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CREATION OF A TEST BATTERY FOR THE EVALUATION 
OF RHYTHMIC FEELINGS IN UNIVERSITY STUDENTS IN 
THE FIELD OF PHYSICAL EDUCATION AND SPORT 
 
Alena Kašparová, Kateřina Doležalová & Viléma Novotná 
 
 
Faculty of Physical Education and Sport, Charles University, Prague, Czech  
 
Original article, DOI:10.52165/sgj.13.2.231-241 
Abstract 
Optimal movement rhythmisation is considered one of the basic prerequisites for 
improvements in the quality of movement performance using a particular technique. Well-
developed rhythm-movement patterns play a role in successful learning of various physical 
activities as well as in athletic performance. University students – future PE and sports 
teachers – should improve their rhythmic feel skills during their studies so that they can use 
them later in their work and develop them in their future students. This requires the creation 
of a test battery for the evaluation of rhythmic feel skills through a series of music tests. This 
paper presents the results of tests taken by 121 university students at UK FTVS in Prague, the 
Czech Republic, and AWFIS in Gdaňsk, Poland. The test battery focused on three types of 
music-motor skills: perception skills and activities (items 1-18), reproduction skills and 
activities (items 19-27) and production skills and activities (item 28). The data were 
statistically processed using the classical test theory (factor analysis) and the item response 
theory (two-parameter model). Statistical methods also included reliability calculation and 
test validity. The expected rejection of the proposed hypothesis was confirmed both for the 
classical test theory and for the item response theory. The only exception was model 4 where, 
however, fit indices (especially TLI = 0.537) pointed more at a lack of evidence for hypothesis 
rejection than a perfect conformity of the model and data. The intention was to create and test 
models with the best data compliance. The best data compliance was found in models no. 1 
and 5. Model 1 [CFI = 0.927, TLI=0.916, SRMR = 0.09, RMSEA (5 %) = 0.03, RMSEA (95 
%) = 0.059] had a structure that corresponded to the proposed test battery and showed a 
relatively good compliance with data although IRT identified several problematic items. 
Model 5 [CFI = 0.956, TLI=0,942, SRMR = 0.073, RMSEA (5 %) = 0.03, RMSEA (95 %) = 
0.111] was unidimensional (reproduction factor feeding items 19 through 27) and its fit 
indices showed better compliance of model and data. An optimised test battery should be 
developed based on these models followed by another validation of the test battery using 
statistical analyses. 
 
Keywords: musical-motor skills, test battery, rhythm, factor analysis, item response theory.
 
INTRODUCTION 
 
The concept of rhythmic feelings 
refers to both rhythm and feelings, things 
that we encounter in many areas of our 
lives. They play a key role in correcting 
both    the    physical    and    psychological  
 
 
 
development including, for example, 
breathing, verbal and memory skills. They 
are also the cornerstone of any physical 
activity technique, movement or athletic 
performance. This is especially true for 

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gymnastics where movements and skills 
are learned in rhythmic structures with or 
without an apparatus and require the 
mastery of movement with optimal rhythm 
or, in other words, the execution of 
movement with the best time and space.  
Gymnastic skills are also used in 
many other sports. A wide range of 
gymnastic coordination and fitness 
exercises are used in the training of young 
athletes in many sports as well as in the 
technical training for other sports that 
require a high degree of coordination 
(Strešková, 2005). Gymnastic exercises are 
often performed to music. Rhythmic 
gymnastics has the most sophisticated 
form of music-motor education. It is the 
basis of training for gymnastics as well as 
rhythmic gymnastics (Mihule & Šťastná, 
1993).  
As part of their study, future teachers 
and coaches learn how to develop and 
assess rhythmic aptitudes. In their future 
work, they should be able to apply their 
skills when training their students and 
athletes in order to improve their motor 
skills and athletic performance (Novotná et 
al., 2012). 
Měkota and Novosad (2005) define 
rhythm as the dynamic and temporal 
division of movement. They describe the 
acoustic and visual aspects of rhythmic 
skills and divide these skills into rhythmic 
perception and rhythmic realisation. High-
level rhythmic skills are believed to help 
with learning processes.  
Váňová together with Skopal and 
Sedlák (2007, 2013) and Holas (1985) 
studied musicality in children. Their study 
inspired us to explore and develop tests for 
the evaluation of rhythmic feeling abilities 
with future physical education teachers and 
sports coaches, taking the definition of 
“rhythmic feeling” as our starting point.  
Rhythmic feeling is considered a 
psychological category. In other words, it 
is one of the musical abilities, or internal 
structures, that is not directly manifested 
and as such cannot be directly measured. It 
is manifested externally through activities 
and perception, reproduction and 
production skills that, in turn can be 
measured. These activities and skills must 
be tested separately, and tests must 
eliminate their mutual interferences 
(Sedlák & Váňová, 2013). 
Perception skills and activities are 
based on the tested subject’s perception 
and internal processing and the evaluation 
of a situation. Reproduction skills and 
activities are based on the repetition of a 
reproduced (demonstrated) task. 
Production skills and activities are based 
on the production of rhythm or movement 
based on a specific task with a strong 
emphasis on creativity. 
Music is an integral part of rhythm 
issues. Music creates ergogenic effects that 
improve work performance beyond 
expected levels of endurance, energy, 
strength, and productivity (Edworthy J. 
and H. Waring, 2006).  
The presented research partially 
follows up on the results of a dissertation 
thesis of Brtníková (2008). Brtníková 
(2008) created a test battery for the 
diagnosis of musicality and motor skills in 
secondary school female students as part of 
their physical education classes. Her work 
is based on the previous research on music 
and movement practice by music experts 
Kos (1975), Mihule and Appelt (1963), and 
also on musicality tests developed by 
music experts Bentley (1966), Seashore 
(1915, 1936) and others. Similar to 
Brtníková (2008), Shmulevich and Povel 
(2000), Moseley (2004), Grühn, Galley and 
Kluth (2006) and others also used the tests 
of music experts in their original or 
modified version in music and movement 
practice. 
More recent research in this area tends 
to focus primarily on the evaluation of 
already acquired specific motor skills, 
rather than on the actual level of rhythmic 
feeling itself.  
The aim of this study is to present a design 
of a new test battery for assessing rhythmic 
feelings and relevant statistical analysis to 
assess whether the proposed test items can 

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be part of a test battery and whether this 
test battery can be used in practice and can 
form the basis for possible future 
standardization. Tests that assess the 
rhythmic feelings of university students are 
still lacking in sports and physical 
education. 
 
METHODS 
 
The newly created test battery is based 
on findings reported in Czech and 
international literature and in collaboration 
with experts on sports and music. From 
Holas (1985), we took and applied the test 
structuring into several subtests. In the first 
section “Perception skills and activities”, a 
new test content was created while keeping 
the example and the number of tests. The 
test structure and design builds on the 
work in music psychology and diagnostics 
by Váňová, Skopal and Sedlák (2007, 
2013), which allowed for the interpretation 
of rhythmic feelings and its components.  
Test description: 
1) Perception skills and activities:  
Each test section contains 1 sample 
and 6 test tasks. 
A) Melodic memory – 3x listening to 
a familiar melody. The subject is asked 
whether or not there are any differences in 
the third recording.  
B) Tonal feel – 2x listening to a tone 
sequence. The subject is asked whether 
another tone, played separately occurred in 
the recording.  
C) Rhythm memory – each task 
contains three rhythmic sections played on 
percussion instruments. The subject is 
asked whether or not there are any 
differences in the third recording.  
These three test partitions (A, B, C) 
are processed on a test CD. The subjects 
are provided with recordings including the 
sound marks and instructions. The testing 
takes place in a group setting. In addition 
to the rhythmic tasks, the tests also include 
tasks focused on other musical abilities. 
We were already aware of this inaccuracy 
when the test battery was created, so it is 
clear that the statistical analysis will reveal 
this fact and allow the appropriate changes 
to be proposed. 
2) Reproduction skills and activities: 
Each test section contains 3 test tasks. 
A) Static rhythmisation (no 
movement) – three rhythmic variations 
reproduced by clapping.   
B) Dynamic rhythmisation 
(movement in space) – subjects are asked 
to repeat a rhythmic movement sequence 
demonstrated by the examiner to a 
metronome beat of 114MM.  
C) Rhythmisation with added 
elements (music and apparatus) – Subjects 
are asked to repeat a short rhythmic 
movement etude using wooden sticks.  
The testing is done individually. 
Before each test, subjects can try out the 
etude and demonstrate the etude with 
verbal rhythmisation.  
3) Production skills and activities: 
A) Production with music and verbal 
rhythmisation  
Subjects are asked to create a 
movement etude of eight 4/4 bars 
including a jump of his/her choice. The test 
section "Production skills and activities" 
contains only one item for time reasons. 
Therefore, this item is worked from the 
point of view of the regression analysis in 
relation to the previous two test sections. 
The point scores in the individual tests 
of the test battery are recorded on paper 
sheets and then transcribed into a 
computer. 1 point = the subject performed 
the rhythmic test flawlessly, 0 points = the 
subject failed to perform the rhythmic task 
or performed it with mistakes. The skill 
diagnostic does not focus on the quality of 
the movement but purely on the rhythmic 
component of movement. The aim of the 
proposed diagnosis and evaluation of the 
rhythmic feelings is to find out which 
activities pose the biggest problems to 
students and where the biggest gaps are in 
their theoretical and practical education. 
The findings may indicate a lack of stimuli 
in the teaching of gymnastics and music-
movement education. The results of the 

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research should help steer teaching 
towards the learning of skills and activities 
that promote and develop rhythmic 
feelings.  
Hypotheses 
H1) The proposed test battery 
includes three dominant factors – 
perception, reproduction and production.  
If H1) is disproved, we expect: 
H2) Items 1 through 18 explained 
through the perception factor. 
H3) Items 19 through 27 explained 
through the reproduction factor.  
The testing sample consisted of 
university students, both female and male, 
over the age of 19, studying Physical 
Education and Sports. The test included 
121 students – 48 women and 73 men. The 
students were recruited at the Faculty of 
Physical Education and Sport, Charles 
University (UK FTVS; n = 76) and the 
Akademia Wychowania Fizycnego i 
Sportu, Gdańsk (AWFIS; n = 45). The 
tests were translated into Polish for the 
Polish subjects.  
Testing took place during 4 to 5 
lessons (1 lesson took 75-90 minutes) in 
the gymnastics gym and the surrounding 
area. During the testing, in addition to the 
examiner, another teacher was present and 
delivered the teaching. 
The research tested the level of 
rhythmic feelings in 121 subjects using 28 
items in a newly created test battery. 
Rhythmic feelings were not demonstrated 
directly but through the perception (items 
1-18), reproduction (items 19-27) and 
production (item 28) skills and activities. 
The statistical analysis of the results was 
performed using the R software.  
At first an exploratory factor analysis 
(EFA) was performed, one of the methods 
of classical test theory (CTT). The goal of 
EFA was to find the true number of 
existing factors and assesses the factor load 
on test items, thus getting an insight into 
the structure of the proposed test in order 
to assign different factors to the relevant 
groups of test items. Further, a 
confirmatory factor analysis (CFA) was 
performed, which is, again a part of the 
CTT. Based on the EFA results, a model 
was created that assigned factors to 
different item groups according to the test 
structure. The conformity of the models 
with the measured data was determined on 
the basis of the so-called fit indexes. 
Specifically, in this case, a model was 
created with 3 factors - perception (items 1 
to 18), reproduction (items 19 to 27) and 
production (item 28). The production 
factor consisted of a single item which was 
included for the purposes of a regressive 
analysis. Classical test theory considers the 
test battery as a whole, which means that if 
only some items or groups of items from 
the test battery were analysed, the results 
would not be valid. This is because the 
CTT considers the items to be 
interdependent and any item that would be 
excluded from the test would remove 
essential test information. This 
consideration is particularly satisfactory 
for those tests that have already undergone 
initial optimization and are used in a stable 
form. A completely new test was created 
for this research, which is why the item 
response theory (IRT) was applied to a 
portion of the statistical processing in order 
to allow individual evaluation of each item 
and to treat every item as a separate test 
tool (Urbánek & Šimeček, 2001). 
 
RESULTS 
 
Exploratory factor analysis 
In the R statistical software, an 
exploratory factor analysis was performed 
using the psych library and the measured 
data, the number of extracted factors and 
the rotation type as input for the specific 
commands. The rotation types used in this 
analysis are the “varimax” argument, 
which is part of the orthogonal rotation1 
type, and the “oblimin” argument, which is 
part of the oblique rotation2 type. 
Extracted factors were counted for values 3 
and 4 using the minimal residue extraction 
method.  
 

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Three factor extraction. The 
application of the three extracted factors 
did not yield a good compliance between 
the model and data, as documented by the 
TLI (Tucker-Lewis Index) with a value of 
0.863, although the (Root Mean Square 
Error of Approximation) index was rather 
favourable with a value of 0.032. More 
information about the factors was provided 
by a percentage value of spread, explained 
by the relevant factor. The biggest spread 
value was detected for factor 1 (14%), 
followed by factor 2 (6%) and factor 3 
(4%). The total value of the spread 
explained by the three extracted factors 
was 24%, which is a very small value.  
Four factor extraction. The results 
yielded by four factor extraction were 
more favourable in terms of the fit indexes 
(RMSEA = 0.025, TLI = 0.928), which 
was to be expected because the additional 
factor contributed to the explanation of a 
larger part of the total spread (a total of 
28%). A factor load analysis also showed a 
trend similar to the three-factor extraction 
in that it was observed that factor 1 fed 
primarily items 19-28 (with some 
exceptions). Other load factors did not feed 
items in a way that would indicate a clear 
trend in line with the test design.  
Another output included in the EFA 
was a test of the internal consistency of the 
test battery using the Cronbach alpha 
numeric parameter. This value was 
calculated to be 0.8, which is generally 
considered as acceptable (the threshold 
typically being 0.7) although some authors 
(Lance, 2006) accept this test as reliable 
only at values higher than 0.9. It should be 
mentioned that the reliability is calculated 
for the entire test battery and is considered 
constant for the entire interval of subjects’ 
skills.  
EFA conclusion. In the light of the 
above results, it can be stated that in the 
proposed test battery concept (three factors 
corresponding to specific items), there was 
only one factor feeding items 19 – 28. The 
question, however, is whether it was the 
reproduction factor or the production 
factor or a factor combining these two 
manifestations of rhythmic feelings. More 
testing with more than one production item 
would be needed to answer this question. 
Another finding stemming from the EFA 
was that at least four factors would need to 
be extracted in order to ensure sufficient 
model-data compliance.  
 
Confirmatory factor analysis 
The confirmatory factor analysis 
worked with a specific model structure 
design. Two models (Model 1 and Model 
2) were analysed – both assigned the 
relevant three factors to all items as per the 
proposed test battery. In one case (Model 
2), we calculated a regression analysis of 
the production-perception and production-
reproduction relationships.  
Figures 1 and 2 show the structure of 
the two models. 
The final fit indexes show model 
compliance with the measured data. It is 
apparent that the model-data compliance 
was not acceptable. The only favourable 
index was the RMSEA index. However, 
literature (Hu & Bentler, 1999) indicates 
that a proof of model-data compliance 
requires more indexes with results under or 
above the calculated value. In this 
particular case, CFI and TLI indexes 
yielded very low values. The chi-square 
test rejected the hypothesis of the proposed 
models.  
CFA conclusion. Three dominant 
factors were assumed in this analysis. 
Based on the fit index values, both models 
failed to show good compliance with the 
measured data. A detailed analysis of the 
co-variation values (standard deviations, 
spreads) would be possible, but these 
values were not interpreted due to the fit 
index results.  
 
Item response theory 
As part of the item response theory 
(IRT), the relationship between the latent 
variable (θ – theta) and the item response 
was studied. In this case, the latent variable 
was the factor and the item response 

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characterised by the probability 
distribution above the latent variable. This 
distribution was defined by three 
parameters – the difficulty parameter, the 
discrimination parameter and the guessing 
parameter.  
 
Factor analysis using IRT 
In this section, a factor analysis was 
performed in the R software using the mirt 
library. Several models were designed and 
tested. Model 1 had the same structure as 
model 1 in the confirmatory factor analysis 
section and the factor correlation was 
permitted. Model 2 was based on model 1 
but the perception factor included only 
items 13 to 18 because the first twelve 
items focused on tonal feelings and 
melodic memory. Model 3 assumed that 
the first 18 items were defined by the same 
factor and similarly Model 4 considered 
items 13 through 18. Model 5 included 
items 19 through 27 in a single factor using 
a two-parameter model. 
 
 
 
 
 
 
 
 
 
Figure 1. Structure of Model 1. 
 
 
 
 
 
 
 
 
 

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Figure 2. Structure of Model 2. 
 
 
 
Table 1  
Final fit indexes of the proposed models 1 to 5. 
  
CFI TLI RMSEA RMSEA (5 %) RMSEA (95 %) SRMR p (χ) 
Cutoff > 0.9 > 0.95 < 0.06 < 0.05 < 0.08 < 0.08 > 0.05 
Model 1 
0.927 0.916 0.046 0.03 0.059 0.09 0.001 
Model 2 0.926 0.907 0.067 0.044 0.087 0.088 0 
Model 3 0.866 0.825 0.045 0.012 0.067 0.089 0.036 
Model 4 0.907 0.537 0.075 0 0.18 0.11 0.168 
Model 5 0.956 0.942 0.074 0.03 0.111 0.073 0.016 
 
 
Table 2 
Correlation matrices of model 1. 
  F1 F2 F3 
F1 1 
  
F2 0.795 1 
 
F3 0.696 0.974 1 
 

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Figure 3. Characteristic curves of items 19 to 27 of model 5. 
 
 
 
 
The above table shows that the worst 
fit indexes were found for Model 4 and 
Model 3 where TLI values reach especially 
low values. Rather surprisingly, the chi-
square test forced a rejection of all models 
with the exception of Model 4, which 
showed favourable results despite the fact 
that TLI, which was based directly on the 
chi-square test, gave very unfavourable 
results. For this reason, Model 4 is no 
longer considered. Model 2, once again, 
showed unfavourable results with only two 
of the six indexes being acceptable. The 
most favourable results were yielded by 
Model 1 and Model 5 with relatively 
satisfactory values for the initial test 
battery analysis.  
 
Model 1 
It turned out that for items 1, 8, 15 and 
18 focused on perceptual skills and 
activities, the difficulty parameter is up to 
a hundred times higher than for all other 
items (I1 = 34.3; I8 = 78.17; I15 = 53.39; 
I18 = 32.53). This means that for a 
proband, in order to have a 50% chance of 
answering an item correctly, it must have a 
latency value several times higher than for 
other items. On the latency scale from -6 to 
6, which includes all other items, the 
characteristic curves of items 1, 8, 15, and 
18 then appear as horizontal lines — that 
is, they do not discriminate at all on this 
scale. The empirical reliability of the 
perception factor was 0.77, the 
reproduction factor 0.85 and the 
production factor 0.85. From this it can be 
concluded that the largest measurement 
error occurs in the perception factor. 
The correlation coefficients between 
factors are also important variables (Table 
2). Significant values of correlation with 
positive signs can be observed, which the 
design concept implicitly assumed. The 
most interesting is the correlation 
coefficient between factor 2 (reproductive 
ability) and factor 3 (production ability), 
which is based on 0.974 and suggests that 

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these two factors correlate very 
significantly. The question is how this 
correlation coefficient would change if 
factor 3 contained more than one item. 
 
Model 5 
Regarding the values of the 
parameters of individual items, all values 
of the discrimination parameter came out 
greater than 1, i.e. the characteristic curves 
of the items (Figure 3) have the trend 
direction. It can be seen from the figure 
that item 23 has the lowest sensitivity, the 
slope of which is the least steep, while 
item 27 distinguishes the most. Another 
monitored parameter is the difficulty 
parameter, which distinguishes between 
difficult items (small difficulty parameter) 
and easy items (large difficulty parameter). 
In the legend, it is then possible to follow 
from top to bottom the most difficult items 
(items 19 and 26) to the simplest (items 25 
and 20). The value of empirical reliability 
for model 5 was 0.785. 
Conclusion of statistical results 
All proposed hypotheses had to be 
rejected because the chi-square determined 
perfect model-data compliance. It was 
clearly impossible to not reject these 
hypotheses for the newly created test 
although the aim was to detect a good 
compliance rather than a perfect one.  
Based on the results of the factor 
analysis using the classic test theory, the 
model-data compliance was not 
acceptable. In a factor analysis, part of the 
item response theory, two models were 
found with an acceptable data compliance 
considering that this was only a pilot test. 
One of these models included three factors 
and the other model included only one 
factor, specifically reproduction skills.  
 
DISCUSSION AND CONCLUSIONS 
 
This paper introduced research using a 
test battery for the evaluation of three 
aspects of rhythmic feelings in tested 
subjects. The purpose of the statistical 
analysis was to verify that the test structure 
was really a three-factor structure and, if 
possible, to differentiate each factor. Both 
the classical test theory and the item 
response theory led to a rejection of the 
proposed hypothesis (models) on a 95% 
level of significance, the only exception 
being Model 4 in the item response theory. 
Considering other fit indexes (especially 
TLI, which is based on the chi-square test), 
the results may be interpreted as failing to 
identify sufficient evidence for model 
rejection. In the current form, therefore, the 
test cannot be used to assess rhythmic 
feelings but requires optimisation, 
followed by more testing and statistical 
analysis.  
Hypothesis rejection had been 
expected because very few newly designed 
test batteries have passed the chi-square 
test. However, this research was focused 
more on finding good model-data 
compliance according to different fit 
indexes, rather than a perfect compliance 
in a chi-square test.  
Based on the results of the statistical 
analysis, the following recommendations 
can be proposed for the next testing:  
• if possible, increase the number of 
test subjects by at least twofold (the more, 
the better), 
• reduce the number of items falling 
into perceptual skills and activities, or, in 
consultation with a music expert, review 
the difficulty of existing items (1 to 18), 
• in the new test include only those 
items from the section of perceptual skills 
and activities that focus on rhythmic 
memory, 
• include more items in the section of 
production skills and activities and observe 
a correlation coefficient between the factor 
of reproductive abilities and production 
abilities. Only then will it be revealed 
whether these two factors are really so 
significantly correlated, 
• reduce the number of items in the 
reproductive skills and activities section, 
for time reasons. The statistical analysis 
performed will help you decide which 
items to exclude. 

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Based on previous recommendations, 
the new structure of the test could look like 
this. The perception skills and activities 
section could include only 6 items focusing 
on rhythmic memory. The reproduction 
skills and activities section could include 
4-6 items considering that this part of the 
test is the most time consuming. The 
production skills and activities section 
could include 2-3 items. The new test 
battery would thus include a total of 12-15 
items. This would significantly reduce the 
time needed for conducting the test and 
would also probably increase the 
informative value of the test. However, 
newly gathered results must be assessed by 
statistical analysis before any decision 
regarding further optimisation or 
standardisation of the test battery.  
 
ACKNOWLEDGEMENT  
 
This research was part of the grant project 
No. 1162218 (Measurement of rhythmical 
feelings with university students in 
physical education and sports) confirmed 
by the Grant Agency of the Charles 
University and the PROGRES Q19 project 
of the UK FTVS. The research was 
approved by the Ethics Committee of the 
UK FTVS under ref. no. 097/2019. 
 
REFERENCES 
 
Bentley, A. (1966). Musical ability in 
children and its measurement. London: 
Harrap. 
Brtníková, M. (2008). Modernizace 
hudebně pohybové výchovy. (Disertační 
práce). Praha: UK FTVS. 
Edworthy, J. & H. Waring. (2006). 
The effects of music tempo and loudness 
level on treadmill exercise, Ergonomics, 
49 (15), 1597-610. doi: 
10.1080/00140130600899104 
Grühn, W., Galley, N., & Kluth, Ch. 
(2006). Do Mental Speed and Musical 
Abilities Interact? Annals New York 
Academy of Sciences 999 (1), 485-496. 
doi.org/10.1196/annals.1284.059 
Hu, L. & P. Bentler. (2009). Cut off 
criteria for fit indexes in covariance 
structure analysis: Conventional criteria 
versus new alternatives. Structural 
Equation Modeling:   
A Multidisciplinary Journal. 
Lawrence Erlbaum Associates, Inc., 6(1), 
1-55. doi: 10.1080/10705519909540118 
Holas, M. (1985). Úvod do hudební 
diagnostiky: určeno pro učitele hudební 
výchovy, učitele hudební nauky na LŠU, 
učitele HV na SPgŠ. Praha: Státní 
pedagogické nakladatelství. 
Kos, B. (1975). Metodika výzkumu 
rytmických schopností sportovce. Teorie 
Praxe tělesné výchovy, 23 (11). 
Kos, B. (1975). Výzkum rytmických 
schopností sportovce. Teorie Praxe tělesné 
výchovy, 23 (12). 
Lance, C., Butts, M. & L. Michels. 
(2006). The Sources of Four Commonly 
Reported Cut off Criteria: What Did They 
Really Say? Organizational Research 
Methods. Sage Publications, 9(2), 202-
220. doi: 10.1177/1094428105284919 
Měkota, K., & J. Novosad. (2005). 
Motorické schopnosti. Olomouc: 
Univerzita Palackého.  
Mihule, J., & K. Appelt. (1963). 
Rytmus a jeho experimentální výzkum. In 
Sborník ITVS UK 4, Praha: Univerzita 
Karlova. 
Mihule, J., & D. Šťastná. (1993). 
Rytmická gymnastika. Praha: Karolinum. 
Moseley, S. (2004). When “Too 
Little” Is Not Enough: Lessons Learned 
and Applied from Teaching One-Credit-
Hour Dance Methods Courses for Physical 
Education Majors. Research Quarterly for 
Exercise and Sport, 75 (1.).  
Novotná, V. et al. (2012). Gymnastika 
jako tvůrčí akt. Praha: Karolinum. 
Seashore, C. E. (1915). The 
measurement of Musical talent. Music 
quarterly. 1(1), 129-148. doi: 
10.1093/mg/l.1.129  
Seashore, C. E. (1936). Objective 
Analysis of Musical Performance. New 
York. 

Kašparová A., Doležalová K., Novotná V.: CREATION OF A TEST BATTERY FOR THE …       Vol. 13 Issue 2: 231 - 241 
 
Science of Gymnastics Journal                                241                           Science of Gymnastics Journal 
 
Sedlák F., & H. Váňová. (2013). 
Hudební psychologie pro učitele. Praha: 
Karolinum.  
Shmulevich, I., & D. J. Povel. (2000). 
Complexity measures of musical rhythms. 
In P. Desain & L. Windsor, Rhythm 
perception and production: Lisse, NL: 
Sweets & Zeitlinger, 239-244. 
Urbánek, T., & M. Šimeček. (2001). 
Teorie odpovědi na položku. 
Československá psychologie: Časopis pro 
psychologickou teorii a praxi. Praha: 
Academia, 45(5), 428-440. ISSN 0009-
062X 
Váňová, H., & J. Skopal. (2007). 
Metodologie a logika výzkumu v hudební 
pedagogice. Praha: Karolinum.  
 
 
 
 
 
Corresponding author: 
 
Mgr. Alena Kašparová 
Department of Gymnastics 
Faculty of Physical Education and Sport  
Charles University 
José Martího 269/31 
162 52 – Praha 6 – Veleslavín 
Česká republika 
e-mail: akasparova@ftvs.cuni.cz 
tel.: 774 853 192 
 
 
Article received: 19.8.2020 
Article accepted: 1.12.2020 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Kašparová A., Doležalová K., Novotná V.: CREATION OF A TEST BATTERY FOR THE …       Vol. 13 Issue 2: 231 - 241 
 
Science of Gymnastics Journal                                242                           Science of Gymnastics Journal