2. 2
Choosing a Career as a Decision-
Making Process: Unique Features
Amount of Information:
Often large N of alternatives
Large N of considerations and factors
Within-occupation variance
Practically unlimited
Quality of Information
Soft, subjective
Fuzzy
Inaccurate or biased
3. 3
Unique Features of Career
Decisions (continued)
Uncertainty
about the individual’s future preferences
about future career options
unpredictable changes and opportunities
the implementation of the choice
Non-cognitive Factors
emotional and personality-related factors
necessity for compromise
actual or perceived social barriers and biases
4. 4
0%
20%
40%
60%
yes somewhat no
CDM Difficulties of 15,000 surfers
on the Future Directions website
(Gati & Meyers, 2003)
Are you experiencing difficulties in making
your career decision?
5. 5
Implications and Conclusion
Many factors contribute to the complexity and
difficulties involved in the career decision-
making process
Career counseling may be viewed as decision
counseling, which aims at facilitating the
clients' decision-making process, and promoting
better career decisions
By adopting decision theory and adapting it to
the unique features of career decisions,
theoretical knowledge can be translated into
practical interventions to facilitate individuals’
career choices
6. 6
How can Theoretical Knowledge and
Empirical Methods be used for
Developing Counseling Instruments?
Today’s Presentation
The three bases of career counseling:
Locating the focuses of the client’s
decision-making difficulties (CDDQ)
Guidance in the decision-making process
The three-stage model (PIC)
Identifying the client’s stage in the
process
Characterizing the client’s decision-making
style (DS)
7. 7
Career Decision-Making
Difficulties
The first step in helping individuals is to locate
the focuses of the difficulties they face in
making career decisions
Gati, Krausz, and Osipow (1996) proposed a
taxonomy for describing the difficulties (see
Figure 1), based on:
the stage in the decision-making process during
which the difficulties typically arise
the similarity between the sources of the
difficulties
the effects that the difficulties may have on
the process and the relevant type of
intervention
8. 8
Prior to Engaging
in the Process
Lack of Readiness
due to
Lack of
motivation
Indeci-
siveness
Dysfunc-
tional
beliefs
During the Process
Lack of Information
about
Cdm
process
Self Occu-
pations
Ways of
obtaining
info.
Inconsistent
Information due to
Unreliable
Info.
Internal
conflicts
External
conflicts
Figure 1: Locating Career Decision-making
Difficulties based on the taxonomy of Gati, Krausz,
& Osipow (1996)
9. 9
The Career Decision-making
Difficulties Questionnaire (CDDQ)
The Career Decision-making Difficulties
Questionnaire (CDDQ) was developed to test
this taxonomy and serve as a means for
assessing individuals’ career decision-making
difficulties
Cronbach Alpha internal consistency
estimates: .70-.90 for the 3 major categories,
.95 for the total CDDQ score
11. 11
Empirical Structure of the
Difficulties (N= 10,000; 2004)
Lack of motivations
Indecisiveness
Dysfunctional beliefs
Lack of info about process
Lack of info about self
LoI about occupations
LoI about addition sources of
help
Unreliable Information
Internal conflicts
External conflicts
12. 12
Computerized Assessment of
Career Decision-Making Difficulties
The CDDQ was incorporated into a career-
related self-help-oriented free of charge
Internet site (www.cddq.org).
Research has shown that the Internet and the
paper-and-pencil versions of the CDDQ are
equivalent (Gati & Saka, 2001; Kleiman & Gati,
2004).
The CDDQ was found suitable for different
countries and cultures and has been translated
into 18 languages.
13. 13
Interpreting the CDDQ results
Measuring career decision-making difficulties is
not enough – interpretation is very important
Interpretation is part of face-to-face counseling
and is crucial for Internet-based assessment of
career decision-making difficulties, where no
expert counselor is available
The proposed interpretation procedure is aimed at
locating the individual’s salient difficulties and
recommending ways to deal with them (with added
reservations when needed)
14. 14
1. Ascertaining Credibility, using validity items and the
time required to fill out the questionnaire
2. Estimating Differentiation based on the standard
deviation of the 10 difficulty-scale scores
3. Locating the Salient, moderate, or negligible
difficulties, based on the individual's absolute and relative
scale scores
4. Determining the need to add reservations to
the feedback provided (based on doubtful credibility, partial
differentiation, or low informativeness)
The Four Stages of Interpretation
15. 15
The 4 Stages of Interpretation
Credible
Doubtful
High
Questionable
Locate Salient
Difficulties
Add Reservation
to Feedback
Low
No
Feedback
Compute
Informativeness
(B /W )
Receives
Feedback
B/W > 1
B/W < 1
Estimating
Differentiation
Evaluating
Credibility
Not Credible
Aggregate
Reasons to Add
Reservation (RAR)
RAR ≤ 2
RAR = 3
1
2
3
4
16. 16
The goal: empirically testing a four-stage
model for interpreting the CDDQ profiles of
individuals
The interpretation is based on the within-
client relative salience of the difficulties as
well as their absolute salience, augmented by
quality-assurance measures
Career counselors' expert judgments were
used to validate the proposed procedures of
analyses
Interpreting the CDDQ results
17. 17
5 Studies
Study 1: Ascertaining the Credibility of
Responses to the CDDQ, based on validity
items
Study 2: Estimating the Differentiation of
Responses, based on the SDs of the 10 scale
scores
Study 3: Determining the Relative Salience of
Difficulties (salient, moderate, negligible)
Study 4: Determining the Need to Add
Reservations to the Feedback
18. 18
Studies 1-4
Career counselors' expert judgments were used in
the four studies for validating the proposed
procedures
Method
Participants: career counselors and graduate
counseling students
Questionnaires: in studies 1,4 - all possible cases;
in studies 2,3 - responses of 16 actual clients
Results:
High similarity between experts’ and students’
judgments, as well as within-groups judgments
High similarity between the experts’ judgments
and the proposed algorithm at each stage
19. 19
Study 5 – Testing the Applicability of
the Proposed Model
Method: Analyzing the CDDQ data of four groups (N =
6,192)
Hebrew paper-and-pencil version – 965 university
students
Hebrew Internet version - 4030 individuals surfing
the Future Directions Internet site (www.kivunim.com)
English paper-and-pencil version - 452 US College
students
English Internet version - 745 individuals who filled
out the CDDQ on the Internet ( www.cddq.org )
Results: see Figures 3 & 4
21. 21
Figure 4: Distribution of types of
feedback in the four groups
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
P & P Internet P & P Internet
feedback
add reservation
no feedback
Hebrew English
22. 22
Conclusions
The incorporation of a middle level of
discrimination increases the usefulness of the
feedback and decreases the chances and
implications of potential errors
Adding reservations when appropriate is
essential for providing meaningful feedback
and decreasing the chances of misleading
conclusions
27. 27
Among the salient difficulties is
“lack of information about
the career decision-making process” (4)
The Distribution of the Three Levels of Difficulties (negligible, moderate,
salient difficulty) in the Ten Difficulty Categories and the Four Groups
(N = 6192; H-Hebrew, E-English, p-paper and pencil, I-Internet)
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
H
H
E
E
H
H
E
E
H
H
E
E
H
H
E
E
H
H
E
E
H
H
E
E
H
H
E
E
H
H
E
E
H
H
E
E
H
H
E
E
p I p I p I p I p I p I p I p I p I p I p I p I p I p I p I p I p I p I p I p I
1 2 3 4 5 6 7 8 9 10
salient difficulty moderate difficulty no difficulty
28. 28
The PIC model (Gati & Asher, 2001)
which separates the career decision-
making process into 3 distinct stages:
- Prescreening
- In-depth exploration
- Choice
Guidance in the decision-making
process
29. 29
Prescreening
Goal: Locating a small set (about 7) of promising
alternatives that deserve further, in-depth
exploration
Method: Sequential Elimination
Locate and prioritize aspects or factors
Explicate within-aspect preferences
Eliminate incompatible alternatives
Check list of promising alternatives
Outcome: A list of verified promising alternatives
worth further, in-depth exploration
30. 30
Locating and prioritizing aspects or factors
Explicate within-factor preferences in the most
important factor not yet considered
Eliminate incompatible alternatives
Too many promising alternatives?
This is the recommended list of occupations
worth further, in-depth exploration
yes
no
Steps in Sequential Elimination
31. 31
A Schematic Presentation of the
Sequential Elimination Process
(within aspects, across alternatives)
Potential Alternatives
1 2 3 4 . . . . N
Aspects
a (most
important)
b (second in
importance)
c
.
n
Promising
Alternatives
32. 32
In-depth exploration
Goal: Locating alternatives that are not only promising
but indeed suitable for the individual.
Method: collecting additional information, focusing on
one promising occupation at a time:
Is the occupation INDEED suitable for me?
verifying compatibility with one’s preferences in the
most important aspects
considering compatibility within the less important
aspects
Am I suitable for the occupation?
probability of actualization: previous studies, grades,
achievements
fit with the core aspects of the occupation
Outcome: A few most suitable alternatives (about 3-4)
33. 33
Choice
Goal: Choosing the most suitable alternative, and rank-
ordering additional, second-best alternatives
Method:
comparing and evaluating the suitable alternatives
pinpointing the most suitable one
Am I likely to activate it?
if not - selecting second-best alternative(s)
if yes - Am I confident in my choice?
if not: Return to In-depth exploration stage
if yes: Done!
Outcome: The best alternative or a rank-order of the
best alternatives
34. 34
Still…
Career decision-making requires collecting a vast
amount of information
Complex information-processing is needed
But luckily,
information and communication
technologies are available
The use of a computer-assisted career guidance
system based on a theoretical model can help
overcome human cognitive limitations
There are several computer-assisted career guidance
systems available, most of them on the Internet
35. 35
However,
although Internet-based, career-related self-
help sites are flourishing,
these sites, as well as “stand-alone” computer-
assisted career-guidance systems, vary greatly
in quality.
Hence,
it is very important to investigate the utility
and validity of these self-help programs.
36. 36
Stand-Alone, Internet-Based
Career-Planning Systems
Possible Solutions
Desirable Features
CDDQ
Assessment of needs
Steps (PIC), factors to
consider, dealing with
compromises and
uncertainty
Providing guidance
concerning the process
potential alternatives,
their characteristics,
training
Providing relevant and
accurate information
37. 37
Stand-Alone Internet-Based
Career-Planning Systems (continued)
Possible Solutions
Desirable Features
User’s input-
continuous feedback,
outcome – sensitivity
analysis
Monitoring the dialogue
on the Internet or
elsewhere
Guiding the user toward
additional sources of
information
informative summary
of the dialogue
Directing the user to
face-to-face counseling
when needed
38. 38
MBCD
Making Better Career Decisions
MBCD is an Internet-based career planning
system that is a unique combination of
a career-information system
a decision-making support system
an expert system
Based on the rationale of the PIC model,
MBCD is designed to help deliberating
individuals make better career decisions
39. 39
Advancing the user’s career decision-making
by locating a small set of promising
occupational alternatives on which s/he may
focus and collect more detailed information.
Increasing the user’s readiness and motivation
to make a career decision.
Presenting a practical model of career
decision-making that can be implemented in
future career decisions as well as other
decisions.
MBCD – Goals
40. 40
MBCD –
System’s Features
Prescreening
Promising alternatives are located using the
Sequential-Elimination model (Gati, 1986),
which takes into consideration those career
aspects that are most important to the
counselee.
MBCD includes 28 career factors
42. 42
MBCD’s Key Features (cont.)
Eliciting both facets of the individual’s
preferences:
(a) the optimal level
(b) additional levels that the user regards as
acceptable (reflecting the user’s willingness
to compromise)
45. 45
MBCD’s Key Features (cont.)
Each occupation is characterized by a range of
levels within each aspect, reflecting the
within-occupation variance.
The system provides detailed feedback and
recommendations according to the user’s input
and its effect on the search results.
The dialogue is flexible and the users can
change their responses at any point.
48. 48
MBCD’s Key Features (cont.)
Promising alternatives are located by the
Sequential-Elimination search
model (Gati, 1986).
But the user can also use a compensatory-
model-based search.
49. 49
Compensatory model-based search
Goal – locating the most compatible occupations
Rationale - advantages of occupations may
compensate for their disadvantages
Steps of the compensatory search
Locate gaps between preferences and the
characteristics of the occupation for each factor
Sum the gaps, weighted by importance of factors
Locate occupations with minimal sum of gaps
50. 50
The Conjunction of the Two Lists
Users are advised to focus on the occupations that were included
in the recommended list of both search models in the in-depth
exploration
Sequential
elimination-based
list
Compensation-
based list
Conjunction
list
56. 56
MBCD’s Features (cont.)
At the end of the dialogue
the user receives a printed summary to take
along for further processing of the
information. The printout also provides
information for the counselor.
The user’s preferences are saved under a
personalized code for future interactions.
60. 60
Prescreening Based on Elimination:
Descriptive Validity (Gati &
Tikotzki,1989)
The monitored dialogues of 384 career
counselees with a computer-assisted career
information system were analyzed.
Results: most users (96%) employed a non-
compensatory strategy during all or at least a
part of the dialogue: many options considered at
a previous stage of the dialogue were not
considered at the following stage, showing that
individuals tend to use a prescreening strategy
based on eliminating alternatives
61. 61
Examine users' perceptions of MBCD
Examine changes in user’s degree of
decidedness
Examine perceived benefits
Locate factors that contribute to these
variables
Criteria for Testing the Benefits of
Making Better Career Decisions
62. 62
METHOD
Participants
247 males and 465 females who filled out
both a pre-dialogue and a post-dialogue
questionnaire
Mean age 22.8; mean years of education 12.6
4% high-school students
6% recent graduates from high school
58% recently completed their military service
9% considering an alternative to their current major
3% college graduates deliberating a job choice
8% considering a career transition
12% "other"
63. 63
Mean Perceived Benefit (MPB) and Willingness to Recommend
(WR) the Use of MBCD to a Friend (%) as a Function of the
Difference in Decidedness after the Dialogue of MBCD
(N=712)
Decidedness
Increased No change Decreased
Frequency 355
(50%)
266
(37%)
91
(13%)
MPB 3.12 2.57 2.52
WR% 93.5 74.8 72.5
Measure
64. Frequencies of Degree of Decidedness
Before and after the Dialogue with MBCD
Decidedness
After the Dialogue
Decidedness Before the Dialogue
1 2 3 4 5
1- no direction 34 7 6 7 0
2 - only a general
direction
41 66 15 9 5
3 - Client is considering a
few specific alternatives
27 58 84 30 6
4 - would like to examine
additional alternatives
23 51 35 54 6
5 - would like to collect
information about a
specific occupation
9 20 21 41 28
6 - sure which
occupation to choose
3 0 1 9 16
65. Willingness to Recommend (WR) the Use of MBCD to a friend as a
Function of the Degree of Decidedness Before and After the Dialogue with
MBCD (N=712)
Decidedness
After the Dialogue
with MBCD
Decidedness Before the
Dialogue with MBCD
1 2 3 4 5
1- no direction 38 14 17 29 --
2 - only a general direction 85 73 67 67 100
3 - considering a few
specific alternatives
100 93 82 97 100
4 - client would like to examine
additional alternatives
100 92 100 82 100
5 - would like to collect information
about a specific occupation
100 85 90 98 89
6 - Client is sure which
occupation to choose
100 -- 100 100 81
66. MBCD’s Effect on Reducing
Career Decision-Making Difficulties (d, Cohen, 1992)
d
Scale
.31
.13
.29
.16
Lack of Readiness
Motivation
General indecisiveness
Dysfunctional Beliefs
.72
.48
.45
.78
.20
Lack of Information About
The Process
The Self
Occupational Alternatives
Additional Sources
.11
.18
.01
-.13
Inconsistent Information
Unreliable Information
Internal Conflicts
External Conflicts
.65
Total CDDQ
67. 67
MBCD’s Effect (d, Cohen, 1992) on Reducing
Career Decision-Making Difficulties
(Gati, Saka, & Krausz, 2003)
0.31
0.72
0.11
0.65
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
Lack of
Readiness
Lack of
Information
Inconsistent
Information
Total CDDQ
d
68. 68
Perceived Suitability of the "Promising Alternatives" List
(N= )
%
%
%
%
%
%
%
%
%
%
%
+
(n= )
-
(n= )
-
(n= )
-
(n= )
(n= )
(n= )
(n= )
-
(n= )
(n= )
Number of Alternatives (n - of users)
too long
suitable
too short
69. 69
Predictive Validity of MBCD
Design: Comparing the Occupational Choice
Satisfaction (OCS) of two groups:
those whose present occupation was
included in MBCD’s recommended list
those whose present occupation was not
included in MBCD’s recommended list
70. 70
Method
Participants
The original sample included 123 clients who
used MBCD in 1997, as part of their
counseling at the Hadassah Career-
Counseling Institute
Out of the 73 that were located after six+
years, 70 agreed to participate in the
follow-up:
44 women (64%) and 26 men (36%),
aged 23 to 51 (mean = 28.4, SD = 5.03)
71. 71
Instruments
MBCD
Questionnaire: clients were asked to report
their field of studies, their satisfaction
with their present occupational choice (scale
of 1 – 9): “low” (1-4), “moderate” (5-7),
“high” (8-9)
Procedure
the located clients were interviewed by
phone, six+ years after visiting the career-
counseling center
Method
73. 73
Frequencies of Occupational Choice
Satisfaction by the Search-Model Whose
Recommendations Were Accepted
3 10
13 10
10
2
2
3 5
1
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Elimination Conjunction Compensation None
low
satisfaction
medium
satisfaction
high
satisfaction
74. 74
Conclusions
Accepting the recommendations of the
sequential-elimination-based search of MBCD
produces the best outcomes (i.e., highest
levels of satisfactions with the occupation)
The data does not support the effectiveness
of the compensatory-based search
The data does not support any advantage of
using the conjunction list over using only the
sequential-elimination-search list
75. 75
Alternative Explanations
Differences in the lengths of the lists
No difference was found in the OCS between clients
whose list included 15 or fewer occupations and clients
whose list included more than 15 occupations.
Therefore, this explanation can be ruled out.
76. 76
Alternative Explanations
(cont.)
Clients who accepted MBCD’s
recommendations are more compliant, and
therefore more inclined to report a high
level of satisfaction.
However, following the compensatory-model-based
recommendations did not contribute to the OCS.
Therefore, this explanation can be ruled out too.
77. 77
Gender Differences in Directly and Indirectly
Elicited Career-Related Preferences
Gadassi and Gati 2006
Method
Participants. 226 females (74.1%) and 79
males (25.9%) who entered the Future
Directions Internet site
Age: 17-30, mean=22.84 (median = 22, SD =
3.34)
Years of education: mean=12.67 (median 12,
SD = 1.48)
78. 78
Instruments
Future Directions
(http://www.kivunim.com)
Making Better Career Decisions (MBCD,
http://mbcd.intocareers.org)
The preference questionnaire: this
questionnaire imitated the preference
elicitation in MBCD. Participants were
presented with 31 aspects, and were asked to
rank-order them according to importance, and
to report their preferences in all 31 aspects
79. 79
Preliminary analysis
Lists of occupations. We used MBCD to generate
three lists of occupations according to:
(1) sequential-elimination
(2) compensation, and, for 235 participants,
(3) the list based on the conjunction between the
sequential elimination and the compensatory search
lists.
80. 80
Preliminary analysis
Lists of occupations. We used MBCD to
generate three lists of occupations according
to:
1. sequential-elimination
2. compensation
and, for 235 participants,
3. the list based on the conjunction
between the sequential elimination and the
compensatory search lists
81. 81
Preliminary analysis
Determining the degree of gender-ratings of
occupations was based on the judgments of 10
undergraduate students.
1 – “most (that is, over 80%) of the individuals who
work in this occupation are women”
5 – “most (that is, over 80%) of the individuals
who work in this occupation are men – over 80%"
The inter-judge reliability was .96,
We computed the mean gender-ratings of the lists
of occupations for each participants
82. 82
Preliminary analysis
Lists of occupations. We used MBCD to
generate three lists of occupations according
to:
1. sequential-elimination
2. compensation
and, for 235 participants,
3. the list based on the conjunction
between the sequential elimination and the
compensatory search lists
83. 83
Means of the Femininity-Masculinity Ratings According to
Type of List and Gender
3.18
2.96
3.13
2.71
2.4
2.5
2.6
2.7
2.8
2.9
3
3.1
3.2
3.3
Explicit
Elimination
Men
Women
Gender Differences in Directly and Indirectly Elicited
Preferred Occupations (Gadassi & Gati, 2007)
84. 84
Summary of Major Findings
PIC is compatible with people’s intuitive ways of
making decisions (Gati & Tikotzki, 1989)
Most users reported progress in the career
decision-making process (Gati, Kleiman, Saka, & Zakai,
2003)
Satisfaction was also reported among those who did
not progress in the process
Users are “goal-directed” – the closer they are to
making a decision, the more satisfied they are with
MBCD
The list of Recommended Occupations are not sex-
type biased (Gadassi & Gati, 2006)
85. 85
Identifying the Client’s Stage
in the Process
It is possible to start the PIC process from
“the middle” – according to the client’s needs
However, it is recommended to start the
process from the beginning, in order to:
Strengthen confidence in the occupational
alternatives considered by the client
Eliminate inadequate alternatives considered by
the client
Offer additional alternatives that were not
considered by the client so far
Teach decisions skills: aspect-based instead of
occupation-based approach
86. 86
The stage in the PIC model decision-process
of pre-academic programs students, at the
beginning and end of the program (N=386)
The stage in the decision-making process – beginning of programs
total
4
3
1 2
The stage in the dcm process – end
of programs
13
1
2
3 7
1-before pre-screening
77
5
17
11 44
2-before in-depths exploration
93
7
29
12 45
3- before choice
203
60
50
8 85
4 – after choice
386
73
98
34 181
Total - over rows
(
55%
)
211 made progress in the process
(
35%
)
136 stayed in the same stage
(
10%
)
39 moved backwards
87. 87
Tailoring the Intervention to the
Client’s Decision-Making Style
There is an advantage in tailoring the counseling
intervention to the client’s decision-making style
Previous research typically characterized individuals
by the most dominant characteristic of their decision-
making style (e.g., intuitive, dependent).
we suggest that a multidimensional analysis should be
used to uncover a comprehensive decision-making
style-profile of clients.
A theoretical framework based on ten dimensions
related to the career decision-making process was
developed for characterizing individuals' career-
decision making styles
88. 88
The Ten Dimensions
1. The degree of analytic vs. holistic information-
processing
2. The level of effort invested in the process
3. The degree of comprehensiveness in gathering and
integrating the information
4. The degree of consultation with others
5. The degree of realism (willingness to compromise)
6. Internal vs. external locus of control
7. The speed of making the final decision
8. The degree of procrastination
9. The degree of dependence on others
10. The degree of acceptance to others’ wills
89. 89
Testing the Proposed Model
To empirically test the proposed taxonomy we
developed the career Decision-making Style
Questionnaire (DSQ), in which each of the
proposed dimensions was represented by a few
statements.
The questionnaire was uploaded to a career-
related, self-help oriented Internet site
(www.kivunim.com )
A cluster analysis supported the proposed
differentiation between all ten dimensions.
92. 92
Locating Repeated Profiles of
Decision-Making Styles
Based on a cluster analysis of the participants,
we located homogeneous groups of participants
with similar career decision-making style
profiles
We found five groups of participants with
similar decision-making styles
These results were discussed in terms of the
hypothesized ten dimensions and the
previously identified career decision-making
styles
93. The Means of the Located Groups in Terms of the 10
Dimensions Red = Low; Green = High
Group
5
4
3
2
1
Dimension
2.4
2.3
4.4
3.4
4.5
Analytic
2.2
3.3
4.2
3.9
4.6
Effort
2.4
3.5
4.2
3.4
4.6
Comprehens.
3.3
3.1
4.4
2.3
4.5
Consulting
3.7
4.0
2.7
3.2
3.6
Realistic
2.6
1.9
4.6
4.1
2.9
Locus of
3.7
3.1
3.7
3.9
2.6
Speed
2.9
3.4
3.9
4.1
3.2
Procrastin
4.1
3.1
4.4
4.9
3.9
Dependence
4.2
2.0
3.6
4.6
4.1
Acceptance
94. 94
General Average of the Located Groups
Sd
M
Group
0.43
2.91
4
0.50
3.17
5
0.48
3.82
2
0.36
3.87
1
0.23
4.03
3
95. 95
To sum up, I presented and
discussed:
The CDDQ for locating the focuses of the
individual’s decision-making difficulties, and the
design and testing of a systematic procedure for
interpreting its results
A general framework for cdm – the PIC model
MBCD – a unique combination of career
information, expert, and a decision-support system
DSQ – A taxonomy and a questionnaire for a
multidimensional analysis of client’s decision-making
styles
96. 96
To sum up
Career choices are decision-making processes,
therefore career counseling is also decision
counseling
Decision theory can be translated into
practical interventions aimed at facilitating
individuals’ career decision-making
Many tools were transformed into user-
friendly Internet-based systems, which can be
incorporated into counseling interventions
The theory-based interventions can and should
be empirically tested for theoretical validity
as well as practical effectiveness
99. 99
credible
doubtful
high
partial
Locate Salient
Difficulty Categories
Add Reservation
to Feedback
low
No Feedback
Compute
Informativeness
(Bv/Wv)
Receives
Feedback
B/W > 1
B/W < 1
Estimating
Differentiation
Ascertaining
Credibility
non
credible
Aggregate
Reasons to Add
Reservation (RAR)
RAR ≤ 2
RAR = 3
Figure 2:
100. 10
0
Results: Compared Means of the Femininity-Masculinity Score
According to Type of List and Gender
3.18
2.71
3.04 3.23 3.13
3.2
2.95 2.96
1
1.5
2
2.5
3
3.5
4
4.5
5
P
o
s
i
t
i
v
e
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l
i
m
i
n
a
t
i
o
n
C
o
m
p
e
n
s
a
t
i
o
n
C
o
n
j
u
n
c
t
i
o
n
femininity-masculinity
rating
male
female
