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Table 5.3 ( continued )
X
1
0
0
1
1
1/4
0
0
1/4
1/3
3
0,428
1
2
X
1
0
2
2
1
1/4
0
1
1/2
1/3
6
0,417
1
2
X
3
0
2
3
1
3/4
0
1
3/4
1/3
9
0,647
3
3
X
0
0
1
0
0
0
0
1/2
0
0
1
0,200
0
1
X
0
0
2
1
1
0
0
1
1/4
1
4
0,399
0
2
X
4
2
2
4
3
1
1
1
1
1
15
1
4
4
X
2
2
0
4
2
1/2
1
0
1
2/3
10
0,567
2
2
X
1
0
0
4
1
1/4
0
0
1
1/3
6
0,319
1
2
X
0
0
1
4
1
0
0
1/2
1
1/3
6
0,329
0
2
X
2
2
0
4
2
1/2
1
0
1
2/3
10
0,567
2
2
X
0
0
0
0
0
0
0
0
0
0
0
0
0
1
If we use of widely applied method of rating computation by the formula
5
=
n
n
j
x
=
y
ω
,
j
then it appears that the respondents No.6 and No.12 have the identical rating
points equal to 1.3 in this case, too.
The developed method of obtaining rating points and assignment of qualification
levels allows obtaining more information on qualification of employees in compari-
son with a traditional method within the limits of the same information. The respon-
dents No.6 and No.12 are assigned to level X , however, they have different rating
points. Fig. 5.1 shows the functional model of evaluation of correspondence of
specialists' training level to requirements of their professional activity sphere.
j
1
Example 5.3. Professional selection of graduates [180—183]. One of the major
problems of professional selection is the problem of detection of candidates which
could master a particular specialty within target dates and further effectively fulfill
their professional duties, by virtue of their educational level within the limits of
subject matters, and also developmental level of personal qualities and cognitive
psycho-physiological processes.
The functional model of multi-criteria professional selection of graduates ac-
counting for fuzzy preferences is shown in Fig. 5.2.
Let us consider academic performance indexes, cognitive psycho-physiological
and personality traits of graduates of a certain specialty. The general educational level
is divided into fundamental sciences education (FE), general professional training
(GPT) and specialized education (SE).
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