TAPAS: Tailored Adaptive Personality Assessment System
TAILORED ADAPTIVE PERSONALITY ASSESSMENT SYSTEM (TAPAS)
Fritz Drasgow, Stephen Stark, and Sasha Chernyshenko
Drasgow Consulting Group
Introduction
Over the past 5 years, we have worked on developing a comprehensive assessment system,
which we refer to as the Tailored Adaptive Personality Assessment System or TAPAS. This
work is supported by an SBIR grant from the Army. Dr. Len White, Contracting Officer’s
Representative.
In our approach, we have combined modern psychometric methods, computing technology, and
research findings from the personnel selection and personality domains to create a system that is
innovative not only in terms of how personality constructs are being measured (i.e., the
psychometric underpinnings of TAPAS), but also what aspects of personality should be
measured, at what level of generality, and for what purposes (i.e., the content of TAPAS).
In a nutshell, TAPAS is designed to be easily customizable to meet the assessment needs of
virtually any civilian or military organization, both in terms of test content and test
administration. Unlike previously available instruments, TAPAS allows users to choose:
1) the response format (items can be presented as single stimulus or two-alternative
forced-choice);
2) the scale length (the user decides on the number of items per personality dimension);
3) the constructs/traits to be assessed (the user picks which traits to administer); and
4) the item presentation algorithm (static forms for everyone or adaptive item selection
tailored to a specific examinee).
Background
TAPAS has its roots in the growing interest in temperament/personality as a predictor of job
performance and other outcomes over the last fifteen years. This increase has been caused by:
 legal and societal concerns about adverse impact associated with the use of intelligence
test scores for selection and promotion;
 empirical evidence showing that temperament constructs provide incremental validity
beyond general cognitive ability in predicting performance across a diverse array of
civilian and military occupations (e.g., Barrick & Mount, 1991; Campbell & Knapp,
2001; Schmidt & Hunter, 1998); and
 the search for a means of predicting contextual performance, adaptability, and retention
of employees because cognitive predictors have little or no ability to predict these
outcomes.
To illustrate, in 2005 the U.S. Defense Manpower Data Center convened a four-member Review
Panel of experts in the areas of personnel selection and psychometrics to consider changes for
the Armed Services Vocational Aptitude Battery (ASVAB). Representatives of the Services told
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TAPAS: Tailored Adaptive Personality Assessment System
the Review Panel that their leadership criticized the ASVAB because it provided little help with
respect to:
 predicting adaptability to the Service;
 creating a culture with a strong commitment to the Service;
 enhancing disciplined initiative;
 fostering teamwork;
 improving problem solving skills;
 promoting continuous learning.
With the exception of problem solving, it is unlikely that any cognitive ability test battery can
help.
Despite the clear need, noncognitive selection tools have been little used by the military. For
example, in the early 1990s, Navy researchers Tom Trent and John Pass sought to implement a
single statement personality measure called the ASAP and Army researchers Len White and
Mark Young had similar intentions for an instrument called the ABLE. An impressive set of
studies showed that these measures predicted important behaviors (e.g., White, Nord, Mael, &
Young, 1993; White, Young, & Rumsey, 2001). Nonetheless, the Department of Defense
Advisory Committee on Military Personnel Testing recommended against implementation
because of concerns that single statement items were easily compromised by faking good (White
et al., 1993).
In sum, there is a critical need for a well-designed personality assessment system capable of
supporting the aforementioned personnel objectives. Developing such system presents a
formidable psychometric challenge. Not only must it be valid for the purposes listed above, but
it must also resist socially desirable responding and, perhaps, be implemented in a way that
minimizes applicants’ motivation to fake good.
Existing Personality Assessment Systems
Nearly all personality inventories available today have evolved from measures developed for
research purposes. As a consequence, the majority of batteries consist of many scales having 10
or so single stimulus items (i.e., the items consist of statements like “I enjoy meeting new
people”) developed and scored using classical test theory methods. Such scales, however, are
more useful in research and counseling settings than for making important personnel decisions.
First, in high stakes testing situations, research shows that single statement temperament items
can be easily faked; i.e., test takers can discern the correct or socially desirable answers and,
thus, increase or decrease their scores to suit their personal needs (White & Young, 1998). This
intentional distortion can severely undermine the utility of temperament measures. Second,
currently used scales are not constructed to measure accurately across all levels of the trait
continuum. Specifically, because classical test theory methods are used to evaluate and choose
items during scale development, only those having moderately positive and moderately negative
standing on the underlying trait continuum are retained; extreme and neutral items are discarded
(Stark, Chernyshenko, & Drasgow, 2003, 2005). This degrades the validity of the rank-order of
high and low scoring individuals who are often of primary interest in selection contexts. Finally,
traditional temperament measures are inefficient and cumbersome to administer and maintain.
They have rigid administration prescriptions in the sense that all items must be administered to
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TAPAS: Tailored Adaptive Personality Assessment System
every individual in a fixed order. This increases testing time and decreases test security through
repeated item exposure. In addition, because organizations are often interested in different
subsets of scales for different occupations, it would be better to have a flexible way of choosing
the constructs assessed on particular occasions, an option not available in most current
inventories.
There have been several attempts to develop inventories having items in a forced-choice rather
than the single statement format (items in these “forced-choice” measures typically consist of
four statements representing different dimensions and respondents are asked to select “most like
me” and “least like me” statements). This alternative format appears to be more resistant to
response distortion, and thus may provide solutions to the faking problem (Jackson, Wrobleski,
& Ashton, 2000). Yet, adopting such inventories brings a new set of psychometric challenges.
First, traditional scoring of forced-choice items produces ipsative or partially ipsative scores.
This means that when a person’s score on a trait is high, it is high relative to that particular
person’s score on other traits. Scores on ipsative measures cannot be interpreted normatively,
i.e., when a person’s score is high, we do not know if it is high relative to other people. Thus,
ipsative measurement raises concerns of between person score comparability. Second, no formal
psychometric model is usually specified, which makes it difficult to evaluate score precision or
to anticipate the performance of newly constructed items. Third, all test items must be
administered to examinees and even small changes in scale length or item composition
compromise the comparability of scores across examinees or test administrations. Finally, to
obviate ipsativity problems, it is usually recommended that a large number of scales be
administered, which is time consuming and often impractical in applied contexts.
Tailored Adaptive Personality Assessment System (TAPAS)
How does TAPAS measure?
The TAPAS measurement approach is rooted in item response theory (IRT) and thus is similar to
such well-known tests as the ASVAB or the Graduate Record Exam (GRE). For each TAPAS
dimension, there is a pool of items that have been pre-calibrated using large representative
samples of military recruits. In computerized settings, to increase test efficiency, items are
selected adaptively and depend on an individual’s previous responses (a.k.a., adaptive item
presentation). If computerized testing is unavailable, then items can be pre-assembled into scales
and presented to examinees (a.k.a., static item presentation).
Unlike ASVAB and many personality measures, TAPAS is designed to be extremely flexible in
its assessment approach. Instead of having a single response format for presenting items and a
single psychometric model for item selection and scoring, TAPAS personality items can be
administered in 4 response formats, each having its own computer adaptive item selection and
scoring algorithms:
1) Single statement dichotomous response format (Agree/Disagree) administered and
scored using the three-parameter logisitic (3PL) model (Birnbaum, 1968) of item
response theory.
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TAPAS: Tailored Adaptive Personality Assessment System
.
In this format, statements are presented one at a time and examinees asked to if they
agree/disagree with the statement. Examples of existing personality inventories using
this format are the California Psychological Inventory and the Hogan Personality
Inventory. (Note that the CPI and HPI are currently scored using classical total score
methods and, hence, don’t have adaptive item selection.)
2) Single statement polytomous response format (Strongly Disagree,
Disagree/Agree/Disagree) administered and scored using the SGR model (Samejima,
1968).
In this format, statements are presented one at a time and examinees asked to indicate the
degree of agreement with the statement using a 4-point Likert scale. Examples of
existing personality inventories using this format are the NEO-PI and Goldberg’s AB5C
(Note that the NEO-PI and AB5C are currently scored using classical total score methods
and, hence, don’t have adaptive item selection. These inventories are also administered
in a 5-point Likert format where the middle option is “Neutral.” TAPAS does not have a
neutral option, because research [Hernández, Drasgow, & González-Romá, 2004] shows
that middle options can be misinterpreted).
3) Unidimensional pairwise preference response format (“Which of these two statements
is more like you?) administered and scored using the Zinnes-Griggs (1974) model and
algorithms developed by Stark and Drasgow (2002) and Stark, Chernyshenko, and
Drasgow (2006).
In this format, statements representing the same personality dimension are presented in
pairs. Examinees are asked to choose one statement that is more descriptive of them.
Examples of existing personality inventories using this format are NCAPS (Note that
NCAPS runs an earlier adaptive item selection algorithm developed by Stark and
Drasgow (2002). The TAPAS algorithm, which was developed by Stark, Chernyshenko
and Drasgow in 2006, is different in terms of how pairs of statements are selected).
4) Multidimensional pairwise preference response format (“Which or the two statements
is more like you?) administered and scored using the multidimensional pairwise
preference (MDPP) model and algorithms developed by Stark (2002) and Stark,
Chernyshenko, and Drasgow (2005).
In this format, statements representing different personality dimension are presented in
pairs. Examinees are asked to choose one statement that is more descriptive of them.
This format is unique to TAPAS. Other multidimensional forced choice inventories
typically are composed of items having 4 statements (a.k.a., tetrad) and respondents are
asked to choose the statements that are the most and least like them. Examples of
existing personality inventories using the tetrad format are Assessment of Individual
Motivation and Occupational Personality Questionnaire (Note that AIM and OPQ are
scored using classical methods and don’t have adaptive item selection.).
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TAPAS: Tailored Adaptive Personality Assessment System
Each of the four response format has its own advantages. The choice of formats depends largely
on the goal of the assessment; the single statement format should probably be favored more for
counseling purposes whereas the forced choice format is more suitable for personnel selection
purposes. Our primary interest to date has been in the multidimensional pairwise preference
(MDPP) format, because it shows the most promise in operational testing contexts where
intentional response distortion is likely.
Our SBIR research has shown that resistance to response distortions seems to be a function of
how multidimensional pairs are formed. We have conducted a number of experiments that
investigated the link between pair fakability and various item parameters (e.g., statement social
desirability, location, etc…). In TAPAS, we can manipulate constraints on how MDPP items are
created depending on the degree of the user’s concern about response distortion.
The adaptive testing format, regardless of the response format or psychometric model used,
offers greater test efficiency than the static, fixed length format. In addition, adaptive testing has
better test security, because each examinee receives what is essentially a unique parallel test
form.
Nevertheless, using TAPAS and our existing item pool, we can create multiple static forms for
any of the four response formats. An example of this is the TAPAS-static95 form that was
created in collaboration with ARI and is currently being administered under the EEE Metrics
effort of HUMRRO and ARI. The TAPAS-static95 form measures 12 personality dimensions
that were selected based on prior empirical research to predict attrition and training performance.
There are a total of 95 fake-resistant item pairs that were selected based on Drasgow Group and
ARI pre-testing research.
The computerized administration of TAPAS is now possible via the Drasgow Group Internet
server. Computer adaptive testing algorithms have been implemented for SGR, ZG and MDPP
models. We are currently working on the 3PL algorithm, which will underlie the single
statement dichotomous response format. Our simulation studies involving ZG and MDPP
models for unidimensional and multidimensional pairwise preference formats have shown good
recovery of trait scores with tests having 10-15 statements per personality dimension. In other
words, to measure 10 personality dimensions accurately, one would need between 100 to 150
items.
What does TAPAS measure?
A comprehensive set of nonredundant narrow facets of fundamental personality traits constitutes
the basic building blocks of TAPAS. Rather than adhering to some existing rational or
theoretical nomenclature (e.g., NEO-PI or 16PF), our approach to developing the lower-order
trait taxonomy was rooted in examining results of large scale empirical factor-analytic studies,
conducted using subjects’ responses to a maximally diverse array of temperament indicators
(e.g., adjectives, behavioral statements, or scales).
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TAPAS: Tailored Adaptive Personality Assessment System
Two studies were utilized. The first study by Saucier and Ostendorf (1999) examined the
structure of 500 adjectives describing human behavior (i.e., assertive, talkative, anxious). The
second empirical study, conducted by the members of our research team together with
researchers from several US Universities, focused on scales from 7 widely used personality
inventories. By factor analyzing responses to scales contained in these seven personality
measures, we were able to establish a shared overall hierarchical structure linking broader,
general temperament traits and narrower facets.
A total of 22 lower-order facets were initially identified (3-6 facets per Big Five dimension).
Within each broad Big Five domain, the lower-order facet structure was organized hierarchically.
This is advantageous for applied purposes because the TAPAS system can report trait scores at
any level of generality, ranging from 5 to 22 dimensions. Moreover, the availability of pattern
loading matrices for each domain allowed us to identify empirical markers for nearly all 22
facets (in the form of adjectives or existing scales). These are important for future construct
validity investigations. Finally, specific to military applications, we added the Physical
Conditioning facet, which we placed on the Extraversion broad factor due to its high positive
correlations with Dominance and Energy facets.
Table 1 presents a summary of the current 23 facet TAPAS taxonomy. The table is organized
into 5 broad clusters representing the Big Five (see column 1). Within these clusters, each row
presents the TAPAS facet name (column 2) followed by examples of other scales assessing this
facet (column 3) and a brief description of a typical high/low scorer (column 4). A detailed
example of Conscientiousness related facets can be found in Roberts, Chernyshenko, Stark, and
Goldberg (2005).
TAPAS can administer any of these 23 facet dimensions in any of the 4 response formats. If the
goal is to provide counseling or developmental feedback then a more comprehensive assessment
is warranted and we would suggest selecting 15-23 facets. In personnel selection contexts, the
facet selection is determined mainly by the types of criteria being predicted.
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TAPAS: Tailored Adaptive Personality Assessment System
Table 1. Lower Order Facet Taxonomy for TAPAS: Trait Names, Markers, and Descriptions
Extraversion
Broad
Factor
TAPAS Facets
Brief Description
Dominance
AIM Leadership, cpi
independence, cpi
dominance, hpi leadership
High scoring individuals are domineering, take charge and are
often called by their peers as "natural leaders".
Sociability
ab5c sociability,neo
gregariousness, jpi social
Describes individual's level of interest in friendly social
interactions.
Unrestraint
neo excitement seeking, hpi
exhibitionistic, hpi
entertaining
Individuals scoring high on the Unrestrained facet engage in
behaviors attract a lot of social attention; they are loud,
loquacious, entertaining, and even boastful.
jpi energy, neo activity,
ABLE energy
High scoring individuals have a lot of energy, can forego sleep
without much detriment to performance, and are interested in
physical activity.
Physical
Condition
ABLE Physical Condition,
AIM Physical Condition
High Scoring individuals routinely participate in vigorous sports
or exercise and enjoy hard physical work.
Warmth
ab5c warmth, 16pf warmth,
neo warmth
Individuals scoring high on this facet are affectionate,
compassionate, sensitive, and caring.
ab5c cooperation, neo
modesty
Individuals scoring high on this facet are generous with their
time and resources, while individuals scoring low are egoistical,
greedy, and snobbish.
Energy
Agreeableness
Key Existing Scale Markers
Generosity
neo trust, hpi no hostility,
hpi trusting, ab5c
Cooperation/Trust
pleasantness, hpi easy to live
with
Individuals scoring high on this facet are trusting, cordial, noncritical, and easy to live with, while those scoring low are
skeptical, suspicious, and even combative.
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TAPAS: Tailored Adaptive Personality Assessment System
Industriousness
Conscientiousness
Order
Self-control
neo order, 16pf
perfectionism, jpi
organization, NCAPS
Dependability
ab5c cautiousness, neo
deliberation, mpq selfcontrol, NCAPS vigilance
Individuals with high scores on this factor would be described as
hard working, ambitious, confident, and resourceful.
Emphasizes the ability to organize tasks and activities and the
desire to maintain neat and clean surroundings.
Individuals with high scores on Self-control tend to be cautious,
levelheaded, able to delay gratification, and be patient.
Responsibility
cpi responsibility, jpi
responsibility, ABLE
Nondeliquency
Individuals with high Responsibility scores like to be of service
to others, frequently contribute their time and money to
community projects, and tend to be cooperative and dependable.
Traditionalism
mpq traditionalism, 16pf
rule consciousness, ABLE
Nondelinquency
People with high scores on Traditionalism tend to comply with
current rules, customs, norms, and expectations; they dislike
changes and do not challenge authority.
cpi good impression, hpi
virtuous
Virtue represents a constellation of beliefs and behaviors
associated with adherence to standards of honesty, morality, and
“good Samaritan” behavior.
No Anxiety
16pf apprehensive, jpi
anxiety, neo anxiety, hpi not
anxious, mpq stress reaction
Individuals scoring low on the No Anxiety facet are high strung,
self-conscious and apprehensive regardless of the type of
situation they are dealing with.
Even Tempered
ab5c calmness, neo hostility,
hpi even tempered, NCAPS
Stress Tolerance
Those scoring low on this facet have a tendency to experience a
range of negative emotions including irritability, anger, hostility,
or even aggression; those scoring high tend to be calm, even
tempered, and stable.
Virtue
Emotional Stability
AIM Work Orientation,
NCAPS achievement, neo
competence, neo
achievement striving
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Openness To Experience
TAPAS: Tailored Adaptive Personality Assessment System
Well-Being
neo depression, ab5c
happiness, cpi well-being
The aim is to assess an individual’s general emotional tone. The
continuum here is despair and depression on the one end, and joy
and well-being on the other.
Intellectual
Efficiency
hpi good memory, hpi
reading,cpi intellectual
efficiency, ab5c intellect
Individuals with high scores on this factor are able to process
information quickly and would be described by others as
knowledgeable, astute, and intellectual.
Ingenuity
ab5c Ingenuity, hpi
generates ideas,ab5c
competence, jpi innovation
A prototypical individual scoring high on the Ingenuity facet is
an inventor, a person who constantly strives to make
improvements to the existing information or products.
Curiosity
16pf sensitivity, hpi
curiosity, hpi science ability,
hpi thrill seeking
Individuals with high scores on this facet would be characterized
as inquisitive and perceptive; they read popular
science/mechanics magazines and are interested in
experimenting with objects and substances.
Aesthetics
neo aesthetics,ab5c
reflection, mpq absorption,
neo feelings, hpi culture
Individuals scoring high genuinely enjoy acquiring,
participating, or creating various forms of artistic, musical, or
architectural outputs
Tolerance
cpi flexibility, neo values,
cpi psychological
mindedness, jpi tolerant
Individuals scoring high on Tolerance like to attend cultural
events or meet and befriend people with different views. They
also tend to better adapt to novel situations.
Depth
16pf abstractness, ab5c
High scoring individuals exhibit behaviors targeted toward
depth, ab5c introspection, jpi understanding the meaning of one’s life and/or facilitating selfcomplexity
improvement and self-actualization.
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TAPAS: Tailored Adaptive Personality Assessment System
Validity of TAPAS personality dimensions
The primary purpose of TAPAS is to help organizations to improve the utility of their
selection systems as well as facilitate personal development. Selection systems, however,
can be quite diverse and target a number of criteria, ranging from job performance (task
proficiency and citizenship) to identifying leadership potential or decreasing attrition.
Adding further to this complexity is the fact that personality/temperament measures used in
the past are not easily comparable to each other and differ markedly in the content and
breadth of constructs assessed. This leads to a lack of consensus among researchers and
applied users about which specific personality facets to use for which criterion.
Our TAPAS validation research aims at overcoming the existing limitation by conducting a
comprehensive meta-analysis of personality-criterion relationships in military contexts. To
do that, we first mapped most existing scales and measures to the unified facet structure
described above (i.e., the Big Five – 23 facet TAPAS taxonomy). We used results of our
factor analyses to empirically identify which scales from seven widely used personality
inventories (i.e., 16PF, NEO, HPI, CPI, MPQ, AB5C, and JPI) had high loadings on which
TAPAS facets. Once this initial set of markers for TAPAS facets was identified, we then
examined the research literature to find other related scales. The resulting tables are similar
to the one presented in Table 2. In this table, we show known scale markers for the
Industriousness facet of TAPAS. As can be seen in the table, four NEO-PI and four AB5C
scale have had high empirical loadings on the Industriousness facet (see columns 1 and 2). A
number of other scales were also identified to measure Industriousness including the AIM
Work Orientation scale, the NCAPS Achievement scale, and the MPQ Hard work scale (see
column 3 of Table 2).
Table 2. Scales Measuring TAPAS Industriousness Facet
neo competence
neo achievement striving
ab5c organization
ab5c purposefulness
neo self-discipline
ab5c efficiency
ab5c rationality
neo dutifulness
.88
.76
.75
.67
.65
.63
.50
.49
PRF Achievement
PRF Endurance
ABLE/AIM Work Orientation (Achievement and
Self Esteem composite)
Proactive Personality (Siebery et al., 1999).
CPI Achievement via Independence
Self esteem [(Rosebberg,1965) see Atwater,
1999)
Achievement orientation (CCSQ composite)
TSDI Conscientiousness
PCI achievement
MPQ Hard Work
NCAPS Achievement
OPQ Achieving, Competitive
ABLE Work Orientation, ABLE Achievement
In the second step of the meta-analysis, we identified 42 unique empirical studies published
between 1988 and 2006 that utilized a variety of personality/temperament scales to predict
performance in military, police, or fire fighter occupations. We then coded a total of 1494
criterion-related validities reported in these studies for 8 criteria most relevant to military
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TAPAS: Tailored Adaptive Personality Assessment System
selection contexts: task proficiency, contextual performance, counterproductivity, attrition,
leadership, training performance, adaptability and fitness level. In Table 3, we present an
example of a table summarizing the meta-analytic results for the Industriousness facet.
Column 1 shows the 8 criterion variables, Column 2 refers to the total sample size used to
compute the observed validity coeffcient, Column 3 and Column 4 indicate the number of
study and unique validity coefficients coded, Column 5 presents the observed meta-analytic
estimate of the validity for the Industriousness facet, and Column 6 shows validity after
predictor and criterion measures were corrected for unreliability (Note that when reliability
values were unavailable, we assumed a conservative .8 reliabilities).
As can be seen in the Table 3, the Industriousness facet is most predictive of Contextual
performance (a.k.a., personal initiative), followed by Physical Fitness, Adaptability,
Leadership, and Counterproductivity. Together with similar validity tables for the other 22
TAPAS facets, this information offers much needed guidance for applied researchers and
policymakers in terms of which personality predictors they may wish to consider.
N
kd
kc
Job/Task Performance
38964
14
36
Contextual Performance
19423
9
18
Counterproductivity
17673
8
17
Attrition
17912
5
8
Leadership
9429
12
20
Training Performance
6156
8
27
Adaptability
1291
3
4
18044
5
17
Criterion
.05
.21
-.14
-.09
.15
.14
.17
.18
Corrected
Validity
.06
.26
-.18
-.10
.18
.17
.21
.23

Physical Fitness
Observed
Validity

Table 3. Meta-analytic Validity Estimates for TAPAS Industriousness Facet
Note that similar meta-analytic tables are available for civilian occupations. These tables
currently are based on 4755 validity coefficients sorted into TAPAS facets and the 8 criteria.
Summary
We believe that TAPAS represents the state-of-the-art in personality assessment because it
uses advanced technology, innovative psychometric theory, a comprehensive analysis of
personality facets, and the latest meta-analytic findings concerning the validity of personality
dimensions. The result is a web-based, adaptive assessment tool, customizable in terms of
the facets assessed and the number of items administered per facet, that provides precise
measurement of the facets identified in a comprehensive analysis of the latent structure of
personality.
Of course, it is impossible to “get something for nothing.” TAPAS requires 10 to 15 items
per dimension in order to produce highly accurate trait scores. Because it is adaptive, this
number of items is equivalent to roughly 20 to 25 items per trait administered in a
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TAPAS: Tailored Adaptive Personality Assessment System
conventional static assessment. In addition to adaptivity, TAPAS uses IRT scoring, which is
able to either increase the precision of an assessment tool for a given test length or reduce test
length for a given level of precision. Thus, for a specified level of measurement precision
(i.e., a given reliability level or standard error of measurement), TAPAS provides the shortest
scale length possible.
We suspect that users will find TAPAS’s customization feature very useful. Instead of
requiring every individual to complete every item for a lengthy list of facets, users can select
the set they desire. For example, applicants for jobs in sales might complete the
Industriousness, Energy, Sociability, and Well Being scales. With ten items per facet,
applicants would be able to complete a single statement assessment in perhaps 5 minutes and
a forced choice assessment in perhaps 10 minutes. Thus, with just a few minutes of
applicants’ time, an employer would be able to substantially increase revenue.
In sum, users can consult our meta-analytic results to identify the traits that drive success for
their jobs. They can then instruct TAPAS to assess just these dimensions, resulting in a
highly efficient assessment process. Moreover, because this process is evidence-based, users
can be very confident that the scores of job applicants will be strongly related to the job
performance.
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TAPAS: Tailored Adaptive Personality Assessment System
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