The Danish delegation of the NATO Training Working Group on
Individual Training and Education Developments.
COGNITIVE LEARNING THEORY
THE DANISH DELEGATION OF
THE NATO TRAINING WORKING GROUP
INDIVIDUAL TRAINING AND
1. The NATO Training Group Joint Services Sub-Group established the Working Group
on Training Technology in 1971 in order to foster the development and application of training technology within the armed forces of the members of the Alliance. The Working Group
in now normally known by its title: The NATO Training Group Working Group on Individual Training and Education Developments, abbreviated to (NTG WG/IT&ED). Included in
the Working Group’s terms of reference are responsibilities for promotion a common understanding of training philosophies and terminology, exchanging information on applications
of training technology, and reporting on the success of innovations.
2. Having accumulated considerable experience in the field, the Working Group decided
to compile a series of papers and publications on various aspects of training systematics and
technology. These documents are intended to summarise development and, where appropriate, to report on difficulties encountered and successes achieved and to offer advice and
3. It should be noted that the NTG WG/IT&ED produces two types of documents: Publications and Papers. Papers are documents covering a topic formally agreed by the Working
Group, but each has been written by an individual nation delegation and may reflect purely
national perceptions. However, Publications are formally agreed NTG WG/IT&ED documents and represent the combined view of all delegates. Furthermore, Publications will be
reviewed annually and updated when necessary and all additions and amendments remain
the responsibility of the NTG WG/IT&ED.
This document is a paper. First issue SEP 2003.
Cognitive learning theory and teaching.
In order to become a capable teacher it is necessary not only to be a subject expert. The
teacher also has to possess extensive knowledge of learning theories, including knowledge
of the way in which these theories are reflected in teaching principles and -methods.
How do teachers create situations in which students learn as much as possible at a minimum
oblivion? These questions will be dealt with during the next pages, including the following
The cognitive paradigm
Implementation of cognitive theories
How to store new information
How to retrieve new information
Since the early 1970s the growth in cognitive psychology has brought about a significant
change in learning theory as foundation of instructional design and teaching.
The behavioural learning theories - normally employed in instructional design models and
from which the most known teaching methods have been developed - are gradually giving
way to the cognitive paradigm. Therefore it is important for teachers and planners to be familiar with the cognitive theories.
The model presented here is based upon a basic idea firstly described by Robert D. Tennysson (1981,1990,1993). 1 The model has served as foundation of the modern instructional
design and teaching in the Danish Armed Forces.
The basic idea of the model is an addressing of acquisition as well as employment of
knowledge. In other words the model deals with how knowledge gets into the human brain,
how it is stored, and finally - which is most important - how to unearth knowledge again,
when necessary? The model also includes the interaction between the knowledge base and
so-called “cognitive abilities” and “thinking strategies”.
The human being is not regarded as a computer even if the brain can be compared to one.
The human being is in possession of emotions, which is not the case as far as the computer
is concerned. These emotions such as likes and dislikes, attitudes, fear and anxiety etc. are
normally described in the affective domain. The model also includes this domain.
The following is a brief description of the components and the interaction in the model (see
The components of the model include:
long-term memory, including knowledge base, cognitive abilities and thinking strategies.
Two sources of information: external- and internal information are included in the model.
The external information enters through the sensory receptors into the system as shown in
Annex and explained in the following.
But it is more interesting that the system itself is capable of creating knowledge based upon
internal information as a result of mutual interaction between components. Hereby new
It must be stressed that the model does not represent a conventional information-processing
system but a dynamic system with constant interaction/integration between components.
The cognitive paradigm 2
a. Sensory receptors
Information is conveyed through the sensory system (ears, eyes, nose and skin) and is passively registered.
Information in this area is easily interrupted and decays equally easy. Far more information
than can be processed and stored is registered in the executive control component entering
through the sensory receptors.
External stimuli include text materials, visuals, audio sources etc. and are very often processed in a rather unsystematic order. If the information is organised before hitting the sensory system, chances of getting into the memory system, in order to be used later, is assumed to be much greater.
The modern computer-based technology is taking the cognitive paradigm into consideration,
and presents information in a way that facilitates this processing.
b. Executive control
Information coming from either external or internal sources passes through the executive
control component, which includes perception, attention and resources.
The perception function performs the processes of being aware of and assessing the potential value of internal- and/or external information. The component services the system with
the purpose of directing attention and determining effort and cognitive resources for conscious action. It is the perception system that decides whether the information is being rejected or disposed of as not interesting, or is being processed further in the system.
The attention function maintains an active interaction with the processes associated with the
working memory component.
Resources mean mental resources or –capacity. Resources assist in the co-ordination of the
various components of the entire model.
Of importance in this functional evaluation is the effort associated with a given situation.
For example, in most situations, there is an abundance of resources available, so in the component determination is made on allocation of necessary resources to the actual situation.
This component controls the internal behaviour of the system by connecting or interfacing
the various components of the entire system.
Additionally, the executive control component controls the output of behaviour or action
ranging from automatic to deliberate, conscious activities.
c. Working memory
The term memory refers to one of the following: The store for information currently being
processed and a store for previously gathered (learned) information.
The first form is referred to as the working memory. This is rather limited in capacity and
information is subject to manipulation such as rehearsal, comparison, matching and reorganisation.
The working memory decides whether or not the information, which is processed in the system, is going to be stored in the long-term memory. If no efforts are made in order to store
information from the working memory, before new information enters, the previously received information is being rejected or “forgotten” due to the rather limited capacity of the
Firstly, the processes in the working memory are encoding processes, which in combination
with processes in the executive control component, deposit incoming information into the
working memory for later use.
Next, storage processes, which interact with the long-term memory for storing information,
are going on.
Finally, working memory performs retrieval processes providing existing knowledge from
the long-term memory when needed, and maintenance processes that keep information in
the working memory long enough to be stored in the long-term memory.
d. Long-term memory
The acquisition of knowledge and the means to employ knowledge occurs within the storage- and retrieval subsystems of the long-term memory component.
Within the storage system information is encoded into the knowledge base according to
various formats, while the retrieval subsystem uses cognitive abilities to employ knowledge.
The long-term memory has no capacity limits. Once stored, information will always remain
in the knowledge base.
The fact that people forget what they have learned does not mean that the information has
disappeared, but only indicates that retrieval processes are not working proberly.
Information is stored in a complex network of schemes, which vary individually in accordance with quantity, organisation, and accessibility of the individual knowledge.
The long-term memory contains the following types of knowledge: declarative-, procedural
and contextual knowledge.
Each type represents a different memory system component or function.
Declarative knowledge implies an awareness of knowledge and refers to the ”knowing
that”; for example, that underlining keywords in a text will help recall.
Procedural knowledge implies a ”knowing how” to use given concepts, rules and principles.
Contextual knowledge implies an understanding of ”knowing when and why” to select and
use specific concepts, rules and principles. This executive control process of ”knowing
when and why” is governed by selection criteria embedded within the organisation of the
Selection criteria are the values by which connections within the schematic structure of a
knowledge base are made and are situated in the affective component of the model
You can say that whereas both declarative knowledge and procedural knowledge form the
amount of knowledge in a knowledge base, contextual knowledge forms its organisation
Contextual knowledge represents a more complete understanding of human behaviour,
which is necessary for defining an educational learning theory.
The retrieval system employs the cognitive abilities of differentiation (i.e. selecting), integration (i.e. adapting and restructuring) and construction in the service of the thinking
strategies of recall, problem solving and creativity.
Differentiation is the ability to understand a given situation and to apply appropriate contextual criteria (i.e. the standards, situational appropriateness, and/or values) by which to
select and retrieve the proper knowledge from the storage. It means an ability to understand the situation and decide which kind of previously stored knowledge and emotions
to be retrieved in order to cope with the situation.
Integration is the ability to elaborate or restructure existing knowledge in the service of a
previously unencountered problem situation, which means the use of and adjustment of
knowledge in new situations, if this is necessary.
Construction is the ability to discover and form new knowledge in new situations. That
is to look at things in other ways and create new knowledge without receiving new information from outside. Construction implies declarative-, procedural-, and contextual
knowledge as well as using the total cognitive system.
It is the schemes, which make it possible for people to overcome the automatic response of
an outside influence and to be able to produce a less automatic and less practised response.
This mechanism has to do with our ability to be flexible and to deal with novel situations,
where well-learned responses are not appropriate. In some way this capacity to solve conflicts is the exact opposite of what the behaviourist learning psychologists were proposing.
They thought that all behaviour could be explained with a complex set of learned associations between stimuli and responses.
According to the cognitive theories we have a mechanism that we can call our ”behaviourist
self” which is called ”contention scheduling”. We have a big set of well-learned schemes of
action comprising organised actions associated to a goal or a purpose. These schemes have
different levels of activation, depending on the current motivations. The schemes compete
with each other and the scheme that receives more activation tends to win over the others
and will be executed. This type of process can be sufficient in very well learned- and ”standard situations”. There are situations; however, in which the contention scheduling will not
work and where the schemes that receives the more activation does not win over the others.
If a strong habitual response competes with a weaker response a second mechanism might
This is called the ”Supervisory Attentional System”. The function of this mechanism is to
modify the activation of the action schemes in order that the one more appropriate for the
situation, even less activated by external factors, will be able to win the competition with
the other, more activated schemas.
As mentioned earlier there are three categories of thinking strategies varying in cognitive
The first category is ”recall strategies” which are the automatic selection ( i.e. differentiation) of knowledge stored in the memory.
The second category, ”problem solving strategies” requires both differentiation and integration. These strategies are formed as consequences of solving a problem at the time of
solution and are stored as contextual knowledge.
The problem solving strategies represent knowledge of “knowing when and why” to select specific items of declarative- and procedural knowledge. They are domain specific
and cannot be transferred between domains.
Therefore, the accumulation of problem solving strategies in the knowledge base occurs
in direct reference to the number of problems solved within given domains.
“Creativity” makes use of differentiation and integration and, in addition to these, the
cognitive ability to create knowledge not already coded in the memory.
All three kinds of thinking strategies (recall, problem solving and creativity) are acquired
while using the cognitive abilities of differentiation, integration and construction.
Each strategy form is embedded by domain in the contextual knowledge structure of the
Consequently, the more the learner is engaged in thinking situations, the more the individual
thinking strategies become abstract and generalisable within the domain.
e. Affective domain
It is still worth a discussion whether the affective domain and the cognitive domain should
be presented as separate. In the model the affective domain is brought directly into the cognitive domain mainly because it is necessary to have a learning theory, which implies that
the affective domain is integral with the development of learning environments.
The affective domain is far more complex than the model shows. However, the model includes some of the more identifiable affective variables such as motivation, emotions (anxiety and fear), attitudes, mood, worries and values.
The immediate interaction of the affective component within the cognitive system is as
mentioned earlier in connection with the executive control component.
Motivation for example influences both attention and maintenance processes. Anxiety influences both the acquisition and the employment processes. Values would influence the criteria associated with acquisition of contextual knowledge.
The affective component needs to be considered during the acquisition of knowledge and as
part of the knowledge base.
Implementation of cognitive theories
a. Teachers guidance
The paradigm should give the teacher and instructor inspiration to create instruction design
systems based upon the paradigm with the aim of improving teaching methodology and thus
improves learning and minimise oblivion.
To do this the teacher must take into consideration how to influence the declarative knowledge, procedural knowledge and context knowledge as well as cognitive abilities.
The traditional way of planning teaching sessions is to concentrate on the subject and the
outcome of the teaching.
The teaching is often organised in accordance with the behavioural theories based upon the
stimuli-response theories. Therefore training contents had to be divided into minor parts
where each part could act as a stimulus with its own response. The final behaviour of the
students was often described based upon these ideas.
In many ways this is fine, but the cognitive paradigm tells us, that it would be a good idea to
consider teaching and learning as a more complex combination of the components. The substance of training has to be analysed in order to separate different kinds of substance knowledge and then apply proper teaching strategies to each kind of substance knowledge, making
sure that storing processes facilitates retrieval processes.
In order to teach and learn declarative knowledge one might achieve better results using explanatory strategies instead of practising strategies. On the other hand the latter are suitable
for teaching procedural knowledge.
However, it is not enough to concentrate on substance knowledge. The entire cognitive system must be taken into consideration when designing teaching systems. It is often forgotten
that teaching not only is a question of learning student’s new knowledge or skills. It is of
utmost importance that students are learning “how to learn” during the process. This means
that planners will have to make sure, that cognitive abilities become integral parts of the
b. Changes in methods and instructional design
The cognitive science and cognitive theories will result in significant changes in methods of
curricular and instructional design that will strongly affect educational practice, which until
now has been dominated by the behaviourally oriented learning paradigm of instructional
design and management.
It is possible to point out at least three major areas where changes must occur. These are (a)
the analyses of the “information to be learned” which will move from task analyses that focus on a hierarchical organisation of the information based on prerequisites, and content
analyses, that focus on defining the critical features of the information and the relationship
of those features to an information analysis. In addition to the conventional task/content
analysis a context analysis is proposed if the goal of the instruction includes solving complex problems.
The other area is (b) the means of evaluating learners. In the behavioural paradigm, evaluation focuses only on observable student performance while in contrast, evaluation in the
cognitive paradigm takes on diagnostic functions.
Evaluation is therefore more than checking attainment of behavioural objectives. More importantly, it is a concurrent element of learning. Diagnosing learner’s needs during instruction is one of the primary focuses in cognitive evaluation.
The focus for instruction design is on design of instruments that measure inference making
within meaningful contexts and construction of tests that evaluate problem solving within
complex-context situations that go beyond the usual limited scope of measuring only right
and wrong responses.
That is, can the learner deal successfully with the type of problems requiring knowledge of
”when and why” as well as knowing ”that” and ”how?”
The third area (c) is linking of the learning theory to the instructional prescriptions that in
this paper is considered the most important area and therefore will be dealt with in details.
The main issue is to introduce an instructional design model that focuses on the planning of
a learning environment so that students not only acquire knowledge but also improve their
cognitive abilities to employ and extend their knowledge.
c. Instuctional design model
The figure on page 12, presents an instructional design model that shows the direct integration of cognitive learning theory with prescribed instructional strategies.
The major components of the model are
- memory systems
- learning objectives
- teaching time
- teaching strategies.
The figure is directly associated with the cognitive paradigm of learning. The memory systems include both the acquisition and the employment of knowledge and therefore refer to
the long-term memory subsystems of storage and retrieval.
The storage system is composed of three basic forms of knowledge: declarative-, procedural- and contextual knowledge. The retrieval system is composed of cognitive abilities
associated with the processes of recall, problem solving and creativity.
The model shows, that there is a connection between the five basic memory systems and
prescribed teaching strategies. The purposes of including teaching strategies in the model
are to establish a direct link between instructional theory and learning theory. This was done
successfully with the behavioural paradigm. The model also creates an association between
the cognitive paradigm and teaching.
Finally the model indicates the relative strengths of the teaching strategies in reference to
the educational goals of knowledge acquisition and employment. The focus of the cognitive
paradigm is on both of these educational goals as contrasted to the behavioural paradigm
The purpose of cognitive based learning objectives is to further elaborate the curricular
goals of knowledge acquisition and employment. Objectives are important in the planning
of learning environments because they provide the means of both allocating teaching time
and identifying specific teaching strategies.
The learning objectives are defined as follows:
Verbal information, which deals with the learners acquiring of awareness and understanding of the concepts, rules, and principles within a specified domain of information
Intellectual skills involve the learner acquiring the skill to correctly use the concepts,
rules and principles of a specified domain of information (procedural knowledge).
Contextual skills focus on the learner’s acquisition of the organisation and accessibility
of a knowledge base (contextual knowledge), which includes the criteria, values and appropriateness of a given domain’s schematic structure.
Cognitive abilities deal with the elaboration of thinking strategies that will arm the student with increased domain specific contextual knowledge and develop the abilities of
differentiation and integration.
These abilities provide the cognitive tools to effectively employ and improve the knowledge base.
Creative processes deal with the most exclusive goal of education, the development and
improvement of learner’s creative abilities.
Creativity is here defined as twofold ability: Firstly creating knowledge to solve a problem from external environment, and secondly creating the problem as well as the knowledge.
An important part of creating both the knowledge and the problem is the criteria by
which consistent judgement can be made. Creativity objectives need to specify not only
the ability to develop and improve, but also to form the criteria.
A key factor in implementing the cognitive goals of knowledge acquisition and employment
is the allocation of teaching time by defined objectives.
The model shows that instead of doing the traditional way and allocate most of the time at
the declarative and procedural levels of the knowledge, 70% should be devoted to learningand thinking situations that involve acquisition of contextual knowledge and development
of cognitive abilities.
The suggestion of allocating 25% time to the contextual knowledge is almost the same used
for declarative knowledge and procedural knowledge because of the necessity to both organise a knowledge base and develop accessibility. Without a sufficient base of contextual
knowledge, the opportunity for employment, future elaborations, and extension of the
knowledge base is severely limited.
The teaching times presented in the model do not imply a linear sequence of knowledge acquisition going from declarative to contextual knowledge. They represent total amount in an
iterative learning environment where learners are continuously acquiring each form of
The idea is to make a direct linkage of teaching strategies to specific memory system components instead of prescribing a given strategy of teaching to all forms of learning.
Explanatory strategies are designed to provide an environment for learning of declarative
knowledge. The teaching variables here provide a context for the “information to-belearned”. That is, presenting a meaningful context for the information as well as a mental
framework of a given domain’s abstract structure extends the concept of advance organisers.
In addition to providing a context for the information, meaning can be further enhanced
by adapting the context to individual student background knowledge.
Practising strategies are called practising because the objective is to learn how to use
They should attempt to create an environment in which the student learns to apply
knowledge to previously unencountered situations while the instructional system carefully monitors the student’s performance so as to both prevent and correct possible misconceptions of procedural knowledge.
Problem oriented strategies are mainly problem oriented simulation techniques. The purpose of this is to improve the organisation and accessibility of information within the
knowledge base by presenting problems that require the students to search through their
memory to propose a solution.
Basically the strategy presents situations where the student should analyse the problem,
work out a conceptualisation of the problem, define specific goals for coping with the
problem and propose solutions or decisions.
Unlike problems in the practising strategies that focus on acquiring procedural knowledge, problem oriented strategies present situations that require employment of the domain’s procedural knowledge. The student is in a problem-solving situation that requires
establishing connection among the facts, concepts, rules and principles of specific domains of information.
Complex dynamic strategies present the initial variables and conditions of the situation,
assess the learner’s proposed solution, and establish the next iteration of the variables
and conditions based on the cumulative efforts of the learner.
Complex dynamic strategies should be designed to provide a learning environment in
which the learners develop and improve higher-order thinking processes by engaging in
situations that require the employment of their knowledge base in the service of problem
Self-directed experience will allow students the opportunity to create knowledge within
the context of a given domain.
Computer-based software instruction programs, that provide an environment for easy
manipulation of new information, increase the learning time available for such activities
and provide environments for self-directed learning experience that may improve the
creative process within given domains.
ACQUISITION OF KNOWLEDGE
EMPLOYMENT OF KNOWLEDGE
Memory sys- Declarative
Total cognitive system
(Learn “thinking” systems)
lay down criteria)
Verbal infor- Intellectual
(Learn “that”) (Learn
Long-term memory storage / Long-term memory retrieval system
How to store new information in the long–term memory?
This is of course just one of the many 64.000 $ questions for a good teacher. Another one is:
How do we retrieve the information when needed?
The connection here is imperative because the quality of the retrieval is very much dependant on the way in which information is presented and stored.
There are three possible strategies, which may be used to store information and memorise
events and new input during the storing process: rehearsal, organisation and imagery.
Rundu (1972) made a study where he showed that, in a free-recall experiment the items that
were presented at the beginning (primacy effect) and toward the end (recency effect) of a
list are more likely to be recalled than those in the middle.
One of the conclusions of Rundu´s experiment was that the probability of recalling an item
in the primacy part of the list is proportional to the number of times that the specific item
was rehearsed. Rundu concluded that rehearsal increases the probability of an item to be
stored in the long-term memory. Again this mainly can be concluded when dealing with
However, Craik and Watkins (1973) demonstrated that pure rehearsal does not actually increase the probability of an item to be recalled. They proposed the existence of two types of
rehearsal: maintenance rehearsal that does not improve memory, and elaborative rehearsal,
that requires a deeper and/or richer encoding and which really improves memory. The elaborative rehearsal consists of more than pure repetition and often includes organising the
information in logical systems.
We know that the organisation of material in a meaningful way dramatically improve recollection and retrieval. We do this quite spontaneously. For example, Bousfield (1953) presented 60-items lists to his subjects. The lists were made up of words belonging to four distinct categories (animals, names, vegetables professions) presented in random order. After
the study phase, participants were given a free-recall test. Participants tended to remember
the items organised by categories (dog/cat/cow, pea/bean, John/Bob.)
Organisation is essential to memory. Mandler (1967) suggested that other memorisation
strategies, such as rehearsal, only prove successful when contributing to reorganising study
material and the same is characteristic for mnemonic techniques.
For teachers this is important to know and take into consideration when organising the contents of the lessons and preparing the way to introduce information to the students.
As concluded above contents must be served in recognisable entities and organised in logical structures.
This is especially important when dealing with procedural knowledge and context knowledge.
c. Visual imagery
Paivio (1971) shoved that subjects performed twice as good in a cued-recall task, when they
were instructed to use an imagery strategy. For example, if the pair of items was elephant
and book subjects were instructed to imagine an elephant with a book.
Paivio proposed that each item in the list be encoded twice in the visual imagery condition:
as a word (book, elephant) and a visual image (an elephant with a book). The system is
called dual coding hypothesis. This richer encoding improves the probability that the item
ca be retrieved.
This encoding strategy is valid for all three knowledge representations, declarative knowledge, procedural knowledge and contextual knowledge but is imperative for the last two.
How to retrieve information from the long-term memory?
Even if we consider encoding and retrieval two different processes we have already seen
that the way we encode the information is crucial for the probability of retrieval.
An essential concept in the memory literature is that of retrieval cue. When information is
retrieved from our long-term memory, we use retrieval cues, which act as useful prompts or
reminders for the information to be retrieved.
The context in which the information was originally encoded is a powerful retrieval cue.
The number of possible retrieval cues for certain information can predict the probability that
this information will be retrieved.
For example, the result that deep processing of information will produce a better memory
than a shallow encoding may be explained by assuming that deep encoding is associated
with a larger number of retrieval cues than shallow encoding.
Everyone has had the embarrassing experience of going to the living room and forget why
we went there. We also know that the best method to remember, what we wanted to do, is to
go back to the bedroom, where we were before, and try to remember. And what about the
difficulties in recognising a person, when he or she is seen in an unusual context.
This type of effect is explained by the concept of encoding specificity, which is the generalisation that the initial encoding of learned material will reflect the influence of the context
in which the learning took place.
The important contextual retrieval cue has also been shown by Godden and Baddeley
(1975). Deep-sea divers were trained to memorise a list of words in two training environments: On land or in an underwater tank. Successively the divers were tested in the same
context or in a different context.
The results showed that recall was better when study and test phases were in the same environment than when they were in different environments.
What divers had learned under water they remembered better when they again were under
water, and what they had learned out of the water tank they remembered much better when
tested out of the tank.
a. Advice to the teacher
Measures mentioned below are very important for the teacher, since he/she is capable of
creating these cues for the students:
− To learn information about a problem area, when actually located in the same kind of
area, will create proper cues for the students.
− The real life situation or the simulated situation covering an almost perfect reality will
improve learning and improve retrieval.
This learning principle is normally referred to as the realistic principle in contrary to the
formal principle, where information is taught in a more ”out of context” manner.
b. Distinctiveness of cues
When dealing with cues for retrieval the generation effect must also be considered.
The generation effect says that generation of a word yields a better memory than simply
reading or hearing the same word. This effect can be explained in terms of deeper processing, and therefore in terms of more retrieval cues. An effect similar to the generation effect
was found by Mantyla (1985).
He presented long lists of words (600) in two conditions. In the first condition, the participants were asked to generate one association for each word presented; in the other condition
they were asked to generate three associations. In the recall phase, words generated in the
study phase were used as recall cues.
The results showed that in both cases retention was much higher than in the usual cued recall condition. Recall was almost perfect (90%) in the ”three associations” condition.
Learning is most often associated with the initial phase of acquiring skills, whereas “retention” relates more specifically to the ability to reproduce an acquired skill after a period of
non-performance. For several decades researchers have been interested in the measurement
of skill retention.
Although numerous theoretical approaches have been proposed, there is still no widely accepted method of measuring the rate of skill decay over time.
a. Importance of skill retention measurement
The period between the completion of training and subsequent performance of the trained
skill is conventionally referred to as the “retention interval”. Significant decay of skill during a retention interval, before it is required in operation, is obviously problematic. Hence,
adequate skill retention is potentially a key criterion of training programme success. Skills
in which retention is of particular importance are those in which there may be long intervals
between training and operational performance, or between one performance and the next.
These include skills that are used in emergencies and other rare situations.
Long-term retention is also of importance whenever skilled personnel are temporarily reassigned to another task (as can occur with job rotation), when there is an interruption in
career service, or when job assignments are sporadic (as can easily occur with reserve
forces). There may also be skill deterioration under operational conditions if performance
errors are allowed to go undetected and uncorrected.
The problem of skill retention and loss of it is of particular concern in the military context
for a number of reasons:
− Firstly, operational conditions often demand reliable rapid and accurate task performance under stress at what can often be very irregular intervals.
− Secondly, the increasing reliance on automation of tasks that once required constant operator involvement can lead to degradation of skills through lack of practice.
− Finally, because of the relatively high cost of most military training, the failure of operators to retain skills can have considerable financial implications.
Skill retention is traditionally plotted against time since original learning, forming what is
known as the retention curve. The classic retention curve is negatively accelerated, falling
quickly immediately after skill acquisition and declining more slowly thereafter. Accurate
prediction models for skill loss could serve as a basis for defining the time intervals for refresher training. They could also be used to identify the particular task that is prone to skill
loss, enabling the training specialist to include measures to counter this loss during initial
Clearly, the development of mathematical models to predict the course of skill decay would
be invaluable to the training specialist; however, because of the intangible nature of the subject area such models have proved difficult to formulate.
Several researchers have used the term “forgetting function” to describe memory decay over
time; however this term is not strictly correct, since we cannot measure what has been forgotten, only what has been retained. Further, failure to remember material at a particular
instant does not mean that it has been forgotten; it may be remembered at a later time under
different testing conditions.
b. Influence on the rate of skill decay
The assumption that a single function can be derived to predict skill retention in a variety of
tasks, populations and retention intervals has obvious appeal, but there is little evidence for
the existence of a single “generic function”.
Research has shown that many factors influence the rate of skill decay, and the complex
interactions between them are the primary reason why progress in this area has been hindered. Each retention study is conducted under slightly different conditions, leading researchers to derive apparently conflicting conclusions.
Although the conclusions may be contradictory, they may each be valid for the specific
conditions being investigated. Hence, rather than attempting to derive a single generic retention function, it is more appropriate to derive a series of functions tailored to different conditions.
Traditionally, retention functions have been either theory- or empirically-driven. Some researchers, e.g. Wickelgren (1972), derived theoretical models from the first principles by
describing the underlying theoretical mechanisms involved in retention, and then attempted
to fit the model to empirical data.
Recently, a more empirical approach has been adopted using curve-fitting techniques to account for particular sets of retention data. Theory must be developed to account for the
mathematical curves with the best fit.
Although this approach can serve to constrain and provide a framework for theory, it also
introduces its own complications due to the nature of mathematically modelling. An infinite
number of mathematical functions can be derived, and often several functions can be found
to fit a set of empirical data. In addition, various transformations of the fundamental data
can be performed, which can also affect the goodness of fit of various functions. It is found
that several functions can accurately describe a set of data; the “correct” function is difficult
Despite the above-mentioned difficulties, the search for a quantitative description of skill
retention is still viewed worthwhile pursuit amongst contemporary researchers and is a topic
of continued research.
This paper has attempted to give a general idea of
− how people learn and
− what teachers have to consider when planning and executing teaching based upon the
Hopefully this may be help in this direction, and maybe it also could serve as an inspiration
for a debate amongst the teachers.
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The collective set of attitudes, values, procedures, techniques, etc. that form the generally accepted perspective of a
particular discipline at a point in time.