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John E. Morrison
J. D. Fletcher
INSTITUTE FOR DEFENSE ANALYSES
IDA Paper P-3735
Log: H 02-002087
Approved for public release;
This work was conducted under contract DASW01 98 C 0067, Task
BE-2-1624, for Biosystems/ODUSD(S&T)/ODDR&E/OUSD(AT&L). The
publication of this IDA document does not indicate endorsement by the
Department of Defense, nor should the contents be construed as reflecting
the official position of that Agency.
© 2002, 2003 Institute for Defense Analyses, 4850 Mark Center Drive,
Alexandria, Virginia 22311-1882 • (703) 845-2000.
This material may be reproduced by or for the U.S. Government pursuant
to the copyright license under the clause at DFARS 252.227-7013
INSTITUTE FOR DEFENSE ANALYSES
IDA Paper P-3735
John E. Morrison
J. D. Fletcher
This study was conducted for Office of the Deputy Under Secretary of Defense for
Science and Technology (ODUSD(S&T)) under the “Cognitive Readiness” task. Technical
cognizance for this task was assigned to Dr. Robert Foster, Director for BioSystems,
We are grateful to Dr. Dennis Kowal, Dr. Rob Johnston, and Dr. Christine Young-
blut for their many helpful comments on a draft of the current paper. Colonel Heinz Florian
of the Austrian military forces also provided helpful comments on an earlier version of this
EXECUTIVE SUMMARY ........................................................... ES-1
I. INTRODUCTION ....................................................................... I-1
A. Readiness vs. Effectiveness ....................................................... I-1
B. Unit Readiness ...................................................................... I-2
C. Definition of Cognitive Readiness ................................................ I-3
II. COMPONENTS OF COGNITIVE READINESS .................................. II-1
A. Situation Awareness ............................................................... II-1
B. Memory and Transfer of Training ................................................ II-2
1. Memory........................................................................... II-2
2. Transfer of Training ........................................................... II-4
C. Metacognition ....................................................................... II-5
D. Automaticity ........................................................................ II-6
E. Problem Solving and Decision-Making ......................................... II-8
1. Problem Solving ................................................................ II-8
2. Decision-Making ............................................................... II-9
F. Mental Flexibility and Creativity ................................................ II-11
G. Leadership ......................................................................... II-12
1. Motives .........................................................................II-12
2. Management Skills ........................................................... II-13
H. Emotion ............................................................................ II-14
1. Emotions as Context ..........................................................II-14
2. Emotions as Cognitions ...................................................... II-16
III. CONCLUSIONS ...................................................................... III-1
A. Review of Components ........................................................... III-1
B. Implementation Issues............................................................. III-3
References ...................................................................................... Ref-1
Glossary ........................................................................................ GL-1
III-1. Summarized Components of Cognitive Readiness.................................... III-2
The following working definition of cognitive readiness is used in this paper:
Cognitive readiness is the mental preparation (including skills, knowledge,
abilities, motivations, and personal dispositions) an individual needs to
establish and sustain competent performance in the complex and unpredict-
able environment of modern military operations.
The concept of cognitive readiness may be of special relevance and significance for
those who must adapt quickly to rapidly emerging, unforeseen challenges. Both individuals
and units can be prepared to perform many of the essential tasks that are anticipated as
necessary for accomplishing the missions assigned to them. However, their readiness to
acquire the additional capabilities needed to meet the unexpected, unforeseen challenges that
inevitably arise in today’s uncertain operational environment will contribute substantially to
the success of their operations. Such readiness is a cognitive capability, which can be
found and measured to an appreciable extent in both individuals and units.
We identified 10 psychological components or theoretical mechanisms underlying
the concept of cognitive readiness. We reviewed the research literature to determine the
extent to which each component can be enhanced by instruction and then assessed. These
components and research findings concerning their trainability are
• Situation awareness. Situation awareness is generally defined as the ability
to perceive oneself in relation to the enemy and the environment. Situation
awareness has been shown to improve with practice and instructional feed-
• Memory. Memory is described as an active, reconstructive process supported
by two underlying theoretical mechanisms: encoding specificity, which
stresses the importance of external and internal cues, and transfer-appropriate
processing, which stresses actions performed during encoding and retrieval.
Tradeoffs exist between instruction used to enhance the retention and speed of
initial acquisition. Conditions of learning, particularly those providing over-
learning, can be designed to enhance retention.
• Transfer of training. Transfer of training is described as the ability to apply
what is learned in one performance context to another performance context.
Massive amounts of practice with feedback will enhance “low-road” transfer
requiring little cognitive mediation. Training in forming mindful, conscious
abstraction will enhance “high-road” transfer, which requires cognitive
• Metacognition. Metacognition refers to the executive functions of thought,
particularly those pertaining to knowledge and regulation of one’s cognitive
processes and progress toward accepted goals. Metacognitive skills can be
enhanced by exercises designed to increase the awareness of self-regulatory
• Automaticity. Automaticity refers to processes that are performed rapidly,
requiring few attentional resources. Practice with feedback and overlearning
can produce automatic processing in many tasks.
• Problem solving. Problem solving transforms goals and subgoals into a
plan of action by processes such as trial-and-error, proximity, fractionation,
and knowledge-based referrals. Techniques for problem solving matched to
goal and situation categories can be successfully taught, as can the information
base needed for “strong” problem-solving methods, which depend on acquired
• Decision-making. Decision-making is described as the selection of tactical
and strategic plans, which are frequently primed by the recognition of learned
patterns. Formal instruction in decision-making techniques may improve the
quality of decisions, but some aspects of successful decision-making are
determined by individual dispositions.
• Mental flexibility and creativity. Mental flexibility and creativity can be
cast as problem-solving—applying “strong” methods (based on acquired
knowledge and skills) to well-defined, structured tasks and applying “weak”
methods to poorly defined, ill-structured, chaotic tasks. Creativity may be
more closely associated with the “weak” methods. The research is unclear as to
whether these weak methods can be trained directly. It seems more likely that
native abilities determine the facility with which people apply appropriate weak
methods (i.e., achieve “creative solutions”) to novel situations.
• Leadership. Leadership appears to consist of motivational patterns and a
combination of technical, conceptual, and interpersonal skills, the last being
the most difficult to acquire and measure. However, technical and conceptual
skills needed by leaders can, to an appreciable extent, be taught. Interpersonal
skills and patterns of motivation required for leadership appear to be more
dependent on native abilities and are thus more difficult to teach.
• Emotion. Emotion must be channeled and controlled if military personnel are
to perform complex tasks under the stress and confusion that accompany
modern military operations. Deeply engaging, sensory immersing simulations
provide promise for training warfighters to retain critical pieces of information
and to perform under highly stressful conditions.
This brief review is intended to continue and motivate discussion of cognitive
readiness, not conclude it. It suggests that cognitive readiness is a tractable, measurable,
and relevant construct that can and should be included in assessments of readiness.
Relevant findings and suggestions are available from behavioral research and, if focused on
the issue of cognitive readiness, can be used to elaborate the concept, develop methods to
train and measure it, and help ensure its availability for military operations.
“Cognitive readiness” is a concept that occasionally receives attention and concern
from the U.S. defense community. This paper is intended to continue and motivate
discussion of this concept, which we suggest is significant and worthy of careful
consideration. In this paper, we briefly discuss this concept and assess its relevance, value,
and feasibility as a goal for military training and as a practicable component of measured
readiness. We identify and review some basic concepts underlying cognitive readiness and
then describe research findings that suggest how these concepts apply to readiness
assessment and training. We finish by discussing research needs and opportunities for
implementing the concept of cognitive readiness to enhance operational effectiveness.
A. READINESS vs. EFFECTIVENESS
Cognitive performance is a significant matter for readiness and effectiveness. It may
be best to begin by contrasting the concepts of readiness and effectiveness. Effectiveness
refers to the summative evaluation of a unit or an individual performing a military
operation. It is usually measured as performance on some outcome or outcomes associated
with mission (especially combat mission) success. Readiness, in contrast, refers to the
potential of units or individuals to perform well in combat or in other military operations.
It is usually measured by assessing a subset of hypothetical elements or components of
effectiveness. Thus, readiness represents an estimate or prediction of effectiveness.
Clearly, effectiveness is a more direct measure of operational competence. How-
ever, reliable measures of effectiveness are only available after the fact—after the operation
the unit was intended to perform has been carried out. Further, the unique circumstances of
every engagement limit the information these measures can provide about overall unit
effectiveness. Assessments of field performance at live simulation centers provide
surrogate measures of effectiveness, but such measures are expensive to obtain and limited
in the range of operational environments they cover. Assessments of performance in
constructive and virtual simulations complement those obtained from the field, are less
expensive to obtain (e.g., Orlansky et al. 1996), and allow measurement of some
capabilities that cannot be obtained in the field; however, their relationship to operational
effectiveness is indirect. Readiness measures provide additional, practicable options for
assessing unit capability, preparation, and likely mission performance.
Readiness measures may be superior to effectiveness measures obtained from real-
world operations in terms of their diagnostic value. Conventional readiness measures are
divided into logical components of performance. Effectiveness measures, in contrast, are
often presented as global assessments of unit success. The componential and analytic
nature of readiness measures makes possible the diagnosis of specific deficiencies in unit or
Based on these considerations, measures of cognitive readiness should be practical
and feasible to obtain, predictive of success across a full range of likely missions, and
sufficiently multidimensional to be diagnostic.
B. UNIT READINESS
Presently, all U.S. military units, regardless of Service, are periodically evaluated
for combat readiness. Overall unit readiness (C) is defined as the lowest rating that the unit
receives on four major components: personnel (P), equipment on hand (S), equipment
serviceability (R), and training (T). Each of these component measures is based on a set of
data elements. For instance, the S-rating is based partly on the quantity of reportable
equipment listed in the unit’s property book.
Two components (P and T) of the overall readiness measure relate directly to
individual performance and training. The P-rating provides objective data on assigned
personnel, including the percent of service members who are qualified in their military
occupation specialty (MOS) and who have attained the skill level required by their present
duties. This component provides a rough estimate of certified competencies possessed by
individuals assigned to a unit. The T-rating reflects training resources available to the unit
and the training events it has completed. An example of the various data elements included
in the T-rating reports is the availability of training resources, such as ranges, facilities,
aids, devices, simulations, and simulators. P and T elements are both rated on a four-point
scale and indicate the impact that resource constraints may have on unit readiness.
Although some components of the existing readiness measures assess (at least
indirectly) the knowledge state of unit members, the data are aggregated at the unit level and
therefore provide limited information on individual service personnel. The measures do not
directly assess the cognitive skills and abilities that underlie the performance of individuals
and their units.
C. DEFINITION OF COGNITIVE READINESS
In developing the concept of cognitive readiness, writers have emphasized the
requirement to perform in the modern battlespace, which is characterized as complex,
dynamic, and resource limited (Etter, Foster, and Steele 2000). The implication is that
individual Service members must be mentally prepared to sustain performance while facing
combat stressors such as information overload, information uncertainty, social isolation,
fatigue, physical discomfort, and danger. This environment requires more than simple
endurance. It requires the individual to be flexible, and even creative, in responding to the
challenges presented by the surrounding chaos of military operations.
As implied by the adjective “cognitive,” the primary factors that determine cognitive
readiness are psychological in nature. This is not to deny that other factors, such as
sociological and health variables, can affect cognitive readiness. However, we regard such
variables as catalysts that facilitate or inhibit cognitive readiness, rather than primary
factors. At the same time, these psychological factors are not limited to those directly
associated with traditional cognitive (i.e., intellectual) variables, but include other factors,
such as personality and disposition, motivation and emotion, and beliefs and attitudes.
Given this background, we provide the following working definition:
Cognitive readiness is the mental preparation (including skills, knowledge,
abilities, motivations, and personal dispositions) an individual needs to
establish and sustain competent performance in the complex and unpredict-
able environment of modern military operations.
The concept of cognitive readiness may be of special relevance and significance for
those who must adapt quickly to rapidly emerging, unforeseen challenges. In the ordinary
course of training, both individuals and units can be prepared to perform many of the
essential tasks that are anticipated as necessary for accomplishing the missions to which
they may be assigned. Such preparation can be accomplished and assessed in advance of
specific operations. However, the readiness of individuals and units to acquire the
additional capabilities needed to meet the unexpected, unforeseen challenges that inevitably
arise in today’s asymmetric operational environments remains an essential component of
their preparation. Their readiness to rise to these challenges will contribute substantially to
the success of their operations. Readiness of this sort concerns their ability to expect the
unexpected and be ready to deal with it rapidly and successfully. Metrics for readiness of
this sort are necessarily keyed to more abstract capabilities than those that are now included
in readiness assessments. Nonetheless, they may be as important to operational
effectiveness as those now being considered. This paper suggest that the current state of the
art allows them to be identified, acquired, and measured to an appreciable extent for
readiness assessments of both individuals and units. It also suggests that if this can be
done, serious consideration should be given to deciding if it should be done.
II. COMPONENTS OF COGNITIVE READINESS
Given our operational definition of cognitive readiness, we can now turn to psycho-
logical mechanisms that may comprise it. Our intent is to reduce the general notion of
cognitive readiness to more specific components in order to identify methods for measuring
and enhancing the construct, providing training for it, and assessing its value as a readiness
measure. The following review focuses on research that suggests new and nontraditional
approaches for enhancing readiness through more thorough consideration of human cogni-
tion. These approaches emphasize the capabilities of cognitive readiness to bring new
concepts to bear on the problem of measuring and enhancing operational readiness.
A. SITUATION AWARENESS
Situation awareness is a relatively new concept in military performance and is
generally defined as the ability to see and understand oneself in relationship to the enemy
and the environment. Endsley (1988) provided a more detailed, three-level definition of
situation awareness as (1) the perception of elements in the environment within a volume of
time and space, (2) the comprehension of their meaning, and (3) the projection of their
status in the near future. Among the complex behaviors and processes involved in cogni-
tion, situation awareness represents the initial perceptual analyses that precede decision and
Much of the situation-awareness literature has been devoted to the design of appro-
priate displays and interfaces intended to enhance an individual’s situation awareness. In
that regard, Endsley (1998) proposed that designers perform a structured analysis to
determine the functional requirements of situation awareness at all three levels, including
the basic data needed, the integration of the data in order to understand the system state in
light of goals, and the projection of the data as future trends and events.
Although situation awareness has implications for system design, awareness is a
product of human perception and cognition—not just a hardware/software capability, as
implied by some system developers. In that regard, Endsley (1998) reviewed several
procedures for measuring the situation awareness of performers. The one he favored
requires that a battle scenario be periodically stopped (presumably, this is a simulated
engagement that permits such interruptions) in order to quiz participants on the location of
battlespace elements, their meaning, and likely courses of action (COAs) in the near future.
The participants’ responses can be compared with ground truth to provide an objective
measure of awareness. Endsley concluded that this approach to measuring situation
awareness has content and predictive validity.
The fact that such performance measures exist suggests that situation awareness
may be a trainable skill. According to most models, repeated practice and feedback on the
situation awareness task implicit in the measurement process described above should
improve subsequent decisions and actions. The extent to which such training generalizes to
the full range of military operations is an issue for future research.
B. MEMORY AND TRANSFER OF TRAINING
Memory and transfer of training are two processes that are central to cognition and
individual performance. Research on these processes dates back before the turn of the
previous century. For instance, Ebbinghaus (1885/1913) established the basic finding that
training beyond established standards of performance (i.e., overlearning) enhances long-
term retention in memory. More recent reviews of the literature confirm that overlearning is
the most potent variable in long-term memory performance (Gardlin and Sitterley, 1972;
Hagman and Rose, 1983; Schendel, Shields, and Katz, 1978).
The following brief review identifies some modern research on memory and
transfer of training to highlight their application to cognitive readiness. As discussed
below, memory and transfer of training have similar implications for cognitive readiness.
The modern concept of the nonlinear battlespace emphasizes the unpredictability of
battle conditions. The chaotic nature of battle all but ensures that the conditions under
which individuals learn tasks will differ from the conditions under which they must
perform them. This is important because research clearly suggests that memory may fail
under conditions where learning and recall conditions are dissimilar. Two theoretical
mechanisms are commonly advanced to explain this phenomenon:
• Encoding specificity hypothesis. This hypothesis, initially advanced by
Tulving and Thomson (1973), states that memory is best when the conditions
of memory retrieval are congruent with the conditions of original learning.
Seemingly irrelevant changes in learning conditions, such as changes in
location or environment, can have a negative effect on recall performance.
• Transfer-appropriate processing. Memory performance increases as the
match between the processes of encoding and the processes of retrieval
increases (Morris, Bransford, and Franks 1977). This concept is very similar
to the encoding specificity hypothesis; however, while the encoding specificity
hypothesis stresses the role of external and internal cues, the transfer-
appropriate processing stresses the processes or actions that the learner per-
forms during memory encoding and retrieval.
Both theories predict that memory will likely fail if conditions at recall do not match
those at original learning. To prevent such memory failures, Druckman and Bjork (1991)
offered the following training strategies:
• Provide contextual interference during training. Interspersing target
tasks with other unrelated tasks during learning or even creating inconsistent
cues sets up interference that slows learning but increases transfer and reten-
• Increase variety and variability in training. Adding varied examples in
verbal learning and variability of practice conditions in motor learning can
(again) slow original learning but increase transfer and retention.
• Reduce augmented feedback. Although augmented or information feed-
back increases the original learning of a motor skill, it has a negative effect on
transfer and retention. Training must be designed to reduce or eliminate
augmented feedback systematically so that performance does not become
dependent on this additional source of information.
Although these three strategies appear to be quite different on the surface, all three
tap the same underlying mechanism for preventing memory failure—that is, they
… teach processes that can be called on by a posttraining task at a later time,
particularly if the posttraining task and setting differ from the training task
and setting. That is, such procedures induce “transfer-appropriate
processing” … that result in a more elaborated mental representation of the
task—a prepresentation that can, to some extent, be used in a different
context. The learner is better prepared, so to speak, not only to perceive the
similarities between the training task and the different versions of that task
in posttraining contexts, but also better equipped to perform by having
achieved the more generalized declarative and procedural knowledge
demanded by that category of task (Druckman and Bjork, 1991, p. 47).
Thus, research on memory appears to have specific implications for the context and
process of military training. The dilemma is that even though these training strategies have
positive effects on skill retention, they often have negative effects on skill acquisition. That
is, methods that enhance memory often slow the learning process. The costs and benefits
of each approach should be assessed in military training settings to determine if its
beneficial effects on retention compensate for the extent to which it may prolong initial
2. Transfer of Training
Transfer of training refers to the ability to apply what is learned in one context to
some other context. In military training, the initial learning context is usually some form of
classroom instruction or simulation training, whereas the criterion context may be a field
exercise or actual combat.
Salomon and Perkins (1989) suggested that there are two qualitatively different
types of transfer of training processes, which they called low-road and high-road transfer.
a. Low-Road Transfer
Low-road transfer is the form that most trainers would recognize as “typical” trans-
fer of training. The defining characteristic of low-road transfer is that it occurs automati-
cally (i.e., without conscious thought or mediation by internal or external representations).
This form of transfer occurs as the direct result of large amounts of practice. One negative
aspect is that overlearning the original task may restrict the range of transferred skills.
However, low-road transfer can lead to generalizable and flexible skills if the original
learning takes place in a variety of contexts. In general, skills acquired through low-road
transfer are gained through a gradual, incremental process instead of sudden, discontinuous
gains or “jumps” in performance.
Certain military skills can and should be acquired through low-road transfer. These
skills include fundamental procedures that must be performed quickly and do not require
conscious control. Examples include basic skills related to gunnery, vehicle control, and
aircraft maneuvering. Many of these skills are currently trained via simulators that are
designed to provide massive amounts of practice and feedback at relatively low cost.
b. High-Road Transfer
In some ways, high-road transfer of training is the reverse of low-road transfer.
Whereas low-road transfer is automatic and reflexive, high-road transfer requires conscious
control. Also, low-road transfer does not require an internal or external representation of
the to-be-transferred skill. In contrast, high-road transfer requires the learner to
decontextualize and re-represent the original information in a more general form that
subsumes cases other than those experienced in training. The process through which this
decontextualization occurs is called “mindful abstraction.” This process of abstraction can
occur either during original learning or at memory retrieval during the transfer task.
Although this process has the potential to increase the amount and range of transfer, it may,
like approaches that enhance memory retention, slow the original training process.
Although low-road transfer of training is required for performance of many essen-
tial military skills, high-road transfer is necessary to achieve the levels of flexibility implied
by the cognitive readiness concept. The problem is that the processes through which high-
road transfer is promoted or achieved (e.g., “mindful abstraction”) are not well defined
and, therefore, are difficult to train. In a follow-on article, Perkins and Salomon (1992)
suggested concrete methods that instructors can use in the classroom. For instance,
instructors should make the learning situation more like the criterion situations to which
transfer is desired in order to help students “bridge” from specific contexts to more general
conceptualizations that enhance high-road transfer. Such pedagogical examples offer
promise that the concept of high-road transfer can be applied to military training and
Metacognition refers to the executive functions of cognition, particularly those
pertaining to knowledge and regulation of one’s cognitive processes. A highly developed
metacognitive competence is the capacity to bring an automated (unconscious) skill under
conscious cognitive control. In other words, people should be aware of their own cognitive
processes during task performance. Brown (1987) maintained that this self-awareness of
internal routines is the highest form of human intelligence. With reference to the relevance
of metacognition for education, Hacker (2001) stated that “… the promise of metacognitive
theory is that it focuses precisely on those characteristics of thinking that can contribute to
students’ awareness and understanding of being self-regulatory organisms, that is, of being
agents of their own thinking” (p. 50).
As initially conceived by John Flavell (1976), metacognition was thought to be a set
of age-dependent competencies that arise at certain stages of development. Soon after the
introduction of the concept, researchers began to question whether the development of
metacognitive skills could be enhanced through instruction. The answer appears to be
“yes.” For instance, Palincsar and Brown (1984) reported that metacognitive skills can be
trained through the use of reflective questioning (e.g., What just happened in the last
paragraph?) and group collaboration while teaching reading to school children. Schoenfeld
(1987) demonstrated similar results while using reflective questioning (e.g., Does that
answer make sense?) to teach mathematics to schoolchildren.
There are numerous lists of metacognitive skills (e.g., Hacker, 2001). Among the
many metacognitive skills that have been identified, the following seem especially pertinent
to the military concept of cognitive readiness:
• Self-monitoring and assessment. The ability to monitor and manage
one’s own thinking and actions.
• Focusing on essentials of tasks. The ability to filter out irrelevancies and
direct attention to variables that affect performance.
• Planning. The ability to understand task goals and devise an appropriate plan
• Using strategies. The ability to evaluate individual COAs in terms of their
consequences. (Strategies here refer to schemes for individual action, not to
plans for military operations.)
From these descriptions, one would assume that such skills are characteristic of
high-performing military personnel. Further, research suggests that components of
metacognition can be enhanced by education in the K–12 context. Unfortunately, there has
been practically no research on the trainability of metacognition in the context of military
education and training. Thus, while metacognition appears to be a desirable component of
cognitive readiness, the extent to which it can be trained in military settings remains an
Conscious, deliberate human information processing is often represented as being
slow and demanding continual attention. This view fails to capture the rapid performance of
tasks that seem to require little attention, as demonstrated by the fact that such tasks can be
performed in parallel with other conscious and effortful tasks. For example, driving or
walking can be conducted while simultaneously engaging in more attention-demanding
tasks, such as listening, comprehending speech, or even conversing with others.
To account for both kinds of phenomena, Shiffrin and Schneider (1977) proposed
that they represent two distinct types of cognitive processing that can occur together and
interact. Controlled processes are slow, serial, and require attention. Perhaps the defining
feature of controlled processes is that they are subject to conscious monitoring. In contrast,
automated processes are fast and require few attentional resources. Again, perhaps the
defining feature of these responses is that they are “ballistic”—that is, they are executed
from start to finish as a unit with little or no conscious monitoring.
For novel tasks, performance during the early stages of learning is characterized by
the predominance of controlled processing. With large amounts of practice (i.e., over-
learning), elements of the task that consistently map stimuli onto responses become auto-
mated. The mapping schemata are based on categories of stimuli and responses that either
pre-exist in the performer’s memory (e.g., numbers, nouns, colors) or are “chunked”
together through practice. Other aspects that are not consistently mapped remain under
consciously controlled processes. For most complex tasks that have aspects of both
consistent and variable mapping, expert performance is characterized as a combination of
automatic and controlled processing.
Automated processing (or automaticity) is commonly measured using one of two
general methods. The first is the dual-task method, where the performer is asked to
perform a primary task (the one being measured) simultaneously with a relatively easy
secondary task. Examples of secondary tasks include shadowing or repeating a word
stream presented over headphones and finger tapping when a designated signal is presented
along with other distractors. Dual-task performance is then compared with performance of
the secondary task alone (single-task condition). If the primary task is under controlled
processing, performance of the secondary task suffers under dual-task conditions because
both tasks compete for a limited pool of attentional resources. On the other hand, if the
primary task is automated, secondary task performance under dual-task conditions will be
close or equal to single-task performance because the primary task requires little or no
attentional resources. A consistent finding from dual-task studies is that performance on the
secondary task decreases as the difficulty of the primary task increases (e.g., Allport,
Antonis, and Reynolds, 1972).
The second method for measuring automated processing is in the context of visual
or memory search tasks. In this paradigm, the subject is trained on a set of target items. He
or she is then given a display set of items that include both targets and distractors and is
required to identify the target. Targets and distractors are related according to one of two
paradigms. In the consistent mapping paradigm, targets and distractors are drawn from
different types or categories (e.g., numbers and letters) that do not overlap. In the varied
mapping paradigm, the two types overlap, with targets being distractors on some trials and
vice versa. The classic Sternberg paradigm is a varied mapping task. His results showed
response time to be a linear function of target set size, suggesting an underlying serial
control process (Sternberg, 1966). Studies using consistent mapping typically show
nonlinear effects of set size that become essentially flat after practice (e.g., Schneider and
Shiffrin, 1977), suggesting that, with practice, processing becomes automatic and requires
little or no attentional resources.
Automaticity has a complex effect on transfer of training. For low-road transfer,
where the learning task can be consistently mapped onto the transfer task, the development
of automaticity enhances transfer. However, when the original task cannot be consistently
mapped onto the transfer task, automaticity can retard transfer. For instance, Fisk, Lee, and
Rogers (1991) provided subjects with practice on targets and distractors in a visual search
task and then reversed them (i.e., old targets became distractors and old distractors became
targets). Results demonstrated that once responses to stimuli have become automated,
changes to the stimuli had a negative effect on performance.
E. PROBLEM SOLVING AND DECISION-MAKING
Like memory and transfer of training, problem solving and decision-making are
closely related areas of research that have similar implications for cognitive readiness.
1. Problem Solving
The 1960s and 1970s were seminal in advancing the scientific study of problem
solving. Miller, Galanter, and Pribram (1960) demonstrated that problem solving can be
cast as an analysis of task goals and subgoals. Newell and Simon (1972) showed how
means-ends analyses can be used to transform this analysis into a plan of action. Since
then, several researchers have sought to use models developed by theoreticians to derive
study strategies and educational practices that are intended to improve thinking skills. For
instance, Hayes (1981) enumerated four methods for searching for problem solutions that
can be used in a variety of situations:
1. Trial-and-error. This method entails searching through alternative solutions,
with no a priori information on the likelihood of the solutions’ success. This
method is effective only in situations with relatively small problem spaces.
2. Proximity. The trial-and-error method does not require the problem solver to
“look ahead.” Proximity methods are an incremental improvement in that they
involve looking exactly one step ahead in the process. The problem solver
determines whether each step takes him or her closer to the desired solution.
3. Fractionation. Problem solvers use this method when they divide a problem
into a sequence of smaller steps or subgoals.
4. Knowledge-based methods. This method includes a wide range of tech-
niques that are based on the problem solver’s prior knowledge of the problem
Hayes referred to the first three problem-solving methods as “weak” methods,
which apply across many problem domains. He referred to the last method (knowledge-
based) as a “strong” method. Strong methods draw on the extensive portfolio of know-
ledge, skills, and techniques that professionals develop to conceptualize a specific field of
interest. Examples include techniques based on the Periodic Table in chemistry and the
harmonic structure of music. There is no question that strong methods must be included in
instruction, but there is an ongoing debate concerning whether weak methods can or should
be explicitly trained. The next section suggests that weak methods play an important role in
creativity and mental flexibility. However, it remains to be seen whether these attributes are
inborn characteristics of problem solvers or are skills that can be acquired through educa-
tion and training.
The military follows a formal model of decision-making to create and implement
tactical and strategic plans. Based on economic theories of utility maximization, this method
assumes that users are (1) completely informed about all major COAs that apply to a given
situation, (2) sensitive to differences that distinguish the COAs, and (3) rational in their
choice of COAs so that the plan’s utility is maximized (Slovic, Lichtenstein, and Fischoff,
1988). These assumptions are not unreasonable if the planners are given sufficient time to
implement the decision-making process. However, the assumptions become increasingly
untenable in time-critical situations. For instance, the standard planning and decision-
making process worked well for the preparation phase of Operation Desert Storm, but it
was not useful once operations were started (Orlansky and Thorpe, 1992; Fallesen, 1995).
Slovic, Lichtenstein, and Fischoff (1988) pointed out that most classic decision-
making theories are prescriptive in intent. That is, they identify formal, systematic proce-
dures for selecting COAs that are logically consistent with the user’s expectations and
goals. Edwards (1977) demonstrated that techniques based on classic decision-making
theory are trainable and, under favorable conditions, improve the quality of individual or
group decision-making. Such approaches fare less well as descriptive theories of how
people make real-world decisions. For instance, Simon (1956) argued that decision-makers
do not actually choose COAs by maximizing utility; rather, they choose alternatives by
selecting the first alternative that is generally workable, a process that he termed
To address the need for descriptive model of decision-making, Klein (1989)
developed a model intended to depict the processes that expert performers actually use to
make decisions in real-world situations and under realistic time constraints. According to
his model, termed “recognition primed decision-making,” a decision-maker initially
assesses the situation in an attempt to recognize familiar patterns. Once an alternative is
generated from memory, the decision-maker mentally simulates its implementation in the
present situation. If the outcome is acceptable, or “satisficing” in Simon’s parlance, it is
implemented. If the outcome is not acceptable, the decision-maker discards it and either
modifies the alternative or generates another alternative from memory.
Research indicates that experienced performers use some form of a recognition-
driven decision-making process without explicit instruction to do so. It is not clear,
however, that this approach to decision-making is optimal. For instance, Dawes, Faust,
and Meehl (1989) reviewed the literature on complex and ambiguous clinical phenomena
and found that the diagnoses of experienced clinicians are often inferior to automated
diagnoses based on established relationships between observed conditions and outcomes.
Further, we do not know if recognition-primed decision-making can be trained directly or if
its use can be facilitated through the accretion of experiences that form the basis of the
recognition process. Finally, the reliance of this theoretical process on prior experience may
be problematic when the decision-maker is faced with a novel situation that requires
Researchers have noted individual differences in decision-making skills and
abilities. Some of these individual differences may be caused by education and training.
For instance, Nisbett et al. (1987) showed that graduate training in psychology and
medicine produced greater improvements in statistical reasoning than did similar training in
either law or chemistry. These researchers also demonstrated that relatively brief training on
statistical reasoning may improve the quality of everyday decision-making. Other individual
differences appear to reflect individual disposition. For example, the quality of decisions is
affected by the degree to which individuals seek or avoid risk and their personal aspirations
or goals (Markham and Medin, 2002).
F. MENTAL FLEXIBILITY AND CREATIVITY
There is a considerable history of research on mental flexibility and creativity.
Unfortunately, this field has not lived up to its promise of yielding insight into complex
cognitive processing. In a recent article, Klahr and Simon (2001) provided some needed
clarity to this field by translating flexibility and creativity concepts into problem-solving
terms. They viewed creativity as requiring the application of both “weak” and “strong”
(knowledge-based) methods to the task of discovery, but they suggest that the essence of
creativity may be more closely associated with the former “weak” methods than with the
latter “strong” methods.
In the context of military training and education, strong methods tap the knowledge
and skills that are traditionally taught in military schools. Thus, strong methods refer to the
use of specific facts and procedures (e.g., organizational structure, maneuvers in air-to-air
combat, surveillance techniques) that apply to a single Service or Branch and to the
application of military subjects and techniques across Services and operational situations.
Strong methods are important in distinguishing competent military professionals from
Weak methods, on the other hand, can potentially distinguish a competent per-
former from a creative genius. Klahr and Simon (2001) maintain that weak methods are
particularly appropriate for ill-structured problems where the starting state, end state,
operators, and/or constraints are not well defined: “The more creative the problem solving,
the more primitive the tools. Perhaps this is why such ‘childlike’ characteristics, such as
the propensity to wonder, are so often attributed to creative scientists and artists” (p. 79).
Weak methods may be particularly appropriate for the ill-structured problems presented by
the chaos of modern military operations.
One interesting example of a weak method taught in military courses is war gaming.
This is a general method by which participants think through a proposed solution step-by-
step while others who are knowledgeable of threat strategy and tactics (e.g., intelligence
officers, weapons specialists) propose countermeasures. War gaming can reveal serious
weaknesses in plans and even suggest possible modifications. War gaming itself is easily
understood and does not require extensive military training to apply. Furthermore, this
technique is generally applicable and has many civilian applications, such as the use of a
stand-in to role-play the opponent when preparing for a debate or even the use of the
“devil’s advocate” position to identify gaps in arguments.
War gaming is an example of a weak method that has been developed in a military
context and successfully exported to other problem domains. At the same time, weak
methods associated with other problem domains can be used in the military. One such
method concerns scientists’ reactions to surprise. Klahr and Simon (2001) argued that the
hallmark of a creative scientist is the ability to accept, rather than deny, surprising results
and use them to explore further the phenomena that produced them. This skill would seem
to be the essence of what is meant by “mental flexibility.” Military personnel do not usually
have an opportunity to “explore” a phenomenon in the scientific sense. Nevertheless,
reacting to surprise is clearly a useful military skill. In this context, it could be redefined as
the capability to recognize when a situation is not going as expected, to understand the root
cause of the problem, and to react accordingly.
In summary, when a situation (usually scientific in nature) is contrived to facilitate
the discovery and use of weak methods, research indicates that problem solvers will use
these methods and performance will benefit. The research is less clear about whether these
methods can be trained directly and later used in representative, uncontrived situations. It
seems likely that the facility with which people apply appropriate weak methods (i.e.,
achieve “creative solutions”) to novel situations is determined, at least in part, by a set of
native abilities, such as curiosity, propensity to wonder, and so forth.
There is a long and multifaceted history of behavioral research on leadership. Van
Fleet (1996) identified over 4,000 references related to the specific topic of military
leadership, many dating from before World War II. Yukl (1989) examined recent literature
identifying individual traits that predict leadership performance. He sorted these traits into
two broad categories: motives and skills.
Research indicates that successful managers are characterized by certain patterns of
motivations. However, no single pattern typifies all leaders. The pattern observed and
reported depends on the taxonomy of motives and measurement instrument employed. For
instance, Miner (1985) used a sentence-completion task to measure six separate motives:
1. Positive attitude toward authority figures
2. Desire to compete with peers
3. Desire to be actively assertive
4. Desire to exercise power
5. Desire to stand out from the group
6. Willingness to carry out routine administrative work.
In contrast, McClelland (1985) employed the Thematic Apperception Test, where respon-
dents make up stories based on a series of ambiguous pictures of people. The researcher
then codes the stories with respect to three abstract motivations:
1. Need for power
2. Need for achievement
3. Need for affiliation.
Yukl (1989) summarized such research by observing that successful leadership in
large hierarchical organizations is characterized by a dominant concern for socialized (as
opposed to personalized) power. This motive puts organizational interests above personal
interests. Further, the leader motivated by socialized power is more likely to use a
participative, coaching management style as opposed to authoritarian, coercive style.
2. Management Skills
Yukl (1989) pointed out that “… it is not enough to have the appropriate
motivational pattern; a person also needs considerable skill to be an effective leader”
(p. 191). In that regard, Yukl identified three basic categories of management skills:
1. Technical skills. This category refers to knowledge about methods directly
related to the job and the ability to use the methods in realistic contexts. In
problem-solving terms, this category corresponds to Klein’s (1989) and Klahr
and Simon’s (2001) strong knowledge-based methods discussed earlier.
2. Conceptual skills. This category includes the higher-order thinking skills
that roughly correspond to weak problem-solving methods and metacognitive
skills, discussed earlier.
3. Interpersonal skills. This unique and wide-ranging category includes three
subtypes of skills.
a. Knowledge and skill in interpersonal processes (empathy and social
b. Communication skills (speech fluency and persuasiveness)
c. The ability to establish relationships (tact, diplomacy, social knowledge/
The first two categories, technical and conceptual skills, overlap substantially with
other content areas discussed in this paper. The interpersonal skills, in contrast, provide a
unique set of competencies. However, measurement of these skills remains a challenge.
Measuring these skills with written tests has achieved only limited success. Measuring
these skills through role-playing exercises, using situations in which no one is designated
as the leader, has achieved somewhat better success.
Interpersonal skills also appear difficult to acquire. Yukl (1989) emphasized that
lectures or texts on social sensitivity, charm, tact, persuasiveness, and so forth are not
effective. Limited success has been achieved by showing films and videotapes to illustrate
critical incidents in interpersonal relations. The most effective approach is one in which
trainees get opportunity to practice techniques and receive feedback. Role-playing has been
an effective approach when it is combined with videotaping for subsequent self-evaluation.
Schroeder et al. (1986) had considerable success training interpersonal skills for
leaders using videodiscs, which are functionally equivalent to today’s CD-ROMs. They
used videodisc presentations and interactions to simulate interpersonal situations (e.g.,
taking charge, providing performance counseling, dealing with insubordination, handling
verbal abuse) and then to provide feedback on learner responses and decisions in these
situations. Their approach turned out to be generally more effective than using programmed
text or “live” (with human actors) role playing.
The topic of emotion is important because military personnel are expected to per-
form complex tasks (maintain cognitive effectiveness) under conditions likely to evoke
strong emotions, such as anxiety and fear. There are at least two general types of theories
about the effects of emotions on performance. The first is that emotion provides an
important class of contextual stimuli that must be considered in training design. The second
is that emotions provide information that either provides input to or results from cognitive
1. Emotions as Context
The first theoretical approach regards internal states, including emotions, as being
no different from external conditions for learning and performance. Given this
interpretation of emotions, both encoding specificity and the transfer-appropriate pro-
cessing hypotheses would predict that performance improves when training conditions
match criterion test conditions. In fact, findings related to “state-dependent learning” appear
to confirm this prediction. These studies indicate that criterion performance is best when the
learner’s internal state during the study matches that during the test, even if the state
generally depresses performance. For instance, Eich et al. (1975) had two groups of
college students learn a list of 48 words. One group learned the words while under the
influence of marijuana, and the other group learned the words while under the influence of
a placebo. The two groups were further subdivided into those tested under the influence of
marijuana or a placebo. Thus, the design specified four separate subgroups defined by the
factorial combination of study conditions (intoxicated vs. sober) and test conditions
(intoxicated vs. sober). As expected, the results indicated that the two subgroups that were
tested while sober made fewer errors than the two subgroups that were tested while
intoxicated. However, comparison of the two subgroups that were tested while intoxicated
indicated that those who studied while intoxicated by marijuana made fewer errors than
those who studied while sober.
So-called “mood-dependent” effects further extend these results to emotional states.
For instance, Bower (1981) reported a study in which college students learned a list of
words while either in a hypnotically induced happy or sad state and then, 10 minutes later,
were tested for retention. As in the Eich et al. findings, Bower’s results indicated
performance improved when the test conditions matched the learning conditions.
From these results, one would predict that performance under emotionally arousing
combat conditions would be improved by training under identical, or at least similar,
arousing conditions. Given this interpretation of emotions, both encoding specificity and
the transfer-appropriate processing hypotheses clearly predict that performance under
emotionally arousing conditions will be optimal when training occurs under similar
emotional conditions. In the past, technology and ethical constraints have acted to limit the
degree to which training evokes the strong emotions associated with combat. Some have
claimed that immersive simulation technology (i.e., simulations that involve multiple
sensory modes—sounds and smells as well as visual stimuli) has the ability to evoke
strong emotions. For instance, Shilling, Zyda, and Wardynski (2002) cited research
showing that high-fidelity surround sound increased physiological responses to a video
game. It remains to be seen, however, whether the emotions evoked in immersive
simulation are similar in quality and intensity to those experienced in combat. Ironically, to
the extent that immersive simulation technologies are able to elicit strong emotions like
those in combat, ethical considerations may constrain the use of these technologies for
training and research. Nevertheless, these new immersive training technologies provide an
environment where warfighters can develop automaticity and develop confidence to
perform under highly stressful conditions.
2. Emotions as Cognitions
In contrast to the notion that emotions are simply contextual stimuli, the second
approach regards emotional states as providing input to cognitive processes. For instance,
Schwarz (1990) advanced the idea that emotions provide important information for tuning
cognitive processes. Positive emotions (e.g., happiness) indicate that the situation is safe,
triggering superficial heuristic processing of information relying on preexisting knowledge.
Negative emotions (e.g., sadness) indicate that something is amiss and that more detailed
or systematic processing is required. The form of processing that is most effective depends
on the nature of the task. Tasks that require specific actions and attention to detail would
benefit from negative moods, whereas those that require originality and creativity would
gain from positive moods.
An alternative to Schwarz’s (1990) position that emotions are input to cognition is
the idea that emotions are output from cognitive processing. Ortony, Clore, and Collins
(1988) were particularly influential advocates of the latter position. Their position,
commonly referred to as the OCC model, is that emotions are the result of the cognitive
appraisal of three general features: events, agents, and objects. The outcome of the
appraisal is a valenced reaction (i.e., a nonspecific positive or negative response) that may
be described as either pleased/displeased with events, approving/disapproving of agents, or
liking/disliking objects. The exact nature of the emotion depends upon the emoter’s focus
of attention. For instance, the emotion identified as “resentment” is experienced when the
person is displeased about an event that is desirable for another.
The OCC model provides a structure for defining 22 distinct emotions. The purpose
is to provide a theory that is not only internally consistent and externally valid, but also
computationally tractable. It is the latter characteristic that makes the OCC model particu-
larly appealing to those interested in creating more realistic intelligent agents to emulate
human behavior and performance.
According to the OCC model and most theories of human affect, emotions are
unlearned subjective experiences (like color or pain). Thus, except in cases of extreme
emotional dysfunction, people have no need to be trained to experience affective states
properly. On the other hand, some recognize the value of better understanding the causes of
one’s own emotions and being able to recognize emotional states in other people. That was
partly the reasoning behind Marsella and Gratch’s (2001) development of emotional agents
for the Mission Rehearsal Exercise project. This project presents a realistic and emotionally
evocative scene where the human trainee assumes the role as the commander of a platoon
involved in an accident concerning a civilian child. The trainee interacts with a simulated
person who is apparently the child’s mother. An intelligent agent that embodies an emo-
tional component based on OCC theory controls the mother’s behavior. The purpose of
including emotions is to increase the realism of the scenario and provide practice in making
decisions in an emotionally evocative situation.
This review suggests that cognitive readiness is an integrative concept that pulls
together diverse themes related to performance improvement and sustainment. It also
suggests that cognitive readiness is a serious candidate for inclusion in routine measures of
readiness in so far as it can be trained and measured. It may be essential in determining the
capabilities of individuals and units to adapt rapidly to the unpredictable exigencies and
challenges of modern asymmetric military operations.
A. REVIEW OF COMPONENTS
Standard techniques of readiness assessment involving materiel, supplies, equip-
ment, personnel, and training resources, along with tallies of the training activities com-
pleted, are helpful in measuring military readiness. However, they provide an incomplete
view of readiness in general and cognitive readiness in particular. This paper has briefly
discussed how cognitive readiness can and, perhaps, should be used to expand our
measurement and understanding of military readiness.
Table III-1 lists 10 components of cognitive readiness that are identified and
discussed in this paper. It summarizes the relevance of each component to military opera-
tions, ways in which it can be measured, and ways in which it might be trained. The table
also suggests several recurring themes, indicating that cognitive readiness may be
understood as a combination of three basic abilities to:
1. Recognize patterns in chaotic situations (situation awareness, memory, transfer
2. Modify problem solutions associated with these patterns as required by the
current situation (metacognition, flexibility, and creativity).
3. Implement plans of action based on these solutions (decision-making,
leadership, automaticity, and control of emotions).
Table III-1 also suggests that, to a significant extent, components of cognitive
readiness are measurable and trainable. Techniques to achieve this end should be developed
and employed. However, some aspects of cognitive readiness are not amenable to training,
Table III-1. Summarized Components of Cognitive Readiness
Component Relevance Measurement Pedagogy
The ability to perceive
and comprehend all
relevant elements of
the current military
situation and to project
status into near future.
that can be interrupted
to compare participants’
Repeated practice and
Memory The ability to recall
patterns in operational
problems for which
there are likely
Direct testing of
knowledge and skill
retention or interrupting
(as above) and
assessing retention of
Tradeoffs exist, but
conditions of learning
can be designed to
Transfer of training The ability to apply
knowledge and skills
learned in one context
to another context.
Assess the application
of learning to contexts
different from those in
which the learning
abstraction of principles
Massive amounts of
practice with feedback
will enhance “low-road”
transfer. Training in
will enhance “high-road”
Metacognition The ability to monitor,
assess, regulate, and
enhance one’s own
Determine the accuracy
with which individuals
regulate or monitor their
own performance in
Most cognitive skills can
be enhanced by
exercises designed to
increase awareness of
Automaticity Allows very rapid
responses (e.g., to
emergencies) that do
not substantially impair
Determine the ability to
the tasks in dual
processing or visual/
memory search modes.
processing in many
Problem solving The ability to analyze
the current situation,
understand goals, and
develop a COA to
Determine the probable
success of proposed
plans of action when
more difficult situations
to deal with and goals to
Techniques matched to
goal and situation
categories can be
successfully taught as
can the knowledge
base needed for
Table III-1. Summarized Components of Cognitive Readiness (Continued)
Component Relevance Measurement Pedagogy
Decision-making Similar to problem
solving, but the
emphasis is on
plans of action,
probable impact of
each, selecting one,
resources to it.
Assess competency in
formal methods by
success in identifying
and selecting COAs
likely to achieve
consistent with given
utilities. Directly assess
quality of decisions vis-
Instruction in formal
improve the quality of
decisions, but some
aspects of successful
The ability to generate,
adapt, and modify
COAs rapidly, as
required in response
to variable situations.
“War gaming” that
assesses the ability to
devise plans and
actions that differ from
“school solutions” and
adapt to rapidly
Knowledge and skills to
widen the range of
options considered in
military operations can
be taught, but higher
levels of creativity are
more likely to be caused
by native abilities.
Leadership Patterns of
knowledge and skills
that encourage and
support others in
carrying out a
designated plan of
contrived to provide
Different groups and
different goals require
assessments of ability
to adjust leadership
style as needed.
conceptual skills can, to
an appreciable extent,
be taught. Interpersonal
skills and patterns of
motivation are more
dependent on native
abilities and are more
difficult to teach.
Emotion The ability to devise
and select appropriate
COAs despite states of
Performance in deeply
can be used to assess
the ability to overcome
emotion and stress.
simulations may train
warfighters to retain
critical pieces of
information and perform
under highly stressful
and a better approach might be to improve techniques to select and acquire talented people
who can achieve higher levels of cognitive readiness.
B. IMPLEMENTATION ISSUES
The first effort in implementing the concept of cognitive readiness should be
devoted to the development of content-valid measures of cognitive readiness for use in
empirical research. These measures would likely be multidimensional. One approach to
developing such measures would be to collect accounts of behavior in critical incidents
from people who have had operational experience. These accounts might be collected from
detailed histories of military operations and/or from personal recollections. The accounts
should include the impact of cognitive readiness on an operational outcome such as combat
success. They could then be subjected to analysis in order to establish (1) the dimensions
of cognitive readiness exhibited and (2) the range and type of impact that cognitive
readiness has on individual and unit outcomes.
Given content-valid measures of cognitive readiness, the next step would be the
development of interventions that increase cognitive readiness in needed areas. So far, we
have focused on training as the most obvious intervention for increasing cognitive readi-
ness, but training may not always be the best approach. Some components of cognitive
readiness may not be trainable at all, while others may be trained, but only at great expense
in time or cost.
At least two other classes of interventions can be used in lieu of or in addition to
training. The first class of nontraining interventions is based on human-factors engineering.
Such interventions are concerned with the design or redesign of military systems (including
both system hardware and job procedures) to enhance their consistency with known human
capabilities and limitations. Operator displays designed to increase situation awareness are
examples of such human-factors interventions intended to increase cognitive readiness.
A second class of nontraining interventions concerns personnel selection and classi-
fication. Some aspects of cognitive readiness, such as leadership traits, may be innate
patterns of behavior rather than acquired (trainable) skills. For such aspects of readiness, it
may be better to use assessment procedures to identify individuals who are more cogni-
tively ready than others. At the least, it may be better to develop assessment procedures to
identify individuals who have a high potential for various levels of cognitive readiness and
thereby reduce the amount and type of training that must be provided.
In practice, combinations of interventions often provide the most promise. For
instance, new displays can provide the potential to increase situation awareness, but
operators must be trained to use these displays to realize that potential. Similarly, job
applicants can be assessed for leadership traits, but training is still required to help
applicants understand how best to use their capabilities to perform the many different tasks
they will encounter.
Etter, Foster, and Steele (2000) noted the potential for advanced distributed learning
(ADL) technologies to improve cognitive readiness. These technologies are intended to
make training and decision-aiding available anytime and anywhere they are needed or
desired (see http://www.aldnet.org ). Their potential is based primarily on the sophisticated
learning and practice environments that technology-based instruction—such as computer-
based instruction (CBI), intelligent tutoring systems (ITSs), tutorial simulations, and
networked simulations—makes accessible.
Overall, it seems reasonable to conclude that cognitive readiness is a tractable and
relevant construct that can and should be included in assessments of readiness. Clearly, we
are at an early stage of thinking about cognitive readiness and much remains to be done if it
is to become a routinely considered aspect of readiness assessment. However, as this paper
suggests, many findings from behavioral research can be used to elaborate the concept of
cognitive readiness, develop methods to train and measure it, and implement capabilities to
help ensure its availability for military operations. More must be done, but much is
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Cognitive readiness is described as the mental preparation an individual needs to establish and sustain competent
performance in the complex and unpredictable environment of modern military operations. Relevant components of
cognitive readiness are identified as situation awareness, memory, transfer of training, metacognition, automaticity,
problem-solving, decision-making, flexibility and creativity, leadership, and emotion. These components were determined
to be measurable and capable of enhancement through training. It was concluded that cognitive readiness contributes
significantly to success in military operations and that it should be routinely included in assessments of readiness.
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automaticity cognition, creativity, decision-making, memory, mental flexibility, metacognition, military training, personnel
selection, problem-solving, readiness, situation awareness, transfer of training
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