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Tacit Knowledge and Practical Intelligence: Understanding the Lessons of Experience

ARI Research Note 2003-04
Tacit Knowledge and Practical Intelligence:
Understanding the Lessons of Experience
Jennifer Hedlund
John Antonakis
Robert J. Sternberg
Yale University
Research and Advanced Concepts Office
Paul A. Gade, Chief
October 2002
United States Army Research Institute
for the Behavioral and Social Sciences
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1. REPORT DATE (dd-mm-yy)
July 2001
3. DATES COVERED (from. . . to)
July 2000 - July 2001
Tacit Knowledge and Practical Intelligence:
Understanding the Lessons of Experience
fE i
BdTitK ld
Jennifer Hedlund, John Antonakis, and Robert J.
Sternberg (Yale University)
U.S. Army Research Institute for the Behavioral and Social
5001 Eisenhower Avenue
Alexandria, VA 22333-5600
U.S. Army Research Institute for the Behavioral and Social
5001 Eisenhower Avenue
Alexandria, VA 22333-5600
Research Note 2003-04
Approved for public release; distribution is unlimited.
14. ABSTRACT (Maximum 200 words):
This report addresses the role of practical intelligence and tacit knowledge in understanding how
individuals learn from experience and develop expertise. We present background on the notion
of practical intelligence as an alternative to conventional conceptualizations of intelligence, and
the exploration of the acquisition and utilization of tacit knowledge as elements of practical
intelligence. We review research on practical intelligence and, in particular, highlight findings
from over 15 years of research on tacit knowledge. We then address new directions aimed at
understanding how individuals learn from experience and acquire tacit knowledge, and present
new approaches for identifying and promoting managerial and leadership potential that are
based on ongoing research on practical intelligence.
eadership, experience, practical intelligence, knowledge acquisition, tacit knowledge
(Name and Telephone Number)
Jonathan Kaplan (703) 617-8828
This report addresses the role of practical intelligence and tacit knowledge in
understanding how individuals learn from experience and develop expertise. We present
background on the notion of practical intelligence as an alternative to conventional
conceptualizations of intelligence, and the exploration of the acquisition and utilization of tacit
knowledge as elements of practical intelligence. We review research on practical intelligence
and, in particular, highlight findings from over 15 years of research on tacit knowledge. We then
address new directions aimed at understanding how individuals learn from experience and
acquire tacit knowledge, and present new approaches for identifying and promoting managerial
and leadership potential that are based on ongoing research on practical intelligence.
Tacit Knowledge and Practical Intelligence: Understanding the Lessons of Experience
The ability to learn from experience is a key to success in almost any domain. When
individuals are asked how they master their jobs, they often say they learned through “trial and
error” or through “experience.” Consider the lesson learned in the following story from a U.S.
Army company commander:
My battalion commander is a micro-manager. Twice a day I go to battalion headquarters
to coordinate with each member of the battalion staff. I see the battalion commander only
at staff meetings or when he wants to see me. I always try to take care of problems at my
level and only have gone to the battalion commander twice with problems I couldn’t
handle. One time it was for a marital problem with one of my lieutenants. The battalion
commander gave me advice and sent me on my way. The other time it was for a soldier
gang in the battalion. I went to him as soon as I found out about it and together we went
to the brigade commander for advice. A fellow company commander who went to the
battalion commander all the time with routine matters was removed from command after
12 months. Another company commander always looked for opportunities to brief the
battalion commander, but the commander would always blow him away with probes and
questions on the details.
This commander learned that by handling problems on his own and only seeking out the boss’s
advice when absolutely necessary, he maintained his autonomy and reduced the boss’s
opportunity to micro-manage . It was not a lesson he learned in a classroom or read in a manual.
It reflected knowledge that this leader acquired by learning from his personal experience about
what did and did not work in that situation.
Many researchers have shown that experience serves as a major source for acquiring job-
relevant knowledge and skills, which, in turn, have a direct influence on how well individuals
perform their jobs (e.g., Borman, Oppler, & Pulakos, 1993; McCall, Lomabardo, & Morrison,
1998; McCauley, Ruderman, Ohlott, & Morrow, 1994; Schmidt, Hunter, & Outerbridge, 1986;
Tesluk & Jacobs, 1998). Furthermore, research on the development of expertise suggests that
experts in a given domain have accumulated an extensive base of knowledge that they can apply
flexibly to most problems (Ericsson, 1996; Sternberg, 1995). What is not well understood is how
individuals learn from experience and what distinguishes those who learn effectively from those
who do not.
One measure of the ability to learn from experience is the acquisition of “tacit
knowledge.” Sternberg and his colleagues (Sternberg, 1988, 1997; Sternberg et al., 2000;
Sternberg & Horvath, 1999; Sternberg, Wagner, Williams, & Horvath, 1995; Sternberg &
Wagner, 1986) consider the acquisition and utilization of tacit knowledge, often characterized as
“street smarts” or “common sense,” to be an aspect of practical intelligence. Tacit knowledge
represents what one needs to know to get along in daily life that typically is not explicitly taught
or even verbalized. The knowledge is considered tacit because often it is not readily articulated
by the individual or widely shared within the performance domain (Sternberg et al., 2000).
Terms like professional intuition and professional instinct have been used to characterize the
tacit quality of knowledge associated with individuals who are successful in their respective
In this report, we present an overview of the construct of tacit knowledge and its
theoretical basis in practical intelligence. Next, we review nearly 15 years of research on the
relationship of tacit knowledge to everyday performance in domains ranging from academic
psychology to military leadership. Then, we consider new approaches for assessing and
promoting one’s ability to learn from work experience by means of tacit knowledge and practical
intelligence. We conclude with directions for future research aimed at improving our
understanding of how leaders, and employees in general, learn effectively from their
Practical Intelligence and Tacit Knowledge
Practical intelligence is formally defined as the ability that individuals use to find an
optimal fit between themselves and the demands of the environment through their adapting to
their environment, shaping (or modifying) their environment, or selecting a new environment in
the pursuit of personally-valued goals (Sternberg, 1985, 1997, 1999b). Practical intelligence
represents one of several concepts that have received increasing attention in recent years as an
alternative to traditional views of intelligence. The traditional view (Brand, 1996; Jensen, 1998;
Ree & Earle, 1993; Schmidt & Hunter, 1998; Spearman 1927) proposes that many of the
competencies needed for success can be viewed as associated with one general intelligence (or
ability) factor. A number of researchers have argued that
g presents a restricted view of the
abilities individuals need to succeed in everyday life, and have proposed broader perspectives
that include concepts like interpersonal and intrapersonal intelligence (Gardner, 1983, 1993,
1999), emotional intelligence (Goleman, 1995; Mayer, Salovey, & Caruso, 2000), and creative
and practical intelligence (Sternberg, 1985, 1997, 1999b). Our focus is on the concept of
practical intelligence as it underlies the acquisition and utilization of tacit knowledge.
Practical Intelligence
The concept of practical intelligence emerged from concerns that traditional intelligence
tests measure abilities associated primarily with academic rather than practical tasks (see Berg,
2000; Ceci &Roazzi, 1994; Sternberg & Wagner, 1986; Wagner, 2000). In other words, the types
of problems found in academic settings and on most intelligence tests often differ in many ways
from the types of problems found in everyday life.
Building on a distinction made by Neisser (1976), Sternberg and his colleagues
(Sternberg, 1985, 1997; Wagner & Sternberg, 1986) have identified several characteristics that
distinguish academic from practical problems. Academic problems tend to be (a) formulated by
others, (b) well-defined, (c) complete in the information they provide, (d) characterized by
having only one correct answer, (e) characterized by having only one method of obtaining the
correct answer, (f) disembedded from ordinary experience, and (g) of little or no intrinsic
Practical problems, on the other hand, tend to be (a) unformulated or in need of
reformulation, (b) of personal interest, (c) lacking in information necessary for solution, (d)
related to everyday experience, (e) poorly defined, (f) characterized by multiple “correct”
solutions, each with liabilities as well as assets, and (g) characterized by multiple methods for
selecting a problem solution. Given the differences in the nature of academic and practical
problems, it is no surprise that people who are adept at solving one kind of problem may well not
be adept at solving problems of the other kind. Research on practical problem solving provides
evidence in support of this distinction (e.g., Cornelius & Caspi, 1987; Denney, 1989).
Studies of practical problem solving have been conducted with schoolchildren (Carraher,
Carraher, & Schliemann, 1985; Perret-Clermont, 1980), racetrack handicappers (Ceci & Liker,
1986, 1988; Ceci & Roazzi, 1994; Ceci & Ruiz, 1992), grocery shoppers (Lave, Murtaugh, & de
la Roche, 1984; Murtaugh, 1985), and college students performing computer simulated tasks
(Dörner & Scholkopf, 1991), to name a few. These studies have shown fairly consistently that
individuals who perform well on various non-academic tasks do not necessarily perform well on
comparable assessments in an academic context. For example, Lave et al. (1984) found that
grocery shoppers who were able to calculate the cost per unit of items in order to identify items
with the best value, were unable to perform equally well on a written math test. Ceci and Liker
(1986, 1988) similarly found that the ability of racetrack handicappers to use complex algorithms
to predict post time odds was unrelated to their IQ scores.
One area that particularly demonstrates the distinction between academic and practical
problems is the domain of business management. Traditionally, managers were taught to follow
rational models in solving managerial problems. Rational models are based on the assumption
that a set of problem-solving principles can be applied to most, if not all, situations (Isenberg,
1984; Kepner & Tregoe, 1965; Plunkett & Hale 1982). Many researchers discovered that
successful managers rarely followed a rational problem-solving approach (Isenberg, 1986;
McCall & Kaplan, 1985; Mintzberg, Raisinhani, & Theoret, 1976). Instead they were action-
oriented very early in the problem-solving process, their analyses were cursory rather than
exhaustive, and their responses were based on their personal experience with analogous
problems rather than on more formal principles of problem solving. Schön (1983) further
suggested that much of managerial competence appears as action that is nearly spontaneous, and
based more on intuition than on rationality. It is "ordinarily tacit, implicit in our patterns of
action and in our feel for the stuff with which we are dealing. It seems right to say that our
knowing is in our action" (Schön, 1983, p. 49).
The action-oriented knowledge that Schön (1983) referred to is consistent with the
approach of Sternberg and his colleagues (see Sternberg et al., 2000; Sternberg, Wagner, &
Okagaki, 1993; Sternberg et al., 1995; Wagner, 1987; Wagner & Sternberg, 1985). Individuals
draw on a broad base of knowledge in solving practical problems, some of which is acquired
through formal training and some of which is derived from personal experience. The latter often
is not openly expressed or stated—it guides action without being readily articulated, and thus, is
considered tacit.
Tacit Knowledge
The term
tacit knowledge has roots in works on the philosophy of science (Polanyi,
1966), ecological psychology (Neisser, 1976), and organizational behavior (Schön, 1983), and
has been used to characterize knowledge gained from everyday experience that has an implicit,
unarticulated quality. Schön (1983) argued that by recognizing patterns of events in their
experiences, individuals create frameworks and schemata—most of which are latent—to make
sense of their experiences. These schemata are continually tested in practice and updated as
environmental conditions change. Tacit knowledge is conceptualized by Sternberg and his
colleagues (Sternberg, 1997; Sternberg & Horvath, 1999; Sternberg et al., 1995; Sternberg et al.,
2000) according to three main features corresponding to the conditions under which it is
acquired, its structural representation, and the conditions of its use.
First, tacit knowledge generally is acquired with little support from other people or
resources. In other words, the individual is not directly instructed as to what he or she should
learn, but rather must extract the important lesson from the experience even when learning is not
the primary objective. Formal training environments facilitate certain knowledge-acquisition
processes, which include selective encoding (sorting relevant from irrelevant information in the
environment), selective combination (integrating information into a meaningful interpretation of
the situation), and selective comparison (relating new information to existing knowledge)
(Sternberg, 1988). When these processes are not well supported, as often is the case in learning
from everyday experiences, the likelihood increases that some individuals will fail to acquire the
Second, tacit knowledge is viewed as procedural in nature. It is often context-specific
knowledge about what to do in a given situation or class of situations. Drawing on Anderson’s
(1983) distinction between procedural and declarative knowledge, tacit knowledge can be
considered a subset of life-relevant procedural knowledge that is drawn primarily from personal
experience rather than formal instruction. As is the case with much procedural knowledge,
knowledge gained from everyday experience tends to guide action without being easily
articulated (Anderson, 1983).
The third characteristic feature of tacit knowledge is that it has direct relevance to the
individual’s goals. Knowledge that is based on one’s own practical experience will likely be
more instrumental to achieving one’s goals than will be knowledge that is based on someone
else’s experience or that is overly generic and abstract. Drawing on the earlier example, the
officer’s goal was to reduce the negative effect of a micromanaging boss. He learned that by only
bringing certain issues to the boss’s attention and handling more trivial issues on his own, he was
able to minimize the boss’s micromanagement.
Research on Tacit Knowledge and Practical Intelligence
Sternberg and his colleagues (e.g., Sternberg et al., 1993; Sternberg et al., 1995;
Sternberg et al., 2000; Wagner, 1987; Wagner & Sternberg, 1985; Wagner, Sujan, Sujan,
Rashotte, & Sternberg, 1999) have developed and validated tests of tacit knowledge with
academic psychologists, salespersons, high school and college students, civilian managers, and
military leaders, among others. The measurement instruments used to assess tacit knowledge
typically consist of a series of situational descriptions accompanied by a variety of possible
response options. These types of measures are similar to those characterized in the literature as
situational judgment tests (SJTs; Chan & Schmitt, 1998; Legree, 1995; Motowidlo, Dunnette, &
Carter, 1990). Individuals are presented with practical problems relevant to their performance
domain (e.g., a manager intervening in a dispute between two subordinates) followed by a set of
options or strategies for solving the problem (e.g., meet with the two subordinates individually to
find out their perspectives on the problem; hold a meeting with both subordinates and have them
air their grievances). Respondents are asked either to choose the best and worst alternatives from
among a few options, or to rate on a Likert scale the quality or appropriateness of several
potential responses to the situation.
In tacit-knowledge (TK) tests, the situational descriptions represent actual incidents from
which individuals learned an important lesson about how to perform their job, and reflect
knowledge that was not taught in school nor read in a textbook or manual. A sample question
from the Tacit Knowledge Inventory for Military Leaders (TKML; see Hedlund et al., 1998) is
shown in Figure 1. Individuals are asked to rate the quality or appropriateness of various possible
responses to the situations described. Their level of knowledge is assessed by comparing their
ratings against a standard, which is derived from the opinion of experts or a theoretical
We briefly summarize findings from the research conducted on tacit knowledge to date.
This review is organized around the relationship of TK to the constructs of experience, general
cognitive ability, personality, and performance. We include in this review findings by other
researchers who have taken similar approaches to studying practical intelligence.
Tacit knowledge and experience. Following the defining characteristics of tacit
knowledge, it is assumed that experience leads to the acquisition of tacit knowledge. Experience
in this case can be viewed as a necessary but not sufficient condition for the acquisition of TK,
since what the individual learns from experience is instrumental in the learning process
(Sternberg et al., 2000). Research on the more general concept of job knowledge has shown that
experience has a direct effect on the acquisition of job-relevant knowledge (Borman et al., 1993;
Schmidt et al., 1986). Research on TK also generally supports the relationship between
knowledge and experience, with a few exceptions.
There are many ways to define experience, including years of experience, rank or level in
the organization, job status, or title. These different conceptualizations often produce different
results. In terms of years of experience, or tenure, studies conducted with salespersons and
managers have found that individuals with more years of experience scored significantly higher
on TK tests (Wagner, 1987; Wagner et al., 1999). However, two studies, one with civilian
managers and the other with military leaders, found that the number of years spent in a job or
organization correlated negatively with TK scores (Sternberg et al., 2000). In both cases, further
research showed that the individual’s level in the organization correlated positively with TK
scores (Hedlund, Sternberg & Psotka, 2000). These findings suggest that mere time in a job may
not guarantee learning, and that individuals who do learn may change positions more often
within and across organizations. Several other studies provide further evidence of a positive
correlation between job level, or rank, and TK scores (Antonakis, Hedlund, Pretz, & Sternberg,
2001; Wagner & Sternberg, 1985; Wagner, 1987), and also have shown mean differences in
scores between groups at different career stages (e.g., undergraduates, business graduate
students, and business managers).
Taken together, these findings suggest that the relationship between experience and tacit
knowledge is not fully resolved. What is clear, however, is that experience is not simply a proxy
for knowledge. Two individuals may spend the same amount of time in a job, but not achieve the
same level of learning. Rank or level may be a better measure of experience because it indicates,
at least hypothetically, that an individual has gained the necessary knowledge for job promotion.
Several researchers (e.g., Quinones, Ford, & Teachout, 1995; Tesluk & Jacobs, 1998) have
suggested that purely quantitative measures do not provide much insight about the
developmental impact of an individual’s experience. Tacit-knowledge tests can provide a more
direct method of evaluating that impact.
Tacit knowledge and general cognitive ability. Tacit knowledge, as an aspect of practical
intelligence, is viewed as largely distinct from general cognitive ability (g). Therefore, one of the
goals of TK research has been to establish the discriminant validity of TK tests relative to
traditional tests of intelligence.
Tacit-knowledge tests typically exhibit trivial and nonsignificant correlations with
measures of
g, with some exceptions. In samples of undergraduate students, business managers
and salespersons, scores on a test of verbal reasoning exhibited nonsignificant correlations with
scores on TK tests (Wagner, 1987; Wagner & Sternberg, 1985, 1990; Wagner et al., 1999). Eddy
(1988), in a study of Air Force recruits, found that scores on four factors of the Armed Services
Vocational Aptitude Battery (ASVAB; vocational-technical information, clerical/speed, verbal
ability, and mathematics) exhibited near-zero correlations with scores on a TK test for managers.
A few studies have found significant correlations between
g and TK, but these
relationships are not always in the positive direction. In research with military leaders, scores on
a verbal reasoning test (Terman, 1950) exhibited correlations ranging from near zero and
nonsignificant, to moderate and significant (r = .25, p < .01), with a TK test for military leaders
(Sternberg et al., 2000). The result regarding the moderate relationship of TK to Terman’s test is
not surprising given that many of these officers had demonstrated high levels of academic
achievement prior to assuming their leadership positions. More importantly, as we review below,
TK scores explained variance in leadership performance beyond scores on the verbal reasoning
test, thus indicating that TK tests are measuring something distinct from g. A study by Fox and
Spector (2000) also found a moderate and significant correlation (r = .25, p < .01) between
scores on a practical intelligence test and g with a sample of undergraduate students. Although
these results indicate that tests of practical and general intelligence may share some common
variance, they do not suggest that they are measuring the same construct.
In contrast to the above findings showing a positive relationship between TK scores and
g, one study conducted in Kenya found that TK scores actually correlated negatively with scores
on tests of g (Sternberg et al., 2001). These results suggest that, in certain environments, the
development of practical skills may be emphasized at the expense of the development of
academic skills. Such environments are not limited to rural Kenya: Artists, musicians, athletes,
and artisans all may decide that development of skills other than those taught in school can be of
more value to them than are the more academic skills.
Tacit knowledge and personality. In addition to exhibiting discriminant validity from
measures of g, TK tests also appear to be distinct from personality tests. Wagner and Sternberg
(1990) found that TK scores generally exhibited nonsignificant correlations with several
personality-type tests, including the California Psychological Inventory, the Myers-Briggs Type
Indicator, and the Fundamental Interpersonal Relations Orientation-Behavior (FIRO-B) with a
sample of business executives. The exceptions were that TK scores correlated with the Social
Presence factor of the California Psychological Inventory, and the Control Expressed factor of
the FIRO-B. However, TK scores consistently accounted for significant incremental variance
beyond the personality measures, even when the zero-order correlations were significant.
Tacit knowledge and performance. An important criterion for evaluating the validity of
TK tests is their ability to explain individual differences in performance. Simply put, individuals
who learn effectively from experience should be more successful. In addition, because tacit
knowledge is a form of practical intelligence rather than academic intelligence, TK scores should
explain aspects of performance that are not accounted for by indicators of
Tacit-knowledge tests have been found to predict performance in a number of domains
and using a number of criteria. Several studies have found that TK scores correlated significantly
with salary and merit-based increases (Wagner & Sternberg, 1985; Wagner, 1987). Tacit-
knowledge scores have also been found to correlate significantly with performance ratings for
bank managers (Wagner & Sternberg, 1985), military leaders (see Sternberg et al., 2000), and a
general sample of workers in the U.S. and Spain (Grigorenko, Gil, Jarvin, & Sternberg, 2000).
Additional research with academic psychologists and salespeople provides further
validity evidence. Tacit knowledge scores of academic psychologists correlated with measures
of scholarship including citation rate, number of publications, and quality of department
(Wagner, 1987; see also Wagner & Sternberg, 1985). Wagner et al. (1994), found that TK scores
of salespeople correlated with sales volume and sales awards received.
In assessing the predictive validity of TK tests relative to conventional ability tests,
Wagner and Sternberg (1990) found that TK scores of business executives explained 32% of the
variance in performance on a managerial simulation beyond scores on a traditional IQ test. In a
study with military leaders, TK scores accounted for small (4 to 6%) yet significant variance in
leadership effectiveness beyond scores on tests of verbal intelligence. These studies provide
evidence that tacit knowledge accounts for variance in performance that is not accounted for by
traditional tests of abstract, academic intelligence. Other researchers have obtained similar
results. Colonia-Willner (1998) found that TK scores of bank managers significantly predicted
an index of managerial skill, whereas psychometric and verbal reasoning did not. Pulakos,
Schmitt, and Chan (1996) found that a situational-judgment test, designed to measure the
practical intelligence of entry-level professionals in a federal investigative agency, predicted
performance ratings, and that scores on the practical intelligence test were not accounted for by a
measure of
Based on the research to date, several conclusions can be made regarding tacit knowledge
and practical intelligence. First, tacit knowledge generally increases with experience, although
merely spending time on a job does not assure that knowledge will be acquired. Second,
measures of tacit knowledge appear to be distinct from measures of general intelligence and
personality traits. Third, TK tests predict performance in several domains using both objective
(e.g., sales, salary) and subjective criteria (e.g., performance ratings). Finally, studies that have
examined the incremental validity of TK tests have consistently found TK scores to account for
unique variance beyond tests of general intelligence (Wagner, 2000).
The expanding research on practical intelligence and tacit knowledge highlights the
importance of exploring alternative approaches to understanding the competencies associated
with success. More research is needed however to provide further evidence to support these
conclusions, and to catch up to the nearly 100 years of research on g. Given the encouraging
findings so far, a number of promising new directions have emerged in the area of practical
intelligence research and are addressed in the remainder of this report.
New Directions for Research on Practical Intelligence
Tacit knowledge—and practical intelligence more broadly—represents one of several
approaches being pursued to understand the competencies beyond
g that underlie success. This
approach holds particular promise in two areas: (a) understanding how individuals learn from
experience and develop expertise, and (b) the development of methods for identifying and
promoting managerial and leadership potential.
Understanding the Development of Expertise
Tacit knowledge can be viewed as a manifestation of developed expertise resulting from
practical experience. It is well established that experts have an extensive and well-developed
knowledge base in their given performance domain (Chi, Glaser, & Farr, 1988; Ericsson, 1996).
Research also indicates that experts differ from novices in the ways they process information and
solve problems (Charnes, Krame, & Mayr, 1996; Patel & Groen, 1991). Sternberg (1998, 1999a)
has further suggested that intelligence should be characterized a form of developing expertise.
According to this view, intelligence is a function of an ongoing interaction of genetic and
environmental factors that results in the acquisition and consolidation of a set of knowledge and
skills needed for high-level mastery in one or more performance domains. As such,
understanding how individuals learn from experience and acquire tacit knowledge can provide
insight into both the development of expertise and practical intelligence.
Many researchers have explored the development of expertise, but primarily focused on
the stages of knowledge acquisition in individuals (Anderson, 1987, 1993) or the role of
deliberate practice (e.g., Ericsson, 1996). Anderson’s ACT theory, for example, is aimed at
understanding the stages involved in skill acquisition. Individuals first encode information in a
declarative form. In the next stage, this declarative knowledge becomes represented as
procedures about what to do in certain situations. Eventually, the procedures become highly
automated, thus requiring fewer cognitive resources on performing the task.
Our focus is on understanding the cognitive processes underlying the development of
expertise, or more specifically, the acquisition of tacit knowledge. By understanding these
processes, we can explore new methods of measuring an individual’s potential to learn, and new
approaches to facilitating learning from experience. Preliminary work aimed at understanding the
acquisition of tacit knowledge is reviewed next, and implications of this work for the assessment
and development of practical intelligence are then discussed.
Knowledge-acquisition processes. The first study to explore TK acquisition was an
experiment conducted by Okagaki, Sternberg, and Wagner (cited in Sternberg et al., 1993),
which focused on methods of facilitating the acquisition of TK. The study examined three key
acquisition processes discussed earlier: selective encoding, selective combination, and selective
comparison. Various cues were provided to participants to help them (a) to distinguish relevant
from irrelevant information (selective encoding), (b) to integrate information according to rules
of thumb (selective combination), and (c) to relate the information to prior knowledge or
experience (selective comparison).
Okagaki et al. found that individuals who received the selective-encoding and selective-
combination prompts exhibited the most gain in scores on a TK test. These findings suggest that
prompting individuals to selectively encode and selectively combine information can enhance
the acquisition of tacit knowledge. How well individuals use these processes on their own
without prompting may provide valuable insight into their potential to learn, or more generally,
their practical ability.
Practical problem-solving skills. A second study currently underway, focuses more
broadly on the information-processing components that are applied to solving everyday problems
(Antonakis et al., 2001). According to Sternberg (1985, 1997), information-processing
components consist of metacomponents, performance components, and knowledge-acquisition
components. Metacomponents, or metacognitive skills, are executive processes used to plan,
monitor, and evaluate problem solving. These processes include problem recognition, problem
definition, allocation of resources, strategy formation, solution monitoring, and outcome
evaluation. Performance components are processes applied directly to solving problems, and
include inferring relations between stimuli, applying relations inferred in one situation to
another, and comparing items of information. Finally, knowledge-acquisition components refer
to the processes previously described: selective encoding, selective combination, and selective
comparison. These components are used interactively in the process of solving and learning from
everyday problems.
Some researchers have associated these processes with the development of expertise
(e.g., Dorner & Scholkopf, 1991; Smith, Ford, & Kozlowski, 1997). Dorner and Scholkopf
(1991) suggested that experts tend to exhibit better use of metacognitive skills, or
metacomponents, than do novices. They are better able to monitor the effectiveness of their
problem-solving strategies and to modify ineffective strategies as needed. Smith et al. (1997)
suggested that metacognitive skills facilitate the development of what they call “adaptive
expertise” by enabling individuals to “recognize novelty or change, select potential responses,
monitor and evaluate progress, and modify or create different responses to the task if necessary”
(p. 96).
These information-processing components serve as the basis for our approach to
measuring an individual’s potential to learn from experience and thus develop expertise in a
given domain. In other words, we are attempting to measure how well the individual (a) defines a
problem, (b) decides what information to attend to and how to interpret the information, (c)
generates and evaluates a set of solution alternatives, and (d) chooses and monitors a course of
action. These processes are measured using detailed, complex problem descriptions, akin to
those found in in-basket tests or case studies. Individuals are presented with 1-2 pages of
background on the problem along with various supporting documents (e.g., memos, financial
reports, performance evaluations, email exchanges, etc.). They are asked to read and sort through
the information, and to answer a set of open-ended questions designed to assess their use of
various problem-solving processes. Sample questions include: “What do you consider to be the
main problem to be addressed? What information did you focus on in defining the problem? and
What course of action would you take to address the problem you identified?” Rating scales to
judge the responses of novices are developed for each of the questions by categorically
aggregating responses of experts to create a “gold-standard” scoring schema. Novices who
generate a response, as identified by experts, receive a score based on the weighting (i.e., the
frequency) of the experts’ response. In this way, a measure of the efficacy of novices’ responses,
that is, of how well they exhibit each of the metacognitive processes in managing the case-study
problem, can be developed.
Preliminary findings aimed at understanding the acquisition of tacit knowledge indicate
that more experienced officers (i.e., Captains) score significantly higher than less experienced
officers (i.e., Lieutenants) on the scale composites (Antonakis, et al., 2001). Based on these
findings, it appears that metacognitive skills of novices are not as well developed as those of
more experienced individuals.
Measuring Practical Intelligence Through Learning Potential
A similar approach to examining practical problem-solving skills has been utilized to
measure the practical intelligence of MBA program applicants (Hedlund et al., 2001). This
project was initiated by the University of Michigan Business School to develop a measure of
managerial potential for MBA applicants as a supplement to the widely used Graduate
Management Admissions Test (GMAT). The GMAT, like most standardized aptitude tests, may
be a better indicator of how an individual will perform on academic rather than practical
problems. Because the goal of most business schools is to produce top business leaders in
addition to successful students, developing a measure of an individual’s potential to be a
successful leader through the ability to solve practical problems is a promising approach.
In the initial stage of this research, we explored two methods of measuring practical
intelligence. One is based on the method of measuring tacit knowledge described earlier, which
uses situational judgment problems (SJPs); the other is based on the approach to measuring
practical-problem solving skills, which uses case scenario problems (CSPs). Several
management scenarios were developed and administered to two incoming classes of over 800
MBA students. Data were collected on each student’s GMAT score, undergraduate GPA, first
year GPA in the MBA program, and performance evaluation for an applied consulting project.
Additional data will be collected on job placements, salaries, and job satisfaction.
Preliminary analyses have been conducted on data from the first class and indicate that
scores on both the situational judgment and case scenario problems predicted first year GPA
(academic performance) and ratings on the applied project (practical performance). In addition,
scores accounted for variance in GPA and applied project grade beyond that accounted for by
GMAT scores and undergraduate GPA. The case scenario problems, which measure practical
problem-solving skills, provided greater incremental validity than did the situational judgment,
or tacit knowledge, problems. The results so far are encouraging and lend support to the claim
that success on academic and nonacademic problems depends on more than what is measured by
conventional intelligence or ability tests. However, further research is required before conclusive
findings can result.
Facilitating Learning from Experience
Finally, in addition to evaluating an individual’s potential to become a successful leader,
our approach to measuring metacognitive processes underlying the practical intelligence of
individuals may be applied to the development of more effective managers and leaders. Because
experience is arguably the most important source of learning for managers and leaders (Davies &
Easterby-Smith, 1984; McCall et al., 1988; Wagner & Sternberg, 1985), it makes sense to
provide opportunities for individuals to capitalize on their experiences. One way to enhance
experience is to learn about the experiences of successful individuals. Reading about a situation
someone else has faced can help an individual reflect on an experience he or she has encountered
or can prompt the individual to seek out the types of experiences that will promote his or her own
learning. Tacit-knowledge scenarios may provide a valuable source of lessons from experience.
A second way to promote learning from experience is to help individuals develop the
skills underlying knowledge acquisition. Clearly some individuals learn more effectively from
their experiences than do others. Once a better understanding of the processes that underlie the
acquisition of tacit knowledge is gained through research like that described above, efforts could
be directed toward promoting the development and use of these processes in individuals. For
example, individuals could be taught strategies to help them to selectively encode, selectively
combine, and selectively compare information, as in the study by Okagaki et al (cited in
Sternberg et al., 1993). Alternatively, individuals could be given practice defining problems,
sorting information, generating solutions, and monitoring outcomes in the context of realistic
problem scenarios. Continuous feedback could be provided to these individuals on how
effectively they used these processes, allowing them to correct inappropriate strategies and thus
to learn how to regulate their metacognitive abilities.
The identification, assessment, and development of practical problem-solving skills
represent promising new directions in the study of practical intelligence and tacit knowledge.
There are, however, many areas that require further research attention.
First, additional research is needed to build on the findings that tacit knowledge is related
to experience and performance, yet is distinct from general cognitive ability and personality. A
related issue that needs to be addressed is the relationship among the various conceptualizations
of intelligence. As the proliferation of these concepts continues, it will be important to determine
whether social intelligence, emotional intelligence, and practical intelligence are distinct
constructs or represent components of a common construct.
Second, several researchers have called for more efforts to understand how individuals
learn from their experiences and what factors predict how well an individual will learn on the job
(McCauley et al., 1994; Tesluk & Jacobs, 1998). The potential to learn and adapt will become
increasingly important in light of rapidly changing technologies, increasing globalization, and
changing workforce demographics. Measures like those being pursued with MBA business
students and military leaders may become increasingly useful in the future.
Finally, once the practical learning process is better understood, methods for enhancing
experience-based learning can be developed and tested. Such research might explore the
effectiveness of metacognitive skills, learning strategies, or different instructional methods (e.g.,
discovery learning) for improving an individual’s ability to learn from experience. The evidence
to date from our own research program as well as research by others suggests that practical
intelligence and tacit knowledge are promising avenues for further understanding the
competencies underlying successful real-world performance.
Preparation of this paper was supported by the U.S. Army Research Institute (contracts
DASW01-99-K-0004 and DASW01-00-K-0014). Although we are grateful to these agencies for
their support, the ideas expressed in this paper are solely those of the authors and do not
represent any official position or policy on the part of these agencies. Send correspondence to
Robert J. Sternberg, The PACE Center, Yale University, 340 Edwards Street, P.O. Box 208358,
New Haven, CT 06520-8358.
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Figure 1. Sample question from the tacit knowledge inventory for military leaders.
1 2 3 4 5 6 7 8 9
Nor Good
You are a company commander, and your battalion commander is the type of person who seems
always to "shoot the messenger"--he does not like to be surprised by bad news, and he tends to
take his anger out on the person who brought him the bad news. You want to build a positive,
professional relationship with your battalion commander. What should you do?
_____ Speak to your battalion commander about his behavior and share your perception of it.
_____ Attempt to keep the battalion commander "over-informed" by telling him what is
occurring in your unit on a regular basis (e.g., daily or every other day).
_____ Speak to the sergeant major and see if she/he is willing to try to influence the battalion
_____ Keep the battalion commander informed only on important issues, but don't bring up
issues you don't have to discuss with him.
_____ When you bring a problem to your battalion commander, bring a solution at the same
_____ Disregard the battalion commander's behavior: Continue to bring him news as you
normally would.
_____ Tell your battalion commander all of the good news you can, but try to shield him from
hearing the bad news.
_____ Tell the battalion commander as little as possible; deal with problems on your own if at all
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Summary The purpose of this research was to examine the potential application of the police officer tacit knowledge inventory (POTKI) as a police recruit screening tool. The POTKI is a situational judgment test and consists of knowledge gained on the job by experienced officers that is thought to be important for problem-solving. In the present study, four police agencies from a western US state administered the POTKI along with other screening measures to police applicants. Performance of the novice recruits was subsequently rated by their supervisors using the measure of professional expertise (MOE). Principal component analysis, multiple regression analysis, and multivariate analysis of variance were conducted on the POTKI response options. POTKI response options were found to be predictive of supervisor MOE ratings. Principal component analysis results identified intrapersonal tacit knowledge components that predicted MOE metacognitive, skill, and social recognition supervisor ratings and distinguished novice from expert police officers.Copyright
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A PhD thesis submitted for a PhD in Economics and Management by Kyoko Sakuma on 18 June, 2012.
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Research summarizes the construction of a Police Officer’s Tacit Knowledge Inventory (Inventory), a situational judgment test comprised of knowledge gained on-the-job by experienced police officers, and examines if it can play a role in the development of expertise. Correlation and regression analysis was done to establish the Inventory’s ability to predict post-Academy graduation performance. Results show that Inventory response patterns correlate with Supervisor ratings; and the Inventory responses correctly predict significant differences between novice patrol officers and experienced police officers.
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Ceci, S. & Roazzi, A. (1994). The effects of context on cognition: Postcards from Brazil. In: R. J. Stenberg & R. K. Wagner (Eds.), Mind in context: Interactionist perspectives on human intelligence (pp. 74-101). Cambridge: Cambridge University Press. Traditional views of abilities have viewed them as internal properties of the organism. The views presented in this book, in contrast, view abilities as inhering in the interaction between minds and the contexts in which they are found. Some of the greatest psychologists of all time, such as Piaget and Vygotsky, have recognised the importance of person-context interaction to the development of intelligence, and even fervent hereditarians have recognised the extent to which when genotypes are expressed phenotypically, there is a reaction range that can limit or enhance the extent to which the genotype is expressed in the environment. The book is divided into three main parts. Part I, focusing on academic tasks, contains chapters by R. E. Snow on abilities in academic tasks, M. K. Gardner on novelty and intelligence, and S. J. Ceci and A. Roazzi on the effects of context on cognition. Part II, focusing on everyday tasks, contains chapters by C. A. Berg and K. S. Calderone on the role of problem interpretations in understanding the development of everyday problem solving, R. K. Wagner on use of cognitive tests in job selection, and F. E. Fiedler and T. G. Link on leader intelligence, interpersonal stress, and task performance. Finally, Part III, containing general perspectives, contains chapters by N. Granott and H. Gardner on interactions, coincidence, and development in domains of ability, J. Valsiner and M.-C. Leung on a sociogenetic process approach to abilities, and R. J. Sternberg on an integrative framework for understanding mind in context. Contents Part I. Academic Tasks: 1. Abilities in academic tasks R. E. Snow; 2. Novelty and intelligence M. K. Gardner; 3. The effects of context on cognition: postcards from Brazil S. J. Ceci and A. Roazzi; Part II. Everyday Tasks: 4. The role of problem interpretations in understanding the development of everyday problem solving C. A. Berg and K. S. Calderone; 5. The case of cognitive ability testing for job selection R. K. Wagner; 6. Leader intelligence, interpersonal stress, and task performance F. E. Fiedler and T. G. Link; Part III. General Perspectives: 7. When minds meet: interactions, coincidence, and development in domains of ability N. Granott and H. Gardner; 8. From intelligence to knowledge construction: a sociogenetic process approach J. Valsiner and M.-C. Leung; 9. PRSVL: an integrative framework for understanding mind in context R. J. Sternberg.
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This article summarizes the practical and theoretical implications of 85 years of research in personnel selection. On the basis of meta-analytic findings, this article presents the validity of 19 selection procedures for predicting job performance and training performance and the validity of paired combinations of general mental ability (GMA) and the 18 other selection procedures. Overall, the 3 combinations with the highest multivariate validity and utility for job performance were GMA plus a work sample test (mean validity of .63), GMA plus an integrity test (mean validity of .65), and GMA plus a structured interview (mean validity of .63). A further advantage of the latter 2 combinations is that they can be used for both entry level selection and selection of experienced employees. The practical utility implications of these summary findings are substantial. The implications of these research findings for the development of theories of job performance are discussed.
'I shall reconsider human knowledge by starting from the fact that we can know more than we can tell', writes Michael Polanyi, whose work paved the way for the likes of Thomas Kuhn and Karl Popper. "The Tacit Dimension", originally published in 1967, argues that such tacit knowledge - tradition, inherited practices, implied values, and prejudgments - is a crucial part of scientific knowledge. Back in print for a new generation of students and scholars, this volume challenges the assumption that skepticism, rather than established belief, lies at the heart of scientific discovery.
Two experiments were conducted to examine the scope and structure of tacit knowledge. In Experiment 1, three groups, whose members differed in level of professional advancement in the field of academic psychology, were presented with simulated work-related situations designed to measure their tacit knowledge. Between-group differences in tacit knowledge were found as a function of level of professional advancement, and strong within-group relations were found between tacit knowledge and external criteria such as rate of citation. The scope of tacit knowledge was found to include (a) knowledge useful in managing oneself, others, and one's tasks, (b) knowledge applicable to both short-term and long-term contexts, and (c) knowledge of ideal quality as well as practical reality. The results of testing four classes of alternative models of the structure of tacit knowledge supported a model characterized by a general factor, similar in form to Spearman's g for academic tasks. Experiment 2 replicated and extended these results to the domain of business management.