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Article

Relationships Between Motor Skills and Academic Achievement: An Exploratory Study on Italian Primary School Children

by
Cristiana D’Anna
1,*,†,
Ilaria Basadonne
2,†,
Giovanna Aquino
3,
Valeria Minghelli
4 and
Pierpaolo Limone
1
1
Department of Education and Sport Sciences, Pegaso University, 80143 Naples, Italy
2
Department of Brain and Behavioral Sciences, University of Pavia, 27100 Pavia, Italy
3
Department of Medicine and Health Sciences, University of Molise, 86100 Campobasso, Italy
4
Department of Human, Philosophical and Educational Sciences, University of Salerno, 84084 Fisciano, Italy
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Educ. Sci. 2025, 15(2), 124; https://doi.org/10.3390/educsci15020124
Submission received: 8 December 2024 / Revised: 16 January 2025 / Accepted: 18 January 2025 / Published: 22 January 2025
(This article belongs to the Section Curriculum and Instruction)
Browse Figure
Versions Notes

Abstract

:
Several studies in recent decades have investigated the relationship between physical activity and learning, emphasising the role of corporeality as an effective tool for embodying knowledge, as well as skills, motor skills, and life. The aim of this exploratory study is to analyse and interpret the correlations existing between motor competence and school performance in all the disciplines included in the curriculum of primary school. Through non-probability sampling, a sample of 120 Italian children aged 6–10 years was involved. The TGMD-3 test was used to assess gross motor competence, while academic achievement was assessed based on the children’s GPA (grade point average) evaluation. Additional information on extracurricular sports practice was acquired through a questionnaire completed by parents. The Spearman correlation conducted between the children’s TGMD-3 scores (Gross Motor Index, Locomotion, and Ball scaled scores) and the academic achievement showed weak intensity and no statistical significance. In the analysis by sex, only weak and non-significant correlations, mostly of a negative type, were revealed in the group of males. In the group of females, on the other hand, positive, mostly moderate, and statistically significant correlations emerged between GMI and the scaled Ball scores with the learning assessments, except for Physical Education. The results suggest the need to expand studies investigating the quantity and quality of physical education and sports in the formal school context to understand whether, in sharing the educational project, it can promote better school performance and, more generally, more harmonious development of cognitive, motor, and social skills.

1. Introduction

The post-pandemic scenario of contemporary society is made up not only of a physiological mutability of the economic and socio-cultural fabrics but also of a more than rapid evolution of technologies (Rivoltella, 2023) that set new and pressing educational and training challenges to those who, in the different formal and non-formal spheres, are responsible for promoting the growth and development process of the new generations.
As the document Fit for Life (UNESCO, 2021) states, the health emergency has shown ‘so cruelly’ the ability of sport and physical activity, in general, to promote personal health and well-being.
What has already been recorded in terms of sedentary lifestyle for digital natives (Ceciliani, 2015) and for the post-millennials generation (Iavarone, 2022) seems to have worsened as a result of the health emergency. Several studies conducted at the national and international level highlighted the drastic reduction of physical activities and the inhibition of the motor vivacity of children, who, by their nature, have a significant need to move and have experiences (Cerniglia et al., 2020; Orgilés et al., 2020), with significant consequences in the personal and social physical dimensions of each person’s life (Dunton et al., 2020; Ford et al., 2021).
Similarly, time spent using technological devices increased significantly (Pietrobelli et al., 2020; WHO, 2020; Schillaci & Varalda, 2021; ten Velde et al., 2021; Stockwell et al., 2021). An interesting study (Hoare et al., 2019) conducted with a large cohort of Australian primary school children, which investigated the relationship between overweight/obesity and obesogenic risk behaviour associated with health-related quality of life and the physical, social, emotional, and school subdomains, has shown significantly higher scores of quality of life among all children who followed the recommendations on physical activity on five of the previous seven days and similarly with those who followed more of the daily recommendations on time spent in front of the screen.
In addition to an undoubtedly complex socio-economic and cultural scenario common with the different realities in the international arena, the Italian scenario presents a further critical element related to the complexity and heterogeneity of the real implementation, in the formal school educational context, of quality physical education starting from primary school (Abate Daga et al., 2024).
These considerations are developed on a dual matrix: the pressing evolution of the media and declination of motor activity practices that are not sufficient to recreate the need for movement. Both these aspects require equally complex investigations and interventions to provide those involved in the processes of training and growth of the new generations (researchers, teachers, educators) with the tools to decipher this complexity. Moreover, it will favour the development of critical decision-making and argumentative skills in the protagonists of this process, i.e., children and young people.
In the international context, already in 2006, and subsequently in 2018, the written recommendations for European key competences stressed the importance of fostering, within learning, the acquisition of functional literacy; multilingualism; mathematics and technology; digital; personal, social, and metacognitive competences related to the ability to learn how to learn; social and civic competences in citizenship; entrepreneurship; as well as cultural awareness and expression (UE, 2018).
At the same time, in the Italian context, with reference to school planning, the national indications and the new scenarios have emphasised the role that certain learning tools play in fostering the integral development of the person, also in relation to the socio-economic and cultural changes that are affecting the new generations: among these, computational thinking and physical education have assumed a privileged position (MIUR, 2018).
The literature confers to the regular practice of physical activity the ability to promote integral personality development (Bailey, 2006), fostering the development of emotional and socio-relational competences (Danish et al., 1993; Fraser-Thomas et al., 2005; Gould & Carson, 2008), also through the promotion of prosocial attitudes (Brunelle et al., 2007).
Motor-sport activities, if properly implemented (Marchetti et al., 2016), are directly related to better levels of perceived self-efficacy (Pesce et al., 2016) and self-esteem (Smoll et al., 1993) as well as to moral and character development (Bredemeier et al., 1986; Miller et al., 1997; Reid, 2012; Isidori, 2013).
Over the past two decades, neuroscientific studies on physical exercise and cognition showed how physical activity and exercise have the power to influence brain plasticity (Adkins et al., 2006; Hillman et al., 2008; Khan & Hillman, 2014; Pesce & Ben-Soussan, 2016; Santana et al., 2017; González-Fernández, 2019; Real-Pérez et al., 2022). In this perspective, the body represents our first element of determination: a true paradigmatic revolution has now been created in which ‘[…] cognition is not only embodied, but also situated, variable, and contextually determined’ (Gomez Paloma, 2009, p. 25).
Therefore, the continuous, complex, dynamic interaction with the environment becomes a stimulus of increasingly embodied knowledge, skills, and competences. The perspective of embodied cognitive science, within the framework of learning processes, is now contributing to providing a new interpretative key to the processes of cognition. According to this multi-perspective vision (Barsalou, 1999; Glenberg et al., 2013; Wilson & Golonka, 2013; M. Wilson, 2002; A. D. Wilson, 2005, 2014), cognition represents the result of a holistic process in which mind, body, and environment interact and redefine each other within a simultaneous and non-hierarchical circular dialogue (Caruana & Borghi, 2016).
As for the relationship between motor activities and academic achievement, a work conducted in Texas with a very large sample of 6–18-year-olds showed that all examined physical variables had a positive association with school performance (Van Dusen et al., 2011). Furthermore, several studies claim that the level of cardiovascular fitness and the consequent improvement of other metabolic and/or neurochemical mechanisms closely related to physical activity are able to influence the functionality and integrity of children’s nervous systems (Tomporowski et al., 2015; Klein & Hollingshead, 2015; Vazou et al., 2019; Liu et al., 2020). Moreover, they seem to favour a more effective acquisition of higher cortical executive functions, such as those responsible for motor control and planning and whose functioning strongly implies learning processes (Tomporowski & Pendleton, 2018; Giuriato et al., 2020; Biino, 2020).
It appears that the neural stimulation generated by the demands and execution of coordinatively complex motor tasks acts positively on the efficiency of brain ‘software’ (Davis et al., 2011; Tomporowski & Pesce, 2019).
Studies investigating the effects of coordinative training on brain neurochemistry have described its benefits in terms of cognitive performance improvements. The practice of sport seems to increase cerebral perfusion (Ellemberg & St-Louis-Deschênes, 2010) and the continuous stimulation of the cerebellum and frontal cortex (Budde et al., 2008; Diamond, 2000) and the consequent increase in steroid hormone levels seem to improve brain function (Budde et al., 2008; Diamond, 2000) and thus increase the potential for school performance in children and adolescents.
In terms of learning, executive functions play a key role in educational success at school as well as in life, in the cognitive, social, and psychological development of the individual (Diamond, 2014). According to scientific literature, the guidelines for Specific Learning Disorders (MIUR, 2011), drawn up in the Italian context, emphasise the fundamental preparatory executive functions to foster the effective acquisition of basic literacy skills, suggesting that both pre-school and primary schools promote the implementation of meaningful and appropriately structured movement activities that foster the acquisition of logical-mathematical skills, as well as reading performance (Blair & Razza, 2007).
The better school performance associated with a higher level of motor competence (Piek et al., 2008; Kwak et al., 2009; Magistro et al., 2015; Pesce & Ben-Soussan, 2016; Schmidt et al., 2017) is believed to be related to the mediating role of executive functions (Hillman et al., 2009; Van der Niet et al., 2014; Duran et al., 2018). Neuroscience attributes a fundamental role to the amygdala and hippocampus (Chavez et al., 2009) in activating attention processes. The latter is orientated towards emotionally relevant stimuli, and the interaction between attention and motivation enables more effective storage of information (Palumbo et al., 2020).
Coordination exercises, which are closely related to neuro-muscular function, stimulate motor functions (Gao et al., 1996), working memory (Klingberg et al., 1996; Rigoli et al., 2012), and attention (Courchesne et al., 1994). The functionality of executive processes is directly involved in motor coordination tasks.
Children with better gross motor coordination show better cognitive performance (Luz et al., 2015), and a recent literature review shows that upper-limb coordination and total gross motor scores are more correlated with school performance (Macdonald et al., 2018).
However, in light of what has been described so far regarding the benefits of practicing motor sport activities and the literature on sedentary levels, it appears that despite the growing evidence supporting the benefits of regular physical activity for children’s physical and mental health, a majority of school-age children are not sufficiently active (Lubans et al., 2016; D’Anna et al., 2024a).
At this point, it seems appropriate to go beyond what has already been pointed out regarding the positive effects of motorsport activities, also in the light of the complexity of the demands emerging from today’s socio-economic and cultural scenario, which urges a deep reflection on what specifically influences learning in relation to the different disciplines.
The scientific framework summarised above shows a wide and growing interest in the analysis of the relationship between motor skills and school achievement. There are numerous studies (Singh et al., 2019) demonstrating positive correlations, but the results often appear inconsistent (Macdonald et al., 2018) and not very orientated towards analysing the relationship between motor competence and specific school subjects.
This aspect is probably due to the complexity of the countless variables that systemically affect learning. This complexity refers to the need to investigate further and to critically analyse the results in order to take a position that is not aprioristically optimistic but pragmatic and honest, in which it is necessary to understand not only the outcomes of the experiments but also their origin in order to responsibly orient future implementations and research.
The aim of this study is to analyse and interpret the correlations between various aspects of motor competence, considering its connection to the practice of motor-sports activities in extracurricular contexts in quantitative terms. The study, moreover, investigates the relationship between motor competence and school performance across all disciplines included in the curriculum of the first, second, third, and fourth classes of primary school in the Italian context, including the behaviour grade.

2. Materials and Methods

2.1. Participants

This exploratory study is part of the research project “Motor development and learning” carried out through an agreement between the Pegaso Telematic University (Italy) and a primary school in a southern Italian city, aimed at analysing the correlation between motor skills and school performance. To be included in the project, participants had to be aged between 5 and 10 years. Moreover, they and their parents had to provide written informed consent. In an attempt to limit the variability of the study sample, children with a certified disability were excluded from the project.
Through non-probabilistic sampling, a convenience sample of 120 children aged between 6 and 10 years (average age = 7.88 ± 1.06 years, 54% male) was reached. Table 1 briefly illustrates the number of participants per class and gender and the frequency and percentages of pupils practising sport in extracurricular contexts.
As emerges from the data, the composition of the sample is substantially homogeneous by gender in the classes considered (χ2 = 0.47, p = 0.92).
Regarding the practice of sports in extracurricular hours, 70 children (58%) were involved in 2 or more hours of motorsports activity outside school; of these, 45 children (64%) were males.
On the other hand, considering only those who practise activities similar to competitive sports (such as with a commitment of four hours a week or more), there is no difference in frequency between males and females, with 25% of both groups being equally engaged in activities of this type.
The data collection took place in September and October 2024, involving classes from the first to the fourth. The motor activities, proposed with an inclusive approach, were carried out during physical education lessons according to the educational objectives of the curriculum. The administration of TGMD3 was carried out over the course of four lessons, required to complete the two subtests (Locomotion and Ball Skills) for all pupils in the class. The motor evaluation was administered by a team of 3 experts with degrees in sports sciences, with physical education teachers present. All examiners participated in a four-hour training session to ensure consistent adherence to the test protocol.
Each 60 min lesson included a general warm-up phase and a specific warm-up phase on the motor tasks to be assessed. This second phase was used to promote the children’s understanding of the motor tasks and to organise the gymnasium setting, preparing the work-stations. In the central part of the lesson (lasting approximately 30 min), each child, after a practice and simulation test, performed the two assessment tests required by the protocol. At the end of the assessment phase, a low-intensity play activity was proposed, which was useful for re-establishing resting conditions.
All children participated in the activity, although the data under investigation was only recorded for those pupils whose parents had provided consent. The research was approved by the ethics committee of the Pegaso Telematic University (ID 004813).

2.2. Tool and Measures

2.2.1. Test for the Assessment of Gross Motor Development (TGMD-3)

In order to understand the level of children’s gross motor development, the Gross Motor Development-3 Test (TGMD-3) has been used. It is an instrument that is highly appreciated by educators and teachers in the educational field as it allows them to assess the progress of the acquisition of basic motor skills in children aged 3 to 11 years and to understand whether the child is able to coordinate the totality of his or her body in movement in space and time, both free practice training (sub-test Locomotion Skills) and using objects (Ball skills) (Ulrich et al., 2023; Webster & Ulrich, 2017; Magistro et al., 2018, 2020). It is a test that is more orientated towards understanding the process of organising and controlling movement rather than on the result of the finalised motor action or performance itself. The instrument, therefore, does not assess the accuracy of throwing or running speed but focuses on the quality of the motor action.
The different skills of Locomotion (no. 6) and Ball (no. 7) are assessed through the systematic observation of a series of performance criteria; when a single criterion is met, a score of 1 is awarded; otherwise, the score is 0. Each individual skill is performed twice.
The total score of the test is given by the sum of the scalar scores obtained in the two subtests. It is certainly one of the most used instruments at the international level for the assessment of gross motor development and has demonstrated (Martins et al., 2024; Martins et al., 2023) good psychometric properties (Ulrich et al., 2023; Webster & Ulrich, 2017; Magistro et al., 2018, 2020; Walters et al., 2024).
In recent years, several validation studies of the TGMD-3 have been published (Valentini, 2012; Kim et al., 2014; Estevan et al., 2017; Wagner et al., 2017), including the Italian version (Ulrich et al., 2023).
The instrument provides, as a quantitative result, output of the scalar scores of the two subtests (Locomotion and Ball Skills) and the global score (Gross Motor Index GMI); as a qualitative interpretation, the final report indicates seven descriptive levels that guide teachers/educators in the global assessment of motor development (Table 2).

2.2.2. Academic Achievement

Starting from the school year 2020/2021, the periodic and final assessment of learning is expressed, for each of the study subjects given by the National Indications for the Curriculum from Kindergarten to the first cycle of Education (MIUR, 2012), including the cross-curricular teaching of civic education, through a descriptive assessment in the evaluation document. The descriptive assessments refer to the assessed objectives defined in the school curriculum and are related to different learning levels. The collection of data on the evaluation of school performance took place at the end of the teaching activities, according to the evaluation criteria laid down in the national evaluation regulations (corresponding to the project implementation period). The recording of the assessments, properly approved by the school and the parents of the pupils involved, included the recording of the final results for all subjects and behaviour. The output learning levels were examined, corresponding to the descriptive assessments in the individual pupil’s evaluation document. Specifically, the levels are as follows:
-
Advanced: the pupil completes tasks in known and unknown situations, using a variety of resources either provided by the teacher or found elsewhere, autonomously and continuously.
-
Intermediate: the pupil completes tasks in known situations autonomously and continuously; solves tasks in unfamiliar situations using resources provided by the teacher or found elsewhere, albeit discontinuously and not entirely autonomously.
-
Basic: the pupil completes tasks only in known situations and using the resources provided by the teacher, either autonomously but discontinuously or non-autonomously but continuously.
-
In the first stage: the pupil completes tasks only in known situations and only with the support of the teacher and specially provided resources.
The analysis of data are consistent with other studies in the literature concerning the correlation between motor skills and learning in school (Piek et al., 2008; Kwak et al., 2009; Magistro et al., 2015; Pesce & Ben-Soussan, 2016; Schmidt et al., 2017; Singh et al., 2019), in order to facilitate the statistical analysis of the data, it refers to GPA, Grade Point Average Scores (Feldman & Kubota, 2015; Batez et al., 2021). The summarised assessment levels were coded as follows:
-
Advanced: 4
-
Intermediate: 3
-
Basic: 2
-
First stage: 1.
In relation to behaviour, regulated by Legislative Decree 62 of 2017, the study refers to the summarised assessment coded as follows for each pupil:
-
Excellent: 5
-
Very good: 4
-
Good: 3
-
Sufficient: 2
-
Not Sufficient: 1.

2.2.3. Information Questionnaire

At the same time as the formal communication of the start of the research project’s teaching activities, the teachers submitted to the families an information questionnaire in order to collect the following information:
  • Personal data
  • Anthropometric data
  • Class
  • Extra-curricular sports practice (discipline, no. of hours per day and week of training).
Extra-curricular sports include all activities of a motor, recreational, or sporting nature that children perform outside school time in non-formal learning contexts at local sports associations. For each activity indicated in the questionnaire, it was requested to specify the type of discipline and the amount of time spent on training.

2.3. Data Analysis

The assessments obtained in the individual disciplines and behaviour were converted into a numerical scale, as described above. It was then decided to consider for each child the average of the assessments in the Theoretical Disciplines (TD: Italian, History, Geography, Mathematics, Science) and the Laboratory Disciplines (LD: Technology, Art, and Music), in addition to the Physical Education (PE) and Behaviour (B) grades. Possible differences in the academic achievements between females and males were assessed using a one-way MANOVA and performing the subsequent t-tests for each of the four assessments considered.
The relationship between gross motor skills and learning was instead tested by calculating the Spearman correlation between the children’s TGMD-3 scores (Gross Motor Index, Locomotion, and Ball scaled scores) and the school assessments. In order to reveal possible differences between genders, the same analysis was conducted separately in the female and male groups.
In addition, the relationship between the practice of extracurricular sporting activity and school performance was analysed. For this purpose, a one-way MANOVA was conducted comparing the children engaged in extracurricular sport (by convention, these will be referred to as ‘sportspeople’ S) and those who were not (these will be referred to as ‘non-sportspeople’ NS) for the school assessments used in the previous analyses. Then, t-tests were performed to reveal differences in the individual assessments. In addition, and limited to the group of sportspeople, the Spearman correlation between the number of hours of extracurricular sport practiced per week and the learning assessments was calculated.
Finally, the relationship between sports practice and learning was investigated separately in the group of females and males by comparing, through the Wilcoxon test for independent samples, the learning assessment obtained by sportspeople and non-sportspeople.
All analyses were conducted with the statistical software R (v4.3.0) (R Core Team, 2023). The statistical significance level was set at alpha = 0.05, and p-values were adjusted using Bonferroni’s correction for multiple comparisons where appropriate.

3. Results

3.1. School Learning and Gender

Regarding the assessments of learning and behaviour, the one-way MANOVA conducted to compare females and males was found to be statistically significant (F(4,115) = 2.676, Pillai’s Trace = 0.085, p = 0.035). The subsequent independent samples t-tests (Table 3) showed a statistically significant difference according to gender only for the assessment of behaviour (t(118) = −2.78, p = 0.006), with the mean of the girls‘ group (4.24 ± 0.92) being higher than that of the boys’ group (3.78 ± 0.86).

3.2. Gross Motor Skills

In relation to the assessment of gross motor skills (Table 4), in general, only a few children were in the ‘Superior’-‘Very Advanced’ bands, while as many as 18% of the sample fell into the ‘Borderline’ or ‘Compromised’ bands for GMI (27% of females against 11% of males), and for Ball skills (29% of females against 7% of males) and 13% for Locomotion skills (16% of females and 11% of males). Fisher’s exact test showed a statistically significant association between gross motor skills level and gender only for Ball skills (p = 0.004).

3.3. Relationship Between Gross Motor Skills and Learning

As shown in Table 5, the Spearman correlation conducted between the TGMD-3 standard scores (Gross Motor Skills Index, Locomotion, and Ball Scaled Scores) and the learning assessments (Theoretical Disciplines Averages, Laboratory Disciplines Averages, Physical Education, and Behavioural Grades) showed weak intensity and no statistical significance. Instead, when the same analyses were carried out separately according to gender, only weak and non-significant correlations, mostly of a negative type, were revealed in the group of males. In the group of females, on the other hand, positive, mostly moderate, and statistically significant correlations emerged between GMI and the scaled Ball scores with the learning assessments, except for Physical Education.

3.4. Relationship Between Extracurricular Sport and Learning

The MANOVA conducted to test possible differences in learning between sportspeople and non-sportspeople showed statistical significance (F(4,115) = 2.550, Pillai’s Trace = 0.081, p = 0.043). Subsequent t-tests for independent samples were found to be significant for all school achievements except Behaviour (Figure 1), showing higher means in the sportspeople.
In the sportspeople group (70 children), a possible relationship was explored between the number of hours of sport practiced per week and the learning assessments. The obtained Spearman’s coefficients were all low (rhoTD = −0.16, rhoLD = −0.07, rhoPE = 0.06, rhoB = −0.15) and lacking statistical significance.
It was also tested whether the differences in learning found in the total sample between sportspeople and non-sports people were also maintained in the group of females and males considered separately. Since the Shapiro–Wilk test revealed a non-normal distribution of the learning assessments in these subgroups, comparisons were conducted using the Wilcoxon test for independent samples (Table 6).
As for the group of females, sporty females showed higher means in all assessments, but reaching a statistically significant difference in the distribution only for LD (p = 0.026) (Table 6). Considering the male group instead, a statistically significant difference was found for LD (p = 0.03) and PE (p = 0.02) and marginal significance for the comparison in TD. In all cases, sporty males had higher mean assessments than non-sporty males (Table 6).

4. Discussion

4.1. School Learning and Gender

As described above, the results of school learning were analysed through the assessments of the curriculum subjects at the end of the school year and considering four variables: Theoretical Disciplines (TD), mean of the assessments of Italian, History, Geography, Mathematics, and Science); Laboratory Disciplines (LD, average of the assessments of Technology, Art, and Music); Physical Education (PE); and Behaviour (B).
The comparison between males and females for each of the four variables showed that the assessments reported by females were on average higher than those of males, reaching statistical significance for Behaviour. This data are in accordance with the scientific literature (Voyer & Voyer, 2014; O’Dea et al., 2018) that reports a better performance in the female gender and seems to be confirmed by the INVALSI surveys analysing the outcomes of school learning in Italy. The 2021 national report shows a higher grade variation in girls who, on average, perform better in all areas, with a more relevant advantage in non-STEM subjects (such as Italian and English) and in behavioural grades. According to the scientific literature, female pupils are more disciplined than male pupils, and better behaviour in terms of conduct and school commitment leads to better performance in studies and daily school activities (Hartley & Sutton, 2013). The European report (Eurydice, 2010), focusing on gender differences in educational achievement, shows that, in general, the relative superiority of females in performance appears to be fairly constant over the years. This female trend is probably linked to psychological factors, certainly including the greater affinity of females to the ‘learning culture,’ while male outcomes are more influenced by discipline and behavioural problems (Halldórsson & Ólafsson, 2009).
In general, there is a relationship between school behaviour, psychological and socio-economic factors; problems are often associated with a combination of factors (Livaditis et al., 2003; Sammons et al., 2008) that appear very complex to analyse. From the boys’ statements, the presence of gender stereotypes, according to which girls are perceived as academically superior in terms of motivation, ability, performance, and self-regulation, seems to affect school performance. However, previous studies investigating gender differences in different domains of academic achievement have found rather inconsistent results (Rimm-Kaufman et al., 2000; Bodrova & Leong, 2008; Ursache et al., 2012).
The study, which here analyses and describes only the quantitative data relating to learning assessments, also provided for a shared consideration between teachers and researchers, aimed at observing certain qualitative information useful for conducting a critical analysis of the results. According to the teachers involved in the project, the girls are, consistent with the literature, more attentive and concentrated in their teaching activities. Studies describe the ability to self-regulate and to be able to sit and listen, as one of the most important requirements for academic success (Rimm-Kaufman et al., 2000).

4.2. Gross Motor Skills

Although the study has provided for the division of the total sample into two groups (sportspeople and non-sportspeople), on the basis of the participants‘ parents’ declarations regarding the performance of motor activities during extracurricular hours, the results that emerged in relation to gross motor skills show values in accordance with the information present in the literature, relating to sedentariness and the impoverishment of movement experiences reported in the introduction (Lubans et al., 2016; D’Anna et al., 2024a). In particular, for the three observation levels of the TGMD-3 (Ulrich, 2020; Ulrich et al., 2023), extremely low values are recorded for the ‘superior/very advanced’ category for the GMI, both for Locomotion and Ball control. Specifically in reference to Ball skills, females are placed in the ‘Borderline—Impaired’ category, with a percentage of 29%, compared to 7% for males. This data, as well as the higher levels of GMI in males, could be associated with the fact that, in the sample investigated in this study, boys have higher levels of organised physical activity, a trend that coincides with the results of the ISTAT surveys of the Italian population.
A recent study conducted in India (Shivaraju, 2024) about gender differences detected through the Test for the Assessment of Gross Motor Development (TGMD-2) (Ulrich, 2000) reported that, while locomotor skills show almost similar values between boys and girls, the results of the Ball skills subtest show significantly better performance in boys.
Regarding the practice of sports in extracurricular hours, 70 children (58%) were involved in 2 or more hours of motor-sports activity outside school; of these, 45 children (64%) were males. This could partly explain the slightly low GMI values since it confirms limited participation in organised physical activity that does not meet the minimum recommended time levels.

4.3. Relationship Between Gross Motor Skills and Learning

The study related the gross motor skills just described with learning. In this regard, the correlation (Spearman’s Rho) between motor skills (in the three variables Gross Motor Index, Locomotion skills, and Ball skills) and learning, grouped in the four variables (TD, LD, PE, B), was generally positive, albeit of weak intensity and not statistically significant. Instead, in the analyses differentiated by gender, in the group of females, the correlations between GMI/TD (0.41) and GMI/LD (0.44) are of medium intensity and statistically significant. The values are also similar in the correlation between TD and LD and the ball control skills subtest, while the correlation between the level of motor skills and the girls’ behaviour grade (GMI/B) is significant (<0.01) with a correlation of 0.48, as well as the correlation between the behaviour grade and ball control skills subtest score (BS/B) with a correlation of 0.41. By contrast, the correlation pattern for boys appears different, with very weak and mostly negative correlations.
The correlation between the results obtained from the motor skills assessment and the PE grade appears to be weak or negative for both females and males, with a prevalence of negative values for the male group in this case. This rather inconsistent data suggests the need to reflect on the complexity of conducting an objective assessment of levels of motor competence in the Italian school context, in which the figure of the specialised physical education teacher has only recently been introduced. In particular, it should be pointed out that, while assessments referring to gross motor skills have seen the involvement of expert personnel (always the same) engaged in the administration of standardised procedures, school assessments have been drawn up and recorded by generalist teachers, belonging to different class councils.

4.4. Relationship Between Extracurricular Sport and Learning

The analysis of the prevalence of sports practice in extracurricular contexts shows that 58% of the children are engaged in 2 or more hours per week in specific training of a motor-sport activity. In general, the comparison by gender in relation to the practice of extracurricular sports activities underlines a significant difference between males and females. The latter are in fact less involved in extracurricular sporting activities than males (46% of females vs. 69% of males carry out extracurricular sports) (Table 1).
These data are consistent with what is reported in statistical surveys on motor and/or sporting practice conducted in Italy: the percentage of females who engage in motor and sporting activities is significantly lower than that of males. According to the ISTAT (2021) report, it emerges, in fact, that the levels of sports practice are higher for the male gender than for the female gender: 27.9% compared to 19.6% for those who practice sport continuously and 11.9% compared to 10.0% for those who do it occasionally.
Concerning the comparison between the group of participants who practiced extra-curricular sports (S) and those who did not (NS), statistically significant differences emerged in relation to theoretical disciplines, laboratory disciplines, and physical education, while no difference emerged concerning the assessment of behaviour. Even in this case, the results appear to be consistent with the rapidly expanding literature examining the association between physical activity, cognition, and school performance. This is also confirmed by a recent systematic review that reports positive and significant associations between several components of motor activity and measures of school performance in mathematics and reading, especially in relation to the early school years (Lopes et al., 2013), as well as a 2018 meta-analysis that highlighted the ability of physical activity to positively influence multiple domains of executive functions, attention, and school performance in preadolescent children (6–12 years of age) (De Greeff et al., 2018).
In the comparison between sportspeople and non-sport people, performed separately in the female and male groups, different results emerged (Table 6). Specifically, females who practiced sports showed a statistically significant higher performance in laboratory disciplines than non-sport females. On the other hand, males showed a marginal significance (p = 0.06) in the difference between sportspeople (M_S) and non-sportspeople (M_NS) in relation to the performance in the theoretical disciplines and statistically significant differences in relation to laboratory disciplines and physical education, with the male sportspeople reporting higher grades.
The above mentioned results lead to the deduction of a better approach to study by those who practice sport, favoured, probably, by the better level of attentional skill of those who practice sport (Gallotta et al., 2015). The focus on particularly relevant sources of information, together with the ability to select different stimuli quickly, to allocate attention to different points in space, or to move it in response to the various unpredictable situations during a competition, are aspects that are strongly stressed during sporting activities (Bagnara, 1993). There are numerous studies in the literature that, in analysing the effects of physical activity on cognitive processes, in addition to the positive relationship between motor practice and the acquisition of executive functions (described as inhibitory control, working memory, and cognitive flexibility) (Donnelly et al., 2016), highlight its benefits in the development of basic literacy skills and competences, as well as in more complex learning processes (Tomporowski & Pesce, 2019; Erickson et al., 2019; Pontifex et al., 2019).
The studies carried out so far, including this survey, give physical education, conducted within the context of school experiences, the ability to contribute to the effective acquisition of an individual repertoire of motor skills, a veritable motor alphabet that, in its corroborated interdependence with other alphabets relating to the learning of reading, writing, mathematics, and drawing (Colella, 2018; Edwards et al., 2017; Whitehead, 2010), contributes to the child’s global development.
It is, however, important to emphasise the fact that the advantages reported above are not directly attributable to participation in school motor and sports activities tout court, the same for all, but rather depend on a conscious and competent implementation of educational approaches that are able to involve the child in meaningful movement experiences capable of stimulating the exercise of agency (Borgogni & Giraldo, 2023), in favouring the pursuit of functional objectives that are co-defined with the environment (Minghelli et al., 2023), and continuously stimulating adaptive functions capable of effectively responding to environmental challenges (Coppola et al., 2024). Furthermore, contexts orientated to the implementation of positive experiences, focused on fun, on the variability of stimuli, and on the active involvement of all (Rudd et al., 2021), structured and managed by committed teachers, prepared and, in extracurricular contexts, supported by coaches and parents who are informed and involved, are able to significantly amplify the potential of motor-sports activities (Bailey, 2005, 2006; D’Anna et al., 2024b). Only in this way will motor and sport activities conducted in school and extracurricular contexts be able to promote learning and personal development.

Strengths and Limitations

This study contributes to expanding the knowledge on the relationship between motor skills and school performance in developmental age, providing valuable insights in relation to the Italian educational context. The use of a standardised tool such as the TGMD3 for the assessment of motor skills is a further strength of this study that supports its scientific solidity. Moreover, the differences between males and females found in some comparisons open up new areas for reflection on the possibilities of designing more personalised approaches to physical education. Nevertheless, several limitations have to be highlighted. The sample size (120 children) is relatively small and might not be completely representative, limiting the generalisability of the results. Also, the lack of statistical significance in some comparisons, especially those related to subgroups, might be attributable to the small sample size. Moreover, the exploratory and correlational character of this study, while highlighting some associations between variables, does not allow for the establishment of causal relationships between motor skills, sports practices, and school performance. In addition, some correlations are weak, suggesting that the factors investigated may not be sufficient to explain the differences in school performance. For instance, information on the socio-economic status of children could have enabled the analysis, study, and interpretation of the various correlations, even taking into account this important variable. Furthermore, this study examined the practice of sports activities in extracurricular contexts, but specific qualitative and quantitative aspects of those activities were not analysed in detail.
We therefore reserve for further research the opportunity to collect more specific information on the type of sports discipline, the intensity of the training sessions, the weekly frequency, the technical level, etc. A further limitation already highlighted in the discussions is that the recent introduction of the specialised teacher in the Italian context and the lack of consistency in disciplinary evaluation could have influenced the results and introduced additional confounding variables. In summary, this study contributes useful information on the link between physical activity, learning, and overall child motor development, with specific regard to the formal school context. However, it also highlights the need for further investigations on larger samples and the implementation of a methodological approach able to overcome the organisational and evaluation criticalities that emerged.

5. Conclusions

The results of the study, which aims to investigate the relationship between motor skills and school learning in the primary school period, show a positive relationship between extracurricular sporting practice and school performance, which is most evident in the female gender.
The data, although collected on a small sample, allow us to analyse the extracurricular sport variable as a source of additional stimuli to the learning and the overall development of the person in relation to the school assessments of the various disciplines in the curriculum, including the behaviour grade.
Critical consideration of the quantitative data analysed has revealed some critical points that are mainly linked to the current organisational and teaching conditions of physical education at school: (1) the recent introduction of the specialised teacher in Physical Education (not yet active in all primary school classes); (2) the difficulties in implementing effective teaching actions and proposing them with constancy and continuity; (3) the lack of specific professional skills in motor assessment by generalist teachers with the consequent implementation of assessments that are not always objective and reliable; (4) lack of uniformity in the system of disciplinary assessments.
It would be interesting to understand whether an adequate and effective organisation and implementation of extracurricular sporting activities, within the formal learning context of the school, can have greater effects on the development and learning of skills and competences than the practice of sports in non-formal learning contexts. In fact, the different intensities and types of practice proposals that could provide very useful information for both policy organisations and the creation of meaningful learning environments, well-calibrated in intensity and characteristics with respect to different age groups, could be investigated. Such studies would best support, in the light of the scientific evidence, teachers’ instructional planning activities by creating the conditions for activating educational alliances that significantly influence the activity and increase the probability of realising its potential benefits.

Author Contributions

Conceptualization, C.D. and I.B.; methodology, C.D. and I.B.; formal analysis, I.B.; investigation, G.A. and V.M.; data curation, G.A. and C.D.; writing—original draft preparation, C.D., I.B. and V.M.; writing—review and editing, C.D., I.B. and V.M.; visualization, I.B.; supervision, P.L.; project administration, C.D.; funding acquisition, P.L. All authors have read and agreed to the published version of the manuscript.

Funding

The APC was funded by Pegaso Telematic University. Project “Human performance and health promotion” PRA L05.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of Pegaso Telematic University (ID 004813 Prot/e 004813, 09/07/2024).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data supporting the findings reported in this study are not publicly available due to privacy reasons. Nevertheless, they can be requested from the corresponding author for well-motivated reasons.

Conflicts of Interest

The authors declare no conflicts of interest.

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Education 15 00124 g001
Figure 1. Comparison in learning assessments according to practising (S) or not practising (NS) extracurricular sport (mean value in each boxplot).
Figure 1. Comparison in learning assessments according to practising (S) or not practising (NS) extracurricular sport (mean value in each boxplot).
Education 15 00124 g001
Table 1. Composition of the sample (gender, class, and extracurricular sport).
Table 1. Composition of the sample (gender, class, and extracurricular sport).
Total SampleFemalesMales
N, %12055 (46)65 (54)
Class
First (N, %)34 (28)16 (29)18 (28)
Second (N, %)43 (36)18 (33)25 (38)
Third (N, %)22 (18)11 (20)11 (17)
Fourth (N, %)21 (17)10 (18)11 (17)
Extracurricular sport
No (N, %)50 (42)30 (55)20 (31)
Yes (N, %)70 (58)25 (45) 45 (69)
 2–3 h per week (N, %)52 (75)18 (75)34 (75)
 ≥4 h per week (N, %)17 (25)6 (25)11 (25)
Table 2. Descriptive terms for TGMD-3 Standard Scores.
Table 2. Descriptive terms for TGMD-3 Standard Scores.
Subtest Scaled ScoresDescriptive TermsGross Motor Index
17–20Gifted or very advanced>129
15–16Superior120–129
13–14Above average110–119
8–12Average90–109
6–7Below average80–89
4–5Borderline impaired or delayed70–79
1–3Impaired or delayed<70
Table 3. Comparison of assessments of female and male learning (N = 120, independent samples t-test).
Table 3. Comparison of assessments of female and male learning (N = 120, independent samples t-test).
Academic AchievementsTotal Sample Mean (SD)Females Mean (SD)Males Mean (SD)t (118)p-Value
Theoretical Disciplines
(range 1 to 4)		3.27 (0.69)3.31 (0.68)3.23 (0.71)−0.590.557
Laboratory Disciplines
(range 1 to 4)		3.36 (0.63)3.42 (0.68)3.30 (0.58)−1.050.294
Physical Education
(range 1 to 4)		3.46 (0.65)3.49 (0.69)3.43 (0.61)−0.510.614
Behaviour
(range 1 to 5)		3.99 (0.91)4.24 (0.92)3.78 (0.86)−2.780.006
Table 4. Assessment of gross motor skills according to TGMD-3 in the total sample and in the group of females and males separately.
Table 4. Assessment of gross motor skills according to TGMD-3 in the total sample and in the group of females and males separately.
TGMD-3Total Sample
(N, %)		Females
(N, %)		Males
(N, %)
Gross Motor Index
Gifted–Superior7 (6)3 (5)4 (6)
Above average–Below average91 (76)37 (68)54 (83)
Borderline–Impaired 22 (18)15 (27)7 (11)
Locomotion skills
Gifted–Superior4 (3)/4 (6)
Above average–Below average 100 (84)46 (84)54 (83)
Borderline–Impaired16 (13)9 (16)7 (11)
Ball Skills
Gifted–Superior 7 (6)4 (7) *3 (5) *
Above average–Below average92 (76)35 (64) *57 (88) *
Borderline–Impaired21 (18)16 (29) *5 (7) *
Note. * Statistically significant association between Ball skills level and gender (Fisher’s exact test, p = 0.004).
Table 5. Correlation between gross motor skills (standard scores) and learning (Spearman’s Rho).
Table 5. Correlation between gross motor skills (standard scores) and learning (Spearman’s Rho).
TGMD-3Theoretical DisciplinesLaboratory DisciplinesPhysical EducationBehaviour
Total sampleGross Motor Index0.150.160.010.12
Locomotion Skills0.030.03−0.150.11
Ball Skills0.170.160.110.07
FemalesGross Motor Index0.41 *0.44 *0.220.48 **
Locomotion Skills0.220.23−0.040.31
Ball Skills0.38 *0.40 *0.280.41 *
MalesGross Motor Index−0.06−0.06−0.18−0.13
Locomotion Skills−0.11−0.12−0.24−0.06
Ball Skills0.01−0.03−0.05−0.17
Note. ** p < 0.01, * p < 0.05 (after Bonferroni correction for multiple comparisons).
Table 6. Comparison of the learnings of sportspeople and non-sports people in the group of females and males considered separately (Wilcoxon test for independent samples).
Table 6. Comparison of the learnings of sportspeople and non-sports people in the group of females and males considered separately (Wilcoxon test for independent samples).
Academic AchievementsF_NS
Mean (SD)		F_S
Mean (SD)		W
p-Value		M_NS
Mean (SD)		M_S
Mean (SD)		W
p-Value
Theoretical Disciplines3.15 (0.75)3.50 (0.54)278
0.095		2.99 (0.68)3.34 (0.70)319
0.060
Laboratory Disciplines3.24 (0.76)3.64 (0.52)254
0.029		3.08 (0.56)3.40 (0.57)304
0.029
Physical Education3.40 (0.72)3.60 (0.65)318
0.272		3.20 (0.52)3.53 (0.63)306
0.022
Behaviour4.03 (1.03)4.48 (0.71)288
0.114		3.75 (0.91)3.80 (0.84)439
0.879
Note: F_NS = non-sporty females; F_S = sporty females; M_NS = non-sporty males; M_S = sporty males.
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D’Anna, C.; Basadonne, I.; Aquino, G.; Minghelli, V.; Limone, P. Relationships Between Motor Skills and Academic Achievement: An Exploratory Study on Italian Primary School Children. Educ. Sci. 2025, 15, 124. https://doi.org/10.3390/educsci15020124

AMA Style

D’Anna C, Basadonne I, Aquino G, Minghelli V, Limone P. Relationships Between Motor Skills and Academic Achievement: An Exploratory Study on Italian Primary School Children. Education Sciences. 2025; 15(2):124. https://doi.org/10.3390/educsci15020124

Chicago/Turabian Style

D’Anna, Cristiana, Ilaria Basadonne, Giovanna Aquino, Valeria Minghelli, and Pierpaolo Limone. 2025. "Relationships Between Motor Skills and Academic Achievement: An Exploratory Study on Italian Primary School Children" Education Sciences 15, no. 2: 124. https://doi.org/10.3390/educsci15020124

APA Style

D’Anna, C., Basadonne, I., Aquino, G., Minghelli, V., & Limone, P. (2025). Relationships Between Motor Skills and Academic Achievement: An Exploratory Study on Italian Primary School Children. Education Sciences, 15(2), 124. https://doi.org/10.3390/educsci15020124

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