Preferred Learning Styles of Sport Students in Higher Education in Algeria: An Analysis Using the Felder-Silverman Model
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Estilos de Aprendizaje Preferidos de los Estudiantes de Deporte en Educación Superior en Argelia: Un Análisis Utilizando el Modelo de Felder-Silverman
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Estilos de Aprendizagem Preferidos dos Estudantes de Esporte no Ensino Superior na Argélia: Uma Análise Utilizando o Modelo de Felder-Silverman

Amina Chafaa
University of Mohamed Lamine Debaghine - Sétif2, Algeria Sciences of physical activities and public health Laboratory, Algeria
a.chafaa@univ-setif2.dz
https://orcid.org/0009-0001-5245-5379

Fecha de Recepción: 17 de septiembre de 2024 (Received:September 17,2024)
Fecha de Aceptación: 14 de marzo de 2025 (Accepted:March 14, 2025)
Fecha de Publicación: 17 de abril de 2025 (Published:April 17,2025)

Financiamiento:
La investigación fue autofinanciada por los autores.
(Funding: This work was funded with personal resources).

Conflictos de interés:
Los autores declaran no presentar conflicto de interés.
(Conflicts of interest: The author declares no conflicts of interest).

Correspondencia:
Nombres y Apellidos: Amina Chafaa
Correo electrónico: a.chafaa@univ-setif2.dz

Abstract
This study aimed to investigate the preferred learning styles of sports students in higher education in Algeria. Using the Felder-Silverman model, which categorizes learning styles into four dimensions: active-reflective, visual-verbal, sensing-intuitive, and sequential-global, the research also examined differences in learning styles based on specialization, academic level, and diploma. The research involved 268 students from the Sports Institute in Setif, and the data were analyzed using SPSS version 28. The findings revealed a predominant preference for the visual learning style, followed by the sensing and sequential styles. No significant differences were found in learning styles according to specialization. However, significant differences were observed between groups based on academic level and diploma, and the study recommended creating training courses for teachers that adopt modern methods and encourage them to consider the learning styles of each student.

Key words: learning styles. sport. student. Felder-Silverman model. learning.

Resumen
El estudio tiene como objetivo investigar los estilos de aprendizaje preferidos de los estudiantes de deporte en la educación superior en Argelia. Utilizando el modelo de Felder-Silverman, que categoriza los estilos de aprendizaje en cuatro dimensiones: activo-reflexivo, visual-verbal, sensorial-intuitivo y secuencial-global, la investigación también examinó las diferencias en los estilos de aprendizaje según la especialización, el nivel académico y el diploma. La investigación involucró a 268 estudiantes del Instituto de Deportes en Setif, analizados utilizando SPSS versión 28. Los hallazgos revelaron una preferencia predominante por el estilo de aprendizaje visual, seguido por los estilos sensorial y secuencial. No se encontraron diferencias significativas en los estilos de aprendizaje según la especialización. Sin embargo, se observaron diferencias significativas entre grupos basadas en el nivel académico y el diploma. El estudio recomendó trabajar en la creación de cursos de formación para profesores que adopten métodos modernos y alentar a los profesores a considerar los estilos de aprendizaje de cada estudiante.

Palabras clave: estilos de aprendizaje. deporte. estudiante. modelo de Felder-Silverman. aprendizaje.

Resumo
O estudo visa investigar os estilos de aprendizagem preferidos dos estudantes de esporte no ensino superior na Argélia. Utilizando o modelo de Felder-Silverman, que categoriza os estilos de aprendizagem em quatro dimensões: ativo-reflexivo, visual-verbal, sensorial-intuitivo e sequencial-global, a pesquisa também examinou diferenças nos estilos de aprendizagem com base na especialização, nível acadêmico e diploma. A pesquisa envolveu 268 estudantes do Instituto de Esportes em Setif, analisados usando o SPSS versão 28. Os resultados revelaram uma preferência predominante pelo estilo de aprendizagem visual, seguido pelos estilos sensorial e sequencial. Não foram encontradas diferenças significativas nos estilos de aprendizagem de acordo com a especialização. No entanto, diferenças significativas foram observadas entre grupos com base no nível acadêmico e diploma. O estudo recomendou trabalhar na criação de cursos de treinamento para professores que adotem métodos modernos e incentivar os professores a considerar os estilos de aprendizagem de cada aluno.

Palavras-chave: estilos de aprendizagem. esporte. estudante. modelo de Felder-Silverman. aprendizagem.

Introduction

Learning style theory aims to indicate that each learner has their own learning style. According to Tilly Mortimore, learning style is an aspect of cognition.^[1] Rita and Dunn defined learning style as the method by which an individual begins to concentrate on processing and retaining difficult and new information.^[2] According to Dunn and Dunn, understanding students' learning is an important part of selecting learning strategies, but unfortunately, education often continues in traditional ways that completely ignore the individual differences between students and their preferred learning styles.^[3]

A study by Gadt and Price indicated that learning styles represent an individual learner's preference for certain educational materials.^[4] The study also concluded that there is a strong relationship between a student's learning style and their academic success, meaning that understanding and recognizing individual learning styles can lead to more efficient learning.^[5] Researchers like Griggs, James, Gardner, and Kolb concurred that accommodating students' learning styles enhances their learning, underscoring the critical role of teachers in adapting educational strategies to meet their needs in the classroom.^[6] Paul also noted that understanding students' needs in terms of learning styles is essential for effective learning.^[7]

Furthermore, learning styles are characterized by an individual's approach to their own learning from the perspective of the learner.^[8] Learning styles refer to the method or style by which a learner perceives things better; each learner has their own individual learning style, similar to a signature.^[9] Utilizing their own learning style allows learners to learn quickly and enjoy themselves.^[10] Dunn and Dunn defined learning styles as a set of biological and developmental characteristics that make learning effective for some students and ineffective for others.^[11] This means that learning styles explain how a learner can focus, understand, process, and retrieve difficult and new information.^[12] The term or concept of learning styles refers to several ways in which most people learn. Jessica Blackmore, quoting Litziger, and Osif believe that learning styles are the different ways through which a learner thinks and learns.^[13]

Learning styles have garnered significant attention from educators for two main reasons: Firstly, studies conducted by various researchers, including Hooker and Vittetoe in 1983 and Svinki and Dixan in 1987, have proven their success and effectiveness in aligning and suiting learners' educational purposes.^[14] Secondly, it is believed that students who can effectively utilize multiple learning styles are able to successfully adapt to any educational situation, as confirmed by Honey, Mumford, and Dixon.^[15] Researchers in educational psychology believe that identifying students' fundamental learning styles can improve teaching.^[16] In addition, Cooper Ryan advocates for the application of learning styles theory, as many educators believe that curricula and teaching methods should offer a variety of lessons tailored to different grades.^[17] This means that teachers must accommodate students' various learning styles by altering teaching methodologies and assessment methods to reach all students. Flexibility and diversity are key, and it should not be assumed that all students learn the way the teacher teaches. We should not underestimate students because their learning styles differ from the teacher's teaching method. It is also a strong approach to academic teaching, in addition to encouraging teachers to use media and technological tools to reach all students.^[18] Over the past forty years, a number of learning style models have been developed, each claiming to evaluate learning in a unique way.^[19] A variety of models exist, such as Honey and Mumford (1983), Kolb's Learning Style Inventory (1984), the Myers-Briggs Type Indicator (1980), and the Felder-Silverman (1988) Index of Learning Styles (ILS).^[20]

The reviewed studies provide a comprehensive analysis of learning styles within the context of sports and physical education, highlighting a significant trend towards kinesthetic learning preferences among athletes and sports-related students. Starting with Ashadi et al., the research focused on the learning styles of college student athletes, particularly in preparation for distance learning.^[21] The study revealed a strong preference for kinesthetic learning styles, emphasizing the need for diverse learning strategies in distance learning environments to cater to these preferences.^[22] Similarly, Bostanci explored the learning styles of prospective teachers in sport sciences education, finding a predominant preference for kinesthetic learning among the students.^[23] This aligns with the physical nature of their studies and suggests that tailoring educational strategies to these learning styles can enhance academic quality and achievement.^[24] Braakhuis investigated the learning styles of elite and sub-elite athletes, noting a preference for kinesthetic and multimodal learning methods.^[25] The study highlighted the importance of considering these preferences in training and educational interventions designed by coaches and sports educators.^[26] In a related study, Cid et al. provided an overview of learning styles in physical education, discussing various theories and models.^[27] The chapter emphasized the importance of adapting teaching methods to suit different learning preferences to improve educational outcomes.^[28] Fuelscher et al. reviewed literature on learning styles in the context of motor and sport skills, advocating for a nuanced understanding of learning styles to optimize training and performance in sports.^[29] Peters et al. examined the learning styles of students enrolled in sports-related programs in higher education, finding a variety of learning preferences with a notable inclination towards kinesthetic learning.^[30] This underscores the need for educational practices to align with these diverse learning styles to enhance learning outcomes.^[31] Lastly, Stradley et al. assessed the learning styles of undergraduate athletic training students, finding a diverse range of learning methods.^[32] The study suggests that athletic training educators should consider these preferences when designing curricula and instructional strategies.^[33] In conclusion, these studies collectively emphasize the prevalence of kinesthetic learning preferences among individuals involved in physical education and sports.^[34] This trend highlights the need for educators, coaches, and program designers to consider these preferences when developing educational and training programs to enhance learning efficacy and performance in sports-related fields.^[35] The study of Braakhuis et al. compared learning style preferences of elite athletes based on gender, sport, and achievement level.^[36] Most athletes preferred kinesthetic and multimodal learning, with significant relationships between gender, athlete level, and VARK preferences.^[37] The results suggest notable differences in learning style preferences between males and females, and athletes at different levels, highlighting the need for health professionals to use a mix of learning styles when working with athletes.^[38]

The study will rely on the Felder and Silverman model, which defines learning styles as a set of cognitive, affective, and psychological behaviors that function together as reasonably reliable indices of students' perceptions, interactions, and responses to the learning environment.^[39] It categorizes students into four dimensions: active-reflective (processing information), visual-verbal (presenting information), sensing-intuitive (organizing information), and sequential-global (understanding information).^[40] Extensive testing has demonstrated that the Felder-Silverman model is a well-established theoretical model that is highly valid and reliable; learner preferences are flexible and not limited to a single category.^[41] Chahida and Gleen justified the Felder-Silverman model's extensive use in the technology field, citing its ease of use with the Index of Learning Styles (ILS).^[42] Furthermore, Gordana confirmed that this model is the most widely used in e-learning.^[43] According to Nabila in her study, the reason for using the Index of Learning Styles is that it is a result of a combination of other important learning style models, such as Kolb's model.^[44] Although the dimensions it uses are not new compared to other models, the way it blends and processes them is novel.^[45] This has led to the following questions:

•      What is the preferred learning style among sports students?
•        Are there statistically significant differences in students’ preferred learning styles based on the field of specialization?
•       Are there statistically significant differences in students’ preferred learning styles according to their academic level?
•      Are there statistically significant differences in students’ preferred learning styles according to diplomas?

2. Method

1. Participants

According to the G-Power analysis results, to detect a medium effect size (d = 0.5) with 80% power and a 5% significance level (two-tailed) when comparing the means of two independent groups of similar size, a total sample size of 128 is required, with 64 participants in each group. Similarly, the G-Power analysis results show that detecting a medium effect size (f = 0.25) with 5 groups, an alpha of 0.05, and a target power of 0.80 requires a total sample size of 200; With 40 participants in each of the 5 groups, the analysis indicated that a sample size of 268 is sufficient to conduct the study. The sample for this study was drawn from the Institute of Physical Activities and Sports Science and Technology in Setif City for the academic year 2022-2023. The participants were randomly selected and had an average age of 24 years.

Table 1. Research Participants.

2. Instruments

The Index of Learning Styles Questionnaire, abbreviated as "ILS" and developed by Felder and Silverman in 1998, is a tool consisting of 44 items designed to assess an individual's preferences across four dimensions: active-reflective, sensing-intuitive, visual-verbal, and sequential-global. Each dimension is represented by 11 mandatory items where the respondent must choose between two options (a) or (b). Learning styles are expressed in values ranging from +11 to -11 for each dimension, with increments of +2 or -2 to achieve three levels of preference: strong, moderate and balanced as shown in the following diagram ^[46]; ^[47].

3. Study procedure

In our study, we initially delved into the theoretical foundations of learning styles before employing the Index of Learning Styles Questionnaire by Felder and Silverman for our survey research.^[48] To validate the relevance and clarity of the scale's items, we consulted with field experts. We then distributed 27 questionnaires to students at the Sports Institute at the University of Setif as part of our preliminary survey. After gathering the responses, we conducted a thorough analysis to ascertain the time required to complete the questionnaire. We evaluated the psychometric properties of the tool before administering it to the primary sample of 268 students.

4.  Psychometric properties Validity

We computed the Pearson correlation coefficient to evaluate the validity of the instrument, as indicated in Table 2.^[49]

Table 2. Correlation coefficients between dimensions

The table shows that the correlation coefficients between the dimensions and others range from 0.406 to 0.585. As a result, the findings show that the instrument has a high internal consistency.

Reliability

To examine the instrument's reliability, we calculated the Cronbach's alpha coefficient for each dimension, as indicated in Table 3.^[50]

Table 3. Reliability coefficients for the Index of Learning Styles Questionnaire  

The reliability coefficient for the ILS   instrument was high and good, ranging from 0.727 to 0.781, indicating that the scale is stable and dependable in measuring the variable under research.

2.5.  Statistical analysis

The data were statistically evaluated with SPSS version 28 software. Several statistical tests were used, including correlation coefficients, Cronbach's alpha for reliability, means, and standard deviations,^[51] an independent samples t-test to assess differences between groups, the Kolmogorov-Smirnov and Shapiro-Wilk tests of normality,^[52] and an ANOVA test to identify differences among groups based on their academic level.^[53]

2. Result

    To determine the preferred learning style among the sample individuals, the researcher calculated the arithmetic means and standard deviations of the scores achieved by the sample individuals for each learning style.

Table. 4: means and standard deviation of the scores achieved by the sample individuals for each learning style and the descending order

It is clear from Table 4 that the most preferred learning style among students is the visual style, followed by the sensing style in second place, while the sequential style occupies the third rank, then the active style in the fourth rank, the reflective style in the fifth rank, and the holistic style in the sixth rank, with the intuitive style coming in seventh, and finally, the verbal style.

Figure. 1: Shows the percentage rates achieved for each learning style 

To know more about the preferred dimension, the researcher calculated the arithmetic means and standard deviations for each dimension separately, as well as the descending order of these dimensions.

Table. 5: Means and Standard Deviations of the Scores Achieved by the Sample Individuals for Each Dimension Separately and the Descending Order.

And through Table 5 the most preferred is the verbal-visual dimension in the first rank, followed by the Sequential/Global dimension, and in the third rank is the Sensing/Intuitive dimension, and finally, the active-reflective dimension.

Figure. 2: Learning Styles by Each Dimension

To determine the differences between learning styles within the same dimension, the researcher calculated the value and significance level of the differences between students.

Table No. 6: Value and Significance Level of the Differences between Students in Learning Styles

It is evident from Table that there are statistically significant differences between the groups of dimensions of learning styles as follows:

• The active style over the reflective style.
• The intuitive style over the sensory style.
• The visual style over the verbal style.
• The sequential style over the global style.

An independent sample t-test on the learning styles was used to evaluate if there were any individual differences between specialist sport training and sport education.

Table 7. Difference in learning styles between groups (training, education)

The t-test for the Active/Reflective learning style shows no significant difference between the training and education groups, as indicated by the similar mean scores and standard deviations. Similarly, the Sensing/Intuitive learning style does not show a significant difference between the two groups (p=0.794). For the Visual/Verbal learning style, there is a significant difference between the training and education groups (p=0.013), with the training group scoring higher. The Sequential/Global learning style shows no significant difference between the training and education groups (p=0.075).

An independent sample t-test on the learning styles was used to evaluate if there were any individual differences between undergraduate and master students.

Table 8. Difference in learning styles between groups (undergraduate, master)

The t-test for the Active/Reflective learning style shows no significant difference between undergraduate and master's students (p=0.284). Similarly, the Sensing/Intuitive learning style does not show a significant difference between the two groups (p=0.133). For the Visual/Verbal learning style, there is also no significant difference between undergraduate and master's students (p=0.726). However, the Sequential/Global learning style shows a significant difference between undergraduate and master's students (p=0.000), indicating that master's students tend to score higher on this dimension.

To determine if there were differences in learning style based on level of education, we conducted an ANOVA test on the sample.

Table 9. The results for the ANOVA test between groups

The ANOVA results indicate that there are no statistically significant differences in the Active/Reflective dimension, as evidenced by an F-value of 0.759 and a significance level of 0.553, suggesting similar variances within and between groups, implying uniformity in this learning style among the groups. Conversely, the Sensing/Intuitive dimension shows a significant variance with a p-value of 0.004 and a higher F-value, indicating that this learning style significantly varies among the groups, with greater differences between groups than within. However, the Visual/Verbal dimension, with an F-value of 1.340 and a significance level of 0.256, shows no significant differences, indicating consistency in this learning style across the groups.

To accurately identify which groups demonstrated statistically significant differences in their performance, the Tukey HSD test was meticulously applied as shown in the table.

Table. 10 The results for the tukey test between groups

Figure 3. Means showed differences between groups (academic level)

4. Discussion

The objective of the research is to examine at the preferred learning styles of sports students in higher education. Using the Felder-Silverman model, which divides learning styles into four dimensions: active-reflective, visual-verbal, sensing-intuitive, and sequential-global, the study explored variations in learning styles depending on specialization, academic level, and graduation. The study included 268 students from the Sports Institute; The results of Table N.4 indicate that the preferred learning style among students at the Institute of Physical Activities and Sports Science and Technology is the visual style, this may be attributed to the significant importance of the sense of sight in learning and mastering movements and in learning in general. Seeing different movements performed as a model in front of the learner, whether by a peer or a coach, through films, drawings, or pictures, allows the learner to form an initial perception of the new movement in its general form. The learner can also grasp the general parts of the new movement and retain a mechanical impression of that movement or skill. If the model is repeated slowly, the learner can form a clearer picture of the movement and always strives to reach it through practice and training.

The sensory style ranks second, this may be due to the nature of the specialization, which involves extensive use of the senses and dealing with tangible objects. Table N.5 indicates that the most preferred dimension is the verbal-visual dimension, followed by the sensory-intuitive dimension in second place, the sequential-global dimension in third place, and finally, the active-reflective dimension.

Table N.6 Shows the value of "T" and its significance for differences in learning styles within each dimension as follows:

• Visual-Verbal Dimension: The differences favored the visual style over the verbal style, meaning that visual students prefer information presented visually through pictures, presentations, and models. They use strategies that involve using colors to organize materials, drawing, and charts, and they prefer seeing relationships and using videos and films^[54].
• Active-Reflective Dimension: The differences favored the active style over the reflective style, meaning that active students understand better by doing something using the means they study with: experimenting, talking about it, explaining it to others, and being placed in a problem situation ^[55].
• Sensory-Intuitive Dimension: The differences favored the sensory style over the intuitive style, as sensory students tend to apply what they learn and are oriented towards facts and procedures. Their preferred information comes through their senses^[56].
• Sequential-Global Dimension: The differences favored the sequential style over the global style, meaning that sequential students prefer following precise sequential steps, following a logical path through different parts of the curriculum to find the appropriate information and solution. ^[57]

The t-test results indicate no significant difference between the training and education groups in the Active/Reflective learning style, suggesting that both groups process information similarly, whether through active engagement or reflective observation, this uniformity might be due to the general nature of these cognitive processes, which are fundamental to learning at all educational levels and are not significantly influenced by the specific focus of training or education. Similarly, the Sensing/Intuitive learning style shows no significant difference between the training and education groups, implying that both groups have comparable preferences for either concrete, practical information (sensing) or abstract, theoretical information (intuitive). This consistency could be attributed to the balanced curriculum that addresses both practical and theoretical aspects, making these preferences stable across different educational and training contexts. For the Visual/Verbal learning style, the significant difference between the training and education groups, with the training group scoring higher, suggests that the training programs may place a greater emphasis on visual learning methods. This could be due to the nature of training, which often involves practical demonstrations, visual aids, and hands-on activities that enhance visual learning. In contrast, education programs might rely more on verbal instruction, such as lectures and readings, which could explain the lower scores in this dimension for the education group. The Sequential/Global learning style shows no significant difference between the training and education groups, indicating that both groups have similar preferences for either sequential learning (following linear, step-by-step processes) or global learning (understanding the big picture and making connections), this uniformity might reflect the structured nature of both training and education programs, which likely incorporate elements that cater to both sequential and global learners.

The t-test results indicate no significant difference between undergraduate and master's students in the Active/Reflective learning style, suggesting that both groups process information similarly, whether through active engagement or reflective observation. Similarly, the Sensing/Intuitive learning style shows no significant difference, implying comparable preferences for either concrete, practical information or abstract, theoretical information. This consistency could be due to a balanced curriculum addressing both aspects. For the Visual/Verbal learning style, the lack of significant difference indicates similar preferences for visual aids or verbal information, reflecting the widespread use of both instructional methods in higher education. However, the significant difference in the Sequential/Global learning style, with master's students scoring higher, suggests a stronger preference for global learning (understanding the big picture and making connections) among master's students. This could be due to the advanced nature of master's programs, which often require integrating and synthesizing complex information, fostering a more global approach to learning.

The ANOVA results indicate that some learning styles, such as Active/Reflective and Visual/Verbal, are uniformly distributed among different student groups. This uniformity suggests that these learning styles are consistently preferred across various groups, implying that educational strategies addressing these styles can be broadly applied without significant customization for different groups. However, other learning styles, specifically Sensing/Intuitive and Sequential/Global, show significant variations among the groups. This indicates that preferences for these learning styles differ notably between groups; such differences suggest that educational strategies need to be tailored to accommodate these varying preferences. For instance, students at higher academic levels might benefit more from abstract and integrative learning approaches, which align with the Intuitive and Global learning styles. In summary, while some learning styles can be addressed with general strategies, others require more customized approaches to effectively meet the diverse needs of students, particularly those at advanced levels who may benefit from more complex and integrative learning methods.

The current study's finding of a predominant visual learning style preference among students at the Institute of Physical Activities and Sports Science and Technology contrasts with several previous studies that highlight a preference for kinesthetic learning styles among sports science students and athletes. For instance, the Bostanci study found a significant preference for kinesthetic styles among sports sciences students,^[58] while Braakhuis indicated elite and sub-elite athletes favored kinesthetic and multimodal methods.^[59] Similarly, Peters et al. noted an inclination towards kinesthetic styles in sports programs.^[60] The preference for kinesthetic learning was also observed by Ashadi et al. among college student athletes.^[61] This discrepancy between the current study and previous research suggests that learning style preferences may vary based on factors such as the specific sample population (e.g., general sports science students vs. elite athletes) and the context of the study. However, the current findings align with Fuelscher et al.'s emphasis on a nuanced understanding of learning styles, as the visual preference highlights the potential benefit of incorporating visual aids in certain educational settings related to sports and physical activities.^[62]

The findings of this study on learning style preferences among students in physical activities and sports science programs hold significant importance for enhancing teaching and learning effectiveness in this field. The predominant preference for visual learning styles, in contrast with previous research highlighting kinesthetic preferences, underscores the need for tailored educational strategies that cater to the specific needs of this student population. By incorporating more visual learning aids, such as video demonstrations, diagrams, and interactive simulations, into sports science curricula, educators can better engage students and optimize their learning outcomes. This approach aligns with the visual learning style preference found in this study and has the potential to improve student performance and skill acquisition in sports-related fields. Furthermore, understanding the relationship between learning style preferences and academic achievement can inform the development of evidence-based teaching methods that match students' preferred styles. By adapting instructional approaches to accommodate diverse learning preferences, educators can create more inclusive and effective learning environments that foster student success in sports science education. The findings also highlight the need for further research to replicate the study with larger and more diverse samples across different institutions and countries. This would help assess the generalizability of the visual learning style preference and provide a more comprehensive understanding of learning styles in sports science education. Additionally, longitudinal studies examining how learning style preferences evolve over the course of a student's academic journey in sports science programs could offer valuable insights for curriculum design and teaching strategies. In conclusion, the results of this study on learning style preferences among students in physical activities and sports science programs have significant implications for enhancing teaching effectiveness and student learning in this dynamic field; By incorporating visual learning strategies, adapting instructional methods to match students' preferred styles, and conducting further research to expand our understanding of learning styles in sports science education, educators can optimize student success and contribute to the advancement of this discipline.

Conclusion

The study applied the Felder-Silverman learning styles model to investigate learning preferences among sports students.^[63] Results revealed a predominant visual learning style, followed by sensing and sequential styles. Significant differences emerged across academic levels, with master's students exhibiting more global and intuitive approaches compared to undergraduates. These findings highlight the importance of considering diverse learning styles when designing educational strategies, especially in sports and physical education contexts. The study recommended the following:

• Working on creating training courses for teachers that adopt modern methods and encouraging teachers to consider the learning styles of each student.
• Teachers should identify and understand the learning styles of students during the teaching process.
• Researchers are invited to explore the topic from other perspectives and to start applied studies specific to the specialization.

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