=Paper=
{{Paper
|id=Vol-2393/paper_382
|storemode=property
|title=The Technique to Evaluate Pupils’ Intellectual and Personal Important Qualities for ICT Competences
|pdfUrl=https://ceur-ws.org/Vol-2393/paper_382.pdf
|volume=Vol-2393
|authors=Svitlana Lytvynova,Oleksandr Burov,Olga Slobodyanyk
|dblpUrl=https://dblp.org/rec/conf/icteri/LytvynovaBS19
}}
==The Technique to Evaluate Pupils’ Intellectual and Personal Important Qualities for ICT Competences==
https://ceur-ws.org/Vol-2393/paper_382.pdf
The Technique to Evaluate Pupils’ Intellectual and
Personal Important Qualities for ICT Competences
Svitlana Lytvynova1, Oleksandr Burov1, Olga Slobodyanyk1
1Institute of Information Technologies and Learning Tools
ayb@iitlt.gov.ua
Abstract. The paper presents the ICT technique for assessment of
schoolchildren abilities, intellectual and personal important qualities for ICT
competences formation, as well as research in this domain. The results of
comparative analysis of abilities of pupils with mathematical and IT abilities in
non-profiled schools in relation to “average” abilities are presented after results
of pilot study. Examples of methodical developments are given. Some expected
and unexpected results of the experimental research are discussed.
Keywords: learning environment, intellect, personality, abilities, high school
children.
1. Introduction
At present, our lives are being built more and more around digital networks. The
cyberspace becomes the general environment of a human life and activity. F.e.,
Internet of Things (IoT) entered our life, about 13 different devices are on average in
each house (computers, laptops and smartphones, routers, IP cameras, digital video
recorders, etc.); in 2018, more than 30 billion IoT-devices around the world were
connected to the Internet.
New challenges of time and new directions of society development - Society 4.0,
Education 4.0, penetration of the latest technologies into all spheres of life – need
digital competences for everybody, not only specialists [1], because he/she becomes
the element of the general intellectual capital [2]. As a result, the importance of
information and communication technology (ICT) for education and training [3]
requires the ability to process a large amount of information, to analyze the data
obtained and provides it correctly using the appropriate and modern ICTs, including
in synthetic environment [4], when the ability to work in on-line and off-line modes,
as well as computer modeling is needed [5].
The purpose of the article is to analyze intellectual and personal important qualities
needed for ICT competences of high school students in general (non-profiled)
schools.
2. Related Work
Specialists in psychology and pedagogics articulate the necessity of forming a person
at the beginning of the XXI century in both formal and informal education [6] with
such professional skills as: informational literacy, inventive analytical thinking, quick
search and processing of information, innovative thinking style, effective
communication, project and team work, problem solving, ability to take
responsibility, high productivity, and life competencies [7]. To date, special attention
is paid to expand the digital competence by not only professional skills, but
understanding threats from the digital environment [8], with special attention to
information security culture [9] and recognition of new nature and features of todays’
networks [10]. This corresponds the general requirements to IT skills [11], but it is
needed to pay more attention to general cognitive abilities of a human [12] for most
professions with regards to importance of the human intellect [13] and possibility to
measure it in accurate manner [14], as well as a human personality features [15] that
form a human as a specialist and as a workforce, and that should be formed
effectively when using computer modeling in class work [16].
3. Method
In a screening study with the help of the ICT developed, and in order to identify the
dominant fields of intellectual activity of high school students (grades 8-11), it was
applied a methodology [17] and technique of psychological test performance, with
subsequent analysis of data obtained. The tests included:
M. Luscher color and associative test (pairs comparison method); purpose of use is
an assessment of stress, balance of psychological qualities; recorded parametersare as
follows: total deviation (CO), Shiposh coefficient (VC), stress level (C), working
capacity (RP), heteronomy-autonomy (GA), concentricity-eccentricity (KE), balance
of personality traits (BL), the balance of the vegetative system (BV).
Myers-Briggs Type Indicator (MBTI); the purpose of use is
an introspective questionnaire to indicate differing psychological preferences in how
people perceive the world around them and make decisions an assessment of the
ability to certain activities and individual properties of communication; traditional
indices of an individual typology estimation according to the Myers-Briggs
methodology are recorded based on the evaluation of the prevailing signs on the 4
criterion scales: extraversion E - introversion I (orientation of consciousness),
intuition N - sensory S (way of orientation in a situation), thought/judgment J -
perception P (method of preparation of decisions), thinking T - experience F
(decision-making); in our research, we used quantitative evaluation of subjects’ report
on each scale, where each value was calculated as a sum of positive answers to the
appropriate question.
Modified Intellectual Structure Test after R. Amthauer (TCI); purpose of the test
use is a definition of the level of development and structural features of intelligence,
adfa, p. 2, 2011.
© Springer-Verlag Berlin Heidelberg 2011
as well as attention, memory; the following subtests are used (the brackets show the
corresponding structural component of the intelligence):
LS (testing of language, ability to formulate judgments),
GE (conceptual intuitive thinking),
AN (combinatorial abilities, mobility and ability to switch thinking),
RA (ability to solve practical computational problems character),
ZR (logical and mathematical thinking),
FS (figurative synthesis),
WU (spatial thinking),
ME (memory, attention).
The values of the structural components of intelligence were calculated as the sum
of the correct answers for each subtest, the values of verbal (VI) and nonverbal (NI)
intelligence were calculated as a sum of values, respectively, LS, GE, AN, ME and
RA, ZR, FS, WU. The overall IQ score was calculated as the sum of values VI and NI
multiplied by the correction factor 1.462 .
The resulting primary data was entered into a spreadsheet for further analysis. Test
results were not personified, but were taken into account for each course separately.
The data analysis included:
comparative evaluation of indices measured;
visualization of these data;
comparative analysis for three groups of pupils: with higher math abilities
(g1), with higher IT abilities (g2) and general group (without abilities), according to
teachers’ marks (g3);
stepwise discriminant analysis to reveal intellect and personality structure
indices for comparable groups.
Subjects. In order to verify the effectiveness of the methodology, 43 pupils of 8 th,
9 and 10th grades of common school (non-profiled) were involved in the testing.
th
4. Results and Discussion
According to our prior results, intellect value of high school pupils of math and IT
profile is significantly higher than in schools in average [18]. But schoolchildren
participated in those research represented a selective sample, and their IQ was higher
than 130, as a rule. Results of the intellect measurement in current research
demonstrated that IQs in grade 9 was 102, 92, 76 (by groups g1, g2 and g3).
Accordingly, IQs in grade 10 were 105, 101 and 80, i.e. a little bit higher, but
significantly less than in pupils of profile schools. We strongly believe that it could be
explained by “blurring” of classes because of children with different abilities.
Important characteristic of the intellect development is an intellect structure.
According to the data known intellect framework impacts the creativity, very
important feature of IT-competence. From the data obtained, such a structure of three
groups analyzed in the research is relatively expected: higher for pupils of the g1
group and less values for g3 (Fig. 1).
Fig. 1. Intellect structure of the 9th grade pupils.
However, unexpected result has been revealed in RA component: ability to solve
practical computational problems character. Pupils of g1 and g2 groups coped with
that task better.
At the same time, in 10th grade results of the test performance were as expected
(Fig.2).
Fig. 2. Intellect structure of the 10th grade pupils.
It is necessary to highlight that personality structure of the pupils of the 9 th grade
was practically the same for pupils of g1 and g2 groups (Fig.3), significantly different
from group g3, especially in decision-making on the base of emotions and
introversion.
But 10th grade pupils’ personality structure was similar for all three groups, though
mindset (thinking T index) demonstrated “average” pupils (Fig.4). That result could
be explained by their less formalized thinking and being ready for activity with “open
mind”.
8
6
4
2
0
N S P J I E F T
Math9 noMath9 IT9
Fig. 3. Personality structure of the 9th grade pupils.
8
6
4
2
0
N S P J I E F T
Math10 noMath10 IT10
Fig. 4. Personality structure of the 10th grade pupils.
The next step of analysis has been carried out in relation to reveal what particular
components of the intellect and personality could be used to differ groups under
research, first of all g1 and g3, because they demonstrated not always expected
tendencies. To solve that task it was used forward stepwise discriminant analysis to
find which indices could describe those groups more reliable.
Significant indices from 27 intellect, personality and nerve balance features
were included into the discriminant model step-by-step according to the criteria of the
highest value of D2-Makhalanobis factor (D2-M). In this case, some additional values
were calculated: group determination’s coefficient of accuracy (DCA1 and DCA3,
respectively), reliability coefficient for discriminant function (RDF). That technique
was propose and developed by one of co-authors for data analysis in emergent
industries [19].
The consequence of indices included into the discriminant model demonstrates
that sensory S (way of orientation in a situation) and RA (ability to solve practical
computational problems character) differs math-oriented pupils and others in the best
way (Table 1). The next important indices (VC and BL) are associated with
vegetative balancing of the human central nerve system and specify the group g3
practically with the reliability 100% (discriminant factor equal 1.0). But this is not
enough to specify g1 pupils who are described good when the model includes
intellectual thinking indices ZR and T.
Table 1. Building of the discriminant model for 10th grade pupils’ g1 and g3
Step Index D2-M DCA1 DCA3 RDF
1 S (sensory) 5.87 0.5 1.0 0.8
2 RA (ability to solve practical 11.95 0.75 0.83 0.8
computational problems)
3 VC (Shiposh’ coefficient) 18.95 0.75 1.0 0.9
4 BL (balance of personality traits) 23.12 0.75 1.0 0.9
5 FS (figurative synthesis) 29.78 0.75 1.0 0.9
6 ZR (logical and mathematical 30.36 1.0 0.83 0.9
thinking)
7 T (thinking) 30.40 1.0 0.83 0.9
The next steps after first 7 were not constructive, because accuracy and reliability of
the groups’ determination could not increase. In other words, pupils with
mathematical and non-mathematical abilities in common classes can be separated by
only 7 significant indices of: personality (sensory and thinking), intellect (ability to
solve practical computational problems, figurative synthesis, logical and
mathematical thinking), as well as personality balance (Shiposh’ coefficient and
balance of personality traits) with quite high accuracy and reliability.
This result demonstrated that schoolchildren of high school can have some clearly
determined features even in common (non-profiled) schools that could be revealed, if
using the appropriate ICT to reveal such “hidden” abilities, usually not determined in
classroom.
At the same time, the results of such an analysis articulated that pupils with math
and IT abilities have similar features in comparison with rest pupils, but all three set
of test indices (intellect structure, psychological preferences and vegetative balance)
are important in formation of psychophysiological portrait of studied g1, g2 and g3
groups. The question that is discussed in psychological literature up to now deals with
the relationship of vegetative features and psychological preferences. In our field of
interests, this relates to the specifics of IT-able pupils in high school. The analysis of
such a relationship could not give a positive answer, i.e. such research should be
continued, maybe on the biggest cohorts.
5 Concluding Remarks and Future Work
The technique proposed for assessment of “hidden” abilities of schoolchildren for the
high non-profiled schools and realized as a special ICT can be used in common
education practice. Indices (important to define math- and/or IT-abilities of pupils)
include elements of the intellects structure, personality structure and balance of
psychological qualities.
Problems that require further research in this area: extended research to collect
more wide set of data from profiled and non-profiled schools with math and IT
teaching.
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