The internal representation of the learners can echo the external reality, which asserts a position of objectivism that the mind can stand separate and independent from the body. Thus, knowledge can be transferred from the outside of the mind into the inside of the mind. knowledge is transferred from the outside of the mind into the inside of the mind. Wilson and Meyers (2000) illustrate such a position pretty well by indicating its impact on instructional design that "Instructional designers could now think of learning in terms of taking experts' cognitive structures and mapping that knowledge into the heads of learners. The degree of similarity in cognitive structure between expert and novice was a good measure of whether learning objectives were being met." However, the internal representation of learners can also be regarded as a subjective construction of integrating incoming information and the existing knowledge structures, which entails a position of constructivism that knowledge cannot exist independently from the knower.

The central issues that interest cognitive psychologists include the internal mechanism of human thought and the processes of knowing. Cognitive psychologists have attempted to find out the answers to mental structures, such as what is stored and how it is stored, and to mental processes concerning how the integration and retrieval of information is operated. The theoretical assumptions in cognitive psychology lend instructional systems a hand in the design of efficient processing strategies for the learners to acquire knowledge, e.g. mnemonic devices to reduce the workload of the short-term memory, rehearsal strategies to maintain information, and the use of metaphors and analogies to relate meaning of the new information to prior knowledge.

Theoretical Foundations
The date cited as marking the beginning of psychology as a science is 1879, when Wilhelm Wundt established the first psychology laboratory in Leipzig, Germany. Introspection, the method of inquiry used by Wundt, is claimed to be a cognitive approach, since it is a tool of self-observation to examine the working of the mind. Winn and Snyder (1996) claimed that Wundt's methodological contribution was "the development of introspection as a means for studying the mind". Many ideas and assumptions of cognitive psychology can be traced back to the early decades of twentieth century, i.e. Gestalt psychology, Edward Tolman's cognitive learning (1932), and Jean Piaget's cognitive development theory.

Anderson (1985) lists three main influences for the modern development of cognitive psychology:

1. Information processing approach: Broadbent's information (1958) processing model gives consideration to perception and attention. The important characteristic of an information-processing analysis is that it involves a tracing of the sequence of mental operations and their products in the performance of a particular cognitive task
2. Artificial Intelligence: Allen Newell and Herbert Simon's work in cognitive psychology has promoted use of concepts from computer science in the development of psychological theories.
3. Linguistics: Noam Chomsky asserted that language learning must include internal constructs. A theory that only considers the observable stimuli and responses in linguistic interaction is not sufficient.
   

Gestalt Psychology
Gestalt Psychologists believed that knowledge comes from more than just experience; it also involves the knower actively imposing organization on sensory data.

Kohler (1925, The Mentality of Apes) proposed that behavior could not be explained by the principles of association alone. He proposed that there was an inner process that enabled the apes to grasp the structure of a situation, in which learners recognized the interconnection based on the properties of things themselves. Learning, therefore, does not occur in a regular, continuous way from a pattern of trial and error. Instead, learning occurs with a realization of a new relationship, 'the insight experience'.

Information Processing Approach
The advent of the modern digital computer provided a rich theoretical metaphor for theorizing about human information processing. The information processing architecture of computers strongly framed much early thinking in modern cognitive psychology.
Cognitive psychologists have spent a lot of effort developing accounts of mechanisms that control information processing (Barsalou, 1992). The cognitive theories propose constructs describing information processing mechanisms. The questions about how humans process information, pick up information from the environment, store information in memory, retrieve information from memory, and send information back to the environment are under investigation. People, like computers, acquire information from the environment. Both people and computers store information and retrieve it when applicable to current tasks; both are limited in the amount of information they can process at a given time; both transform information to produce new information; both return information to the environment. Research projects frequently aim at verifying and articulating this theoretical perspective (Atkinson & Shiffrin, 1968; Broadbent, 1958; Newell & Simon, 1972).

Broadbent (1958) proposed a general model of the human information-processing system. This information processing model presented the basic mechanisms: three main memory storages in which the information is operated on, and the processes of transforming the information from input to output within each storage and from output to input between these storages. The model suggested that the processing is a fixed serial order from one memory storage to the next, and voluntary control of the system was represented by a selective-attention device and by information feedback loops from the high-level processing system to earlier processing stages.

The most widely accepted theory is labeled the "stage theory," based on the work of Atkinson and Shriffin, 1986). The stage model assumes that the brain embodies a nervous system that processes the information from the time of the input to the time of storage in long-term memory. The system comprises three main stages that contain different physiological properties: the sensory registers, short-term memory and long-term memory.

The sensory registers briefly store representations of external stimuli from the environment until the information can be transferred further. There appears to be different sensory registers for each sense. In any case, the sensory registers can hold information for only a very brief period of time. The information is assumed to be lost from the registers unless it is passed along into short-term memory.

Short-term memory can be thought of as conscious memory because, in addition to holding information, it allows information to be manipulated, interpreted and transformed. The new information in short-term memory, by subjection to further processing, may be transferred to and made part of long-term memory.
Long-term memory is a relatively unlimited and permanent repository of information. Long term memory stores for later use of information. Once the information is stored in the long-term memory, it stays.

The information processing model highlights the basic mechanisms in terms of stages and the processes, and the representation and storage of information:

1. Three main stages in which the information is operated on: sensory memory, short-term memory (temporary working memory), and long-term memory
2. The processes of transforming the information from input to output within each stage and from output to input between these stages, e.g. attention/pattern recognition, encoding and retrieval.
3. Representation and storage of information, e.g. network models (Collins and Quillian, 1969), Feature Comparison Models (Smith, Shoben, and Rips, 1974); Propositional Models (Klatzky, 1980; Anderson, 1976); Parallel Distributed Processing Models (McClelland, Rumelhart, and the PDP research group, 1986); Duel Coding Models (Pavivio?)
   

Major Theories
I am interested in the following cognitive theories:

• Piaget's Cognitive Development
• John Anderson's ACT-R theory
• Schema Theory

Piaget's Cognitive Development

Piaget's theory intends to explain the following phenomena:

1. What are the psychological states that children pass through at different points in their development?
2. What are the mechanisms by which they pass from one state to another? How do changes in children's thinking occur?
   

Piaget (1970) proposed that children progress through an invariant sequence of four stages: sensormotor, pre-operational, concrete operational and formal operational. Those stages are not arbitrary, but are assumed to reflect qualitative differences in children's cognitive abilities. Being controlled by the logical structures in the different developmental stages, learners cannot be taught key cognitive tasks if they have not reached a particular stage of development.

Also, Piaget (1985) suggested that learning process is iterative, in which new information is shaped to fit with the learner's existing knowledge, and existing knowledge is itself modified to accommodate the new information. The major concepts in this cognitive process include:

• Assimilation: it occurs when a child perceives new objects or events in terms of existing schemes or operations. Children and adults tend to apply any mental structure that is available to assimilate a new event, and they will actively seek to use a newly acquired structure. This is a process of fitting new information into existing cognitive structures
• Accommodation: it has occurred when existing schemes or operations must be modified to account for a new experience. This is a process of modifying existing cognitive structures based upon new information.
• Equilibration: it is the master developmental process, encompassing both assimilation and accommodation. Anomalies of experience create a state of disequilibrium which can be only resolved when a more adaptive, more sophisticated mode of thought is adopted.
  

Piaget's conception of equilibration (1985) implied a dynamic construction process of human's cognitive structure. There is no structure apart from construction because the being of structure "consists in their coming to be, that is, their being 'under construction'".

Anderson's ACT-R Theory

Anderson's ACT-R system is a unitary theory of cognition. The theory has origins in the human associative memory (HAM) theory of human memory (Anderson & Bower, 1973). It also borrows ideas from Newell and Simon's symbolic framework (1973). The ACT-R theory started first as an ACT production system, presented by Anderson in 1976. The ACT production system proposed a distinction between procedural knowledge and declarative knowledge. In 1983, Anderson provided a fuller description of the ACT and developed a theory called ACT*. Integrated with a set of neurally plausible assumptions about how production might be acquired, the ACT* theory was evolved into the ACT-R (Atomic Components of Thought) theory (1993), in which an architecture of cognition is modeled to explain how the process of acquisition can be tuned to the statistical structure of the environment.

In ACT-R, the current goal acts as a filter to select relevant productions. There are two long-term memory stores: a declarative and a procedural memory (Anderson & Lebiere, 1998). The knowledge in the declarative memory, i.e., facts and goals, is represented in terms of chunks. At the symbolic level, chunks are structured as a semantic network. On the other hand, the knowledge in the procedural memory is represented as production rules in forms of condition-action pairs, in which the flow of control passes from one production to another when the actions of one production create the conditions needed for another production to take place. It is these production systems that provide the basis for a unitary theory of cognition. The selected production and the current goal will influence together the retrieval of information via their connections to declarative memory. Finally, the contents of retrieved nodes are used to update the current goal according to the production's action specification. Hierarchically organized goal structures are used to represent plans of action, and to control the course of cognitive processing.

Stages of Skill Acquisition
The ACT-R keeps with Fitt's three stages (1964) in the process of skill acquisition, which are the cognitive stage, associative stage and autonomous stage. The acquisition of a cognitive skill is a progressive process from cognitive stage to the autonomous stage, which, in terms of the ACT-R theory, is the transformation from declarative knowledge to procedural knowledge. The process starts with the interpretive application of declarative knowledge in the cognitive stage. Then it proceeds to compile declarative knowledge into production rules during the associative stage. Gradually the production, a set of condition-action rules, becomes increasingly fine-tuned. During the autonomous stage, the effort required by condition-action rules continually decrease.

1. Cognitive Stage:

   At the beginning of the process of skill acquisition, new information enters in declarative form. In this stage, learners learn about a set of facts relevant to the skills, such as descriptions of the procedure. The knowledge of how to carry out a procedure is declarative, as step-by-step performance statements. At this point the learners generate actions through interpretations of the verbal statements, and carefully monitor the results of the actions when they carry out each step of the procedures. The processing in this stage is conscious, deliberate, slow and requires full attention.

2. Associative Stage:

   The major development of this stage is knowledge compilation. The compilation process is aimed to produce successful procedures in order to speed up the execution of procedures, drop the verbal rehearsal and eliminate piecemeal application. During the associative stage, we have in the process of composition and proceduralization a means of converting declarative facts into production form. Composition is the process of organizing a series of actions together into a unified production. This produces considerable speedup by composing sequences of steps into one single action. Also, once the skill is proceduralized, the new integrated production no longer requires the domain specific declarative information to be retrieved into working memory. An important consequence of proceduralization is that it reduces the load on working memory, and thus achieves a great deal of efficiency.

3. Autonomous Stage:

   After a skill has been compiled into a task-specific procedure, the learning process involves an improvement in the search for the right production. In this stage, the procedure becomes more and more automated and rapid. The process underlying this stage is tuning. Three learning mechanisms serve as the basis of tuning: generalization, discrimination, and strengthening.

   The basic function of the generalization process is to extract from different productions what they have in common. The generalization process produces broader production rules in their range of applicability. It facilitates the transfer of knowledge in a novel situation. On the contrary, the discrimination process produces narrow production rules. The discrimination process restricts the ranges of application of productions to the appropriate circumstances. It helps identify specific conditions and multiple variants on the conditions controlling the same action. The discrimination process facilitates the development of powerful, domain specific productions. Moreover, the specificity of the condition statements can help resolve conflicts.

   In this stage, learners are also getting better at selecting appropriate production in a particular context. The criterion of selection is degree of strength. Each production has a strength that reflects the frequency with which the production has been successfully applied.
   

Computational processing in ACT-R
The ACT-R is not only a theory that addresses knowledge acquisition. It has also developed an explanation to the question of how people select the appropriate knowledge in a particular context (Anderson, 1995). Using the rational analysis, the ACT-R theory claim (Anderson, 1995) that the mind determines what knowledge is available according to its odds of being used in a particular context. In fact, the mind implicitly performs a Bayesian inference to calculate these odds by keeping track of general usefulness and combining this with contextual appropriateness (Anderson, 1990). The basic equation is as follows:
Activation-level = Base-level + Contextual Priming

The main implication of this equation is that the accessibility of certain information is determined by both its past use and its relevance to the current goal.

Production Compilation
In ACT-R 4.0 production compilation, the production rule is created immediately upon popping the dependency goal - hence at zero delay. So, the need is eliminated to maintain the declarative information.

• There are chunks of type DEPENDENCY and represent a person's understanding of a particular step in a problem-solving episode.
• A dependency is created when a person sets a goal t understand a bit of an example or instruction
• When this dependency goal is popped, a production rule is induced form the dependency and added to the production system.
• Four special slots of the dependency structure: goal slot (holding what the goal was like before the problem solving step); constraints slot (holding chunks that serve as the bridges from condition to action and becoming retrieval patterns in the compiled rule); modified slots (holding what changed goal look like); stack slot (indicating any changes to the goal stack in terms of pushes and pops)
  

Schema Theory

Bartlett first introduced the notion of schema as early as 1932 in order to explain why people reconstructed a story when recalling it so as to make more sense of it in terms of their own knowledge and experience. According to Bartlett, the story is assimilated to pre-stored schemata based on previous experience. Rumelhart (1980) defined a schema as "a data structure for representing the generic concepts stored in memory. In other words, schema is an "organizing and orienting attitude that involves active organization of past experience" (Driscoll, 2000). Modern versions of schema theory incorporate many of Bartlett's ideas. For example, Shank and Abelson's concept of scripts (1977) proposed that such event schemata could be organized into a temporally ordered sequence of events. Alba and Hasher (1983) examined all schema theories and identified four major processes: selection, abstraction, interpretation, and integration. It explicitly illustrates how memory and comprehension operate.

One of the central issues that cognitive psychologists are interested in is mental structure. According to schema theory, the knowledge we have stored in memory is organized as a set of schemata or mental representations, each of which incorporates all the knowledge of a given type of object or event that we have acquired from past experience.

Schema theory provides an account to the knowledge structure and emphasizes the fact that what we remember is influenced by what we already know. Schemata facilitate both encoding and retrieval. Moreover, the mental structures are active. Memory can be reconstructed through the integration of current experience with prior knowledge. In other words, schemata represent an active process and can change over time as a result of new experiences and learning.

There are two information resources: the incoming from the outside world and information already stored in memory. The analysis of the sensory information coming in from the outside is known as bottom-up processing or data-driven processing because it relies on the data received via the senses. The information already stored in the memory in the form of prior knowledge influences our expectations and helps us to interpret the current input. This influence of prior knowledge is known as top-down or conceptual-driven processing. Schemata operate in a top-down direction to help us interpret the bottom-up flow of information from the world. Research on functions of the schema focused on the impact of prior knowledge on comprehension and memory (Driscoll, 2000).

Characteristics of schema
Rumelhart and Norman (1983) list five characteristics of schema:

1. Schema represents knowledge of all kinds from simple to complex.
2. Schema can be linked together into related systems.
3. A schema has slots which may be filled with fixed, compulsory values or with variable, optional values.
4. Schema incorporates all the different kinds of knowledge we have accumulated, including both generalizations derived from our personal experience and facts we have been taught.
5. Various schemata at different levels may be activity engaged in reorganizing and interpreting new inputs.

Winn and Snyder (1996) also described the characteristics of a schema as follows:

• Schema as Memory Structure: schema contains the sum of knowledge of the world from different aspects of the environment
• Schema as Abstraction: Schema exists at a higher level of generality than our immediate experience with the world.
• Schema as Network: Schema consists of concepts that are linked together in a proposition.
• Schema as Dynamic Structure: Schema is dynamic, amenable to change by general experience or through instruction, assimilation, and accommodation.
• Schema as Context: Schema provides a context for interpreting new knowledge as well as a structure to hold it.

The processes of schema acquisition and modification
Three different processes have been proposed to account for changes in existing schemata and the acquisition of new schemata due to learning (Rumbelhart and Norman, 1978):

1. Accretion: information is remembered that was instantiated within a schema as a result of text comprehension or understanding of some events.
2. Tuning: Tuning occurs when existing schemata evolve to become more consistent with experience.
3. Reconstructing: It involves the creation of entirely new schemata which replace or incorporate old ones.
   

Theory into Practice: The influence to Instructional Systems Design

Information Processing Theory to ISD

Two key assumptions in information processing theories have great influence in the formulation of instructional principles:

• The memory system is an active organized processor of information
  1. Research studies in attention and perception, such as the pattern recognition filter models of attention, and dual coding theory, have great impacts on the instructional message design both in text and visual message in order to maximize the attention and perception of the learners.
  2. Studies in the characteristics of short-term memory, such as limited space and short duration, give rise to the importance of mnemonic devices to reduce the workload of the short-term memory, information organization in chunks or smaller components to increase capacity. Also, the information processing models proposes the use of rehearsal strategies to maintain information, and content organization, such as elaboration theory, to help encode information by relating incoming information to concept and ideas already in memory.
  3. Theoretical explanations on the retention in long-term memory emphasize the effects of different conditions on levels of processing. Meaningful encoding facilitates later retrieval. Graphic representations have been particular effective in facilitating encoding and memory storage of information
• Prior knowledge plays an important role in learning
  1. The influence is evidenced by the use of advance organizers and any instructional strategies to strengthen activation of the existing memory structure. . Elaboration strategy and Ausbel's meaningful learning employed in instructional design systems suggests the importance of relating meaning of the new information to each individual learner. Also, the use of the metaphors and analogies provides instructional effectiveness.
  2. Emphasize the importance of self-regulatory skills in learning: conscious reasoning and thought

Moreover, with the development of information processing view of learning, the task can be examined from the perspective of human thought process. The cognitive operations that a learner needs to carry out in order to complete a task or to solve a problem become the target of analysis. Information processing task analysis uses flowcharts to represent cognitive operations step by step and indicate the decision making process (Scandura, 1973; Merrill,1976).

The conceptualization of an active memory system put a lot of attention on the operation of information. The focus is on what and how this system is related to learning and cognition. In this framework, a lot of different hypotheses are proposed to explain different types of memory systems, the representation/structure of knowledge in memory, and how these representations influence and interact with incoming information. In turn, those hypotheses provide implications on how to control the instructional conditions. The assumption is that the correspondence between the instructional conditions and the internal conditions of this active memory system will maximize the effectiveness of the instruction.

Piaget's cognitive development to ISD

Piaget's theory has the following impacts on learning and instruction:

• The learning environment should support the activity of the child: children acquire knowledge through their actions, and thinking is considered to be action-based. Thus, a learning environment should be created that encourages children to initiate and complete their own activities.
  1. An active, discovery-oriented environment
  2. Feedback from the actions; there should be concrete manipulable material
  3. Active self-discovery: play effectively represents all of the requisite characteristics of Piagetian-inspired instruction
• Children's interactions with their peers are an important source of cognitive development: peer interactions are essential in helping children move beyond egocentric thought.
• Adopt instructional strategies that make children aware of conflicts and inconsistencies in their thinking: equilibration, i.e. children must experience disequilibrium, or an imbalance between their current cognitive structures and new information to be assimilated, in order for them to move to a new stage of development.
  1. Use problems to confront student's prior knowledge structure
  2. Use Socratic dialogue to help learners to bring out misconceptions and faulty reasoning
  3. Criticality of diagnosing what children already know and how they think. Content is not introduced until the child is cognitively ready to understand it.
  4. Questions or experience designed to induce conflict will only be effective when the logical structures on which they depend have been or are being developed

ACT*R to Instructional Systems Design

This system now serves as a computer simulation tool for a research community. Scholars have created intelligent tutors, computer-based instructional systems, to teach cognitive skills based on the production system.

The stage analysis of human learning gives an account of the development of expertise. The implications to instructional strategies are the power of the practice and the explicit rule-based instruction.

The ACT-R theory also provides two primary mechanisms controlling working memory: spreading source activation and decaying base-level activation. These theoretical assumptions emphasize the strategy of rehearsal in learning facts and the learning-by-doing strategy in procedural knowledge acquisition.

• Task Analysis

  The ACT-R theory, as analysis of the performance of a cognitive skill but also an analysis of its acquisition, provides a framework to analyze the knowledge and skills that a learner must develop in order to perform tasks. It illustrates the importance of the goals and intentions on the determination of what is learned. The GOMS (Goals-Operated-Method-Selection) model corresponds to the characteristics of the goal-driven and rule-based learning mechanism described in the ACT-R theory. The model analyzes the goals, operators, methods, and selection rules for a specific task by breaking down the task into a meaningful series of goals and subgoals.

• Problem-Solving Process

  The ACT-R theory claims that the basic control architecture across different learning situations is hierarchical, goal-structured, and organized for problem solving (Anderson, 1982). It models the essential processes of problem solving: identifying the goal structure of the problem space, and analyzing the contextual information. The instructional implications of this model include learning via the context of problem solving, and immediate feedback to learners.

• Analogy

  The analogy mechanism involved the following steps:

  1. At some point in time, a declarative knowledge structure was created to represent the understanding of a step in a problem solving
  2. At another point in time, when a similar problem-solving state was reached, this declarative structure could be retrieved and used as a basis for analogy. Two searches are evoked: source of the analogy, and making correspondence between the past example and current example
  3. Analogy was an architectural primitive that created a production rule to represent ACT-R's understanding how the example applied to the current situation. This production rule was then available for later use if needed without re-analogy.
     
  4. If a production rule was not strong enough to fire, it had to be re-analogized. It would be strengthened and eventually become available.

Schema Theory to Instructional Systems Design

• The reconstructive memory proposed in schema theory gives emphasis to the encoding process and the importance of activation of the prior knowledge in learning. The instruction design should focus on the development of an instructional method to facilitate the process of organizing schematic structures, and to make meaningful connections between what the learners know and what they are to learn.
• Design should focus on:
  1. Providing a relevant context for learning in order to activate an existing schema
  2. Developing and applying techniques for students to use to impose structure on what they learn and thus make it more memorable, such as the use of information mapping, or advance organizer.
  3. Representing what the experts know in order to facilitate the learning process: Case-based reasoning, a formalism for knowledge representation, is used to model knowledge in intelligent tutoring systems. The design of the system focuses on the index of the expert stories. When students have problems, access to the stories can provide help.
  4. Making instructional material meaningful: Provide conceptual models invented by teachers, designers, scientists, or engineers to help make some target system understandable; identify learner's mental model.

   

References:

Anderson, J. R. (1982). Acquisition of cognitive skill. Psychological Review, 98 (4), p. 369-406.

Anderson, J. R. (1983). The architecture of cognition. Cambridge, MA: Harvard University Press.

Anderson, J. R. (1985). Cognitive psychology and its implications. 2nd Ed. New York: Freeman.

Anderson, J.R. (1996). ACT: A simple theory of complex cognition. American Psychologist, 51 (4), 355-365.

Atkinson, R. L., & Shriffrin, R. M. (1968). Human memory: A proposed system and its control processes. In K. W. Spence & J. T. Spence, (Eds.), The psychology of learning and motivation: Advances in research and theory, Vol. 2. New York: Academic.

Drisoll, M. P.( 2000). Psychology of learning for instruction. 2nd. Needham Heights, MA: Allyn and Bacon.

Piaget, J. (1970). Genetic epistemology. (E. Duckworth, Trans.). New York: Columbia University Press.

Piaget, J. (1985). The equilibration of cognitive structures. Chicago, IL: University of Chicago Press.

Rumelhart, D.E., & Norman, D. A. (1981). Analogical processes in learning. In J. R. Anderson, (Ed.), Cognitive skills and their acquisition. Hillsdale, NJ: Erlbaum.

Shank, R. C., & Abelson, R. (1977). Scripts, plans, goals and understanding. Hillsdale, NJ: Elbarum.

Winn, W., & Snyder, D. (1996). Cognitive Perspectives in Psychology. In D. H. Jonassen (Ed.), Handbook of Research for Educational Communications and Technology (pp. 112-142). New York: Macmillan.