Criterion Referenced Instruction (R. Mager)

Overview:

The Criterion Referenced Instruction (CRI) framework developed by Robert Mager is a comprehensive set of methods for the design and delivery of training programs. Some of the critical aspects include: (1) goal/task analysis -- to identify what needs to be learned, (2) performance objectives -- exact specification of the outcomes to be accomplished and how they are to be evaluated (the criterion), (3) criterion referenced testing -- evaluation of learning in terms of the knowledge/skills specified in the objectives, (4) development of learning modules tied to specific objectives.

Training programs developed in CRI format tend to be self-paced courses involving a variety of different media (e.g., workbooks, videotapes, small group discussions, computer-based instruction). Students learn at their own pace and take tests to determine if they have mastered a module. A course manager administers the program and helps students with problems.

CRI is based upon the ideas of mastery learning and performance-oriented instruction. It also incorporates many of the ideas found in Gagne's theory of learning (e.g., task hierarchies, objectives) and is compatible with most theories of adult learning (e.g., Knowles, Rogers) because of its emphasis on learner initiative and self-management.

Scope/Application:

Criterion referenced instruction is applicable to any form of learning; however, it has been applied most extensively in technical training including troubleshooting.

Example:

CRI has been applied to a workshop that Mager gives about CRI. The workshop consists of a series of modules (mostly print materials) with well-defined objectives, practice exercises, and mastery tests. Participants have some freedom to choose the order in which they complete the modules, provided they satisfy the prerequisites shown on the course map. For example, in one module on Objectives, the student must learn the three primary components of an objective, recognize correctly formed objectives (practice exercises), and be able to draft correct objectives for specified tasks. This module has one pre-requisite and is the pre-requisite to most other modules in the course.

Principles:

1. Instructional objectives are derived from job performance and reflect the competencies (knowledge/skills) that need to be learned.

2. Students study and practice only those skills not yet mastered to the level required by the objectives.

3. Students are given opportunities to practice each objective and obtain feedback about the quality of their performance.

4. Students should receive repeated practice in skills that are used often or are difficult to learn.

5. Students are free to sequence their own instruction within the constraints imposed by the pre-requisites and progress is controlled by their own competence (mastery of objectives).

References:

Mager, R. (1975). Preparing Instructional Objectives (2nd Edition). Belmont, CA: Lake Publishing Co.

Mager, R. & Pipe, P. (1984). Analyzing Performance Problems, or You Really Oughta Wanna (2nd Edition). Belmont, CA: Lake Publishing Co.

Mager, R. (1988). Making Instruction Work. Belmont, CA: Lake Publishing Co.

Related Web Sites:

For more on the work of Mager, see:
http://www.cepworldwide.com/Bios/mager.htm
http://www.e-learningguru.com/articles/art3_4.htm

Conversation Theory (G. Pask)

Overview:

The Conversation Theory developed by G. Pask originated from a cybernetics framework and attempts to explain learning in both living organisms and machines. The fundamental idea of the theory was that learning occurs through conversations about a subject matter which serve to make knowledge explicit. Conversations can be conducted at a number of different levels: natural language (general discussion), object languages (for discussing the subject matter), and metalanguages (for talking about learning/language).

In order to facilitate learning, Pask argued that subject matter should be represented in the form of entailment structures which show what is to be learned. Entailment structures exist in a variety of different levels depending upon the extent of relationships displayed (e.g., super/subordinate concepts, analogies).

The critical method of learning according to conversation theory is "teachback" in which one person teaches another what they have learned. Pask identified two different types of learning strategies: serialists who progress through an entailment structure in a sequential fashion and holists who look for higher order relations.

Scope/Application:

Conversation theory applies to the learning of any subject matter. Pask (1975) provides an extensive discussion of the theory applied to the learning of statistics (probability).

Example:

Pask (1975, Chapter 9) discusses the application of conversation theory to a medical diagnosis task (diseases of the thyroid). In this case, the entailment structure represents relationships between pathological conditions of the thyroid and treatment/tests. The student is encouraged to learn these relationships by changing the parameter values of a variable (e.g., iodine intake level) and investigating the effects.

Principles:

1. To learn a subject matter, students must learn the relationships among the concepts.

2. Explicit explanation or manipulation of the subject matter facilitates understanding (e.g., use of teachback technique).

3. Individual's differ in their preferred manner of learning relationships (serialists versus holists).

References:

Pask, G. (1i975). Conversation, Cognition, and Learning. New York: Elsevier.

Background information about Pask can be found at http://www.venus.co.uk/gordonpask

Contiguity Theory (E. Guthrie)

Overview:

Guthrie's contiguity theory specifies that "a combination of stimuli which has accompanied a movement will on its recurrence tend to be followed by that movement". According to Guthrie, all learning was a consequence of association between a particular stimulus and response. Furthermore, Guthrie argued that stimuli and responses affect specific sensory-motor patterns; what is learned are movements, not behaviors.

In contiguity theory, rewards or punishment play no significant role in learning since they occur after the association between stimulus and response has been made. Learning takes place in a single trial (all or none). However, since each stimulus pattern is slightly different, many trials may be necessary to produce a general response. One interesting principle that arises from this position is called "postremity" which specifies that we always learn the last thing we do in response to a specific stimulus situation.

Contiguity theory suggests that forgetting is due to interference rather than the passage of time; stimuli become associated with new responses. Previous conditioning can also be changed by being associated with inhibiting responses such as fear or fatigue. The role of motivation is to create a state of arousal and activity which produces responses that can be conditioned.

Scope/Application:

Contiguity theory is intended to be a general theory of learning, although most of the research supporting the theory was done with animals. Guthrie did apply his framework to personality disorders (e.g. Guthrie, 1938).

Example:

The classic experimental paradigm for Contiguity theory is cats learning to escape from a puzzle box (Guthrie & Horton, 1946). Guthrie used a glass paneled box that allowed him to photograph the exact movements of cats. These photographs showed that cats learned to repeat the same sequence of movements associated with the preceding escape from the box. Improvement comes about because irrelevant movements are unlearned or not included in successive associations.

Principles:

1. In order for conditioning to occur, the organism must actively respond (i.e., do things).

2. Since learning involves the conditioning of specific movements, instruction must present very specific tasks.

3. Exposure to many variations in stimulus patterns is desirable in order to produce a generalized response.

4. The last response in a learning situation should be correct since it is the one that will be associated.

References:

Guthrie, E.R. (1930). Conditioning as a principle of learning. Psychological Review, 37, 412-428.

Guthrie, E.R. (1935). The Psychology of Learning. New York: Harper.

Guthrie, E.R. (1938). The Psychology of Human Conflict. New York: Harper.

Guthrie, E.R. & Horton, G.P. (1946). Cats in a Puzzle Box. New York: Rinehart.

Constructivist Theory (J. Bruner)

Overview:

A major theme in the theoretical framework of Bruner is that learning is an active process in which learners construct new ideas or concepts based upon their current/past knowledge. The learner selects and transforms information, constructs hypotheses, and makes decisions, relying on a cognitive structure to do so. Cognitive structure (i.e., schema, mental models) provides meaning and organization to experiences and allows the individual to "go beyond the information given".

As far as instruction is concerned, the instructor should try and encourage students to discover principles by themselves. The instructor and student should engage in an active dialog (i.e., socratic learning). The task of the instructor is to translate information to be learned into a format appropriate to the learner's current state of understanding. Curriculum should be organized in a spiral manner so that the student continually builds upon what they have already learned.

Bruner (1966) states that a theory of instruction should address four major aspects: (1) predisposition towards learning, (2) the ways in which a body of knowledge can be structured so that it can be most readily grasped by the learner, (3) the most effective sequences in which to present material, and (4) the nature and pacing of rewards and punishments. Good methods for structuring knowledge should result in simplifying, generating new propositions, and increasing the manipulation of information.

In his more recent work, Bruner (1986, 1990, 1996) has expanded his theoretical framework to encompass the social and cultural aspects of learning as well as the practice of law.

Scope/Application:

Bruner's constructivist theory is a general framework for instruction based upon the study of cognition. Much of the theory is linked to child development research (especially Piaget ). The ideas outlined in Bruner (1960) originated from a conference focused on science and math learning. Bruner illustrated his theory in the context of mathematics and social science programs for young children (see Bruner, 1973). The original development of the framework for reasoning processes is described in Bruner, Goodnow & Austin (1951). Bruner (1983) focuses on language learning in young children.

Note that Constructivism is a very broad conceptual framework in philosophy and science and Bruner's theory represents one particular perspective. For an overview of other Constructivist frameworks, see http://carbon.cudenver.edu/~mryder/itc_data/constructivism.html.

Example:

This example is taken from Bruner (1973):

"The concept of prime numbers appears to be more readily grasped when the child, through construction, discovers that certain handfuls of beans cannot be laid out in completed rows and columns. Such quantities have either to be laid out in a single file or in an incomplete row-column design in which there is always one extra or one too few to fill the pattern. These patterns, the child learns, happen to be called prime. It is easy for the child to go from this step to the recognition that a multiple table , so called, is a record sheet of quantities in completed mutiple rows and columns. Here is factoring, multiplication and primes in a construction that can be visualized."

Principles:

1. Instruction must be concerned with the experiences and contexts that make the student willing and able to learn (readiness).

2. Instruction must be structured so that it can be easily grasped by the student (spiral organization).

3. Instruction should be designed to facilitate extrapolation and or fill in the gaps (going beyond the information given).

References:

Bruner, J. (1960). The Process of Education. Cambridge, MA: Harvard University Press.

Bruner, J. (1966). Toward a Theory of Instruction. Cambridge, MA: Harvard University Press.

Bruner, J. (1973). Going Beyond the Information Given. New York: Norton.

Bruner, J. (1983). Child's Talk: Learning to Use Language. New York: Norton.

Bruner, J. (1986). Actual Minds, Possible Worlds. Cambridge, MA: Harvard University Press.

Bruner, J. (1990). Acts of Meaning. Cambridge, MA: Harvard University Press.

Bruner, J. (1996). The Culture of Education, Cambridge, MA: Harvard University Press.

Bruner, J., Goodnow, J., & Austin, A. (1956). A Study of Thinking. New York: Wiley.

More about Bruner can be found at:
http://www.infed.org/thinkers/bruner.htm
http://www.psy.pdx.edu/PsiCafe/KeyTheorists/Bruner.htm

Connectionism (E. Thorndike)

Overview:

The learning theory of Thorndike represents the original S-R framework of behavioral psychology: Learning is the result of associations forming between stimuli and responses. Such associations or "habits" become strengthened or weakened by the nature and frequency of the S-R pairings. The paradigm for S-R theory was trial and error learning in which certain responses come to dominate others due to rewards. The hallmark of connectionism (like all behavioral theory) was that learning could be adequately explained without refering to any unobservable internal states.

Thorndike's theory consists of three primary laws: (1) law of effect - responses to a situation which are followed by a rewarding state of affairs will be strengthened and become habitual responses to that situation, (2) law of readiness - a series of responses can be chained together to satisfy some goal which will result in annoyance if blocked, and (3) law of exercise - connections become strengthened with practice and weakened when practice is discontinued. A corollary of the law of effect was that responses that reduce the likelihood of achieving a rewarding state (i.e., punishments, failures) will decrease in strength.

The theory suggests that transfer of learning depends upon the presence of identical elements in the original and new learning situations; i.e., transfer is always specific, never general. In later versions of the theory, the concept of "belongingness" was introduced; connections are more readily established if the person perceives that stimuli or responses go together (c.f. Gestalt principles). Another concept introduced was "polarity" which specifies that connections occur more easily in the direction in which they were originally formed than the opposite. Thorndike also introduced the "spread of effect" idea, i.e., rewards affect not only the connection that produced them but temporally adjacent connections as well.

Scope/Application:

Connectionism was meant to be a general theory of learning for animals and humans. Thorndike was especially interested in the application of his theory to education including mathematics (Thorndike, 1922), spelling and reading (Thorndike, 1921), measurement of intelligence (Thorndike et al., 1927) and adult learning (Thorndike at al., 1928).

Example:

The classic example of Thorndike's S-R theory was a cat learning to escape from a "puzzle box" by pressing a lever inside the box. After much trial and error behavior, the cat learns to associate pressing the lever (S) with opening the door (R). This S-R connection is established because it results in a satisfying state of affairs (escape from the box). The law of exercise specifies that the connection was established because the S-R pairing occurred many times (the law of effect) and was rewarded (law of effect) as well as forming a single sequence (law of readiness).

Principles:

1. Learning requires both practice and rewards (laws of effect /exercise)

2. A series of S-R connections can be chained together if they belong to the same action sequence (law of readiness).

3. Transfer of learning occurs because of previously encountered situations.

4. Intelligence is a function of the number of connections learned.

References:

Thorndike, E. (1913). Educational Psychology: The Psychology of Learning. New York: Teachers College Press.

Thorndike, E. (1921). The Teacher's Word Book. New York: Teachers College.

Thorndike, E. (1922). The Psychology of Arithmetic. New York: Macmillan.

Thorndike, E. (1932). The Fundamentals of Learning. New York: Teachers College Press.

Thorndike, E. at al. (1927). The Measurement of Intelligence. New York: Teachers College Press.

Thorndike, E. et al. (1928), Adult Learning. New York: Macmillan

Relevant Web Pages:

For more about Thorndike and his work, see:

http://www.indiana.edu/~intell/ethorndike.shtml
http://www.psy.pdx.edu/PsiCafe/KeyTheorists/Thorndike.htm

Conditions of Learning (R. Gagne)

Overview:

Component Display Theory (CDT) classifies learning along two dimensions: content (facts, concepts, procedures, and principles) and performance (remembering, using, generalities). The theory specifies four primary presentation forms: rules (expository presentation of a generality), examples (expository presentation of instances), recall (inquisitory generality) and practice (inquisitory instance). Secondary presentation forms include: prerequisites, objectives, helps, mnemonics, and feedback.


The theory specifies that instruction is more effective to the extent that it contains all necessary primary and secondary forms. Thus, a complete lesson would consist of objective followed by some combination of rules, examples, recall, practice, feedback, helps and mnemonics appropriate to the subject matter and learning task. Indeed, the theory suggests that for a given objective and learner, there is a unique combination of presentation forms that results in the most effective learning experience.

Merrill (1983) explains the assumptions about cognition that underlie CDT. While acknowledging a number of different types of memory, Merrill claims that associative and algorithmic memory structures are directly related to the performance components of Remember and Use/Find respectively. Associative memory is a hierarchial network structure; algorithmic memory consists of schema or rules. The distinction between Use and Find performances in algorithmic memory is the use of existing schema to process input versus creating a new schema through reorganization of existing rules.

A significant aspect of the CDT framework is learner control, i.e., the idea that learners can select their own instructional strategies in terms of content and presentation components. In this sense, instruction designed according to CDT provides a high degree of individualization since students can adapt learning to meet their own preferences and styles.

In recent years, Merrill has presented a new version of CDT called Component Design Theory (Merrill, 1994). This new version has a more macro focus than the original theory with the emphasis on course structures (instead of lessons) and instructional transactions rather than presentation forms. In addition, advisor strategies have taken the place of learner control strategies. Development of the new CDT theory has been closely related to work on expert systems and authoring tools for instructional design (e.g., Li & Merrill, 1991; Merrill, Li, & Jones, 1991)

Scope/Application:
CDT specifies how to design instruction for any cognitive domain. CDT provided the basis for the lesson design in the TICCIT computer based learning system (Merrill, 1980). It also was the basis for the Instructional Quality Profile, a quality control tool for instructional materials (Merrill, Reigeluth & Faust, 1979).

Example:

If we were designing a complete lesson on equilateral triangles according to CDT, it would have the following minimum components:

Objective - Define an equilateral triangle (Remember-Use)
Generality - Definition (attributes, relationships)
Instance - Examples (attributes present, representations)
Generality Practice - State definition
Instance Practice - Classify (attributes present)
Feedback - Correct generalities/instances
Elaborations - Helps, Prerequisities, Context
If the generality was presented by an explanation or illustration, followed by practice examples, this would be an expository strategy (EG,Eeg). On the other hand, if the students were required to discover the generality on the basis of practice examples, this would be an inquisitory strategy (IG, Ieg).

Principles:

1. Instruction will be more effective if all three primary performance forms (remember, use, generality) are present.

2. Primary forms can be presented by either an explanatory or inquisitory learning strategy

3. The sequence of primary forms is not critical provided they are all present.

4. Students should be given control over the number of instances or practice items they receive.

References:

Li, Z. & Merrill, M.D. (1991). ID Expert 2.0: Design theory and process. Educational Technology Research & Development, 39(2), 53-69.

Merrill, M.D. (1980). Learner control in computer based learning. Computers and Education, 4, 77-95.

Merrill, M.D. (1983). Component Display Theory. In C. Reigeluth (ed.), Instructional Design Theories and Models. Hillsdale, NJ: Erlbaum Associates.

Merrill, M.D. (1987). A lesson based upon Component Display Theory. In C. Reigeluth (ed.), Instructional Design Theories in Action. Hillsdale, NJ: Erlbaum Associates.

Merrill, M.D. (1994). Instructional Design Theory. Englewood Cliffs, NJ: Educational Technology Publications.

Merrill, M.D., Li, Z. & Jones, M. (1991). Instructional transaction theory: An introduction. Educational Technology, 31(6), 7-12.

Merrill, M.D., Reigeluth, C., & Faust, G. (1979). The instructional quality profile: Curriculum evaluation and design tool. In H. O'Neil (ed.), Procedures for Instructional Systems Development. New York: Academic Press.

Relevant Web Sites:

For more about Merrill and his work, see:

http://cito.byuh.edu/merrill

Component Display Theory (M.D. Merrill)

Overview:

Component Display Theory (CDT) classifies learning along two dimensions: content (facts, concepts, procedures, and principles) and performance (remembering, using, generalities). The theory specifies four primary presentation forms: rules (expository presentation of a generality), examples (expository presentation of instances), recall (inquisitory generality) and practice (inquisitory instance). Secondary presentation forms include: prerequisites, objectives, helps, mnemonics, and feedback.


The theory specifies that instruction is more effective to the extent that it contains all necessary primary and secondary forms. Thus, a complete lesson would consist of objective followed by some combination of rules, examples, recall, practice, feedback, helps and mnemonics appropriate to the subject matter and learning task. Indeed, the theory suggests that for a given objective and learner, there is a unique combination of presentation forms that results in the most effective learning experience.

Merrill (1983) explains the assumptions about cognition that underlie CDT. While acknowledging a number of different types of memory, Merrill claims that associative and algorithmic memory structures are directly related to the performance components of Remember and Use/Find respectively. Associative memory is a hierarchial network structure; algorithmic memory consists of schema or rules. The distinction between Use and Find performances in algorithmic memory is the use of existing schema to process input versus creating a new schema through reorganization of existing rules.

A significant aspect of the CDT framework is learner control, i.e., the idea that learners can select their own instructional strategies in terms of content and presentation components. In this sense, instruction designed according to CDT provides a high degree of individualization since students can adapt learning to meet their own preferences and styles.

In recent years, Merrill has presented a new version of CDT called Component Design Theory (Merrill, 1994). This new version has a more macro focus than the original theory with the emphasis on course structures (instead of lessons) and instructional transactions rather than presentation forms. In addition, advisor strategies have taken the place of learner control strategies. Development of the new CDT theory has been closely related to work on expert systems and authoring tools for instructional design (e.g., Li & Merrill, 1991; Merrill, Li, & Jones, 1991)

Scope/Application:
CDT specifies how to design instruction for any cognitive domain. CDT provided the basis for the lesson design in the TICCIT computer based learning system (Merrill, 1980). It also was the basis for the Instructional Quality Profile, a quality control tool for instructional materials (Merrill, Reigeluth & Faust, 1979).

Example:

If we were designing a complete lesson on equilateral triangles according to CDT, it would have the following minimum components:

Objective - Define an equilateral triangle (Remember-Use)
Generality - Definition (attributes, relationships)
Instance - Examples (attributes present, representations)
Generality Practice - State definition
Instance Practice - Classify (attributes present)
Feedback - Correct generalities/instances
Elaborations - Helps, Prerequisities, Context
If the generality was presented by an explanation or illustration, followed by practice examples, this would be an expository strategy (EG,Eeg). On the other hand, if the students were required to discover the generality on the basis of practice examples, this would be an inquisitory strategy (IG, Ieg).

Principles:

1. Instruction will be more effective if all three primary performance forms (remember, use, generality) are present.

2. Primary forms can be presented by either an explanatory or inquisitory learning strategy

3. The sequence of primary forms is not critical provided they are all present.

4. Students should be given control over the number of instances or practice items they receive.

References:

Li, Z. & Merrill, M.D. (1991). ID Expert 2.0: Design theory and process. Educational Technology Research & Development, 39(2), 53-69.

Merrill, M.D. (1980). Learner control in computer based learning. Computers and Education, 4, 77-95.

Merrill, M.D. (1983). Component Display Theory. In C. Reigeluth (ed.), Instructional Design Theories and Models. Hillsdale, NJ: Erlbaum Associates.

Merrill, M.D. (1987). A lesson based upon Component Display Theory. In C. Reigeluth (ed.), Instructional Design Theories in Action. Hillsdale, NJ: Erlbaum Associates.

Merrill, M.D. (1994). Instructional Design Theory. Englewood Cliffs, NJ: Educational Technology Publications.

Merrill, M.D., Li, Z. & Jones, M. (1991). Instructional transaction theory: An introduction. Educational Technology, 31(6), 7-12.

Merrill, M.D., Reigeluth, C., & Faust, G. (1979). The instructional quality profile: Curriculum evaluation and design tool. In H. O'Neil (ed.), Procedures for Instructional Systems Development. New York: Academic Press.

Relevant Web Sites:

For more about Merrill and his work, see:

http://cito.byuh.edu/merrill

Cognitive Load Theory (J. Sweller)

Overview:

This theory suggests that learning happens best under conditions that are aligned with human cognitive architecture. The structure of human cognitive architecture, while not known precisely, is discernible through the results of experimental research. Recognizing George Miller's research showing that short term memory is limited in the number of elements it can contain simultaneously, Sweller builds a theory that treats schemas, or combinations of elements, as the cognitive structures that make up an individual's knowledge base. (Sweller, 1988)

The contents of long term memory are "sophisticated structures that permit us to perceive, think, and solve problems," rather than a group of rote learned facts. These structures, known as schemas, are what permit us to treat multiple elements as a single element. They are the cognitive structures that make up the knowledge base (Sweller, 1988). Schemas are acquired over a lifetime of learning, and may have other schemas contained within themselves.

The difference between an expert and a novice is that a novice hasn't acquired the schemas of an expert. Learning requires a change in the schematic structures of long term memory and is demonstrated by performance that progresses from clumsy, error-prone, slow and difficult to smooth and effortless. The change in performance occurs because as the learner becomes increasingly familiar with the material, the cognitive characteristics associated with the material are altered so that it can be handled more efficiently by working memory.

From an instructional perspective, information contained in instructional material must first be processed by working memory. For schema acquisition to occur, instruction should be designed to reduce working memory load. Cognitive load theory is concerned with techniques for reducing working memory load in order to facilitate the changes in long term memory associated with schema acquisition.

Scope/Application:
Sweller's theories are best applied in the area of instructional design of cognitively complex or technically challenging material. His concentration is on the reasons that people have difficulty learning material of this nature. Cognitive load theory has many implications in the design of learning materials which must, if they are to be effective, keep cognitive load of learners at a minimum during the learning process. While in the past the theory has been applied primarily to technical areas, it is now being applied to more language-based discursive areas.


Example:
In combining an illustration of blood flow through the heart with text and labels, the separation of the text from the illustration forces the learner to look back and forth between the specified parts of the illustration and the text. If the diagram is self-explanatory, research data indicates that processing the text unnecessarily increases working memory load. If the information could be replaced with numbered arrows in the labeled illustration, the learner could concentrate better on learning the content from the illustration alone. Alternatively, if the text is essential to intelligibility, placing it on the diagram rather than separated will reduce cognitive load associated with searching for relations between the text and the diagram (Sweller, 1999).

Principles:

Specific recommendations relative to the design of instructional material include:

1. Change problem solving methods to avoid means-ends approaches that impose a heavy working memory load, by using goal-free problems or worked examples.

2. Eliminate the working memory load associated with having to mentally integrate several sources of information by physically integrating those sources of information.

3. Eliminate the working memory load associated with unnecessarily processing repetitive information by reducing redundancy.

4. Increase working memory capacity by using auditory as well as visual information under conditions where both sources of information are essential (i.e. non-redundant) to understanding.



References:

Sweller, J., Cognitive load during problem solving: Effects on learning, Cognitive Science, 12, 257-285 (1988).

Sweller, J., Instructional Design in Technical Areas, (Camberwell, Victoria, Australia: Australian Council for Educational Research (1999).

ACT* (J. Anderson) - General Theory of Cognition

Overview:

ACT* is a general theory of cognition developed by John Anderson and colleagues at Carnegie Mellon Univeristy that focuses on memory processes . It is an elaboration of the original ACT theory (Anderson, 1976) and builds upon HAM, a model of semantic memory proposed by Anderson & Bower (1973). Anderson (1983) provides a complete description of ACT*. In addition, Anderson (1990) provides his own critique of ACT* and Anderson (1993) provides the outline for a broader development of the theory. See the CMU ACT site for the most up-to-date information on the theory.

ACT* distinguishes among three types of memory structures: declarative, procedural and working memory. Declarative memory takes the form of a semantic net linking propositions, images, and sequences by associations. Procedural memory (also long-term) represents information in the form of productions; each production has a set of conditions and actions based in declarative memory. The nodes of long-term memory all have some degree of activation and working memory is that part of long-term memory that is most highly activated.

According to ACT*, all knowledge begins as declarative information; procedural knowledge is learned by making inferences from already existing factual knowledge. ACT* supports three fundamental types of learning: generalization, in which productions become broader in their range of application, discrimination, in which productions become narrow in their range of application, and strengthening, in which some productions are applied more often. New productions are formed by the conjunction or disjunction of existing productions.

Scope/Application:
ACT* can explain a wide variety of memory effects as well as account for higher order skills such as geometry proofs, programming and language learning (see Anderson, 1983; 1990). ACT* has been the basis for intelligent tutors (Anderson, Boyle, Farrell & Reiser, 1987).

Example:
One of the strengths of ACT is that it includes both proposition and procedural representation of knowledge as well as accounting for the use of goals and plans. For example, here is a production rule that could be used to convert declarative sentences into a question:

IF the goal is to question whether the proposition (LVrelation LVagent LVobject) is true THEN set as subgoals

1. to plan the communication (LVrelation LVagent LVobject)

2. to move the first word in the description of LVrelation to the beginning of the sentence

3. to execute the plan

This production rule could be used to convert the sentence: "The lawyer is buying the car." into the question: "Is the lawyer buying the car?"

Principles:
1. Identify the goal structure of the problem space.

2. Provide instruction in the context of problem-solving.

3. Provide immediate feedback on errors.

4. Minimize working memory load.

5. Adjust the "grain size" of instruction with learning to account for the knowledge compilation process.

6. Enable the student to approach the target skill by successive approximation.

References:
Anderson, J. (1976). Language, Memory and Thought. Hillsdale, NJ: Erlbaum Associates.

Anderson, J. (1983). The Architecture of Cognition. Cambridge, MA: Harvard University Press.

Anderson, J. (1990). The Adaptive Character of Thought. Hillsdale, NJ: Erlbaum Associates.

Anderson, J. (1993). Rules of the Mind. Hillsdale, NJ: Erlbaum.

Anderson, J. & Bower, G. (1973). Human Associative Memory. Washington, DC: Winston.

Anderson, J., Boyle, C., Farrell, R. & Reiser, B. (1987). Cognitive principles in the design of computer tutors. In P. Morris (ed.), Modeling Cognition. NY: John Wiley.

Note: Many of Anderson’s articles are available from his CMU home page at http://act-r.psy.cmu.edu/people/ja

Cognitive Flexibility Theory (R. Spiro, P. Feltovitch and R. Coulson)

Overview:

Cognitive flexibility theory focuses on the nature of learning in complex and ill-structured domains. Spiro & Jehng (1990, p. 165) state: "By cognitive flexibility, we mean the ability to spontaneously restructure one's knowledge, in many ways, in adaptive response to radically changing situational demands...This is a function of both the way knowledge is represented (e.g., along multiple rather single conceptual dimensions) and the processes that operate on those mental representations (e.g., processes of schema assembly rather than intact schema retrieval)."

The theory is largely concerned with transfer of knowledge and skills beyond their initial learning situation. For this reason, emphasis is placed upon the presentation of information from multiple perspectives and use of many case studies that present diverse examples. The theory also asserts that effective learning is context-dependent, so instruction needs to be very specific. In addition, the theory stresses the importance of constructed knowledge; learners must be given an opportunity to develop their own representations of information in order to properly learn.

Cognitive flexibility theory builds upon other constructivist theories (e.g., Bruner, Ausubel, Piaget) and is related to the work of Salomon in terms of media and learning interaction.

Scope/Application:
Cognitive flexibility theory is especially formulated to support the use of interactive technology (e.g., videodisc, hypertext). Its primary applications have been literary comprehension, history, biology and medicine.

Example:
Jonassen, Ambruso & Olesen (1992) describe an application of cognitive flexibility theory to the design of a hypertext program on transfusion medicine. The program provides a number of different clinical cases which students must diagnose and treat using various sources of information available (including advice from experts). The learning environment presents multiple perspectives on the content, is complex and ill-defined, and emphasizes the construction of knowledge by the learner.

Principles:
1. Learning activities must provide multiple representations of content.

2. Instructional materials should avoid oversimplifying the content domain and support context-dependent knowledge.

3. Instruction should be case-based and emphasize knowledge construction, not transmission of information.

4. Knowledge sources should be highly interconnected rather than compartmentalized.

References:
Jonassen, D., Ambruso, D . & Olesen, J. (1992). Designing hypertext on transfusion medicine using cognitive flexibility theory. Journal of Educational Multimedia and Hypermedia, 1(3), 309-322.

Spiro, R.J., Coulson, R.L., Feltovich, P.J., & Anderson, D. (1988). Cognitive flexibility theory: Advanced knowledge acquisition in ill-structured domains. In V. Patel (ed.), Proceedings of the 10th Annual Conference of the Cognitive Science Society. Hillsdale, NJ: Erlbaum.

Spiro, R.J., Feltovich, P.J., Jacobson, M.J., & Coulson, R.L. (1992). Cognitive flexibility, constructivism and hypertext: Random access instruction for advanced knowledge acquisition in ill-structured domains. In T. Duffy & D. Jonassen (Eds.), Constructivism and the Technology of Instruction. Hillsdale, NJ: Erlbaum.

Spiro, R.J. & Jehng, J. (1990). Cognitive flexibility and hypertext: Theory and technology for the non-linear and multidimensional traversal of complex subject matter. D. Nix & R. Spiro (eds.), Cognition, Education, and Multimedia. Hillsdale, NJ: Erlbaum.

Relevant Web Sites:

For more on this work, see:
http://www.cogflextheory.org