Sustainable Development of Basic Motor Competencies Related to Socioeconomic Status of Primary School Children

Abstract

In this study, we focus on the relationship between the socioeconomic status (SES) of children and the level of their motor development related to motor competencies. Various research findings confirm the predominantly significant influence of the SES of the family or the environment where the child comes from, to the level of motor development evaluated on the basis of the results achieved in various motor tests. In this research we focused on primary school children, who participated in the MOBAK tests related to basic motor competencies and on the SES, which was determined by an online questionnaire for the parents. Despite the fact that we did not statistically confirm the relationship between the level of basic motor competencies and SES, the results indicate the tendency that children with higher SES perform better in object-movement and self-movement and are in line with the results of previous studies. This relationship should be respected and taken into account when designing physical and sports education lessons with regard to the sustainability of basic motor competencies development.

1. Introduction

Physical literacy is a lifelong value, it is the ability and motivation to use one’s own movement potential; the society and culture in which the individual finds him/herself also play a role. Furthermore, it encompasses the level of movement skills and abilities but also knowledge. It can be described as a quality acquired through knowledge and movement learning throughout an individual’s life [1,2]. Physical literacy is an interactive, multidimensional construct that should be measured and that a physical education and quality movement program should strive to achieve. The goal of physical literacy in the school setting, then, is the holistic development of the child’s physical activity and knowledge [2,3].

Basic motor competencies are the key indicators of an individual’s level of physical literacy, as well as the level of their motor development. Motor competencies can be defined as the control of movement skills and movement patterns, which enable a smooth participation in movement activities [3,4]. They can be assessed from the point of view of the process or the result of the performance. Process-oriented evaluations focus on form, i.e., quality of movement (e.g., how a child throws a ball) and usually assesses motor competency in terms of movement patterns such as running, throwing, or jumping. Performance-oriented assessment measures movement outcomes such as speed, distance, or accuracy (e.g., whether the ball hits the target) and typically assesses motor competency in terms of movement skills such as balance, speed, agility, and coordination. Weak to strong correlations were found between process-oriented and outcome-oriented evaluation performance. Therefore, both perspectives can broaden the understanding of motor competence over the course of a child’s developmental period [4,5,6].

The studies of various authors support the relationship between the level of basic motor competencies and socio-economic status. For example, in one study the authors investigated the socio-economic and gender differences in the level of motor competencies [3]. The results showed that the coordination of boys was much more influenced by SES than of girls. In general, the children with higher SESs showed higher levels of performance in all motor tests). Authors of the next study focused in their study on the level of physical activity and physical fitness related to SESs. They confirmed that in the school with higher SESs the children also achieved higher levels of physical activity and physical fitness [6]. The aim of another study was to investigate how the home environment, including SES, affects motor development in school-aged children. The results showed that motor development increases with increasing SESs. Taken together, these findings suggest that both the home environment and SES may play an important role and influence motor development in school-aged children [7,8].

Slovakia is one of the European countries with higher amount of children with special education needs in primary schools (11.5%), including children from socially disadvantaged areas (more than 6%) [8,9]. There has not been a lot of research performed related to the level of basic motor competencies and the socio-economic status of children in primary schools. Therefore, our data were based on the research of school-aged children in a primary school in Zeleneč, Slovakia and the aim of the study was to examine the relationships between pupils’ levels of motor competence with their socioeconomic statuses. The main research question we asked was whether there is a statistically significant relationship between pupils’ performances on the MOBAK motor tests, i.e., between their levels of motor competence and their SESs. We divided the pupils tested into three categories (low SES, medium SES, and high SES) according to their SES as measured by their household income; this distribution corresponds to the categorization of pupils into SES categories according to the other authors’ studies on which we based our research design. Based on the results of the research carried out in the field in other countries, we adopted the assumption/hypothesis that pupils coming from higher SESs will score higher on motor tests than pupils coming from medium and especially lower SESs.

2. Materials and Methods

A standardized research tool, MOBAK (MOBAK 1–2 and MOBAK 3–4), was used to assess the basic motor competencies [9,10]. The MOBAK 1–2 was created for children aged 6–7 years, i.e., pupils in grades 1 and 2 of primary school; the MOBAK 3–4 was created for 8–9-year-old children, i.e., pupils in grades 3 and 4 of primary school. Both versions of the test capture basic movement competencies in two categories, namely Object Movement with four test items (catching, throwing, dribbling, foot leading the ball) and Self-movement also with four test items (balancing, rolling, jumping, running). The difficulty and complexity of the requirements are adjusted to the age of the child. The testing was performed in the gymnasium during physical education classes. The evaluation of the MOBAK test items is straightforward because it is only a dichotomous pass/fail coding and clearly standardized criteria. We assessed the Object Movement and Self-movement separately, but we also evaluated the Overall Competence for both of these competencies. Each item on the MOBAK test battery is scored from 0–2 points. For each of the six items of dribbling, foot leading the ball, rolling, balancing, jumping, and running, the number of successful attempts is counted (0 points = no successful attempts, 1 point = one successful attempt, 2 points = two successful attempts). In the two items throwing and catching, 6 attempts are performed and scored as follows: 0 points = 1–2 successful attempts, 1 point = 3–4 successful attempts, and 2 points = 5–6 successful attempts. The assessment of the basic motor competences is then carried out by summing the values obtained in each test item, i.e., a total of 8 points can be obtained for each category (4 tests × 2 points). Therefore, in the overall MOBAK score, which summarizes both areas of competence, a child can score a maximum of 16 points. The MOBAK test instrument was validated in accordance with the curriculum documents applicable to both boys and girls—coeducational teaching of physical and sport education [10,11], therefore there is no need to take gender differences into account when assessing pupils. The test battery presented by the authors is not only suitable for scientific evaluation, but also for (internal) evaluation in the case of implementation in regular teaching practices. Based on the test results, teachers can adapt their teaching and content to the current performance level of their students. Teachers not only receive information about the overall score, but also specific information about which pupil has passed which test item (e.g., 50% of pupils cannot perform a forward roll) [11,12]. With respect to these specifications, we chose the MOBAK test battery, which we consider to be a suitable and effective testing tool for assessing the level of basic motor competencies.

The school-level SES was used as an indicator in the studies by several authors [3,6]. As our study was the first research probe conducted in a single school, this method of assessing SESs would not be feasible for us. We were therefore inspired by other studies in the area of interest. Other authors [12] investigated the association between risks in motor development with SESs in preschool children in northeastern Germany. They collected data from parents using a standardized questionnaire. The questionnaire included questions on education (e.g., high school diploma), occupational status, and monthly income. Based on this information, the SES (Winkler index) was assessed and respondents were classified into low, medium, and high SES groups [13]. In another study [7] the SES was determined using the questionnaire of the Brazilian Association of Market Research Institutes. The questionnaire includes questions on the level of education of the household head, ownership of goods (e.g., television and refrigerator), presence of a housekeeper or housekeeper, and housing amenities. These items are used to calculate an SES index called the “economic classification criteria”, which is widely used in Brazil. The total score is used to classify an individual into a category represented by a letter. Where A is the highest and E is the lowest category. For the purpose of this study, the authors combined the categories into high SES (classes A + B1), medium SES (classes B2 + C1), and low SES (classes C2 + D − E) Furthermore, there are some authors [13] who focused on identifying SESs and family characteristics that are related to preschool children’s motor development, surveyed SESs based on data such as family income and family structure. These were collected in face-to-face interviews. The questions included race/ethnicity, family income, family size, living with other child(ren) in the household, cultural assimilation, television (TV)/video viewing, and others. The family income was categorized into three categories of less than $25,000, from $25,000 to $75,000, and more than $75,000. Taking inspiration from the above-mentioned methods of SES surveys, for the purpose of testing in our conditions we created our own research instrument. A parent/legal guardian questionnaire was created to obtain the data needed to categorize children by socioeconomic status (SES) using the online platform survio.com. It contains 5 main sections (A–E), most of the questions were closed, i.e., with the possibility of selecting the answer from the already offered ones. Section A: basic data about the respondent (5 questions—gender, age, nationality, region of residence, number of inhabitants of the municipality from which he/she comes). Section B: basic data on the education of the parent/guardian (2 questions—highest education attained, field of education). Section C: basic data on employment (4 questions—current economic status in terms of type of employment; type of employment in terms of entrepreneur, employee, etc.; number of employees in the firm; occupation or job title). Section D: Basic household data (6 questions—number of household members and their age; household arrangement in terms of whether it is a complete family with the mother and father living together, etc.; type of housing in terms of house, flat, etc.; type of housing, e.g., sublet, own house with mortgage, etc.; other material and economic conditions such as owning a car, pet, etc.; the amount of the net monthly income of all household members, including all pensions, social benefits, child allowances, scholarships, and any other income, e.g., rent, etc.). Section E: child status (7 questions—at what level is the respondent able to provide food, clothing, school materials and supplies, extracurricular activities such as clubs, etc.) for a child, a primary school pupil who participated in the MOBAK testing, from his/her income; in what space does the child live, e.g., his/her own room, etc., how often the child sees a pediatrician, dentist for basic health care; how often they go on outings as a family (e.g., holidays, cinema, theatre, dinner, etc.).

The questionnaire included questions focusing on the parent’s education and employment, material security of the family and household, living situation, number of household members and their age group, total monthly household income, and leisure activities (holidays, cultural events, etc.). Due to the too low return rate of the questionnaire (explained in the following sections), it was not possible to use the collected data to the extent originally intended, so we decided to use only monthly household income as a relevant determinant for the purpose of creating the SES categories. This was the net monthly household income reported by respondents, which included the income of all household members, including pensions, social benefits, child allowances, etc. Respondents had to be classified into one of nine income categories (1. up to EUR 500, 2. EUR 501–700, 3. EUR 701–900, 4. EUR 901–1100, 5. EUR 1101–1300, 6. EUR 1301–1500, 7. EUR 1501–1700, 8. EUR 1701–2000, 9. more than EUR 2001). We then divided the income of the household members (using the upper limit) by the number of members of that household to acquire a more accurate figure of the net monthly budget per person in each household. Based on this assessment, three SES categories were created: high SES (EUR 500 or more/person), middle SES (EUR 300–499), and low SES (EUR 299 or less).

2.1. Participants and Settings

A total of 108 pupils (48 boys and 60 girls) of primary education, i.e., 1st–4th grade of primary school (the average decimal age of the respondents was 8.76 years) participated in the testing of motor competences. The other average values of the respondents were height (133.08 cm), weight (31.53 kg), and BMI (19.68). The testing was performed in the gymnasium during physical education lessons. The data were collected by a trained team including a researcher, physical education secondary teacher, and a student of the Faculty of Education as an assistant. We required written consent for participation from the school’s headmaster.

In addition to testing the pupils’ motor skills, an electronic questionnaire was distributed to the parents of the tested pupils, aimed at identifying the SESs from which the pupils come. The questionnaire was distributed to parents in electronic form via the edupage.org portal (the school’s communication system), but also in printed form via the pupils who participated in the motor competence testing. Despite several requests for parental participation in the research, the return rate was very low, with a total of 22 questionnaires collected.

All pupils were assigned unique codes, which we used to match the results of the motor competency testing to the results of the SES questionnaire. In this way, we selected those 22 pupils whose parents provided us with the information needed for further processing the results through the SES questionnaire. Thus, the results interpreted in the following parts of the study evaluate the 22 tested pupils, 13 boys and 9 girls based on their level of their motor competences and their relationship with the SES from which these pupils come from.

2.2. Data Analysis

The research aim was to find a relationship between a student’s level of motor competence and his/her socioeconomic status.

We analyzed the data in August 2022 using SPSS for windows. Fisher’s F-Test One-Way ANOVA—analysis of variance—and descriptive statistics were used, where we used descriptions to characterize individual values. Furthermore, we used the Spearman’s non-parametric correlation test.

3. Results

Firstly, we present the results of the descriptive statistics (

Table 1. Descriptive statistics from one-way ANOVA.

		N	Mean	Std. Deviation	Std. Error	95% Confidence Interval for Mean		Minimum	Maximum
						Lower Bound	Upper Bound
Object Movement	High SES	11	5.7273	2.24013	0.67542	4.2223	7.2322	0.00	8.00
	Middle SES	5	4.8000	1.78885	0.80000	2.5788	7.0212	3.00	7.00
	Low SES	6	5.3333	1.86190	0.76012	3.3794	7.2873	2.00	7.00
	Total	22	5.4091	1.99187	0.42467	4.5259	6.2922	0.00	8.00
Self-movement	High SES	11	6.0909	1.81409	0.54697	4.8722	7.3096	3.00	8.00
	Middle SES	5	5.8000	1.78885	0.80000	3.5788	8.0212	4.00	8.00
	Low SES	6	5.3333	2.73252	1.11555	2.4657	8.2009	1.00	8.00
	Total	22	5.8182	2.01509	0.42962	4.9247	6.7116	1.00	8.00
Overall Competence	High SES	11	11.8182	3.51620	1.06017	9.4560	14.1804	3.00	15.00
	Middle SES	5	10.6000	2.60768	1.16619	7.3621	13.8379	7.00	13.00
	Low SES	6	10.6667	4.08248	1.66667	6.3824	14.9510	3.00	14.00
	Total	22	11.2273	3.39372	0.72354	9.7226	12.7320	3.00	15.00

and

Table 2. Means—Report.

Socioeconomic Status		Object Movement	Self-Movement	Overall Competence
High SES	Mean	5.7273	6.0909	11.8182
	N	11	11	11
	Std. Deviation	2.24013	1.81409	3.51620
Middle SES	Mean	4.8000	5.8000	10.6000
	N	5	5	5
	Std. Deviation	1.78885	1.78885	2.60768
Low SES	Mean	5.3333	5.3333	10.6667
	N	6	6	6
	Std. Deviation	1.86190	2.73252	4.08248
Total	Mean	5.4091	5.8182	11.2273
	N	22	22	22
	Std. Deviation	1.99187	2.01509	3.39372

), which contain important basic data such as the mean and standard deviation. We compared the means between groups of movement tests and between different socioeconomic statuses of the children. To increase the clarity, we also present this comparison in graphical form (Figure 1a–c). When comparing the means, we noticed several interesting findings. We can clearly state that children from the high SES group achieved the highest mean scores in all three categories, in Object Movement, Self-movement, and also in Overall competence. Although we are aware that the measured values are very close to each other, i.e., these are not significant differences, this finding nevertheless points to similarities with findings from other studies from other countries where differences in movement test scores of children with higher SESs have been shown to be significant. However, comparisons of mean scores of low SES children are not very clear, these pupils achieved lower mean scores than high SES pupils in all categories of movement tests; we cannot say that this same relationship holds with respect to middle SES pupils. We might indeed assume a similar tendency here, but when comparing the results of the two groups, it appears that the lower SES pupils achieved higher mean scores than the middle SES pupils in the Object Movement domain and lower mean scores in the Self-movement domain. This seems to be contrary to the other research findings), where they found better performances of children with lower SESs in locomotor movement, not the object movement [14,15]. In Overall Competence, we see again a slight difference in mean scores in favor of the lower SES pupils compared to the middle SES pupils, although here the differences are almost negligible, on the basis of which we could conclude a rather obvious equivalence of performance in the movement tests of these two SES groups of pupils. However, overall, since we consider the measured values of the means to be too similar we cannot point to the differences between them as significant.

Subsequently, the Fischer’s F-Test One-Way ANOVA—analysis of variance—provided results that confirm the conclusions drawn from the previous comparison; the data are presented in

Table 3. Fischer’s F-Test one-way ANOVA.

		Sum of Squares	df	Mean Square	F	Sig.
Object Movement	Between Groups	3.003	2	1.502	0.355	0.706
	Within Groups	80.315	19	4.227
	Total	83.318	21
Self-movement	Between Groups	2.230	2	1.115	0.255	0.777
	Within Groups	83.042	19	4.371
	Total	85.273	21
Overall Competence	Between Groups	7.694	2	3.847	0.312	0.736
	Within Groups	234.170	19	12.325
	Total	241.864	21

. For Object Movement, the values obtained were F = 0.355; p > 0.05 (p = 0.706), for Self-movement F = 0.255; p > 0.05 (p = 0.777), and for Overall Competence F = 0.312; p > 0.05 (p = 0.736). In interpreting these data, we must state the essential information that there no significant relationship was found between the two variables. The possible error rate is higher than 0.05, so we cannot interpret the results as statistically significant.

Finally, the Spearman’s non-parametric correlation test was performed (

Table 4. Nonparametric Correlations SPEARMAN.

			Socioeconomic Status	Object Movement	Self-Movement	Overall Competence
Spearman’s rho	Socioeconomic status	Correlation Coefficient	1.000	−0.200	−0.126	−0.198
		Sig. (2-tailed)		0.371	0.576	0.378
		N	22	22	22	22
	Object Movement	Correlation Coefficient	−0.200	1.000	0.259	0.687 **
		Sig. (2-tailed)	0.371		0.245	0.000
		N	22	22	22	22
	Self-movement	Correlation Coefficient	−0.126	0.259	1.000	0.854 **
		Sig. (2-tailed)	0.576	0.245		0.000
		N	22	22	22	22
	Overall Competence	Correlation Coefficient	−0.198	0.687 **	0.854 **	1.000
		Sig. (2-tailed)	0.378	0.000	0.000
		N	22	22	22	22

** Correlation is significant at the 0.01 level (2-tailed).

), which speaks of the so-called bivariate test, i.e., it always puts two and two variables in a relationship. The values found were r = −0.200; p = 0.371; N = 22 for SES and Object Movement; r = −0.126; p = 0.576; N = 22 for SES and Self-movement; and r = −0.198; p = 0.378; N = 22 for SES and Overall Competence. While r= is the value of the correlation coefficient, p= is what is called achieved significance and N= is the number of probands in a given test. We only report a statistically significant value as one where two or one asterisk (* **) comes out in it. The asterisk tells us whether the number below it is less than 0.05 or 0.01. Based on this analysis, we can conclude that the results did not show a statistically significant relationship between SES and either category of movement competencies, Object Movement and Self-movement. Similarly, the relationship between SES and Overall Competence cannot be interpreted as significant based on our results. On further analysis, we can note that the relationship between Object Movement and Overall Competence emerged as significant and that the relationship between Self-movement and Overall Competence is also significant. This implies that as one increases, the other increases, so naturally if scores in one of the two areas of movement competence increase, then the overall score must also increase, i.e., overall competence. While Object Movement is not statistically significant correlated with Self Movement, which means that if a pupil is “good” at Object Movement, it does not necessarily mean that he will be “good” at Self-movement.

4. Discussion

At first, we looked at the topic through several recent research studies by different authors from different countries around the world. We can state that the above findings are consistent in that they attribute, to varying but mostly significant degrees, the influence of the socioeconomic status of the family or environment from which the child comes on the level of his/her motor development. It is therefore necessary to pay attention to this issue and to carry out even more similar investigations in our conditions in order to develop a suitable program that takes into account and reduces to a minimum the differences in pupils’ SESs and will be applicable in practice for teachers and schools in the teaching of physical education.

Although the results of the study did not show statistically significant differences between the individual groups of pupils according to SES and their scores on the MOBAK tests of motor competences, we can see that even with such a small sample, slight, but nevertheless observable, differences between pupils with high and low SESs are beginning to emerge. We can justify the too similar results by several claims. First of all, the small number of respondents or the small number of pupils whose results in the motor competence testing could be further evaluated in relation to SES played a role, as we did not receive the necessary feedback from parents and guardians when they participated in the research through the SES questionnaire. Nevertheless, we attempted to process the collected data as accurately as possible and using several statistical methods. Furthermore, we can talk about the fact that all the pupils were from one primary school, i.e., the research group had little variability, or we could say that they were similar pupils who had acquired similar motor competences, acquired in a comparable environment in PE classes in the same school. The choice of this group, however, was a first choice for us precisely because of the accessibility and the willingness of the school management to participate in this type of research, as it was research conducted by a first grade PE teacher at the school in the context of the first research probe of her dissertation. The question for discussion remains as to why the results of middle and low SES pupils are almost equal. One possible reason could be precisely that in today’s society the differences between the middle and lower classes are blurring, where we encounter opinions that the middle class will disappear altogether in the future, which would further widen the gap between the higher and lower classes. We also understand some limitations in the correct interpretation of the data. As we have not found significant correlation between the SES and the level of basic motor competencies measured by the MOBAK test battery, we need to consider both argumentations—that the children with lower SESs are more qualified in movements than other students who were in medium and high socioeconomic status as concluded by other authors or that the children with higher SESs achieve in some movement areas better results than children with lower SESs [15,16,17]. We are closest to the findings of another study, whose authors stated that there are no statistical significant differences between the different socio-economic groups and their level of motor skills [17,18]. Therefore, we consider further, more extensive research in this field to be necessary, especially in relation to cultural and regional differences as this might also effects the impact of SES on motor performance

5. Conclusions

Despite the fact that we can find a lot of studies looking at the impact of socioeconomic status on children’s motor competence with a positive impact of higher SESs [18,19], there are still also research findings proving the opposite, that high SES sometimes outperforms middle and/or low SES scores in overall, fine, and gross motor development. However, in some regions, the children coming from lower SESs showed good performances in object movement or locomotor movement. Those responsible for developing interventions in the related areas need to be further aware of the motor development identified in the various studies and ensure that they are delivering targeted and differentiated programs for socially disadvantaged children. There is a need to further understand children’s motor skills within the wider constructs of assessing motor performance in schools.

A sustainable development of basic motor competencies as a part of physical literacy is obviously dependent on the social-economic status of the families where the children grow up. We should, therefore, carefully observe the situations in schools and strengthen the inclusive approach in physical education classes. The MOBAK instrument seems to be a useful tool to acquire information about the level of basic motor competencies of primary school children. This information could help the teacher to choose the appropriate teaching methods and strategies in primary physical education classes to develop the basic motor competencies of all children respecting their SESs.

The differences in the level of motor competence among children could contribute to inequalities in physical activity in later life, such as the gender inequalities observed in physical activity during adolescence and the social differences in relation to the performance of leisure-time physical activities observed in adulthood. Given that the benefits of physical activity for health and overall well-being are now clearly established, addressing these inequalities is key. To do this, we need to improve our understanding of disparities in motor competence and motor development in children [19,20]. This will then enable a tailored and sustainable physical education for quality education in the school environment including all children without any differences.