| Cognitive psychologists challenge the limitations
of behaviorism in its focus on observable behavior. They incorporate mental
structure and process into their learning theories. Like behaviorists,
they engage more in the hypotheico-deductive scientific inquiry. The primary
focus of the research study in cognitive psychology emphasizes the internal
processes and structures processes inferred through the observation of
behavior. However, the focus on the mental structures and processes in
cognitive psychology does not explicitly indicate its philosophical position.
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.
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:
- 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
- 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.
- 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 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
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
- Three main stages in which the information is operated on: sensory
memory, short-term memory (temporary working memory), and long-term
- 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.
- 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?)
I am interested in the following cognitive theories:
Piaget's Cognitive Development
Piaget's theory intends to explain the following phenomena:
- What are the psychological states that children pass through at
different points in their development?
- 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
- 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
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.
- 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.
- 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.
- 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.
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)
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
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,
Characteristics of schema
Rumelhart and Norman (1983) list five characteristics of schema:
- Schema represents knowledge of all kinds from simple to complex.
- Schema can be linked together into related systems.
- A schema has slots which may be filled with fixed, compulsory values
or with variable, optional values.
- 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.
- 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
- 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):
- Accretion: information is remembered that was instantiated within
a schema as a result of text comprehension or understanding of some
- Tuning: Tuning occurs when existing schemata evolve to become more
consistent with experience.
- Reconstructing: It involves the creation of entirely new schemata
which replace or incorporate old ones.
Theory into Practice: The influence to Instructional
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
- 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.
- 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
- 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
- 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.
- 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,
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
- An active, discovery-oriented environment
- Feedback from the actions; there should be concrete manipulable
- 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.
- Use problems to confront student's prior knowledge structure
- Use Socratic dialogue to help learners to bring out misconceptions
and faulty reasoning
- Criticality of diagnosing what children already know and how
they think. Content is not introduced until the child is cognitively
ready to understand it.
- 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
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.
The analogy mechanism involved the following steps:
- At some point in time, a declarative knowledge structure was
created to represent the understanding of a step in a problem
- 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
- 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.
- If a production rule was not strong enough to fire, it had to
be re-analogized. It would be strengthened and eventually become
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:
- Providing a relevant context for learning in order to activate
an existing schema
- 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.
- 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.
- Making instructional material meaningful: Provide conceptual
models invented by teachers, designers, scientists, or engineers
to help make some target system understandable; identify learner's
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.