situations than did a design which emphasised the mastery of declarative knowledge.

	Conclusion

	A great advantage ofCognitive Flexibility Theory is that it has been devised especially to be used with hypertext. From the point of view of constructing mental models, this theory would appear to be very appropriate as its use would result in the formation of a very complete, well linked model. The only difficulty with it is finding ways of 'criss-crossing' the subject material. In the example of KANE, this is done in a very logical way, but how could this be applied to a topic, for example, in science?


	Server: http://scs.une.edu.au Author: Tony Brown Created: 25.6.97 © The University of New England, NSW, Australia