The Relationship of Motor Skills Development to Verbal and Visual Short-Term Memory of Children Aged 9-10 Years

THE RELATIONSHIP OF MOTOR SKILLS DEVELOPMENT TO VERBAL AND VISUAL SHORT-TERM MEMORY OF CHILDREN AGED 9-10 YEARS

Fadya Mahrous Jerojeis

A DISSERTATION

Submitted to Michigan State University in partial fulfillment of the requirements for the degree of

Kinesiology-Doctor of Philosophy

2017

ABSTRACT

THE RELATIONSHIP OF MOTOR SKILLS DEVELOPMENT TO VERBAL AND VISUAL SHORT-TERM MEMORY OF CHILDREN AGED 9-10 YEARS

Fadya Mahrous Jerojeis

Introduction: the association between physical and cognitive development relies on the essential role that early motor development has in improving cognitive ability over time. This association highlights the need to explore the relationship between motor skills and cognitive functions (e.g., working memory capacity, attention, and inhibition) and whether the relation is specific to certain categories of motor and cognitive skills. Thus, the purpose of the current study is to examine the relationship among the level of fundamental motor skills (FMS) of both locomotor and object-control skills, verbal short-term memory (STM) and visuospatial short- term memory (STM), and gender. Information regarding ethnicity, BMI, and parents’ education level of the participants was collected for exploratory purposes.

Method: A cross-sectional study was used to examine the relationship between FMS and verbal

STM and visuospatial STM. Sixty-one children aged 9-10 years (boys: n = 28; 45.9% and girls: n = 33; 54.1%) were selected from five regions in Michigan. Two instruments were used to examine the relationship between FMS and verbal STM and visuospatial STM. The level of motor skills development determined by Test of Growth and Motor Development-2 (TGMD-2), and the level of verbal STM and visuospatial STM determined by Automated WM Assessment–

Second Edition (AWMA). Statistical analyses were based on Chi-Square Test to determine the relationship between FMS and verbal STM and visuospatial STM, and on Cochran-Mantel-

Haenszel Test to determine the relationship between FMS, verbal STM and visuospatial STM, and gender. simple linear regressions, and multiple linear regressions were used for further

exploration of the relationship between FMS, verbal STM and visuospatial STM, and covariate variables included (gender, BMI, regions, ethnicity, and mother’s and father’s education levels).

Results: In the level of FMS, boys and girls scored higher in object control skills (43.39± 3.77) than locomotor skills (39.88 ± 4.93). Gender differences were found in the total FMS and object control skills, boys scored higher in the total FMS (86.32± 6.35) and object control skills (45.14±

3.22) than girls. In the level of verbal STM and visuospatial STM, no significant differences were found between boys and girls in any of verbal STM and visuospatial STM and in any of their subcomponents (digit recall, word recall, non-word recall, dot matrix, mazes memory, and block recall). The results of the Pearson's chi-square test showed no strong evidence of a relationship between FMS and verbal STM and visuospatial STM. One-way ANOVA test revealed that there were significant differences in the level of total FMS, F(4) = 2.904, p = .030 and locomotor skills, F(4) = 6.191, p = .000 across regions. The results of Cochran-Mantel-

Haenszel Test also showed no statistical differences between boys and girls in term of the relationship between FMS and verbal STM and visuospatial STM. The results of the simple linear regressions and multiple linear regressions showed that object control skills was the only independent variables was a statistically significant predictor verbal STM, and region was the only covariate variable statistically significant predictor of verbal STM and visuospatial STM, p

< .05.

Conclusions: Boys and girls seem to have equal opportunity to develop FMS, especially object control skills, which positively impact their verbal STM. Such improvement in verbal STM provides evidence of the direct link between sub-categories of the FMS and WMC. Region found have a role in children FMS and verbal STM and visuospatial STM development

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I dedicate my dissertation work to my beloved parents and family (Dad, Mom, Alia, Talal, Nadya, Alaa and Ziad) for their love, endless support, encouragement and sacrifices. I also dedicate this dissertation to my dear and sweet husband Sam. Thank you for loving me enough to spend your life with me doing what no other man that I cared for had the courage to do. You have strong faith in our God and the strength to do all the things you have done for me. I love and respect you until death do us part.

ACKNOWLEDGMENTS

I would like to take this opportunity to express my heartfelt gratitude to my committee.

Without you feedback, encouragement, and support I may have dropped this ball long ago.

Thanks especially to Dr. Crystal Branta and Dr. Marty Ewing for their expert assistance on my research. You all were a gift of God when I needed help the most. Thank you Dr. Jodene Fine and Dr. Florian Kagerer for agreeing to serve on my committee.

I would like to acknowledge and thank the school districts and churches who allowed me to conduct my research and provided any assistance requested.

I want to express my deepest appreciation and gratitude to all of the people who helped, support, encouraged, and guided me through this project. I could never adequately express my gratitude to my friends (Frank, Elaine, and Mary). I never would have completed this project without your guidance and counsel. Thank you for your patience, understanding, endless, encouragement, and for teaching me how to think before I write!! A special thanks to my friend

Anmar, because of you I got a scholarship from my country Iraq. Thank you for giving me this chance to get my degree.

A special thank you for all colleagues, staff, and friends at the Department of

Kinesiology/Michigan State University, especially Dr. Deborah Feltz, George Harnick, Dr. Karin

Pfeiffer, Marlene Green, Christina Mazuca. Special thanks goes to Dr. Janet Hauck for her continued support.

I would also like to express my sincere appreciation to the Iraqi Ministry of Higher

Education and Scientific Research, Iraqi Cultural Office in the US, and all staff at the College of

Physical Education/ University of Mosul and Salahaddin University-Erbil/Iraq

What could I possibly say to express my appreciation to my family? Thank you for allowing me this past years to be a social hermit. I love you with all my heart. Thanks to my parents, my siblings (Talal, Alia, Alaa, Nadya, Zeeyad), and Satar, Kanar, Rana, and all my nieces and nephews for your lifelong support, always believing in me, for your prayers, and standing with me in all that I have done. God has given me the best parents on earth!! To Talal and Alia, you two are wonderful. You act as second parents, who like to see their dreams come true by me. I am so blessed to have brother and sister who are forever encouraging me and lifting me up.

To my Husband Sam Abdo, thank you babe, for your prayers and support. Also for being first-rate research assistant, making extra trips to schools and churches for me, sharing with me your knowledge in explaining and support my research results. I do thank God for you.

Thank you to the lord. Life itself would not be possible or have meaning without you.

Thank you for all the people you have placed in my life. I pray that in small measure, you are honored through this work.

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TABLE OF CONTENTS

LIST OF TABLES ...... xi

LIST OF FIGURES ...... xiv

CHAPTER 1: INTRODUCTION ...... 1 The Statement of Purpose ...... 1 The Importance of Fundamental Motor Skills ...... 3 The Importance of Working Memory ...... 6 Gender Differences in FMS and WMC ...... 8 Justification for the Study ...... 9 Purpose ...... 11 Hypotheses ...... 12

CHAPTER 2: REVIEW OF LITERATURE ...... 13 Introduction ...... 13 Stages and Theories of Fundamental Motor Skills ...... 13 Stages of Learning Motor Skills ...... 14 The Cognitive Stage ...... 15 The Associative Stage ...... 15 Autonomous Stage ...... 16 Theories of Motor Learning ...... 17 Closed-Loop Theory...... 17 Schema Theory ...... 18 Dynamical Systems Theory ...... 19 Memory ...... 22 The Interaction between Short and Long Term Memories ...... 24 Working Memory Capacity ...... 26 Model of Working Memory ...... 28 The Central Executive System ...... 30 Phonological Loop System ...... 31 The Visuospatial Sketchpad System ...... 33 The Episodic Buffer System ...... 35 Associating Fundamental Motor Skills with Working Memory Capacity ...... 36 Gender Differences in Fundamental Motor Skills and Working Memory ...... 38 Summary ...... 40

CHAPTER 3: METHODOLOGY ...... 42 Method ...... 44 Research Design...... 44 Participants ...... 44 Measures ...... 45 Physical Characteristics and Demographics ...... 45

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Fundamental Motor Skills...... 46 Verbal STM and Visuospatial STM ...... 47 Procedures ...... 48 Data Analysis ...... 51

CHAPTER 4: RESULTS ...... 54 Introduction and Overview ...... 54 Physical Characteristics and Demographics ...... 55 Fundamental Motor Skills Performance ...... 60 Verbal STM and Visuospatial STM Capacity Level ...... 67 Fundamental Motor Skills Performance Across Five Regions ...... 69 Verbal STM and Visuospatial STM Performance Across Five Regions ...... 72 The Relationship Between FMS and Verbal STM and Visuospatial STM ...... 73 The Relationship Between FMS and Verbal STM and Visuospatial STM and Gender ...... 82 Exploratory analyses: FMS and Verbal STM and Visuospatial STM, Gender, and Covariate Variables ...... 95 Exploratory analyses: FMS and Verbal STM and Visuospatial STM ...... 97 Exploratory analyses: FMS, Verbal STM and Visuospatial STM, Gender, and Covariate Variables ...... 102 Summary of Findings ...... 108 The level of FMS performance ...... 108 The level of Verbal STM and Visuospatial STM performance ...... 108 The level of FMS Across Regions ...... 108 The level of Verbal STM and Visuospatial STM Across Regions ...... 109 Findings of the first hypothesis: FMS, Verbal STM and Visuospatial STM ...... 109 Findings of the second hypothesis: FMS, Verbal STM and Visuospatial STM and gender ...... 109 Findings of the exploratory analyses: FMS and Verbal STM and Visuospatial STM, and Covariate Variables ...... 110

CHAPTER 5: DISCUSSION ...... 111 Hypothesis 1 ...... 112 Hypothesis 2 ...... 117 Exploration Data for FMS and Verbal STM and Visuospatial STM ...... 120 Exploration Data for FMS and Verbal STM and Visuospatial STM and Covariate Variables ...... 121 Conclusions & Future Directions ...... 123 Strengths and Limitations ...... 124 The Limitations of the Study ...... 124 The strengths of the study ...... 125

APPENDICES ...... 126 APPENDIX A: Parental Consent Form ...... 127 APPENDIX B: Participant Assent Form ...... 131 APPENDIX C: Questionnaire ...... 133 APPENDIX D: Flyers ...... 136

APPENDIX E: The Test of Gross Motor Development, Second edition (TGMD–2) ...... 138 APPENDIX F: Alloway Working Memory Assessment (AWMA) ...... 141 Alloway Working Memory Assessment (AWMA) ...... 142 APPENDIX G: Partial Correlation ...... 144 APPENDIX H: Regions for Data Collection ...... 151

BIBLIOGRAPHY ...... 153

LIST OF TABLES

Table 1: Physical Characteristics of the Total Sample, Boys, and Girls ...... 55

Table 2: Demographic Characteristics of the Total Sample, Boys, and Girls ...... 58

Table 3: Mother's and Father's Educational Levels Across Regions ...... 59

Table 4: Description of TGMD-2 Raw Scores of the Total Sample, Boys, and Girls ...... 61

Table 5: Description of FMS Level Results by the Six Levels of TGMD-2 Performance of the Total Sample, Boys, and Girls ...... 62

Table 6: Description of FMS Level Results by the Two Levels of TGMD-2 Performance of the Total Sample, Boys, and Girls ...... 65

Table 7: Description of AWMA Standard Scores (Test and Subtests) of the Total Sample, Boys, and Girls ...... 67

Table 8: Description of Verbal STM and Visuospatial STM by the two Levels of AWMA Performance of the Total Sample, Boys, and Girls ...... 68

Table 9: Description of FMS (Total FMS, Locomotor Skills, and Object Control Skills) Across Five Regions ...... 70

Table 10: Description of Verbal STM and Visuospatial STM Across Five Regions ...... 72

Table 11: Description of the Chi-Square Test of the Relationship Between Total FMS and Verbal STM (VSTM)...... 74

Table 12: Description of the Chi-Square Test of the Relationship Between Locomotor Skills (LOS) and Verbal STM (VSTM) ...... 75

Table 13: Description of the Chi-Square Test of the Relationship Between Object Control Skills (OCS) and Verbal STM (VSTM) ...... 77

Table 14: Description of the Chi-Square of the Relationship Between Total FMS and Visuospatial STM (VSSTM) ...... 78

Table 15: Description of the Chi-Square of the Relationship Between Locomotor Skills (LOS) and Visuospatial STM (VSSTM)...... 80

Table 16: Description of the Chi-Square Test of the Relationship Between Object Control Skills (OCS) and Visuospatial STM (VSSTM) ...... 81

Table 17: Description of the Cochran-Mantel- Haenszel Test of the Relationship Between Total FMS, and Verbal STM (VSTM) Control by Gender ...... 84

Table 18: Description of the Cochran- Mantel-Haenszel Test of the Relationship Between Locomotor Skills (LOS) ad Verbal STM (VSTM) Control by Gender ...... 86

Table 19: Description of the Cochran-Mantel-Haenszel Test of the Relationship Between Object Control Skills (OCS) and Verbal STM (VSTM) Control by Gender ...... 88

Table 20: Description of the Cochran-Mantel-Haenszel Test of the Relationship Between Total FMS and Visuospatial STM (VSSTM) Control by Gender...... 90

Table 21: Description of the Cochran-Mantel-Haenszel Test of the Relationship Between Lcomotor Skills (LOS) and Visuospatial STM (VSSTM) Control by Gender ...... 92

Table 22: Description of the Cochran-Mantel-Haenszel Test of the Relationship Between Object Control Skills (OCS) and Visuospatial STM (VSSTM) Control by Gender ...... 94

Table 23: The Results of Pearson Correlation (r) of the Relationship Between FMS (Total FMS, Locomotor Skills, and Object Control Skills) and Verbal STM and Visuospatial STM ...... 98

Table 24: Results of Overall Fit Statistics of the Simple Linear Regressions to Predict Verbal STM ...... 99

Table 25: Results of Coefficient of the Simple Linear Regression to Predict Verbal STM ...... 100

Table 26: Results of Overall Fit Statistics of the Simple Linear Regression to Predict Visuospatial STM ...... 101

Table 27: Results of Coefficient of the Simple Linear Regressions to Predict Visuospatial STM ...... 102

Table 28: Partial Correlations Between FMS and Verbal STM and Visuospatial STM and Controlling for Gender, BMI, Region, Ethnicity, and Mother's and Father's Educational Levels ...... 103

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Table 29: Results of Overall Fit Statistics of the Multiple Linear Regressions (Predictor, Gender, and Covariate Variables) to Predict Verbal STM ...... 104

Table 30: Results of the Coefficient of the Multiple Linear Regressions (Predictor, Gender, and Covariate Variables) to Predict Verbal STM ...... 105

Table 31: Results of Overall Fit Statistics of the Multiple Linear Regressions (Predictor, Gender, and Covariate Variables) to Predict Visuospatial STM ...... 106

Table 32: Results of the Coefficient of the Multiple Linear Regressions (Predictor, Gender, and Covariate Variables) to Predict Visuospatial STM ...... 107

Table 33: Example of Evaluating Running ...... 140

Table 34: Partial Correlations Between Locomotor Skills (LOS) and Verbal STM (VSTM) Controlling for Gender (G), BMI, Region (R), Ethnicity (Eth), and Mother's (M) and Father's (F) Education Levels (EL) ...... 145

Table 35: Partial Correlations Between Object Control Skills (OCS) and Verbal STM (VSTM) Controlling for Gender (G), BMI, Region (R), Ethnicity (Eth), and Mother's (M) and Father's (F) Education Levels (EL) ...... 145

Table 36: Partial Correlations Between Total FMS (TFMS) and Verbal STM (VSTM) Controlling for Gender (G), BMI, Region (R), Ethnicity (Eth), and Mother's (M) and Father's (M) Education Levels (EL) ...... 147

Table 37: Partial Correlations Between Locomotor Skills (LOS) and Visuospatial STM (VSSTM) Controlling for Gender (G), BMI, Region (R), Ethnicity (Eth), and Mother's (M) and Father's (F) Education Levels (EL) ...... 148

Table 38: Partial Correlations Between Object Control Skills (OCS) and Visuospatial STM (VSSTM) Controlling for Gender (G), BMI, Region (R), Ethnicity (Eth), and Mother's (M), and Father's (F) Education Levels (EL) ...... 149

Table 39: Partial Correlations Between Total FMS (TFMS) and Visuospatial STM (VSSTM) Controlling for Gender (G), BMI, Region (R), Ethnicity (Eth), and Mother's (M) and Father's (F) Education Levels (EL) ...... 150

Table 40: Regions for Data Collection ...... 152

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LIST OF FIGURES

Figure 1: A Schematic Diagram of Working Memory Components. From: Baddeley & Hitch (1974) ...... 7

Figure 2: Declarative and Non-Declarative Memory. From: Squire (2004) ...... 24

Figure 3: The Revised Model of Working Memory. From: Baddeley (2000) ...... 30

Figure 4: The Phonological Loop, with the Phonological Store and the Articulatory Loop. From: Baddeley (1986) ...... 32

Figure 5: Description of the Mother's and Father's Educational Levels Across Regions ...... 60

Figure 6: A Relationship Between Six Levels of Total FMS, Locomotor Skills, and Object Control Skills by Gender ...... 63

Figure 7: A Relationship Between Two Levels of Total FMS, Locomotor Skills, and Object Control Skills by Gender ...... 66

Figure 8: A Relationship Between Two Levels of Verbal STM and Visuosptial STM and Gender ...... 69

Figure 9: The Level of FMS (Total FMS, Locomotor Skills, and Object Control Skills) and Verbal STM and Visuospatial STM Across Five Regions ...... 71

Figure 10: The Level of Verbal STM and Visuospatial STM Across Five Regions ...... 73

Figure 11: A Relationship Between Total FMS and Verbal STM...... 74

Figure 12: A Relationship Between Locomotor Skills and Verbal STM ...... 76

Figure 13: A Relationship Between Object Control Skills and Verbal STM ...... 77

Figure 14: A Relationship Between Total FMS and Visuospatial STM ...... 79

Figure 15: A Relationship Between Locomotor Skills and Visuospatial STM ...... 80

Figure 16: A Relationship Between Object Control Skills and Visuospatial STM ...... 82

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Figure 17: A Relationship Between Total FMS and Verbal STM Control by Gender ...... 85

Figure 18: A Relationship Between Locomotor Skills and Verbal STM Control by Gender ...... 87

Figure 19: A Relationship Between Object Control Skills and Verbal STM Control by Gender 89

Figure 20: A Relationship Between Total FMS and Visuospatial STM Control by Gender ...... 91

Figure 21: A Relationship Between Locomotor Skills and Visuospatial STM Control by Gender ...... 93

Figure 22: A Relationship Between Object Control Skills and Vosuospatial STM Control by Gender ...... 95

Figure 23: $10 for Children ...... 137

Figure 24: The Test of Gross Motor Development, Second Edition (TGMD-2) ...... 139

Figure 25: AWMA Administration ...... 143

CHAPTER 1: INTRODUCTION

The Statement of Purpose

The purpose of this study is to examine and understand the relationship of physical and cognitive development in young children. Specifically, physical development and motor skills will be investigated in relation to the verbal STM and visuospatial STM of children aged 9-10 years. While it may appear that each of these areas is separate and are indeed different areas of potential study, these unique branches of human development are all interconnected and dependent upon each other. Physical development includes physical growth and maturation as well as the development of fine and gross motor skills. These motor skills are considered critical elements for healthy development at an early age. Cognitive development is characterized by the ability of the brain to process information, learn, and develop thought patterns associated with memory, reasoning, and problem solving. During growth, children will potentially improve both physical and cognitive attributes. Physically, this gain may be manifested as children coordinate muscles more fluently; cognitively, they may begin to process information more coherently and adapt more easily to the rules and expectations of the classroom environment. These improvements in physical and cognitive domains help children improve in other areas such as language, literacy, social, and emotional development (Murray, Veijola, Moilanen, Miettunen,

Giahn, Cannon et al., 2006; Piek, 2006; Bushnell & Boudreau, 1993).

The association between physical and cognitive development relies on the essential role that early motor development has in improving cognitive ability over time. Children, from birth through childhood, rely on moving their bodies to learn about the world around them (Elena,

Georgetaa, Cecilab, & Lupuc, 2014). As an example, infants who begin to crawl use higher levels of effort in order to master the motor skill and explore the surrounding environment. At a

slightly older age, toddlers, because of their developing locomotor abilities, have better chances of touching, manipulating or using objects. During the elementary school years, learning, practicing, and developing sequences of fundamental motor skills (FMS) allow young children to practice a variety of games and participate in physical and sports activities. Thus, developing these skills over time provides great opportunities for children to interact with the environment and to learn a variety of important concepts that can help them develop cognitive ability during early childhood (Elena, Georgetaa, Cecilab, & Lupuc, 2014; Henninger, 2008).

Due to a lack of evidence, the relationship between early motor skills and cognitive development was thought to be indirect, and was investigated through examining the role of physical activity and sport involvement (Cohen, Morgan, Plotnikoff, Callister, & Lubans, 2014;

Morrow, Tucker, Jackson, Martin, Greenleaf, & Petrie, 2013; Livesey, Lum Mow, Toshack, &

Zheng, 2010; Stodden & Goodwin, 2007; Fairclough, & Stratton, 2005; Goodway & Branta

2003). This led researchers in different fields (e.g. neuropsychology and cognitive development) to shift their attention into improving children’s physical activity instead of developing their

FMS. In turn, the percentage of children with low levels of FMS development, especially in girls, has been increasing in elementary or middle schools (Bardid, Deconinck, Descamps,

Verhoeven, De Pooter, Lenoir et al., 2013; Robinson, Wadsworth, & Peoples, 2012; Goodway,

Robinson, & Crowe, 2010; Graf, Koch, Kretschmann-Kandel, Falkowski, Christ, Coburger, et al., 2004; Goodway & Branta, 2003; Okely, Booth, & Patterson, 2001). Therefore, this area of study needs further investigation to identify the nature of the relationship among developing

FMS, improving cognitive function, and gender.

Examining the relationship between children’s level of FMS and cognitive development will help explain the change of cognitive function through practicing and learning FMS or vice

versa. It may provide evidence for a direct role of FMS in improving cognitive ability, which also increases with participation in physical and sports activities. This evidence can potentially improve the current teaching structures in schools to help children develop these skills at an early age. For example, understanding the role of the different sensory experiences (verbal and non- verbal) that are necessary for learning FMS will help teachers design age-specific intervention programs. In addition, investigating the gender difference in verbal and non-verbal processing at various levels of FMS development will contribute to understanding additional factors in development.

Thus, the main purpose of this study is to investigate the potential relationship between

FMS and cognitive development through examining verbal STM and visuospatial STM of children aged 9-10 years. The second purpose of the study is to describe gender differences in the relationship between FMS (locomotor and object control skills) and, verbal STM and visuospatial STM.

The Importance of Fundamental Motor Skills

FMS is defined as the specific movement patterns that involve different body parts important to the performance of more complex skills used in games, sports, gymnastics, and recreational physical activity (Landy & Burridge, 1999). FMS includes gross motor skills that require large groups of muscles to move the body from one point to another. The FMS are divided into two skill categories: locomotor skills and object control skills. Locomotor skills consist of running, hopping, galloping, leaping, jumping, and sliding. Object control skills consist of striking, dribbling, catching, kicking, throwing, and rolling (Stodden, Goodway,

Langendorfer, Roberton, Rudisill, Garcia, et al., 2008).

Early FMS development plays a critical role to optimal brain development (size, complexity, and synaptic connections, and function), resulting from the interactions between growth, maturation, and physical development with the surrounding environment (Wang, 2004;

Blank, 1999). These interactions provide opportunities for young children to process complex information to move their body and begin to develop a repertoire of basic motor skills. This leads to increasing the strength of synaptic connections and brain function (Greenough & Black,

1992).

FMS development during infancy and early childhood has an essential role in children’s physical development. Researchers indicated that FMS are developed gradually in a head-to-toe order and from the center of the body outward. As children practice these skills they will grow and strengthen better through improving muscular control, and developing coordination. A critical time in which children should develop their FMS is during the preschool years (aged 2 to

6); after which the skills should be refined into a specialized movement phase through the teenage years and into adulthood (Lubans, Morgan, Cliff, Barnett & Okely, 2010; Pachta, &

Derri, 2007; Caine & Caine, 1991). These skills are considered to be a “mountain of motor development” that children must learn and master in order to reach higher levels of motor- development known as context-specific skills or skillful movement (Clark & Metcalfe, 2002).

Research reveals a clear connection between early FMS development and later children's physical, cognitive, social and emotional development, and educational achievement (Lubans,

Morgan, Cliff, Barnett, & Okely, 2010; Wrotniak, Epstein, Dorn, Jonesc, & Kondilisc, 2006;

Fisher, Reilly, Kelly, Montgomery, Williamson, Paton et al., 2005; Okely, Booth, & Patterson,

2001; Westendorp, Hartman, Houwen, Smith, & Visscher, 2011). Evidence indicates that FMS increases children’s participation in physical activity, sports, and improves cardiorespiratory

fitness. Studies have shown that FMS, physical activity, and sport-and-cardiorespiratory fitness are all interconnected and related to each other (Kalaja, 2012; Raudsepp & Pall, 2006; Wrotniak,

Epstein, Dorn, Jonesc, & Kondilisc, 2006; Fisher et al., 2005; Branta, Haubenstricker, &

Seefeldt, 1984). Studies showed that children who had mastered motor skills in childhood had improved their physical activity levels and cardiorespiratory fitness in adolescence at an accelerated rate in comparison to their peers who had not mastered motor skills in childhood

(Barnett, Van Beurden, Morgan, Brooks & Beard, 2008; Foley, Harvey, Chun, & Kim, 2008;

Okely, Patterson & Booth, 2001). Sufficient FMS is considered to be one of the most important antecedents to physical activity and can facilitate participation and success in many sport-and- exercise activities (Kalaja, Jaakkola, Liukkonen, & Watt, 2010). Also, FMS was linked to improving many psychological factors in children such as self-confidence, self-esteem, and perceived competence (Kelly, 2010, Bunker, 1991).

FMS contributes positively to physical activity and sports ability and psychological factors; FMS also has been found to have an effective role in developing children’s cognition.

Through practicing FMS-related activities children can experience different cognitive functions such as memory, problem-solving and critical thinking which, in turn, are important to developing cognition in early childhood. This assertion is validated through a number of studies that indicate a positive relationship between FMS and academic performances in reading, spelling, and mathematics (Westendorp, Hartman, Houwen, Smith, & Visscher, 2011; Vuijk,

Hartman, Mombarg, Scherder, & Visscher, 2011; Visscher, Houwen, Scherder, Moolenaar, &

Hartman, 2007).

The Importance of Working Memory

Improving working memory (WM) during early childhood has been a major interest for neuropsychologists and cognitive psychologists over the last few decades due to the vital role of

WM in improving cognitive function. Cognitive function is important in human decision making, goal planning, and choosing appropriate behavior (Miyake, Friedman, Emerson, Witzki,

Howerter, & Wager, 2000). The research interest was due also to the important role of WM in developing children in general and in acquisition and use of knowledge in particular (Brod,

Werkle-Bergner, & Shing, 2013). WM is defined as a set of cognitive processes by which information that underlies human thoughts is encoded, stored, and retrieved. It is a limited capacity system in processing, manipulating, and storing information that can improve by age and experiences (Baddeley & Hitch, 1974). Based on the Baddeley and Hitch (1974) model

(Figure 1), this system consists of three basic stores: the central executive and two slave systems including the phonological loop and visuospatial sketchpad. In 2000, this model was expanded with the addition of the multimodal episodic buffer (Baddeley, 2000). It was suggested that the central executive system plays a critical role in integrating the information from the slave systems. The central executive system is considered responsible for the control and regulation of cognitive processes (Miyake, Friedman, Emerson, Witzki, Howerter, & Wager, 2000). The cognitive processes involved include the executive and attention control of short-term memory which provide for the temporary integration, processing, disposal, and retrieval of different types of old or new information (Baddeley & Hitch, 1974).

Figure 1: A Schematic Diagram of Working Memory Components. From: Baddeley & Hitch

(1974)

WM has been viewed as a predictor for academic achievement in different school levels

(Bayliss, Jarrold, Gunn, & Baddeley, 2003; Just & Carpenter, 1992). Extensive research found a significant relationship between WMC and academic achievement through improving reading and math abilities as well as language comprehension (Raghubar, Barnes, & Hecht, 2010).

Adams and Hitch found children’s mental arithmetic was determined by their WM levels rather than their arithmetical competence (Adams & Hitch, 1997). Ewing (2011) pointed out that it would be better to depend on measuring WM to predict children’s academic achievement than to depend on traditional measures of intelligence.

Improving WMC is based on optimal experiences and practices for different mental processes such as problem solving and decision-making (Alloway, 2011). Gathercole and Hitch showed that young children had poorer STM than older children and adults due to their limited cognitive process in the brain. However, those young children can improve their STM capacity by changing the learning strategy such as using visual information, vocal and subvocal speech

recognition, and rehearsal process that can help boost their STM (Gathercole & Hitch, 1993).

Researchers clarified that WMC is not related with the children’s background or environmental influence. Instead, all children are able to develop their memory capacity by continuous exposure to information and the practice of using this information in learning new concepts (Du Toit,

Krüger, Naicker, Govender, Jay-Du Preez, Grobbelaar, et al., 2011; Sibley& Beilock, 2007;

Hillman, Kramer, Belopolsky, & Smith, 2006.

Gender Differences in FMS and WMC

During early childhood (ages 2-to-5 years), children begin to learn groups of fundamental motor skills including locomotor skills and object control skills (Hughes & Riley, 1981). The improvement level of FMS development continues during middle childhood, 7-8 years old.

During this time, children reach intermediate to advanced patterns of locomotor skills, while they reach the mature patterns in most of object control skills during late childhood (ages10-11 years)

(Ture, 2014; Ulrich, 2000; Branta, Haubenstricker & Seefeldt, 1984). Children acquire FMS in a sequential manner during childhood (ages 2-10 years) before moving into the skillful stage

(Clark & Metcalf, 2002; Bunker, 1991). Children of the 9-10 years age group scored higher on cognitive functions than the 7-8 group, and the 2-5 group. The elder children are more field independent than younger children (Arya, & Mishra, 2012). At this stage, the WM system can manipulate the current contents as well as update information to accomplish task goals simultaneously (Baddeley & Hitch, 1974).

This review of the literature provided an age-related framework to be sure that the children have appropriate skills level. This age-related time frame helps in comparing FMS and

WMC to other health factors during different intervals in childhood.

Justification for the Study

Neuroscience research indicates an essential interrelatedness between motor development and cognitive development even though these systems are developing at different times

(Diamond, 2000). This interrelatedness was examined through the brain structure, the level of dopamine, and the activation level in the brain regions. Functional neuroimaging studies showed that (a) the cerebellum, prefrontal cortex, and caudate nucleus are critical elements in a neural circuit for motor functions and cognitive functions, (b) activation of the dorsolateral prefrontal cortex, contralateral cerebellum, and caudate as a cognitive task increases (Diamond, Park,

Heman, & Rose, 1999; Poldrack, Wagner, Prull, Desmond, Glover, & Gabrieli, 1999; (c) the neuroanatomical structure of the cerebellum and the basal ganglia shares a common role in controlling and managing the speed, accuracy, and effort of movement during performance of a task that required motor functions or cognitive functions (Helie, Chakravarthy, & Moustafa,

2013; Courchesne, Pierce, Schumann, Redcay, Buckwalter, Kennedy, et al., 2007; Middleton &

Strick,1994, (d) the cerebellum also plays a role in the learning of procedural memory, such as playing a musical instrument and learning motor skills, such as learning to catch or hit a baseball

(Ferrucci, Brunoni, Parazzini, Vergari, Rossi, Fumagalli, et al.,2013, and (e) the prefrontal cortex and basal ganglia, particularly in the globus pallidus provide the WM system with the relevant information that need to be remembered during performing a movement (Klingberg & McNab,

2008).

Reduced levels of dopamine in the caudate and the basal ganglia were found in patients who have difficulty in their movements such as occurs with Parkinson's disease, hypertonia, and

Huntington's chorea. Those patients also have difficulties in performing cognitive tasks and were lacking WMC (Silkis, 2013; Albin, Young, & Penney, 1995).

Increased activation in the dorsolateral prefrontal cortex, contralateral cerebellum, and caudate is, usually, based on the novelty of the task. As a task has been practiced or become familiar the activations of these brain regions will decrease because of reduced concentration levels and cerebellar firing (Ethofer, Kreifelts, Wiethoff, Wolf, Grodd, Vuilleumier, et al.,2009;

Boecker, Jankowski, Ditter, & Scheef, 2008; Ben-Yehudah, Guediche, & Fiez, 2007; Desmond,

Gabrieli, Wagner, Ginier, & Glover, 1997; Nagahama, Fukuyama, Yamauchi, Matsuzaki,

Konishi, Shibasaki, et al., 1996; Frith, Frackowiak, & Paulesu, 1993).

The activation level is also based on the differences between gender. Studies showed females had more activation in the left hemisphere, while males had more activation in the right hemispheres during processing motor and cognitive tasks (Goldstein, Jerram, Poldrack,

Anagnoson, Breiter, Makris, et al., 2005; Speck, Ernst, Braun, Koch, Miller, & Chang, 2000).

This evidence may be the reason behind why boys do better on performing object control skills and spatial and mathematical tasks than girls (Gong, He, & Evans, 2011; Zaidi, 2010; Cliff,

Okely, Smith, & McKeen, 2009). Despite the biological evidence for the connection between motor development and cognitive development, to date, little is known regarding the relationship between cognitive function, specifically WMC, and fundamental motor skills during early child’s development. There is less evidence for the differences between boys and girls in processing sensory and motor information through practicing and learning FMS.

motor and cognitive centers of the brain, the process of producing FMS, and the outcomes of movement (e.g., pattern, speed, accuracy, movement time, and reaction time).

Despite the biological evidence for the connection between motor development and cognitive development, to date, little is known regarding the relationship between cognitive functions, specifically WMC, and fundamental motor skills during early child’s development.

There are fewer evidences for the differences between boys and girls in processing sensory and motor information through practicing and learning FMS.

Thus, examining the relationship between FMS development, verbal STM and visuospatial STM, and gender may help to build up more effective gender-specific intervention programs that are based on integration strategies to improve motor and cognitive skills development, specifically WMC. Thus, it is critical to understand the connection between the motor and cognitive centers of the brain, the process of producing FMS, and the outcomes of movement (e.g., pattern, speed, accuracy, movement time, and reaction time).

Purpose

The purpose of this study is to attempt to address the research questions through examining the relationship between the level of fundamental motor skills of both locomotor and object-control skills, verbal STM and visuospatial STM and gender. Information regarding ethnicity, BMI, and parents’ education level of the participants was collected for exploratory purposes.

Hypotheses

H1: Children, who have higher levels of FMS (total FMS, locomotor skills, and object

control skills), will show better verbal STM, and visuospatial STM compared to children

who have lower levels of FMS.

H2: Boys will have better verbal STM, and visuospatial STM compared to girls in all levels

of FMS.

CHAPTER 2: REVIEW OF LITERATURE

Introduction

This review of literature examines the current research on the relationship between FMS and verbal STM and visuospatial STM of children aged 9-10 years. The study variables will be introduced independently then the relationship between them will be described. The stages of motor learning and theories of learning FMS will be discussed. The focus then will shift towards how these stages and theories are related with early cognitive development of children. The concept of memory, working memory, and model of WM will also be reviewed. Evidence of an association between fundamental motor skills and WMC will be also provided. Then, gender differences in fundamental motor skills and WM will also be discussed. Finally, a summary of the literature review to state the purpose of the study is given.

Stages and Theories of Fundamental Motor Skills

FMS are a continuous process of motor development that is initiated before birth and continues throughout a lifetime. Developmental change in FMS may occur as a result of maturation, cognitive development that improves through interaction with environmental factors and learning, or a combination (Adolph & Berger, 2006; Piek, 2006). In addition, the primary movement experiences in the early childhood years play a major role in the development of

FMS. Practicing specific structures plays a critical role in mastering these skills. Therefore, children with early experience and practice of FMS have better opportunities to master such skills.

Early mastery of FMS enables children to be successful in different life-domains. For example, there is a positive association between FMS development and (a) increase children participation in physical activity (Wrotniak, Epstein, Dorn, Jonesc, & Kondilisc, 2006; Fisher et

al., 2005; Okely, Booth, & Patterson, 2001; Branta, Haubenstricker, & Seefeldt, 1984), (b) development of specialized skills for sports and leisure later in their life (Raz-Silbiger, Lifshitz,

Katz, Steinhart, Cermak, & Weintraub, 2015; Graf, Koch, Kretschmann-Kandel, Falkowski,

Christ, Coburger, et al., 2004, (c) improved cardiovascular endurance and decreased body fatness

(Lubans, Morgan, Cliff, Barnett, & Okely, 2010; Koutedakis, & Bouziotas, 2003; Okely, Booth,

& Patterson, 2001, and (d) improved academic achievement in different school levels (Ericsson

& Karlsson, 2014; Westendorp, Hartman, Houwen, Smith, & Visscher, 2011).

The association between FMS and cognitive function, specifically WMC, is less considered by researchers may be due to the difficulty in following the changes in the cognitive process during development of FMS (Taylor & Ivry, 2012). This literature review addresses this limitation through highlighting evidence that deals with the contribution of working memory, as a part of cognitive function, to learning and mastering motor skills. Then, it addresses how WMC could be developed through practicing motor skills.

Stages of Learning Motor Skills

Motor learning is a set of brain processes in response to practice or experience that cause changes in the central nervous system pathways to produce a new motor skill (Zwicker & Harris,

2009; Luft, & Buitrago, 2005; Gentile, 1972). To learn a new motor skill, learners must use cognitive and WM processes that are verbal or visual (Newell, 1990; Adams, 1971; Fitts &

Posner, 1967). For example, Fitts and Posner (1967) suggested three main stages to represent the acquisition of motor skills and how learning occurs over time: the cognitive stage, the associative stage, and the autonomous stage.

The Cognitive Stage

In this stage, understanding the nature of the task is essential to develop strategies that could be used to execute the movement and to evaluate the performance. For example, the learner must understand the objective of the skill (e.g., throwing, catching, etc.) and determine the way to perform the skill. This requires relying on processing verbal and non-verbal information from the provider and from the environment surrounding such as facilities, space, and hazards (Scott & Bansal, 2014; Malone & Tranter, 2003). Trial and error also guides learning. The cognitive stage requires a high degree of processing and organizing information into meaningful form. Therefore attention and memory are important factors to achieve this. This cognitive focus can help learners to understand the requirements and parameters of the skill and create a motor program to perform the skill (Shumway-Cook & Woollacott, 2007; Schmidt &

Lee, 2005; Adams, 1971). During the cognitive stage, learners usually have a general idea about the movement and how to execute it. Therefore, the performance at this stage is distinguished by its variability, use of a variety of strategies, and a large number of errors (Zwicker & Harris

2009). At this stage, it is important to provide learners with an optimal environment and the necessary information and guidance to establish a proper memory and cognitive processes for movement.

The Associative Stage

This stage of motor learning is considered an intermediate stage in skill acquisition as described by Fitts and Posner (1967). During this stage, learners should be able to select the best strategy to execute the skill and to begin refining it with practice. The performance during this stage is likely to be more consistent with fewer errors and slow improvement in performance.

The proprioceptive cues (i.e. stimuli) become very important to allow learners to move on from

the first stage “what to do” to focus on “how to do” (Shumway-Cook & Woollacott, 2007).

Information from the movement must be translated from declarative knowledge into procedural knowledge (Schmidt & Lee, 2005). Thus, the performance requires less verbal and visual cues, cognitive aspects of learning, and guidance from the instructor. Learners are able to make errors and learn from these errors to modify subsequent movements independently (Zwicker & Harris

2009; Poole, 1991). Moreover learners can generalize the same strategy to similar motor tasks.

At this stage, the learners’ cognitive ability, as well as the intensity of practice, play an important role to advance learners beyond this stage. This process may take different lengths of time ranging from several days and up to several months.

Autonomous Stage

Performing during this stage becomes mostly automatic. Generally, years of training are required to reach the autonomous stage (Fitts & Posner, 1967). This stage requires less brain activation and little cognitive effort during skill performance compared with the first and second stages (Goldstein, Jerram, Poldrack, Anagnoson, Breiter, Makris, et al., 2005; Wu, Kansaku, &

Hallett, 2004). Automaticity is evident when learners are able to perform the motor skill in any environment while engaging in another task (e.g., being able to use kicking successfully in soccer and dealing with other players on the field simultaneously).

Overall, within each stage of motor learning, a different length of time is needed to complete practicing and learning the movement within the specified cognitive process. This time varies between learners based on internal and external factors that can impact learning and mastering motor skills. Internal factors are represented by learners’ cognitive ability and the presence of musculoskeletal or neuromuscular factors such as the dynamic equilibrium of joints

and joint capsule flexion; while the external factors are represented by motivation level of individuals and feedback received.

Theories of Motor Learning

A number of theories have been proposed since 1943 (Schmidt, 1975) to explain the processing of information during learning motor skills. They emphasize the contributions of internal and external variables to performing and learning motor skills. This literature review focuses on three theories: closed-loop theory, schema theory, and dynamic systems theory to explain the role of these variables in FMS development.

Closed-Loop Theory

The primary aspect of the closed-loop theory (Adams, 1971) is based on the role of a

“motor program” to select and initiate movements, and on the role of sensory feedback to learn movements. In addition, the theory is based on the repeat practice mechanism to minimize error in order to acquire the skills. Planning appropriate motor programs to process afferent information plays an essential role in learning and acquiring motor skills. The motor program consists of a memory trace and a perceptual trace. The memory trace (i.e. verbal and non-verbal learning) is responsible for initiating the motor movement such as determining the direction and the earliest body segments that are involved in the movement. The perceptual trace (i.e., recognition memory) is responsible for guiding the limb to the correct trajectory position. Error correction following performing the skill is achieved by receiving feedback (i.e., correct/incorrect) from the sensory consequences of the limb to the perceptual trace (i.e., knowledge of results). Practicing this cycle (closed-loop) would continue until the desired position is reached (Braun, Aertsen, Paz, Vaadia, Rotter, & Mehring, 2011). The mechanism of learning a new skill requires connection between the stimuli and the responses (i.e., knowledge

of results) to detect and correct the error before the next performance. This cycle is behind the

“closed-loop” designation to Adam’s theory. Based on this theory, storing of information

(memory) of a previous experience and planning a motor program (thinking) plays a key role for successful learning and acquiring motor skills (Schmidt & White, 1972). This theory’s description of learning a new motor skill is noteworthy. It gives a framework of how learning a new skill improves cognitive processes through continuous arousing of the perceptual trace by the memory trace (feedback) to correct the performance of the skill (thinking). However, it has limitations. For example, learning a skill is a slow process, self-paced and positioning response.

Learning a new skill also depends on only corrects the errors through practicing the skill

(Schmidt & Wrisberg, 1973).

Schema Theory

This model, proposed by Schmidt (1975) to address the weakness in the closed-loop theory, consists of an open-loop process. In his theory, Schmidt suggested that three main processes are needed to learn and acquire basic movements: a generalized motor program, recall schema, and recognition schema. A generalized motor program contains general rules that generate the spatial and temporal muscle patterns to produce a specified movement. Schmidt also indicated that learning a new skill depends on recalling from memory the basic form of movement experience to generalize a motor program. Recall schema is a process responsible for recalling information regarding performing the skill. Also known as knowledge of results, recall acts to modify the generalized motor program. Recall schema links to recognition schema (third process), both of which are responsible for storing information about the performance including the initial conditions and response outcomes. Recognition schema controls response outcomes through evaluating and providing sensory consequences of performing the skill such as how the

skill felt, looked, and sounded during performance. Recall schema modifies the performance based on information retrieved from sensory feedback and knowledge of results regarding past performance. This information can be used to determine the initial conditions and response specifications (e.g. direction, speed, power, height, distance, and force) for a second attempt at the skill (Mudge, 2012; Schmidt, 1975).

Based on this theory, learning a new skill depends not only on processing information resulting from repeated practice of a skill, but also on processing a variety of sensory information to produce a suitable movement. The framework of this theory of learning weighs more on the cognitive and memory process than on the closed-loop theory to achieve the desired movement.

Despite the lack of clarity on how a generalized motor program is initially formed, Schmidt proposed significant motor learning concepts such as knowledge of results process and variability of practice to teach children motor skills (Zwicker & Harris, 2009).

Dynamical Systems Theory

This theory, proposed by Bernstein (1967), resurfaced in the 1980s. In addition to the role of the central nervous system (CNS) in controlling movement and behavior development

(Zwicker & Harris, 2009), Bernstein added physical and biological systems as complementary components in emerging and controlling the growth of movement and behavior (Bernstein,

1967). Based on this theory, a new form of movement emerges from the interaction of three general systems: the person, the task, and the environment (Kamm, Thelen, & Jensen, 1990;

Mathiowetz & Haughen, 1994; Newell, 1990). Interactions between these three main systems create a complex network that assists emerging movements (Davids,Glazier, Araujo, & Bartlett,

2003). Thelen and Ulrich (1991) found that the nervous and the neuromuscular systems play essential roles in generating intrinsic patterns of movement in infants. The overall pattern of

movement is decided through interaction with the environment (e.g., social and emotional environment) and with the task content (e.g., type of floor or speed of treadmill). Learning and acquiring new knowledge or skill is based on principles related to the dynamic systems theory.

These principles are complexity; multidimensional, cooperative systems; non-linearity; and self- organization (Thelen & Smith, 1994; Heriza, 1991; Kamm, Thelen, & Jensen, 1990). These principles provide a framework that explains how the new movement or behavior emerges and what factors impact its development. Based on this framework, any pattern of movement is produced by what is referred to as “compressing multiple degrees of freedom” that are produced from the interaction between theory components (person, environment, and task). For example, as children shift from a pattern of walking to a pattern of running many degrees of possible movements emerge. Children may experience several failure attempts (e.g., falling down) when switching to performing a new pattern of movement such as running. Thus, different patterns of movements (e.g., different types of gait) will emerge during the transition period between attractor states until children acquire the pattern of the new movement. If children fail to reach the new pattern of movement, they will return to a previous pattern. Shifting from one pattern to another requires compressing degrees of freedom. For example, shifting from walking to running requires producing optimal forces in muscles, bones, and joints to maintain balance and overcome gravity (Thelen & Smith, 1994). Changes in the components of the systems lead to perturbing the pattern of movement, which then leads to seeking another pattern (Kelso, 1995).

The process of shifting from one stable movement form to another is called a “phase shift”

(Gabbard, 2009). Thelen and Ulrich (1991) emphasized that the phase shift is a very important principle of dynamic systems theory because much can be learned about the nature of developing a new form of movement through transitions. For example, during the replacement of an old

pattern of movement the system becomes ‘open’ and free to reform into any configuration.

Therefore, observation of a phase shift may lead to understanding the subsystems that are important in skill acquisition. A crucial assumption in the dynamic strategy is that the pattern of movement changes over time in a non-linear fashion.

Based on the dynamic system theory, individuals use different cognitive processes to learn and to pass through different development stages (e.g., infant, child, adolescent, and adult stages). The different cognitive processes of learning result from responding to different challenges (e.g., development and environment changes) that children face in learning a new pattern of movement (Gabbard, 2009). This theory emphasizes the critical role of environmental constraints in developing cognitive and motor processes to learn FMS during early childhood

(Haywood & Getchell, 2009).

Overall, the presented stages and theories of motor learning highlight the kinds of processes occurring during performing and learning motor skills. They provide evidence for the role of cognitive function, particularly memory in learning motor skills. In addition, they also reveal the possibility of improving cognitive function and memory during learning these skills through the availability of the appropriate task and environmental constraint in early childhood development. This improvement was found through the evidence in infant motor development that emphasizes a relationship between early gross motor development and adult cognitive function. It also was found through the role of affordances within the home environment in improving the motor and cognitive skills of infants at age 5 months and 9 months

(Miquelotea, Santosa, Cacola, Montebelo, & Gabbard, 2012; Spencer, Samuelson, Blumberg,

McMurray, Robinson, & Bruce Tomblin, 2009; Piek, Dawson, Smith, & Gasson, 2008; Adolph

& Berger, 2006; Schoner & Thelen, 2006; Murray et al., 2006). Despite this evidence, the role

of FMS in cognitive development during childhood has not yet been investigated. Further research is necessary to investigate the relationship between FMS and cognitive development, especially WMC.

Memory

Memory is the mental process that enables individuals to encode, store and retrieve information. It consists of both short-term and long-term memories. Short-term memory (STM) is the system, which is responsible in recoding the new information by using two methods: link this information with the information that is already stored and available in long-term memory

(LTM), and rehearsal of incoming information. This system also is responsible for retrieving information from long-term memory to practice a new activity (Baddeley, 1986, 1990). For example, retrieve information related with the story want to tell or information needed to solve math equations. STM is located in the prefrontal lobe of the brain and is characterized by limited storage capacity ranging from milliseconds to 9 seconds. Sensory memory and working memory

(WM) are a broader concept for STM. This is due to evidence related with different functions of

STM, such as recoding, retrieving, rehearsal, and transferring information to Long-term memory

(LTM), which was found require different brain systems that operate independently (Baddeley,

1986, 1990).

Long-term memory is system responsible for storage information over a long period of time. This system can hold unlimited amounts of information, and this information declines for few minutes, days, years or longer. This information can be semantic (meaning), visual

(pictorial), and verbal (acoustic). LTM includes two types of memories (Figure 2): declarative memory (explicit) and non-declarative memory (procedural). Declarative memory consists of episodic memory (experience) and semantic memory (factual information) and is located in the

medial temporal lobe. Non-declarative memory is located in the basal ganglia and cerebellum

(Squire, 1992).

Declarative memory is meant when the term ‘‘memory’’ is used in everyday language. It is capacity for conscious recollection about facts and events and allows remembered material to be compared and contrasted. Declarative memory supports the encoding relationships among multiple items and events. It is representational. Declarative memory divided into semantic memory (facts about the world) and episodic memory (the capacity to re experience an event in the context in which it originally occurred). Episodic memory requires the participation of brain systems in addition to those that support semantic memory, for example, the frontal lobes.

Non-declarative memory is expressed through performance rather than recollection. It occurs as modifications within specialized performance systems. The memories are revealed through reactivation of the systems within which the learning originally occurred.

The different memory systems can be distinguished in terms of the different kinds of information they process and the principles by which they operate. In declarative memory, an important principle is the ability to detect and encode what is unique about a single event, which occurs at a particular time and place while in case of non-declarative memory; an important principle is the ability to gradually extract the common elements from a series of separate events.

Multiple memory systems evolved because they serve distinct and functionally incompatible purposes. Not only the task that is to be learned is important, but also what strategy is used during learning, because it reflects what memory system is engaged. Under some circumstances the strategy that is engaged is not optimal for solving a task. “When humans acquire a difficult habit-learning task, structures important for habit learning and structures important for memorizing can appear to compete for control of performance” (Squire, Stark, &

Clark, 2004). The notion of multiple memory systems is now widely accepted (Eichenbaum &

Cohen, 2001; Schacter, Wagner, & Buckner, 2000; Squire, Stark, & Clark, 2004).

Figure 2: Declarative and Non-Declarative Memory. From: Squire (2004)

Transferring the information from STM to LTM is called the consolidation process that may take days, weeks, months or even years. It is a biological change that underlies the retention of learned information. This change strengthens the association between multiple stimulating inputs and the activation of previously stored information. The hippocampus is responsible for this strengthening process. However, after the consolidation occurs, retrieval of the memory is independent of the hippocampus. It is thought that the hippocampus is engaged in transferring of information from STM to LTM while the dorsomedial nucleus of the thalamus and mamillary bodies are involved in memory storage (Simons & Spiers, 2003; Baddeley & Hitch, 1974, 1977,

2000).

The Interaction between Short and Long Term Memories

Understanding the nature of interactions between different brain regions during memory processes can help provide a framework on how children successfully learn and remember motor

skills (Simons & Spiers, 2003). These interactions, in turn, provide children with appropriate strategies to develop these skills (Thorn & Page, 2009). Evidence from functional neuroimaging, neurophysiology and computational modeling underscores the role of interactions between the medial temporal and frontal lobes in LTM function. Medial temporal lobe has traditionally been associated with the encoding, storing and retrieving of LTM. The prefrontal cortex has been linked with cognitive control processes such as selection, engagement, monitoring and inhibition

(Simons & Spiers, 2003). The medial temporal lobe consists of the hippocampus, fornix and amygdala, and the surrounding entorhinal, perirhinal and parahippocampal cortices (Suzuki,

2009). Other brain regions, such as the thalamus, mamillary bodies, and retrosplenial cortex also are involved in LTM. These brain regions support the recollection of stored memories with their associated spatiotemporal context. Perirhinal cortex and hippocampus are thought to be responsible for the underlying familiarity-based recognition of previous occurrence, while the basal forebrain is important to produce and distribute acetylcholine throughout the brain. The basal forebrain consists of a group of structures that are located near the bottom of the front part of the brain and includes the nucleus basalis, diagonal band, medial septum and substantia innominata. Acetylcholine acts as neurotransmitter that influences the ability of brain cells to transmit information to one another, and to encourage plasticity and learning.

Several brain regions in the prefrontal cortex have been distinguished in memory processing during various cognitive tasks. For example, the left and right frontal cortices are lateralized for the encoding and retrieval of memories, respectively (Simons & Spiers, 2003).

Another region that has been distinguished is the medial surface of the frontal cortices or, in particular, the orbitofrontal cortex. This brain region is activated during processing of stimulus– response mappings on the basis of reward task (Bush, Luu, & Posner, 2000).

A recent computational model was proposed to explain the role of the prefrontal cortex in strategic encoding and retrieval of LTM. This model designates that the prefrontal cortex develops mnemonic codes that can be used to retrieve information from several medial temporal lobe regions during different LTM processes. The codes are developed through reinforcement learning that is carried out during repeated encoding and retrieval sessions. Another connection between prefrontal and medial temporal regions was found through the medial dorsal thalamus during processing familiarity-based memory task (Simons & Spiers, 2003).

Working Memory Capacity

The important role of WM in daily life has increased recently due to the rising need for individuals to extend their ability to store and retrieve information that has been learned such as remembering telephone numbers, friends’ names, a bank account access code, etc. It is necessary for individuals to maintain, manipulate, and transfer critical pieces of information in their memory systems to be successful in performing a variety of cognitive tasks. These short-term mental storage and manipulation operations are collectively called WM. Relatedly, WMC is “the amount of information that can be processed efficiently in working memory” (Burnham, Sabia,

& Langan, 2014, p.391). During the last decade, WMC has generated much interest among scientists, particularly cognitive psychologists (Phye & Pickering, 2006). This interest is due to the important role of WMC in many higher brain functions such as acquiring and retaining knowledge and using this knowledge to allow individuals to understand and accurately frame their surrounding environment (Brod, Werkle-Bergner, & Shing, 2013). WMC also plays a large role in all cognitive processes such as decision making, goal planning, and choice behavior

(Miyake, Friedman, Emerson, Witzki, & Howerter, 2000).

There is a growing awareness of the critical role WMC could play in the discovery of abnormalities in early child development (Alloway, Rajendran & Archibald , 2009; Alloway &

Temple, 2007; Roodenrys, 2006; Barkley,1997). Archibald and Alloway (2008) and Alloway and Temple (2007) indicated that WMC can be used to detect many neuropsychological diseases and neurobehavioural disorders in children. For example, children with a visuospatial WM deficit often have Developmental Coordination Disorder (DCD) (Giofre, Cornoldi, &

Schoemaker, 2014; Archibald & Alloway, 2008; Alloway & Temple, 2007). This deficit is related to many difficulties such as the inability to throw and catch a ball, read and write, and hold a pencil. Studies show that children with Attention-Deficit/Hyperactivity Disorder (ADHD) have problems with executive functions, which include working memory, particularly in their central executive system, related to uninhibited behavior (Rapport, Alderson, Kofler, Sarver,

Bolden, & Sims, 2008); Roodenrys, 2006; Barkley, 1997). This deficit is characterized by inappropriate/excessive motor activity such as impulsive/hyperactive behaviors (Archibald,

Kerns, Mateer, & Ismay, 2005). It is also characterized by low behavioral predictability, inattention and distractibility (Aase, Meyer, & Sagvolden, 2006).

The concept of WMC has recently been viewed as a better predictor for academic achievement than IQ among different school levels. Lewis, Vasishth, and Van Dyke (2006) posed that it would be better and more accurate to use WMC indicators to predict the academic achievement of children than traditional measures of intelligence. WMC not only measures the normal general intellectual abilities of children, but also places proper relevance on sensory functions and environmental exposure available for learning and acquiring knowledge and complex skills (Lewis, Vasishth, & Van Dyke, 2006). Extensive research has found a significant relationship between WMC and the measures of learning and academic achievement such as

mathematics, reading, and language comprehension (van der Donk, Hiemstra-Beernink, Tjeenk-

Kalff, Van der Leij, & Lindauer, 2013; Chaddock-Heyman, Erickson, Voss, Knecht, Pontifex,

Castelli et al., 2013; Kamijo, Pontifex, O’Leary, Scudder, Wu, Castelli et al., 2011; Lewis,

Vasishth, & Van Dyke, 2006; Alloway, Gathercole, Adams, Willis, Eaglen & Lamont, 2005;

Gathercole, Pickering, Knight & Stegmann, 2004; Bayliss, Jarrold, Gunn, & Baddeley, 2003;

Just & Carpenter, 1992). For instance, children’s mental arithmetic skills were better predicted by their WMC level than by their arithmetical competence (Adams & Hitch, 1997). Other studies validated that children who had lower scores on standardized assessments of reading and mathematics also had lower scores on complex memory tasks (Passolunghi & Siegel, 2001; Bull

& Scerif, 2000; Gathercole & Pickering, 2000a; McLean & Hitch, 1999, Siegel & Ryan, 1989).

Model of Working Memory

In 1974, Baddeley and Hitch suggested a WM model instead of the existent STM model by Atkinson and Shiffrin (1968). They indicated that STM is not a single system that operates in a unitary fashion; it is more complicated and has subsystems. It is comprised of multiple components including the central executive system and two temporary storage systems: the phonological loop and visuospatial sketchpad loop. These components specialized not only in storing information from the past experiences, but also in comprehending and manipulating such information (Baddeley & Hitch, 1974). This process allows individuals to acquire new knowledge, solve problems, and act on their current environment (Baddeley & Logie, 1999).

Based on this model, WM is a system with limited capacity which is not only due to the limited ability to store information for a short time, but also because of the limited ability to prohibit irrelevant information (inhibitory mechanism), delete items that are no longer needed for processing information (inferences), and limit the processing speed and the amount of resources,

knowledge, and skills (Park & Payer, 2006; Miyake & Shah, 1999; Baddeley and Hitch, 1974).

Due to the need for the long-term knowledge that is required to process new information or thoughts, Baddeley and Hitch (2000) later added a fourth component to the model ‘episodic buffer’ (Henry, 2012; Baddeley and Hitch, 2000). The Baddeley and Hitch model (Figure 3,

Henry, 2012, p.5) has proved valuable in the field of WM and has been used in various fields such as cognitive psychology, behavioral neuroscience, and animal behavior fields (Miyake &

Shah, 1999). The proven model was also found helpful in understanding the role of STM in other advanced cognitive functions such as language, learning, comprehension and reasoning (Martin,

& Ellis, 2012; Baddeley, 2003).

In this study, Baddeley’s and Hitch’s model was used to gain a better understanding of the functionality of representation and categorization in learning fundamental motor skills, it is fundamental that researchers understand how movements are represented in STM and LTM. It is our position that human motor control requires that our actions be planned and represented in terms of intended perceptual effects and future task demands, and that the individual has a well- structured mental representation of the task so that the movement can be carried out successfully.

Figure 3: The Revised Model of Working Memory. From: Baddeley (2000)

The Central Executive System

Also known as the supervisory attentional system, the central executive system is considered the most important component in the Baddeley and Hitch model for controlling and allocating attention (Baddeley, 2007, 2000, 1990, 1986). It is the real ‘brain’ of the WM system because it is responsible for many cognitive functions such as (a) decision making, (b) integration of information from multiple sources into coherent episodes, (c) regulation, control, and coordination of activity between all of the WM components, (d) shift between tasks or retrieval strategies, and (e) selective attention and inhibition (Henry, 2012). The central executive system plays an essential role in directing behavior when new ideas, thoughts, plans, and strategies are required to deal with new situations (Shallice, 1990). This system is located in the prefrontal areas of the frontal lobe including the ventral lateral prefrontal cortex (VLPFC), dorsal lateral prefrontal cortex (DLPFC), and anterior prefrontal cortex (APFC) (Kane & Engle,

2003; Simone & Spliers, 2003; Baddeley, 1986, 1990).

Phonological Loop System

The phonological loop system is described as the ‘slave system’ for its exclusive and limited responsibility in storing auditory or verbal information in a speech-based form over short periods of time (Baddeley, 2007). It is composed of two subcomponents including the

‘phonological store’ and the ‘articulatory rehearsal mechanism’. The phonological store is responsible for holding speech information for a short time (two seconds). This process is known as ‘memory trace’. The process of forgetting the speech information after storing it is known as

‘trace decay’ (Baddeley, 2007). Preventing decay of speech information is controlled by the articulatory rehearsal mechanism. This process plays an important role in improving the capacity of phonological STM by reciting (re-entering) the information in the phonological store

(Baddeley, Gathercole, & Papagno, 1998).

Henson, Burgess, and Frith (2000) indicated several brain regions, associated with storing speech information in the phonological loop, are located in the left hemisphere. These regions include the left inferior parietal cortex which is involved in rehearsal mechanism; Broca’s areas

(left inferior frontal lobe) involved in speech production, and Wernicke’s area (left superior temporal lobe) involved in speech comprehension (Simons & Spiers, 2003; Jonides, Smith,

Marshuetz, Koeppe, & Reuter-Lorenz, 1998; Frith, Frackowiak, & Paulesu, 1993).

The articulatory rehearsal mechanism has two different functions: the first function stores verbal information known as phonological/verbal recoding while the second function stores visual information known as phonological/verbal coding (Baddeley, 1992, 1986). Visual information enters this subcomponent through converting visual form presentation (e.g., words, letters/numbers, and pictures) into speech (Figure 4; Baddeley, 1986). The articulatory rehearsal mechanism plays a major role in increasing the capacity and the duration of phonological short-

term memory. Several techniques can influence the efficiency of the articulatory rehearsal mechanism and can change the memory span in the phonological loop to store and remember information. Among these techniques are the similarity effect, the word length effect, the memory span and reading rate, and the articulatory suppression. An example of the similarity effect would be when similar sounding letters (e.g., B, G, V, P, T) are much more difficult to store and remember compared with dissimilar sounding letters (e.g., Y, W, H, K, R). This is due to the fact that similar sounding letters (rhyming lists) cause confusion in the ability of the memory trace system to store information (Conrad & Hull, 1964; Baddeley, 1966). This, in turn, affects the efficiency of the articulatory rehearsal mechanism to maintain information for longer time.

Figure 4: The Phonological Loop, with the Phonological Store and the Articulatory Loop. From:

Baddeley (1986)

A series of experiments by Baddeley and his colleagues (1975) showed the effect of word length in storing words in the phonological loop system. For instance, shorter words were better to recall than longer words. Baddeley argued that longer words require longer time to maintain and rehearse by the articulatory rehearsal mechanism than shorter words (Baddeley, Lewis &

Vallar, 1984; Baddeley, Thomson, & Buchanan, 1975). Experiments by Baddeley and others showed that increasing memory span was related to increasing speech rates for one-syllable words. Their experiments also showed that decreasing memory span was related to decreasing speech rate, or to adding more syllables to the words (Schweickert & Boruff, 1986; Stevenson,

Lee, & Stigler, 1986; Ellis & Hennelly, 1980; Baddeley, Thomson, & Buchanan, 1975). In addition, memory span was also found to be influenced by the articulatory suppression technique. Baddeley indicated any suppression or blocking during phonological coding or verbal rehearsal would decrease the memory span, such as when listening to loud music while carrying out the remembering task (Baddeley & Larsen, 2007a, 2007b; Jones, Hughes & Macken, 2007).

The Visuospatial Sketchpad System

The visuospatial sketchpad system is another ‘slave system’ as it is responsible to hold visual and spatial information such as the location, form, speed, size, color, etc. about the objects for short periods of time. This system integrates this information from multiple sources including visual, tactile, kinesthetic, episodic buffer system, and semantic LTM (Baddeley, 2007). It also visualizes and stores the information in the form of mental images acquired verbally (Baddeley,

2003). Maintenance of this information via a spatial rehearsal mechanism enables the system to provide information necessary during thinking, remembering, and processing tasks (Zimmer,

2008; Logie, 1995). The visuospatial sketchpad system is proposed to store, coordinate, and manipulate two different types of information in separate mechanisms described as a visual cache and inner scribe (Della Sala, Gray, Baddeley, Allamano, & Wilson, 1999; Logie, 1995).

The visual cache system deals with information related to the form/color of objects while the inner scribe system deals with information related to the space and movement of objects (the spatial task). These two systems are located in the right hemisphere. The spatial task activates

several areas in the right hemisphere, particularly the prefrontal, premotor, occipital and parietal cortices; whereas, the visual task activates several areas in the left hemisphere, particularly the parietal and inferotemporal cortices. There is evidence supporting the separation of visual cache and inner scribe components, as there is no interference between visual and spatial tasks when they are performed together (Baddeley & Hitch, 1974).

Like the phonological loop, memory span in this system can be influenced by the number of items that can be held in the system. Researchers reported that visuospatial sketchpad system cannot hold more than four object files perfectly with a certain number of features in each object such as a color and a shape (Zimmer, 2008; Vogel, Woodman, & Luck, 2001). Experiments on a sequence of square matrix pattern and random block patterns showed that the visual memory system is able to hold one-item only of the immediate recency effect (a single pattern) in recognition memory (Broadbent & Broadbent, 1981; Philips & Christie, 1977). Memory span in this system also was found to be influenced by the visual similarity technique. Studies indicated that visual similarity between the items that need to be retained (e.g., pictures, letters, and digits) decreases the capacity of this system. In recognition memory task, for example, children showed difficulties to remember pictures that look visually similar such as a brush, a rake, and a pen compared with visually distinct pictures such as a pig, a ball, and a pen (Hitch, Halliday,

Schaafstal, & Schraagen, 1988). Similar results were found among older children (Hitch,

Woodin, & Baker, 1989) and adults (Walker, Hitch, & Duroe, 1993) under articulatory suppression conditions. Decrease the complexity of items and increase the practice plays an essential role in increasing the capacity limitation of this system (Gerton, Brown, Meyer-

Lindenberg, Kohn, Holt, Olsen, et al., 2004).

The Episodic Buffer System

The episodic buffer is a fourth component to the WM model proposed by Baddeley in

2000 (Baddeley, 2000). This system is responsible for combining information from the subsidiary systems (phonological loop and visuospatial sketchpad loop) and from LTM into a coherent episode (Baddelely, 2007). This system is considered a bridge connection between the central executive and LTM that allows the central executive system to access information in

LTM during ongoing memory and processing tasks. It provides information to the central executive system in a single ‘multidimensional’ code based on the conscious awareness principal

(Allen, Baddeley & Hitch, 2006; Baddeley, 2000).

Similar to all WM components, the episodic buffer system also has a limited capacity to provide a temporary storage of information that is held in a multimodal code (Baddeley, 2000).

The capacity can be increased by two different mechanisms: controlling attention and increasing the number of chunks of information in the episodic buffer system. Controlling attention is regulated by the central executive system while retrieving information from LTM or integrating information from two slave systems (Allen, Baddeley & Hitch, 2006). The number of information chunks can be increased by recoding words in a sentence or a paragraph format

(Baddeley, 2007). This was found in individuals who are able to recall five to six unrelated words at a time, but this number increased when they recalled these words as one sentence

(Baddeley, 2007; Hulme, Maughan, & Brown, 1991).

Overall, the structure of the WM model reveals the importance of providing appropriate verbal and visual information to increase memory span in both phonological and visuospatial sketchpad systems, which, in turn, increases the capacity and efficiency of the central executive system to process information. Baddeley and others (Baddeley, 2007, Della Sala, Gray,

Baddeley, Allamano, & Wilson, 1999; Logie, 1995) provided a framework of the role of each

WM component in storing, maintaining, manipulating, and processing information to learn a new concept, knowledge, or skill. This model has not yet been adopted in teaching FMS to children.

Therefore, the current study’s purpose is to identify how learning FMS is related to WMC particularly in two of the WM components (verbal STM and visuospatial STM) that were proposed in this model.

Associating Fundamental Motor Skills with Working Memory Capacity

Motor experiences during early childhood are necessary for healthy brain development

(Dalton & Bergenn, 2007). These motor experiences play a significant role in providing the brain with various sensory inputs (stimuli) through environmental interaction (Kolb, Mychasiuk,

Muhammad, Li, Frost, & Gibb, 2012; Rinaman, Banihashemi, & Koehnle, 2011; Ben-Ari,

Sirota, Holmes, Buzsáki, Khazipov, & Leinekugel, 2004). These sensory inputs are considered a major component to improving cognitive functions and specially the capacity of WM. This process seems to be manifested in the role of early motor experiences in increasing intercellular connections (wiring) in the brain, and in improving bond strength of the synapses that connect nerve cells (Gazzaniga, 2009). Theories like ‘windows of opportunity’ (Chugani, 1998) support the effective role of early motor experiences in simulating wiring cells in the brain. Chugani

(1998) referred to the highest influence of the windows of opportunity theory in developing motor control, vision, language, feelings, etc. The foundation of this theory is based on opening certain windows for experiences that begin before birth and narrow with age. Chugani also stated that any missed opportunities can have an effect on optimizing brain function and development.

Based on this theory, the role of motor experiences in increasing brain circuits is broken down into three periods. The first window of opportunity for developing the primary motor circuits

starts from the prenatal period until the end of the second year. During this period, the cerebellum plays an essential role in enabling the child to control posture and coordinate body parts. This period provides considerable experience to the child through the ability to move around and interact with the environment. The second window of opportunity for developing gross motor skills starts around age 2- 3 and narrows considerably at age 10. The window for developing fine motor skills starts after birth directly and narrows around age 9 (Chugani, 1998).

Therefore, researchers suggest that providing appropriate motor experiences during early years can improve children’s development both biologically and functionally. Logan (1988) postulated that learning motor skills is naturally accompanied with cognitive and memory-retrieval processes. The contribution of these processes changes over time as the memory base increases

(Lindsey, 1998).

On examining the reciprocal effect of the role of WMC in enhancing the learning of motor skills, Taylor and Ivry (2012) showed that blocking visual information during reaching movements had a significant effect on the deformation in performance and on obstruction of the visuomotor adaptation. They indicated that providing appropriate and precise sensory feedback

(visual and verbal) reduced performance errors during reaching practice. They also concluded that visual feedback is considered a crucial factor to facilitate performing and learning motor skills. Sensory feedback, which results from past experiences, helps optimize performance of the skill through modifying the biological network mapping (i.e., current brain’s neural pathway)

(Taylor & Ivry, 2012). Accumulation of sensory feedback was found to increase brain ability and capacity in dealing with a variety of cognitive tasks. For example, visual cues were found to play an essential role in improving the ability of children to track objects, enhance spatial awareness, and facilitate learning motor skills such as catching, throwing, and striking (Benelli & Yongue,

1995). Also, verbal and visual cues were found to facilitate and optimize learning motor skills

(Taylor & Ivry, 2012; Valentini, 2004). Therefore, researchers emphasized the importance of using these cues in teaching motor skills due to their roles in reinforcing memory, improving selective attention, and increasing retention ability of a particular skill. Taylor and Ivry’s (2012) experiment showed that participants who had high levels of WMC, particularly spatial WMC, were faster in adapting and learning the movement than their peers.

Overall, the aforementioned biological and psychological evidence reveals that developing motor skills and improving WM share overlapping processes. The efficiency in one of these variables predicts the efficiency of the other. The evidence also reveals the importance of the motor cortex in early child development for its role in forming brain structure. In addition, research highlights the importance of providing children with optimal motor experiences (visual and verbal feedback) that can help optimize the development in the motor cortex and other brain regions.

Gender Differences in Fundamental Motor Skills and Working Memory

Differences in the FMS level between genders occur as early as 3 years of age and these differences increase across childhood and adolescence (Spessato, Gabbard, Valentinia, &

Rudisill, 2012; Barnett, Van Beurden, Morgan, Brooks, & Beard, 2010). The differences varied among studies. For example, studies found boys had advanced levels in most motor skills over girls (Spessato, Gabbard, Valentinia, & Rudisill, 2012; Hume, Okely, Bagley, Telford, Booth,

Crawford et al., 2008; Thomas & Thomas, 1988). While other studies found boys were demonstrating superior skills to girls in only object control skills specifically in throwing, catching, and kicking (Cliff, Okely, Smith, & McKeen, 2009; Valentini, Spessato, & Rudisil,

2007; Okely, Booth, 7 Chey, 2004). No gender differences were found in locomotor skills

(Wong & Cheung, 2006; Goodway, Crowe, & Ward, 2003). However, Cliff, Okely, Smith, and

McKeen (2009) found girls ages 3- to 5 years were better than boys in their level of locomotor skills.

These differences could be due to biological factors such as body composition during growth and maturation (shoulder: hip ratio), muscular strength, joint diameters, and percent body fat (Thomas, Gallagher, & Thomas, 2001; Thomas & French, 1985). Environmental sources

(e.g., practice opportunities) and sociocultural factors such as bias for specific sport activities

(e.g., football) or specific gender roles in society could be contributing to the differences

(Gabbard, 2012; Hume et al., 2008; Payne & Isaacs, 2008; Goodway & Branta, 2003)

Gender differences were found in brain functioning during verbal and non-verbal WM tasks (Allen, Tranel, Bruss, & Damasio , 2006; Bell, Willson, Wilman, Dave, & Silverstone,

2006; Goldstein, Jerram, Poldrack, Anagnoson, Breiter, Makris, et al., 2005; Schweinsburg,

Nagel, & Tapert, 2005; Speck, Ernst, Braun, Koch, Miller, & Chang, 2000; Gur, Mozley,

Resnick, Gottlieb, Kohn, Zimmerman et al., 1991). In verbal WM tasks, functional neuroimaging studies found females had higher activation in the middle, inferior, and orbital prefrontal cortices than males (Goldstein et al., 2005). Speck et al. (2000) showed a significant difference between males and females in activating prefrontal cortices (LPFC), the parietal cortices (PC) and caudate. The examination of fMRI revealed males had bilateral activation or right-sided activation in these three brain regions (LPFC, PC, & caudate). Their results also showed females had more activation in the left hemisphere in the same brain regions. According to this study, males were more accurate and slower in performing all verbal WM tasks compared with females

(Speck et al., 2000). In the visual spatial task, studies showed males had right-lateralized brain activation patterns compared to females, they also had higher activation in the anterior cingulate

cortex and a larger response in frontopolar cortex (Schweinsburg, Nagel, & Tapert, 2005; Gur et al., 1991). Our findings indicate that the frontal and parietal neural networks involved in spatial

WM change over the adolescent age range and are further influenced by gender. These changes may represent evolving mnemonic strategies subserved by ongoing adolescent brain development.

Investigating the gender difference in verbal and non-verbal processing at various levels of FMS development will contribute to understanding additional factors in development.

Therefore, describing gender differences in the relationship between FMS (locomotor and object control skills) and, WMC including its two components (verbal STM and visuospatial STM) adds another reason for the importance of conducting this study.

Summary

This literature review discussed the nature of the interrelationship between FMS and

WMC. The stages and theories of motor learning reveal that planning an appropriate motor program to execute any motor skill requires appropriate information. The information is retrieved from memory systems. Early motor experiences were found to play essential roles in providing the memory systems with the information required to process cognitive tasks to learn and acquire the skill and knowledge. Cognitive ability was also found to have a positive contribution to learning motor skills by increasing the ability of children to maintain, manipulate, and process critical pieces of information that are required when learning movements.

The role of WM model, as proposed by Baddeley and Hitch, in temporarily manipulating and storing information during processing various tasks in everyday life was provided. This model consists of four components: the central executive system, the two slave systems (the phonological loop and visuospatial sketchpad), and the episodic buffer. Baddeley and Hitch

(1973, 2000, 2007, and 2012) indicated all WM components have limited capacity in storing and processing information, but this capacity can be increased through following specific strategies and mechanisms. In addition, understanding gender differences in processing verbal and non- verbal information opened a new window to investigate these differences during FMS development.

Therefore, the purpose of this study is to investigate the relationship between motor skills and WMC through studying the associations between the level of FMS with the capacity of the verbal STM and visuospatial STM. This study also aims to identify the natural relationship between FMS and verbal STM and visuospatial STM among gender in children aged 9-10 years.

CHAPTER 3: METHODOLOGY

A cross-sectional study was used to examine the relationship between FMS and verbal

STM and visuospatial STM. Sixty-one children aged 9-10 years were selected from five regions in Michigan including regions 1, 2, 3, 4, and 5 (see Appendix H). Two approvals were obtained from the Michigan State University Institutional Review Board (IRB). The first approval was to get a permission to contact children at region 1 in February 13, 2015, and the second approval was to contact children from four other regions (see Appendix H) in Michigan in May 28, 2015.

Additional permissions from appropriate people in each region were obtained prior conducting the study.

Two instruments were used to examine the relationship between FMS and verbal STM and visuospatial STM. The level of motor skills development determined by Test of Growth and

Motor Development-2 (TGMD-2; Ulrich, 2000), and the level of verbal STM and visuospatial

STM determined by Automated WM Assessment– Second Edition (AWMA; Alloway, 2007).

Each of the FMS components (total FMS, locomotor skills, and object control skills) were compared with verbal STM and visuospatial STM separately. Each of the FMS components

(total FMS, locomotor skills, and object control skills) consisted of two levels (level 1 and level

2): level 1 included superior, above average, and average level (level 1 ≥90), and level 2 included below average, poor, and very poor (level2 ≤89). Each of the verbal STM and visuospatial STM consisted of three levels (above average, average, and below average).

Because there were no children in the below average level, the below average level was not included in the data analysis. Gender differences were considered through examining the relationship between FMS and verbal STM and visuospatial STM. A demographic information

questionnaire was used to gather data such as age, gender, ethnicity, BMI, and parents’ education level of the participants to describe the sample.

The measurement protocol required approximately 45-50 minutes for each child: 15-20 minutes for TGMD-2, and 30 minutes for AWMA. Statistical analysis was conducted using

SPSS.22 statistical software with the significance level set at p0.05. A Kolmogorov-Smirnov

Test (K-S Test) in SPSS was used prior to analyzing data to check the normality of distribution of the demographic and anthropometric data of the study sample. An independent samples t-test was used to identify differences between boys and girls in all study variables. A Chi-Square Test was used to determine the relationship between FMS and WMC. A Cochran-Mantel-Haenszel

Test was used to determine the relationship between all study variables including FMS, WMC, and gender.

Collecting data required almost one year to complete testing 61 children (February 25,

2015- January 30, 2016). Data were collected at different places (see Appendix H). A quiet room in each place (see Appendix H) was used to collect verbal STM and visuospatial STM data.

Gymnasium at the selected (school and department) and the tennis court (close area of each parents’ home) in region 1,2, and 3 were used to collect FMS data. Eight undergraduate students from the Department of Kinesiology at Michigan State Unviersity helped in FMS data collection at the regions 1. The primary researcher trained the examiners on administrating TGMD-2 according to a standard protocol (Ulrich, 2000). All examiners were informed about the goals, methods, and procedures of the study to ensure they understand the assessment steps. The researcher collected the rest of the data including FMS and WMC. A pilot study was conducted prior to data collection in February 25, 2015. The researcher provided gift cards, $10 for every child who completed data collection and $25 for every examiner.

Method

Research Design

This was a cross- sectional study, which identified a relationship between the level of

FMS and WMC and its two components (verbal STM, visuospatial STM). Gender differences between FMS (total FMS, locomotor skills, and object control skills), and verbal STM and visuospatial STM were examined in children aged 9-10 years.

Participants

Sixty-six children were recruited to participate in this study. Only sixty-one children aged

9-to-10 years in fourth grade were included in the study: two children were obese (BMI < 90.2 and 92.8), one child had ADHD with medication, and two were in the fifth grade. Participants were typically developing children with normal weight between 5th < BMI < 85th percentile

(CDC, 2009), due to the negative association between the level of FMS and overweight/obese children (Cliff, Okely, Morgan, Hones, Steele, & Baur, 2012). Only seven children (11.5%) of the total participants were overweight were included in this study, as they were only a few pounds above the average BMI< 86-89.60. Children’s level of physical activity was not a concern due to the weak relationship between physical activity and motor skills (Kalaja, 2012;

Reed, Metzker, & Phillips, 2004).

The participants selected from five different regions (see Appendix H) including region1

(n=20; 32.8%), region 2 ( n=15; 24.3%), region 3 (n=12; 21.3%), region 4 (n=6; 9.8%), and region 5 (n=7; 11.5). Twenty children (32.8%) of the total participants (sixty-one) were selected from region 1, and the rest of the participants, forty-one (66.9%), were selected from other regions. This was due to several factors, such as the lack of number of participants who agreed to participate in the study, and the school selected allowed to test children verbal STM and

visuospatial STM only before and after school program. This time was suitable to test only two children a day, one child before the school program and one child after the school program. This time also did not fit with any examiner, who was assigned to help in collecting verbal STM and visuospatial STM data. The assessment was based on parents’ decision to decide the day, the time, and the location to test their child.

Measures

Physical Characteristics and Demographics

The demographic information questionnaire (Appendix C) gathered the following data:

Date of birth, gender, height and weight, and ethnicity (African- American, Asian, Caucasian,

Hispanic, and other). Parents’/guardians’ education level was represented by these categories

(GED, high school, some college, associate’s degree, bachelor’s degree, and post-graduate degree). Parents/guardians were asked to indicate if their child had been diagnosed as having any of the following problems: mental health problem (e.g., depression and anxiety); neurological disorder (e.g., epilepsies, neuromuscular disorders, neurodegenerative disorders, etc.); disruptive behavior disorders (e.g., ADHD, ODD, and CD); and learning disabilities (e.g., reading, writing, and math). They also were asked if their child was taking any mediation and why. Only one child was diagnosed with ADHD and was taking medication and was not included in the study.

Children’s standing height and weight was measured directly after verbal STM and visuospatial STM assessment to determine the actual BMI. Children were asked to remove their shoes and heavy clothing (e.g., jackets, sweaters) and stand in a standard erect posture before being measured. Participants’ height was measured to the nearest 1/8th inch or 0.1 centimeter using a portable stadiometer. Participants’ weight was measured to the nearest 1⁄4 pound using a digital scale. Digital scale was calibrated to check the accuracy of the scale before testing the

child by using 5-pound weights (Neoprene Dumbbell). BMI was calculated as individual’s weight (kg) divided by the square of the height (m2) (Malina, Bouchard, & Bar-Or, 2004).

Fundamental Motor Skills

The Test of Gross Motor Development, second edition (TGMD–2) was used to assess children’s FMS (Ulrich, 2000). TGMD–2 is a quantitative measure designed for children ages 3 to 10 years (Appendix E). This test has a test-retest reliability of r = 0.91 (Ulrich, 2000). It requires 15-20-minute for each participant to be completed. TGMD–2 consists of 12 skills divided into two-subtests: locomotor (6 skills) and object control (6 skills). Locomotor skills include running, galloping, hopping, leaping, horizontal jumping, and sliding. Object control skills include striking, dribbling, catching, kicking, overhand throwing, and underhand rolling.

The performance of each skill is assessed quantitatively on three to five criteria depending on the skill. Criteria are coded (1) if met and (0) if not. Two trials were scored and added together for a total raw skill score. The total maximum raw score of all the FMS trials was 48.

Evaluating examinees’ levels of FMS were obtained by converting the raw scores of each of the two subtests (locomotor skills and object control skills) separately into standard scores.

Based on TGMD-2 process- assessment (TGMD-2, Ulrich, 2000), the sums of both subtests standard scores were converted into a gross motor quotient. The gross motor quotient scores were converted into descriptive rating level of the total FMS including very superior, superior, above average, average, below average, poor, and very poor. Evaluating examinees’ levels of each locomotor and object control skills separately were obtained by converting the raw scores of each of the two subtests (locomotor skills and object control skills) separately into standard scores. The standard score of each subtest was converted into descriptive rating level of the FMS

subtest including very superior, superior, above average, average, below average, poor, and very poor.

Participants at the region 1(n=20; 32.8%) were asked to rotate in small groups through four stations (3 skills/ station) inside a school gymnasium in order to perform all FMS.

Participants at the region 4 (n=6; 9.8%), and region 5 (n= 7; 11.5), were asked to align in one line in order to perform all FMS. Participants from region 2 and region 3 were performed all

FMS individually. All FMS tested by using standard protocols. For example, all participants were given a time to practice each skill twice before recording their performances, and after demonstrating the skill by the examiner or by the researcher.

All FMS performances were recorded by using a digital camera full HD camcorder

(Canon, VIXIA HF R400), which was placed on either side of the child, at a distance that allowed recording all skills clearly without affecting the children’s performance. The number of cameras used in recording the participants’ performance was varied among the number of participants at each assessment time (see Appendix H), one camera at each station. Evaluating of the digital FMS performances were done by the primary researcher. The evaluation scores were compared with ratings assessed by a developmental expert (associate professor of kinesiology) for each skill to establish inter-rater reliability and objectivity of the assessment. The results of inter-rater reliability of the Intraclass Correlation Coefficient= 0.875.

Verbal STM and Visuospatial STM

Alloway Working Memory Assessment (AWMA) was used to assess verbal STM and visuospatial STM. AWMA is a quantitative measure to assess individuals’ WM ability for ages

4-22 years (Alloway, 2007: Appendix F). AWMA is a computer-based standardized battery consisting of four components including two storage components (verbal STM and visuospatial

STM) and two processing components (verbal WM and visuospatial WM). Verbal STM and verbal WM are for measuring the activity in the phonological loop, verbal central executive, and episodic buffer. Visual-spatial short-term memory and visual-spatial WM are for measuring visuospatial sketchpad, visuospatial central executive and episodic buffer.

Participants’ levels in these four components were determined by 12 subtests. For example, the verbal STM determines by three subtests including digit recall, word recall, and non-word recall. The verbal WM determines by three subtests including listening recall, counting recall, and backwards digit recall. The visuospatial STM determines by three subtests including dot matrix, mazes memory, and block recall. Finally, the visuospatial WM determines by three subtests including odd one out, miser X, and spatial recall backwards (Alloway, 2007). Each of the twelve subtests consists of a series of practice trials before the test trials. The test trials are presented as a series of blocks; each block consists of six trials. In each case, children have to remember a piece of information and then recall it back immediately. Minimal requirement of training is needed to administer this test. The full form requires 45 minutes to complete. In this study, participants were only tested on the verbal STM and visuospatial STM, which required 30 minute from each participant to identify the capacity of verbal STM and visuospatial STM of children aged 9-10 years in Michigan. All participants were tested individually in a quiet place by a single examiner for each examinee. The score and report form is automatically provided at the end of the test.

Procedures

The Michigan State University Institutional Review Board (IRB) approved the study procedures. Different permissions were obtained prior to conducting the study from the following people: administrator in the region 1 School District, principal of the school, physical

education teacher at selected school, priests of the selected churches, and parents. The investigator started to recruit children beginning from the school selected by sending home with the children sealed envelopes to all the parents/ legal guardians of the fourth graders. The envelope included a flyer, consent and assent forms, a copy of the school principal approval letter, and a questionnaire (a demographic information questionnaire). The flyer, consent, and assent forms included information about the study (Appendix A, B, & D), such us study goals, method, and procedures. Thirty parents agreed to participate in the study and returned the consent and assent forms and questionnaire in the same envelope. Only 20 children of 30 included in the study from the school selected. The remaining ten children were not selected in the study because they did not complete verbal STM and visuospatial STM test (eight children) or were obese (two children; BMI < 90.2 and 92.8).

The researcher provided a training session for one time for eight undergraduate students at the Department of Kinesiology, Michigan State University. The training session covered the appropriate protocol to collect FMS data, such as demonstrate the skills, trails, and recoding the skills. All eight examiners completed training through the MSU IRB website prior to starting data collection.

A pilot study was conducted prior to data collection to test the protocol of the entire research project including IQ, TGMG-2, and AWMA assessments; the position of the equipment and filming; and the quality of the equipment that was used for the TGMD-2 test. Four children recruited from the region 1 to participate in the pilot study. Those children were not included in the study, as they did not complete all research requirements (i.e., did not complete the questionnaire form and all FMS assessments).

Based on the pilot study, several changes were made in the study procedures to facilitate the application of the study: Reducing the assessment time by removing the IQ test from the study, which required a 15-minute test session for each participant. Additionally, the assessment time of the WMC was reduced from 45-minute to 30-minute for each participant by testing only two WMC components (verbal STM and visuospatial STM) instead of four components. The time of WMC assessment was changed to be only before and after school program and not during the school time, which was based on the school principal decision. Finally, children’s height and weight was measured immediately after verbal STM and visuospatial STM assessments to determine BMI level.

The first step of the data collection was at the region 1. Twenty children (32.8%) were included in this study. Collecting FMS was during three consecutive PE classes from March 2-4,

2015. Collecting verbal STM and visuospatial STM and height and weight was before and after the school program for three consecutive weeks and was based on parents’ available time.

Testing FMS in the region 1 was at the school gymnasium in four stations with three skills being tested at each station in each day. Locomotor skills, running, hopping, and leaping were assessed at the first station, and jumping, sliding, and galloping were assessed at the second station. Object control skills, kicking, rolling, and dribbling were assessed at the third station, and catching, throwing, and striking were assessed at the fourth station. The performances were videotaped by digital cameras each camera at each station. Eight undergraduate students from the

Department of Kinesiology at MSU, who are trained to test TGMD-2, helped in testing FMS for three days. Testing verbal STM and visuospatial STM was in a quiet room at the region 1, one child before the school program and one child after school program. Parents received schedule

via their emails to decide the time that works for them to test their child verbal STM and visuospatial STM.

The second step of data collection started after obtaining the second approval from IRB.

Information and flyers about the study were sent to all MSU staff (via their emails), and posted in several gyms in regions 1 and region 2 (e.g., boys and girls club), and several church bulletins in all regions 1,2,3,4, and 5. Data were collected from participants whose parents signed the informed consent and children signed the assent forms with completed questionnaires before testing their child (see Table 2 and Appendix H). Researcher followed the same procedures to test all FMS for all children, such as demonstrating skills, providing trails to practice the skills, and following same order to test all FMS. Children were first started with performing locomotor skills and then object control skills. Testing verbal STM and visuospatial STM was after completing FMS in a quiet room in each selected place. School and all parents were provided the results of their children’s assessments in both tests (FMS and verbal STM and visuospatial

STM). All children were given a $10 Meijer gift card for their participation. Testing FMS for all children was done individually.

Data Analysis

Power analysis was conducted prior to data collection to determine the sample size by using G*Power 3.1 (Faul, Erdfelder, Buchner, & Lang, 2009). Roughly 60 participants were necessary to have 95% power level, at the significance level α = 0.05 for detecting a moderate effect (f2(V) = 0.25). All statistical analyses were conducted by using IBM SPSS.22 Statistics.

Descriptive statistics (means and standard deviations) were determined for all study variables to describe the sample. A Kolmogorov-Smirnov Normality Test (K-S Test) in SPSS was used prior to analyzing data to check the normality distribution of the demographic and anthropometric data

of the study sample. An independent samples t-test was used to identify differences between boys and girls in all study variables. A one-way ANOVA was used to identify the difference in the level of FMS (total FMS, locomotor skills, and object control skills) and verbal STM and visuospatial STM across five regions. Chi-Square Test was used to determine the relationship between FMS and verbal STM and visuospatial STM. And Cochran-Mantel-Haenszel Test was used to determine the relationship between all study variables including FMS, verbal STM and visuospatial STM, and gender.

The statistical analyses were based on the research hypotheses

H1: Children, who have higher levels of FMS (total FMS, locomotor skills, and object

control skills), will show better verbal STM, and visuospatial STM compared to children

who have lower levels of FMS.

Chi-Square Test was used to determine the relationship between:

- Total FMS and verbal STM

- Locomotor skills and verbal STM

- Object control skills and verbal STM

- Total FMS and visuospatial STM

- Locomotor skills and visuospatial STM

- Object control skills and visuospatial STM

H2: Boys will have better verbal STM, and visuospatial STM compared to girls in all levels

of FMS.

Cochran-Mantel-Haenszel Test was used to determine the relationship between:

- Total FMS and verbal STM and gender

- Locomotor skills and verbal STM and gender

- Object control skills and verbal STM and gender

- Total FMS and visuospatial STM and gender

- Locomotor skills and visuospatial STM and gender

- Object control skills and visuospatial STM and gender

An independent samples t-test was used to identify differences between boys and girls in all

study variables including:

- Covariate variables (age, heights, weights, BMI, BMI percentile, ethnicity, regions,

mother’s and father’s educational levels).

- FMS (total FMS, locomotor skills and object control skills)

- Verbal STM and visuospatial STM and subcomponents

A one-way ANOVA was used to identify the difference in the level of:

- FMS (total FMS, locomotor skills, and object control skills)

- Verbal STM and visuospatial STM

- Across five regions.

In addition, exploratory analyses were used on the raw scores to more fully understand the data and the relationships among the study variables and covariates.

CHAPTER 4: RESULTS

Introduction and Overview

This chapter explains the practical method of the research design that was used in this study to answer research questions. Descriptive statistics were used to describe the sample and to understand the study findings in terms of age, gender, ethnicity, SES, and BMI. All participants completed the study’s requirements including the TGMD-2 and AWMA instruments. They all were typically developing children with normal weight between 5th < BMI < 85th percentile

(Chung, 2015). Seven children (11.5%) were overweight but were included in this study as they were only a few pounds above the average.

Statistical analysis was conducted using SPSS.22 statistical software A Kolmogorov-

Smirnov Test (K-S Test) in SPSS was used prior to analyzing the data to check the normality of the distribution of the demographic and anthropometric data of the study sample. Independent t- tests were used to identify differences between boys and girls in all study variables. A one-way

ANOVA was used to identify the difference in the level of FMS (total FMS, locomotor skills, and object control skills) and verbal STM and visuospatial STM across five regions. A Chi-

Square Test was used to explore the association between two independent variables (2x2), FMS and WMC. The Cochran-Mantel-Haenszel Test was used to explore the associations between three groups (2x2x2) including the explanatory variable (FMS), the response variable (verbal

STM and visuospatial STM), and gender (Adejumo & Adetunji, 2013).

Further exploration of the data was conducted by using Pearson correlation coefficients

(r) to determine the correlation between FMS (total FMS, locomotor skills, and object control skills), and verbal STM and visuospatial STM, and the covariate variables included gender, BMI, regions, ethnicity, and mother’s and father’s education levels. Partial correlations were

conducted to examine the potential influence of the covariate variables (gender, BMI, ethnicity, regions, and mother’s and father’s education levels) on the study variables. Finally, different sets of a simple linear regression and a multiple linear regression were used to determine the relationship among the research variables (FMS, verbal STM and visuospatial STM, and covariate variables).

Physical Characteristics and Demographics

Table 1 presents the physical characteristics (age, height, weight, and BMI) of the study sample including the total sample, boys, and girls. The total number of participants was (61;

45.9%) of the sample was boys (n = 28) and 54.1% was girls (n=33). The results of the independent samples t-test showed no differences existed between boys and girls in terms of age, height, weight, and BMI. Boys and girls differed significantly in the BMI percentile t(59)=4.731, p=0.034, boys were higher (59.8 ± 25.38) than girls (48.88 ± 29.47). The majority of children in the total sample were a healthy weight. Only seven children (11.5%) were classified as overweight (BMI percentile ≥85-94.9), including 4 boys (14.3%) and 3 girls (9.1%).

Table 1:

Physical Characteristics of the Total Sample, Boys, and Girls

Boys Girls Total Physical Characteristics (N =28) (N =33) (N =61) Age (yrs) 9.8 ± 0.5 9.5 ± 0.68 9.6 ± 0.62 Height (cm) 138.7 ± 8.52 138.1 ± 7.55 138.38 ± 7.95 Weight (kg) 33.33 ± 4.9 32.26 ± 5.29 32.75 ± 5.1 Percent overweight 4 (14.3 %) 3 (9.1 %) 7 (11.5%) BMI (kg/m2) 17.27 ± 1.56 16.74 ± 1.79 16.95 ± 1.72 BMI percentilea 59.8 ± 25.38 48.88 ± 29.47 53.91 ± 28.19 aSignificant differences existed between boys and girls, t(59) = 4.731, p = 0.034

Table 2 presents the demographic characteristics (ethnicity, parents’ education level, and region) of the study sample including the data for the total sample, boys, and girls. The distribution of children by ethnicity for the total sample was Caucasian (n=20; 32.8%), Hispanic

(n=16; 26.2%), 1others (n=10; 16.4%), Asian (n=8; 13.1%), and Africa-American (n=7; 11.5%).

The distribution of ethnicity for boys was, respectively, Caucasian (n=10; 35.7%), Hispanic

(n=7; 25%), others (n=5; 7.5%), Asian (n=3; 10.7%), and Africa-American (n=3; 10.7%). For girls, the ethnic distribution was Caucasian n= 10 (30.3%), Hispanic (n=9; 27.3%), others (n=5;

15.2%), Asian (n=5; 15.2%), and Africa-American (n=4; 12.1%).

The level of parents’ education varied among children’s mothers and fathers. The results of descriptive statistics showed that the educational level for the postgraduate degree was higher for mothers than fathers. The education level for bachelor’s degree, associate’s degree, some college, and high school was higher for fathers than mothers. The distribution of the children’s mothers’ education level for the total sample was postgraduate degree (n=25; 41%), bachelor’s degree (n=10; 16.4%), GED (n=9; 14.7%), high school (n=7; 11.5%), some college (n=6; 9.8%), and associate’s degree (n=4; 6.6%). The distribution of the mothers’ education level for boys was postgraduate degree (n=10; 35.7%), bachelor’s degree (n=5; 17.9%), high school (n=5; 17.9%), some college (n=3; 10.7%), GED (n=3; 10.7%), and associate’s degree (n=2; 7.1%). For girls, the distribution of the mothers’ education level was postgraduate degree (n=15; 45.5 %), GED

(n=6; 18.1%), bachelor’s degree (n=5; 15.1%), some college (n =3; 9.1%), associate’s degree

(n=2; 6.1%), and high school (n=2; 6.1%).

The total sample of the children’s father’s education level was postgraduate degree

(n=19; 31.1%), bachelor’s degree (n=13; 21.3%), some college (n=10; 16.4%), high school (n=9;

1 Others represent participants born in the USA and their parents’ background from Iraq.

14.%), associate’s degree (n=6; 9.8%), and GED (n=4; 6.6 %). Father’s educational level for boys was postgraduate degree (n=6; 21.4%), bachelor’s degree (n=6; 21.4%), some college (n=6;

21.4%), high school (n=5; 17.9%), associate’s degree (n= 3; 10.7%), and GED (n=2; 7.2%). For girls, father’s educational level was postgraduate degree (n=13; 39.4 %), bachelor’s degree (n=7;

21.2%), some college (n=4; 12.1%), high school (n=4; 12.1%), associate’s degree (n=3; 9.1%), and GED (n=2; 6.1%).

Children were recruited from five different regions in Michigan (see Appendix H). The total sample was, respectively, regions 1 (n=20; 32.8%), region 2 (n=15; 24.6%), region 3 (n=13;

21.3%), region 4 (n=6; 9.8%), and region 5 (n= 7; 11.5%). The boys were respectively from regions 1 (n= 10; 35.7%), region 2 (n=7; 25.0%), region 3(n=4; 14.3%), region 5 (n=4; 14.3%) and region 4 (n=3; 10.7%). The girls were, respectively, region 1 (n=10; 30.3%), region 3 (n=9;

27.3%), region 2 (n=8; 24.2%), region 4 (n=3; 9.1%) and region 5 (n=3; 9.1%).

Parents in region 1 have higher educational levels than those in the other four regions, with a significantly higher percentage having completed postgraduate degrees. In addition, children in region 1 have access to numerous school and community enriching skill instructional environments. Region 5 is considered a poorer area with low levels of parental education. Many schools in region 5 have been closed due to lack of funding (see Table 2 and Table 3).

Table 2:

Demographic Characteristics of the Total Sample, Boys, and Girls

Demographic Characteristics Boys Girls Total (N =28) (N =33) (N =61) Ethnicity Africa-American 3 (10.7%) 4 (12.1%) 7 (11.5%) Asian 3 (10.7%) 5 (15.2%) 8 (13.1%) Caucasian 10 (35.7%) 10 (30.3%) 20 (32.8%) Hispanic 7 (25%) 9 (27.3%) 16 (26.2%) Others 5 (7.5%) 5 (15.2%) 10 (16.4%) Parents Education Mother GED 3 (10.7%) 6 (18.1%) 9 (14.7%) High school diploma 5 (17.9%) 2 (6.1%) 7 (11.5%) Some College 3 (10.7%) 3 (9.1%) 6 (9.8%) Associate’s Degree 2 (7.1%) 2 (6.1%) 4 (6.6%) Bachelor’s Degree 5 (17.9%) 5 (15.1%) 10 (16.4%) Postgraduate Degree 10 (35.7%) 15 (45.5 %) 25 (41.0%) Father GED 2 (7.2%) 2 (6.1%) 4 (6.6 %) High school diploma 5 (17.9%) 4 (12.1%) 9 (14.8%) Some College 6 (21.4%) 4 (12.1%) 10 (16.4%) Associate’s Degree 3 (10.7%) 3 (9.1%) 6 (9.8%) Bachelor’s Degree 6 (21.4%) 7 (21.2%) 13 (21.3%) Postgraduate Degree 6 (21.4%) 13 (39.4 %) 19 (31.1%) Regions Region 1 10 (35.7%) 10 (30.3%) 20 (32.8%) Region 2 7 (25.0%) 8 (24.2%) 15 (24.6%) Region 3 4 (14.3%) 9 (27.3%) 13 (21.3%) Region 4 3 (10.7%) 3 (9.1%) 6 (9.8%) Region 5 4 (14.3%) 3 (9.1%) 7 (11.5%)

Table 3 presents mother’s and father’s educational level across regions for the study sample. A higher percentage of the mother’s educational level was in the postgraduate degree and in the region 1 (n = 12, 65%) compared with other regions: region 2 (n = 9; 60%), region 3

(n = 3; 23.1%), region 4 (n =0; 0.0%), and region 5 (n = 0; 0.0%). Pearson's chi-square test revealed statistical differences in the mother’s educational level between regions, 2 (20) =

31.897, p = 0.044. For father’s educational level, a higher percentage of father’s educational

level was in the postgraduate degree and in the region 1 (n = 12; 60%) compared with other regions: region 2 (n = 5; 33.3%), region 3 (n = 2; 15.4%), region 4 (n = 0; 0.0%), and regions 5

(n = 0; 0.0%). Pearson's Chi-square test revealed that there is no evidence of statistical differences in the father’s educational level between regions, 2 (20) = 25.817, p = 0.172.

Table 3:

Mother's and Father's Educational Levels Across Regions

Mother’s Educational Level GED HS SC AD BD PGD Total R 1 MEL Count 0 1 2 1 3 13 20 % within R 0.0% 5% 10% 5% 15% 65% 100% R 2 MEL Count 2 1 0 0 3 9 15 % within R 13.3% 6.7% 0.0% 0.0% 20% 60% 100% R 3 MEL Count 3 3 0 1 3 3 13 % within R 23.1% 23.1% 0.0% 7.7% 23.1% 23.1% 100% R 4 MEL Count 2 1 2 1 0 0 6 % within R 33.3% 16.7% 33.3% 16.7% 0.0% 0.0% 100% R 5 MEL Count 2 1 2 1 1 0 7 % within R 28.6% 14.3% 28.6% 14.3% 14.3% 0.0% 100% Total MEL Count 9 7 6 4 10 25 61 % within R 14.8% 11.5% 9.8% 6.6% 16.4% 41% 100% Father’s Educational Level R 1 FEL Count 0 1 4 2 1 12 20 % within R 0.0% 5% 20% 10% 5% 60% 100% R 2 FEL Count 1 2 2 0 5 5 20 % within R 6.7% 13.3% 13.3% 0.0% 33.3% 33.3% 100% R 3 FEL Count 1 3 2 1 4 2 13 % within R 7.7% 23.1% 15.4% 7.7% 30.8% 15.4% 100% R 4 MEL Count 1 1 1 2 1 0 6 % within R 16.7% 16.7% 16.7% 33.3% 16.7% 0.0% 100% R 5 FEL Count 1 2 1 1 2 0 7 % within R 14.3% 28.6% 14.3% 14.3% 28.6% 0.0% 100% Total FEL Count 4 9 10 6 13 19 61 % within R 6.6% 14.8% 16.4% 9.8% 21.3% 31.1% 100% Note: Region (R), high school (HS), some college (SC), associate’s degree (AD), bachelor’s degree (BD), and post graduate degree (PGD)

Figure 5: Description of the Mother's and Father's Educational Levels Across Regions

Fundamental Motor Skills Performance

Table 4 contains the means of the total raw skill scores of FMS level (total FMS, locomotor skills, and object control skills) for the study sample including total sample, boys, and girls plus the maximum scores, provided in the TGMD-2 norms (Ulrich, 2000). In general, boys and girls scored higher in object control skills (43.39± 3.77) than locomotor skills (39.88 ±

4.93). An independent samples t-test revealed that there were significant differences between study groups (see Table 3); boys scored higher in total FMS (86.32± 6.35) and object control skills (45.14± 3.22) than girls, total FMS (81.30± 7.66) and object control skills (41.91± 3.59).

Table 4:

Description of TGMD-2 Raw Scores of the Total Sample, Boys, and Girls

Boys Girls Total Maximum Description of TGMD-2 (N =28) (N =33) (N =61) Raw Score Object Control Skillsa 45.14± 3.22 41.91± 3.59 43.39± 3.77 48

Locomotor Skills 40.92± 4.81 39.00± 4.94 39.88 ± 4.93 48

Total FMSb 86.32± 6.35 81.30± 7.66 83.60 ± 7.47 96 Notes: aSignificant differences existed between boys and girls, t(59) = 0.773, p = 0.001 bSignificant differences existed between boys and girls, t(59) = 2.145, p = 0.008

Table 5 presents the level of FMS performance within six levels (superior, above average, average level, below average, poor, and very poor). The data are presented for the three categories of skills, and for each group of the study. These levels were based on the normative data provided in the TGMD-2 Examiner’s Manual (Ulrich, 2000).

As shown in (Table 4 and Figure 6), the majority of the sample was in the average level of FMS development including; total FMS (n=36; 59%); locomotor skills (n=35; 57.4%); and object control skills (n=37; 60.7%). The majority of the sample for boys was in an average level of FMS: total FMS (n=18; 64.3%); locomotor skills (n=18; 64.3%); and object control skills

(n=15; 53.6%). For girls, the majority of the sample was also in the average level of FMS: total

FMS (n=18; 54.5%); locomotor skills (n=17; 51.5%); and object control skills (n=22; 66.6%).

Pearson's chi-square test revealed no statistical differences between groups for locomotor skills, 2 (4) = 2.857, p = 0.582, object control skills, 2 (4) = 6.443, p = 0.168, and total FMS,

2 (4) = 2.221, p = 0. 695.

Table 5:

Description of FMS Level Results by the Six Levels of TGMD-2 Performance of the Total

Sample, Boys, and Girls

Six Levels of FMS Performance Above Below Superior Average Poor Very Poor Average Average N (%) N (%) N (%) N (%) N (%) N (%) Total Sample (61) 3 14 37 5 2 Object Control Skills (4.9%) (23%) (60.7%) (8.2%) (3.3%) 1 35 15 7 3 Locomotor Skills (1.6%) (57.4%) (24.6%) (11.5%) (4.9%) 7 36 11 5 2 Total FMS (11.5%) (59%) (18%) (8.2%) (3.3%) Boys (28) 8 15 3 2 Object Control Skills (28.6%) (53.6%) (10.7%) (7.1%) 1 18 6 2 1 Locomotor Skills (3.6%) (64.3%) (21.4%) (7.1%) (3.6%) 4 18 3 2 1 Total FMS (14.3%) (64.3%) (10.7%) (7.1%) (3.6%) Girls (33) 3 6 22 2 Object Control Skills (9.1%) (18.2%) (66.6%) (6.1%) 17 9 5 2 Locomotor Skills (51.5%) (27.3%) (15.1%) (6.1%) 3 18 8 3 1 Total FMS (9.1%) (54.5%) (24.2%) (9.1%) (3%)

Figure 6: A Relationship Between Six Levels of Total FMS, Locomotor Skills, and Object Control Skills by Gender

Table 6 presents the level of FMS performance collapsed within two levels: level 1 was composed of the superior, above average, and average level (level 1 ≥90); and level 2 included below average, poor, and very poor (level2 ≤89). The data are presented for total FMS, locomotor skills, and object control skills, and for each group of the study sample including total sample, boys, and girls. These levels were based on the normative data, which were indicated in the TGMD-2 Examiner’s Manual (Ulrich, 2000).

As shown in Table 6 and Figure 7, the majority of the total sample was in level 1; total

FMS (n=43; 70.5%); locomotor skills (n= 36; 59%); and object control skills (n=54; 88.5%). The same level, a higher percentage of children were in object control skills (2=54; 88.5%) compared with locomotor skills (n=36; 59%). The majority of the sample for boys was in level 1 and in object control skills (n=23; 82.1%). For girls, the majority of the sample was in level 1 and in object control skills (n=31; 93.9%). Pearson's chi-square test revealed no statistical differences between groups for locomotor skills, 2 (1) = 1.673, p = 0.196, object control skills, 2 (1) =

2.075, p = 0.150, and total FMS, 2 (1) = 1.624, p = 0. 202.

Table 6:

Description of FMS Level Results by the Two Levels of TGMD-2 Performance of the Total

Sample, Boys, and Girls

Two Levels of FMS Performance Level 1 Level 2 N (%) N (%) Total Sample (61) Object Control Skills 54 (88.5%) 7 (11.5%) Locomotor Skills 36 (59%) 25 (41%) Total FMS 43 (70.5%) 18 (29.5%) Boys (28) Object Control Skills 23 (82.1%) 5 (17.9%) Locomotor Skills 19 (67.9%) 9 (32.1%) Total FMS 22 (78.6%) 6 (21.4%) Girls (33) Object Control Skills 31 (93.9%) 2 (6.1%) Locomotor Skills 17 (51.5%) 16 (48.5%) Total FMS 21 (63.6%) 12 (36.4%)

Figure 7: A Relationship Between Two Levels of Total FMS, Locomotor Skills, and Object Control Skills by Gender

Verbal STM and Visuospatial STM Capacity Level

Table 6 contains the means of the total raw scores of verbal STM and visuospatial STM for the study sample. The raw scores were indicated in the AWMA norms (AWMA; Alloway,

2007) within three levels including (above average ≥ 120, average ≥ 85, and below average ≤ 80) for each WMC components (verbal STM and visuospatial STM) and subcomponents; verbal

STM consisted of three subtests included digit recall, word recall, and nonword recall; and visuospatial STM consisted of three subtests included dot matrix, mazes memory, and block recall (see Table 7). An independent samples t-test revealed no significant differences between study groups (boys and girls) in any of the storage components of the WMC and subcomponents.

Table 7:

Description of AWMA Standard Scores (Test and Subtests) of the Total Sample, Boys, and Girls

Boys Girls Total Description of AWMA (N =28) (N =33) (N =61) Verbal STM 108.04±14.16 110.611±14.72 109.43± 14.41

Digit recall 108.53±17.34 110.21±16.03 109.43± 16.53

Word recall 107.21±11.72 109.39±12.59 108.39± 12.15

Non-word recall 111.49±19.13 111.58±20.99 111.54± 19.99

Visuospatial STM 116.07±12.94 116.82±11.38 116.48± 12.01

Dot matrix 116.06±14.50 115.05±12.93 115.52± 13.57

Mazes memory 114.89±11.59 117.79±12.32 116.46± 11.98 Block recall 113.32±12.98 112.73±11.36 113.00± 12.03

Table 8 presents verbal STM and visuospatial STM levels within three levels including

(above average ≥ 120, average ≥ 85, and below average ≤ 80). However, the verbal STM and visuospatial STM levels for the study sample represented only two levels (above average and average level). The majority of the total sample (see Figure 8) was in an average level of verbal

STM (n=43; 70.5%). They were also in the average level of visuospatial STM (n=33; 54.1%).

Pearson's chi-square test revealed no statistical differences between boys and girls in the verbal

STM, 2 (1) = 0.022, p = 0.883, and in the visuospatial STM, 2 (1) = 0.350, p = 0.554.

Table 8:

Description of Verbal STM and Visuospatial STM by the Two Levels of AWMA Performance of the Total Sample, Boys, and Girls

Study Sample Level of verbal STM Girls Boys Total Sample and visuospatial STM N=33 N=28 N=61 Verbal STM Above average 10 (30.3%) 8 (28.6%) 18 (29.5%) Average 23 (69.7%) 20 (71.4) 43 (70.5%) Below average ------Visuospatial STM Above average 14 (42.4%) 14 (50%) 28 (45.9%) Average 19 (57.6%) 14 (50%) 33 (54.1%) Below average ------

Figure 8: A Relationship Between Two Levels of Verbal STM and Visuosptial STM and Gender

Fundamental Motor Skills Performance Across Five Regions

Table 9 contains the means of FMS level (total FMS, locomotor skills, and object control skills) for the study sample across five regions (see Figure 9). In general, the higher scores in the total FMS was in the region 2 (86.93±4.38) compared with other regions (1, 3, 4, and 5). For the locomotor skills level, the higher scores were in the region 1 (42.45±4.03) compared with other regions (2, 3, 4, and 5). The level of the object control skills was higher in the region 2

(45.00±3.09) compared with other regions (1, 3, 4, and 5). One-way ANOVA test revealed that there were significant differences in the level of total FMS, F(4) = 2.904, p = .030 and locomotor skills, F(4) = 6.191, p = .000 across regions.

Table 9:

Description of FMS (Total FMS, Locomotor Skills, and Object Control Skills) Across Five

Regions

Regions N. Object Control Skills bLocomotor Skills aTotal FMS Region 1 20 43.05±3.10 42.45±4.03 85.50±6.41 Region 2 15 45.00±3.09 41.73 ±2.84 86.93±4.38 Region 3 13 43.15±4.12 35.84±4.05 79.15±6.70 Region 4 6 42.00±4.33 37.83±5.34 82.33±9.52 Region 5 7 42.57±5.47 37.85±6.49 80.42±11.05 Notes: aSignificant differences existed in the level of total FMS across regions, F(4) = 2.904, p = .030. bSignificant differences existed in the level of locomotor skills across regions, (F(4) = 6.191, p = .000

Figure 9: The Level of FMS (Total FMS, Locomotor Skills, and Object Control Skills) and Verbal STM and Visuospatial STM Across

Five Regions

Verbal STM and Visuospatial STM Performance Across Five Regions

Table 10 contains the means of the total raw scores of verbal STM and visuospatial STM for the study sample across five regions (see Figure 10). In general, the higher scores in the verbal STM were in the region 3 (115.38±15.06) compared with other regions (1, 2, 4, and 5).

For the visuospatial STM, the higher scores were in the region 2 (120.66±11.47) and regions 5

(120.00±13.22) compared with other regions (1, 3, and 4). One-way ANOVA test revealed that there was no significant differences in the level of verbal STM, F(4) = 2.145, p= .087 and visuospatial STM, F(4)= 1.922, p = .120 across regions.

Table 10:

Description of Verbal STM and Visuospatial STM Across Five Regions

Regions Verbal STM Visuospatial STM

Region 1 105.50±12.34 110.75±12.38 Region 2 114.66±15.75 120.66±11.47 Region 3 115.38±15.06 117.69±10.72 Region 4 102.50±9.35 118.33±9.30 Region 5 104.28±14.55 120.00±13.22

Figure 10: The Level of Verbal STM and Visuospatial STM Across Five Regions

The Relationship Between FMS and Verbal STM and Visuospatial STM

The first research aim was to examine the relationship between the level of FMS (total

FMS, locomotor skills, and object control skills) and the level of verbal STM, and visuospatial

STM. Pearson's chi-square test was used to determine this relationship in order to answer the first research hypothesis (Children, who have higher levels of FMS (total FMS, locomotor skills, and object control skills), will show better verbal STM, and visuospatial STM compared to children who have lower levels of FMS). The results of the Pearson's chi-square test are presented in Tables 11 through 16. Two levels of FMS; level 1 (superior, above average and average); and level 2 (below average, poor, and very poor) were compared with two levels of verbal STM and visuospatial STM (above average and average).

Table 11 presents the relationship between total FMS and verbal STM (see also Figure

11). The majority of children (n=48; 78.7%), were in level 1 of FMS and between above average and average level in their verbal STM capacity compared with children in level 2 (n=13; 21.3%).

The percentage of children in level 1 of the FMS was higher in the average level of verbal STM

(n=32; 66.7%) than above average (n=16; 33.3%). The results of Pearson's chi-square test

showed that there is no strong evidence of a relationship between total FMS and verbal STM,

2(1) = 1.584, p = 0.208. This result did not support the first research hypothesis in terms of the relationship between total FMS and verbal STM.

Table 11:

Description of the Chi-Square Test of the Relationship Between Total FMS and Verbal STM

(VSTM)

FMS levels Verbal STM Above Average Average Total Total FMS Level 1 N. 16 32 48 % within FMS levels 33.3% 66.7% 100.0% % within VSTM 88.9% 74.4% 78.7% % of total 26.2% 52.5% 78.7% Level 2 N. 2 11 13 % within FMS levels 15.4% 84.6% 100.0% % within VSTM 11.1% 25.6% 21.3% % of total 3.3% 18.0% 21.3% Total N. 18 43 61 % within FMS levels 29.5% 70.5% 100.0% % within VSTM 100.0% 100.0% 100.0% % of total 29.5% 70.5% 100.0%

Figure 11: A Relationship Between Total FMS and Verbal STM

Table 12 presents the relationship between locomotor skills and verbal STM (see also

Figure 12). The percentage of children in the above average and average level of verbal STM is roughly higher for children in level 1 of locomotor skills (n=36; 59%), than children in level 2

(n=25; 41.0%). The percent of children in the average level of verbal STM (n=25; 69.4%) is higher than children in the above average level (n=11; 30.6%), for children in level 1 of locomotor skills. The results of Pearson's chi-square test showed that there is no strong evidence of a relationship between locomotor skills and verbal STM, 2 (1) = 0.46, p = 0.830. This result did not support the first research hypothesis in terms of the relationship between locomotor skills and verbal STM.

Table 12:

Description of the Chi-Square Test of the Relationship Between Locomotor Skills (LOS) and

Verbal STM (VSTM)

Locomotor Skills Verbal STM Levels Above Average Average Total Locomotor Level 1 N. 11 25 36 Skills % within LOS levels 30.6% 69.4% 100.0% % within VSTM 61.1% 58.1% 59.0% % of total 18.0% 41.0% 59.0% Level 2 N. 7 18 25 % within LOS levels 28.0% 72.0% 100.0% % within VSTM 38.9% 41.9% 41.0% % of total 11.5% 29.5% 41.0% Total N. 18 43 61 % within LOS levels 29.5% 70.5% 100.0% % within VSTM 100.0% 100.0% 100.0% % of total 29.5% 70.5% 100.0%

Figure 12: A Relationship Between Locomotor Skills and Verbal STM

Table 13 presents the relationship between object control skills and verbal STM (see also

Figure 13). The percent of children in the above average and average level of verbal STM is higher for children in level 1 of object control skills (n=54; 88.5%), than children in level 2,

(n=7; 11.5%). The percent of children in the average level of verbal STM (n=38; 70.4%) is higher than children in the above average level, (n=16; 29.6%), for children in level 1 of object control skills. The results of Pearson's chi-square test showed that there is no strong evidence of a relationship between object control skills and verbal STM, 2 (1) = 0.03, p = 0.954. This result did not support the first research hypothesis in terms of the relationship between object control skills and verbal STM.

Table 13:

Description of the Chi-Square Test of the Relationship Between Object Control Skills (OCS) and

Verbal STM (VSTM)

Object Control Skills Verbal STM Levels Above Average Average Total Object Level 1 N. 16 38 54 Control % within OCS levels 29.6% 70.4% 100.0% Skills % within VSTM 88.9% 88.4% 88.5% % of total 26.2% 62.3% 88.5% Level 2 N. 2 5 7 % within OCS levels 28.6% 71.4% 100.0% % within VSTM 11.1% 11.6% 11.5% % of total 3.3% 8.2% 11.5% Total N. 18 43 61 % within OCS levels 29.5% 70.5% 100.0% % within VSTM 100.0% 100.0% 100.0% % of total 29.5% 70.5% 100.0%

Figure 13: A Relationship Between Object Control Skills and Verbal STM

Table 14 presents the relationship between total FMS skills and visuospatial STM (see also Figure 14). The percent of children in the above average and average levels of visuospatial

STM is higher for children in level 1 of total FMS skills (n=48; 78.7%), than children in level 2,

(n=13; 21.3%). In level 1 of FMS, there were an equal percent of children (n=24; 50.0%) at each

verbal STM category. The results of Pearson's chi-square test showed that there is no strong evidence of a relationship between total FMS skills and visuospatial STM, 2 (1) = 1.523, p=

0.217. This result did not support the first research hypothesis in terms of the relationship between total FMS skills and visuospatial STM.

Table 14:

Description of the Chi-Square of the Relationship Between Total FMS and Visuospatial STM

(VSSTM)

Total FMS Skills Visuospatial STM Levels Above Average Average Total Total FMS Level 1 N. 24 24 48 % within FMS levels 50.0% 50.0% 100.0% % within VSSTM 85.7% 72.7% 78.7% % of total 39.3% 39.3% 78.7% Level 2 N. 4 9 13 % within FMS levels 30.8% 69.2% 100.0% % within VSSTM 14.3% 27.3% 21.3% % of total 6.6% 14.8% 21.3% Total N. 28 33 61 % within FMS levels 45.9% 54.1% 100.0% % within VSSTM 100.0% 100.0% 100.0% % of total 45.9% 54.1% 100.0%

Figure 14: A Relationship Between Total FMS and Visuospatial STM

Table 15 presents the relationship between locomotor skills and visuospatial STM (see also Figure 15). The percent of children in the above average and average level of visuospatial

STM is higher for children in level 1 of locomotor skills (n=36; 59%), than children in level 2,

(n=25; 41.0%). Within locomotor skills level 1, the percent of children in the average level of visuospatial STM (n=19; 52.8%) is higher than children in the above average (n=17; 47.2%).

The results of Pearson's chi-square test showed that there is no strong evidence of a relationship between locomotor skills and visuospatial STM, 2 (1) = 0.62, p = 0.804. This result did not support the first research hypothesis in terms of the relationship between locomotor skills and visuospatial STM.

Table 15:

Description of the Chi-Square of the Relationship Between Locomotor Skills (LOS) and

Visuospatial STM (VSSTM)

Locomotor Skills Visuospatial STM Levels Above Average Average Total Locomotor Level 1 N. 17 19 36 Skills % within LOS levels 47.2% 52.8% 100.0% % within VSSTM 60.7% 57.6% 59.0% % of total 27.9% 31.1% 59.0% Level 2 N. 11 14 25 % within LOS levels 44.0% 56.0% 100.0% % within VSSTM 39.3% 42.4% 41.0% % of total 18.0% 23.0% 41.0% Total N. 28 33 61 % within LOS levels 45.9% 54.1% 100.0% % within VSSTM 100.0% 100.0% 100.0% % of total 45.9% 54.1% 100.0%

Figure 15: A Relationship Between Locomotor Skills and Visuospatial STM

Table 16 presents the relationship between object control skills and visuospatial STM

(see also Figure 16). The percent of children in the above average and average level of verbal

STM is higher for children in level 1 of object control skills (n=54; 88.5%), than children in level

2, (n=711.5%). The percent of children in the average level of visuospatial STM (n=30; 55.6%) is higher than children in the above average level (n=24; 44.4%) for children in level 1 of object control skills. The results of Pearson's chi-square test showed that there is no strong evidence of a relationship between object control skills and visuospatial STM, 2 (1) = 0.402, p=0.526. This result did not support the first research hypothesis in terms of the relationship between object control skills and visuospatial STM.

Table 16:

Description of the Chi-Square Test of the Relationship Between Object Control Skills (OCS) and

Visuospatial STM (VSSTM)

Object Control Skills Visuospatial STM Levels Above Average Average Total Object Level 1 N. 24 30 54 Control % within OCS levels 44.4% 55.6% 100.0% Skills % within VSSTM 85.7% 90.9% 88.5% % of total 39.3% 49.2% 88.5% Level 2 N. 4 3 7 % within OCS levels 57.1% 42.9% 100.0% % within VSSTM 14.3% 9.1% 11.5% % of total 6.6% 4.9% 11.5% Total N. 28 33 61 % within OCS levels 45.9% 54.1% 100.0% % within VSSTM 100.0% 100.0% 100.0% % of total 45.9% 54.1% 100.0%

Figure 16: A Relationship Between Object Control Skills and Visuospatial STM

The Relationship Between FMS and Verbal STM and Visuospatial STM and Gender

The second aim of this research study was to examine gender differences within the study variables (total FMS, locomotor skills, object control skills, verbal STM, and visuospatial STM).

The Cochran-Mantel-Haenszel Test was used to determine this relationship in order to answer the second research hypothesis (Boys will have better verbal STM, and visuospatial STM compared to girls in all levels of FMS). The results of the Cochran-Mantel-Haenszel Test are presented in Tables 17 through 22. Two levels of FMS, level 1 (superior, above average and average) and level 2 (below average, poor, and very poor), were compared with two levels of verbal STM and visuospatial STM (above average and average).

Table 17 presents the relationship between boys and girls, total FMS, and verbal STM

(see also Figure 17). A higher percentage of boys (n=22; 78.6%) was in level 1 of FMS and in the above average and average level of verbal STM capacity compared with boys in level 2 (n=6;

21.4%). A higher percentage of girls (n=21; 63.6%), were in level 1 of FMS and in the above

average and average level of verbal STM capacity compared with girls in level 2 (n=12; 36.4%).

The results of the Cochran-Mantel-Haenszel Test showed that there is no strong evidence of a relationship between total FMS and verbal STM across gender, 2 MH (1)= 2.146, p = 0.143. This result did not support the second research hypothesis in terms of the relationship between total

FMS and verbal STM across gender.

Table 17:

Description of the Cochran-Mantel-Haenszel Test of the Relationship Between Total FMS, and

Verbal STM (VSTM) Control by Gender

Total FMS Verbal STM levels Above Average Average Total Boys Total Level 1 N. 6 16 22 FMS % within FMS levels 27.3% 72.7% 100.0% % within VSTM 75.0% 80.0% 78.6% % of total 21.4% 57.1% 78.6% Level 2 N. 2 4 6 % within FMS levels 33.3% 66.7% 100.0% % within VSTM 25.0% 20.0% 21.4% % of total 7.1% 14.3% 21.4% Total N. 8 20 28 % within FMS levels 28.6% 71.4% 100.0% % within VSTM 100.0% 100.0% 100.0% % of total 28.6% 71.4% 100.0% Girls Total Level 1 N. 9 12 21 FMS % within FMS levels 33.3% 57.1% 100.0% % within VSTM 90.0% 52.2% 63.6% % of total 27.3% 36.4% 63.6% Level 2 N. 1 11 12 % within FMS levels 16.7% 91.7% 100.0% % within VSTM 10.0% 47.8% 36.4% % of total 3.0% 33.3% 36.4% Total N. 10 23 33 % within FMS levels 30.3% 69.7% 100.0% % within VSTM 100.0% 100.0% 100.0% % of total 30.3% 69.7% 100.0% Total Total Level 1 N. 15 28 43 FMS % within FMS levels 34.9% 65.1% 100.0% % within VSTM 83.3% 65.1% 70.5% % of total 24.6% 45.9% 70.5% Level 2 N. 3 15 18 % within FMS levels 16.7% 83.3% 100.0% % within VSTM 16.7% 34.9% 29.5% % of total 4.9% 24.6% 29.5% Total N. 18 43 61 % within FMS levels 29.5% 70.5% 100.0% % within VSTM 100.0% 100.0% 100.0% % of total 29.5% 70.5% 100.0%

Figure 17: A Relationship Between Total FMS and Verbal STM Control by Gender

Table 18 presents the relationship between boys and girls, locomotor skills, and verbal

STM (see also Figure 18). A higher percentage of boys (n=19; 67.9%), was in level 1 of locomotor skills and in the above average and average level of verbal STM capacity compared with boys in level 2 (n=9; 32.1%). A slightly higher percentage of girls (n=17; 51.5%) was in level 1 of locomotor skills and in the above average and average level of verbal STM capacity compared with girls in level 2 (n=16; 48.5%). The results of the Cochran-Mantel-Haenszel Test showed that there is no strong evidence of a relationship between locomotor skills and verbal

STM across gender, 2 MH (1) = 0.113, p=0.737. This result did not support the second research hypothesis in terms of the relationship between locomotor skills and verbal STM across gender.

Table 18:

Description of the Cochran-Mantel-Haenszel Test of the Relationship Between Locomotor Skills

(LOS) ad Verbal STM (VSTM) Control by Gender

Locomotor Skills Verbal STM Levels Above Average Average Total Boys Locomotor Level 1 N. 4 15 19 Skills % within LOS levels 21.1% 78.9% 100.0% % within VSTM 50.0% 75.0% 67.9% % of total 14.3% 53.6% 67.9% Level 2 N. 4 5 9 % within LOS levels 44.4% 55.6% 100.0% % within VSTM 50.0% 25.0% 32.1% % of total 14.3% 17.9% 32.1% Total N. 8 20 28 % within LOS levels 28.6% 71.4% 100.0% % within VSTM 100.0% 100.0% 100.0% % of total 28.6% 71.4% 100.0% Girls Locomotor Level 1 N. 6 11 17 Skills % within LOS levels 35.3% 64.7% 100.0% % within VSTM 60.0% 47.8% 51.5% % of total 18.2% 33.3% 51.5% Level 2 N. 4 12 16 % within LOS levels 25.0% 75.0% 100.0% % within VSTM 40.0% 52.2% 48.5% % of total 12.1% 36.4% 48.5% Total N. 10 23 33 % within LOS levels 30.3% 69.7% 100.0% % within VSTM 100.0% 100.0% 100.0% % of total 30.3% 69.7% 100.0% Total Locomotor Level 1 N. 10 26 36 Skills % within LOS levels 27.8% 72.2% 100.0% % within VSTM 55.6% 60.5% 59.0% % of total 16.4% 42.6% 59.0% Level 2 N. 8 17 25 % within LOS levels 32.0% 68.0% 100.0% % within VSTM 44.4% 39.5% 41.0% % of total 13.1% 27.9% 41.0% Total N. 18 43 61 % within LOS levels 29.5% 70.5% 100.0% % within VSTM 100.0% 100.0% 100.0% % of total 29.5% 70.5% 100.0%

Figure 18: A Relationship Between Locomotor Skills and Verbal STM Control by Gender

Table 19 presents the relationship between boys and girls, object control skills, and verbal STM (see also Figure 19). A higher percentage of boys (n=23; 82.1%), was in level 1 of object control skills and in the above average and average level of verbal STM capacity compared with boys in level 2 (n=5; 17.9%). The percentage of girls (n=31; 93.9%) was considerably higher in level 1 of object control skills and in the above average and average level of verbal STM capacity compared with girls in level 2 (n=2; 6.1%). The results of the Cochran-

Mantel-Haenszel Test showed that there is no strong evidence of a relationship between object control skills and verbal STM across gender, 2MH (1) = 0.615, p=0.433. This result did not support the second research hypothesis in terms of the relationship between object control skills and verbal STM across gender

Table 19:

Description of the Cochran-Mantel-Haenszel Test of the Relationship Between Object Control

Skills (OCS) and Verbal STM (VSTM) Control by Gender

Object Control Skills Verbal STM Levels Above Average Average Total Boys Object Level 1 N. 7 16 23 control % within OCS levels 30.4% 69.6% 100.0% skills % within VSTM 87.5% 80.0% 82.1% % of total 25.0% 57.1% 82.1% Level 2 N. 1 4 5 % within OCS levels 20.0% 80.0% 100.0% % within VSTM 12.5% 20.0% 17.9% % of total 3.6% 14.3% 17.9% Total N. 8 20 28 % within OCS levels 28.6% 71.4% 100.0% % within VSTM 100.0% 100.0% 100.0% % of total 28.6% 71.4% 100.0% Girls Object Level 1 N. 9 22 31 control % within OCS levels 29.0% 71.0% 100.0% skills % within VSTM 90.0% 95.7% 93.9% % of total 27.3% 66.7% 93.9% Level 2 N. 1 1 2 % within OCS levels 50.0% 50.0% 100.0% % within VSTM 10.0% 4.3% 6.1% % of total 3.0% 3.0% 6.1% Total N. 10 23 33 % within OCS levels 30.3% 69.7% 100.0% % within VSTM 100.0% 100.0% 100.0% % of total 30.3% 69.7% 100.0% Total Object Level 1 N. 16 38 54 control % within OCS levels 29.6% 70.4% 100.0% skills % within VSTM 88.9% 88.4% 88.5% % of total 26.2% 62.3% 88.5% Level 2 N. 2 5 7 % within OCS levels 28.6% 71.4% 100.0% % within VSTM 11.1% 11.6% 11.5% % of total 3.3% 8.2% 11.5% Total N. 18 43 61 % within OC levels 29.5% 70.5% 100.0% % within VSTM 100.0% 100.0% 100.0% % of total 29.5% 70.5% 100.0%

Figure 19: A Relationship Between Object Control Skills and Verbal STM Control by Gender

Table 20 presents the relationship between the total FMS and visuospatial STM by gender (see also Figure 20). A higher percentage of boys (n=12; 42.9%) was in level 1 of FMS and in the above average level of visuospatial STM capacity compared with boys in level 2 (n=2;

7.1%). For girls, a higher percentage (n=11; 33.3%) was in level 1 of FMS and in the average level of the visuospatial STM capacity compared with girls in level 2 (n=8; 24.2%). The results of the Cochran-Mantel-Haenszel Test showed that there is no strong evidence of a relationship between total FMS and visuospatial STM across gender, 2MH (1) = 0.003, p=0.958. This result did not support the second research hypothesis in terms of the relationship between total FMS and visuospatial STM across gender.

Table 20:

Description of the Cochran-Mantel-Haenszel Test of the Relationship Between Total FMS and

Visuospatial STM (VSSTM) Control by Gender

Total FMS Visuospatial STM levels Above Average Average Total Boys Total Level 1 N. 10 12 22 FMS % within FMS levels 45.5% 54.5% 100.0% % within VSSTM 71.4% 85.7% 78.6% % of total 35.7% 42.9% 78.6% Level 2 N. 4 2 6 % within FMS levels 66.7% 33.3% 100.0% % within VSSTM 28.6% 14.3% 21.4% % of total 14.3% 7.1% 21.4% Total N. 14 14 28 % within FMS levels 50.0% 50.0% 100.0% % within VSSTM 100.0% 100.0% 100.0% % of total 50.0% 50.0% 100.0% Girls Total Level 1 N. 10 11 21 FMS % within FMS levels 47.6% 52.4% 100.0% % within VSSTM 71.4% 57.9% 63.6% % of total 30.3% 33.3% 63.6% Level 2 N. 4 8 12 % within FMS levels 33.3% 66.7% 100.0% % within VSSTM 28.6% 42.1% 36.4% % of total 12.1% 24.2% 36.4% Total N. 14 19 33 % within FMS levels 42.4% 57.6% 100.0% % within VSSTM 100.0% 100.0% 100.0% % of total 42.4% 57.6% 100.0% Total Total Level 1 N. 20 23 43 FMS % within FMS levels 46.5% 53.5% 100.0% % within VSSTM 71.4% 69.7% 70.5% % of total 32.8% 37.7% 70.5% Level 2 N. 8 10 18 % within FMS levels 44.4% 55.6% 100.0% % within VSSTM 28.6% 30.3% 29.5% % of total 13.1% 16.4% 29.5% Total N. 28 33 61 % within FMS levels 45.9% 54.1% 100.0% % within VSSTM 100.0% 100.0% 100.0% % of total 45.9% 54.1% 100.0%

Figure 20: A Relationship Between Total FMS and Visuospatial STM Control by Gender

Table 21 presents the relationship between locomotor skills and visuospatial STM by gender (see also Figure 21). A higher percentage of boys (n=19; 67.9%), was in level 1 of locomotor skills and in the above average and average level of visuospatial STM capacity compared with boys in level 2 (n=9; 32.1%). The percentage of girls in level 1 of the locomotor skills and in the above average and average level of visuospatial STM capacity (n=17; 51.5%) was slightly higher than girls in level 2 (n=16; 48.5%). The results of the Cochran-Mantel-

Haenszel Test showed that there is no strong evidence of a relationship between locomotor skills and visuospatial STM across gender, 2MH (1) = 0.023, p=0.878. This result did not support the second research hypothesis in terms of the relationship between locomotor skills and visuospatial

STM across gender.

Table 21:

Description of the Cochran-Mantel-Haenszel Test of the Relationship Between Locomotor Skills

(LOS) and Visuospatial STM (VSSTM) Control by Gender

Locomotor Skills Visuospatial STM Levels Above Average Average Total Boys Locomotor Level 1 N. 9 10 19 Skills % within LOS levels 47.4% 52.6% 100.0% % within VSSTM 64.3% 71.4% 67.9% % of total 32.1% 35.7% 67.9% Level 2 N. 5 4 9 % within LOS levels 55.6% 44.4% 100.0% % within VSSTM 35.7% 28.6% 32.1% % of total 17.9% 14.3% 32.1% Total N. 14 14 28 % within LOS levels 50.0% 50.0% 100.0% % within VSSTM 100.0% 100.0% 100.0% % of total 50.0% 50.0% 100.0% Girls Locomotor Level 1 N. 8 9 17 Skills % within LOS levels 47.1% 52.9% 100.0% % within VSSTM 57.1% 47.4% 51.5% % of total 24.2% 27.3% 51.5% Level 2 N. 6 10 16 % within LOS levels 37.5% 62.5% 100.0% % within VSSTM 42.9% 52.6% 48.5% % of total 18.2% 30.3% 48.5% Total N. 14 19 33 % within LOS levels 42.4% 57.6% 100.0% % within VSSTM 100.0% 100.0% 100.0% % of total 42.4% 57.6% 100.0% Total Locomotor Level 1 N. 17 19 36 Skills % within LOS levels 47.2% 52.8% 100.0% % within VSSTM 60.7% 57.6% 59.0% % of total 27.9% 31.1% 59.0% Level 2 N. 11 14 25 % within LOS levels 44.0% 56.0% 100.0% % within VSSTM 39.3% 42.4% 41.0% % of total 18.0% 23.0% 41.0% Total N. 28 33 61 % within LOS levels 45.9% 54.1% 100.0% % within VSSTM 100.0% 100.0% 100.0% % of total 45.9% 54.1% 100.0%

Figure 21: A Relationship Between Locomotor Skills and Visuospatial STM Control by Gender

Table 22 presents the relationship of object control skills and visuospatial STM for boys and girls (see also Figure 22). A higher percentage of boys (n=23; 82.1%), was in level 1 of object control skills and in the above average and average level of visuospatial STM capacity compared with boys in level 2 (n=5; 17.9%). likewise for girls, a higher percentage was in level

1 of object control skills and in the above average and average level of visuospatial STM capacity (n=31; 54.5%) compared with girls in level 2 (n=2; 6.1%). The results of the Cochran-

Mantel-Haenszel Test showed that there is no strong evidence of a relationship between object control skills and visuospatial STM across gender, 2MH (1) = 0.286, p=0.593. This result did not support the second research hypothesis in terms of the relationship between object control skills and visuospatial STM across gender.

Table 22:

Description of the Cochran-Mantel-Haenszel Test of the Relationship Between Object Control

Skills (OCS) and Visuospatial STM (VSSTM) Control by Gender

Object Control Skills Visuospatial STM Levels Above Average Average Total Boys Object Level 1 N. 11 12 23 control % within OC levels 47.8% 52.2% 100.0% skills % within VSSTM 78.6% 85.7% 82.1% % of total 39.3% 42.9% 82.1% Level 2 N. 3 2 5 % within OC levels 60.0% 40.0% 100.0% % within VSSTM 21.4% 14.3% 17.9% % of total 10.7% 7.1% 17.9% Total N. 14 14 28 % within OC levels 50.0% 50.0% 100.0% % within VSSTM 100.0% 100.0% 100.0% % of total 50.0% 50.0% 100.0% Girls Object Level 1 N. 13 18 31 control % within OC levels 41.9% 58.1% 100.0% skills % within VSSTM 92.9% 94.7% 93.9% % of total 39.4% 54.5% 93.9% Level 2 N. 1 1 2 % within OC levels 50.0% 50.0% 100.0% % within VSSTM 7.1% 5.3% 6.1% % of total 3.0% 3.0% 6.1% Total N. 14 19 33 % within OC levels 42.4% 57.6% 100.0% % within VSSTM 100.0% 100.0% 100.0% % of total 42.4% 57.6% 100.0% Total Object Level 1 N. 24 30 54 control % within OC levels 44.4% 55.6% 100.0% skills % within VSSTM 85.7% 90.9% 88.5% % of total 39.3% 49.2% 88.5% Level 2 N. 4 3 7 % within OC levels 57.1% 42.9% 100.0% % within VSSTM 14.3% 9.1% 11.5% % of total 6.6% 4.9% 11.5% Total N. 28 33 61 % within OC levels 45.9% 54.1% 100.0% % within VSSTM 100.0% 100.0% 100.0% % of total 45.9% 54.1% 100.0%

Figure 22: A Relationship Between Object Control Skills and Vosuospatial STM Control by

Gender

Exploratory analyses: FMS and Verbal STM and Visuospatial STM, Gender, and

Covariate Variables

The third goal of this research was to explore further the relationships between the research variables (FMS, verbal STM and visuospatial STM) based on the raw scores on each of these variables. Pearson correlation coefficients (r) and multiple linear regressions were used to determine the relationship among FMS, verbal STM and visuospatial STM. Pearson correlation coefficient (r) was used to determine the relationship between total FMS and verbal STM, locomotor skills and verbal STM, object control skills and verbal STM, total FMS and visuospatial STM, locomotor skills and visuospatial STM, and object control skills and visuospatial STM.

Six separate simple linear regressions were conducted to predict the relationship between

FMS (total FMS, locomotor skills, and object control skills) as independent variables, and verbal

STM and visuospatial STM as dependent variables. Total FMS, locomotor skills, and object control skills were used to predict verbal STM and visuospatial STM separately.

Another six separate multiple linear regressions were conducted using gender and all covariate variables to predict the relationship between FMS (total FMS, locomotor skills, and object control skills) as independent variables, and verbal STM and visuospatial STM) as dependent variables. Total FMS, locomotor skills, and object control skills were used to predict verbal STM and visuospatial STM separate. Gender (boys and girls), BMI, regions, ethnicity, and mother’s and father’s education levels were added to the model to predict verbal STM and visuospatial STM separately. The entry model was used to build the regression model by entering all the independent variables into the equation in one step. This model is considered appropriate analysis to deal with a small number of predictors and non-preferable variables

(Leech, Barrett, & Morgan, 2008). Statistical significance was set at p < .05. The assumptions of linearity, homoscedasticity, multicollinearity, residuals (errors), and outliers were checked before running the regression model. The independence of errors (lack of correlation) was certified by a

Durbin-Watson statistic (critical values of 1.5 < d < 2.5). The independence of errors to predict verbal STM were 2.111 (locomotor scores), 2.069 (object control scores), and 2.044 (total FMS).

The independence of errors to predict visuospatial STM was in locomotor scores (1.613), object control scores (1.560), and total FMS (1.561). The Variance Inflation Factor (VIF), which is the impact of collinearity for each independent variable, revealed no existence of multicollinearity between all independent variables. The critical values should be between (tolerance >0.1,VIF

<10). The VIF value to predict verbal STM and visuospatial STM was locomotor scores (.995 –

1.005), object control scores (.814 – 1.228), and total FMS (.898-1.114).

Variables, such as ethnicity, regions, and mother’s and father’s education level were treated as a continuous variable by using dummy coding to enter these variables into the regression model. For example, ethnicity was coded as (Caucasian = 1, non Caucasian = 0), regions were coded as (Local=1, other regions=0), and education level was coded as (post graduate degree=1, other education levels=0).

Two separate partial correlations were conducted before running the simple linear regressions and the multiple linear regressions: The first correlation was to check the associations between study variables FMS and verbal STM and visuospatial STM. The second correlation was to check the influence of covariate variables including gender, BMI, regions, ethnicity, and mother’s and father’s education levels on the relationship between independent variables (FMS and gender) and the dependent variable (verbal STM and visuospatial STM).

Exploratory analyses: FMS and Verbal STM and Visuospatial STM

In order to explore the relationship between FMS, verbal STM and visuospatial STM,

Pearson Correlation Coefficients and six simple linear regressions analyses were conducted separately.

Table 23 presents the Pearson correlation coefficient (r) between FMS (total FMS, locomotor skills, and object control skills) and verbal STM and visuospatial STM. The results showed a significant relationship between object control skills and verbal STM (r = 0.291). No significant relationship was found between each of the following relationships: Total FMS and verbal STM (r= 0.119); locomotor skills and verbal STM (r = -0.037); total FMS and visuospatial STM (r = -0.019); locomotor skills and visuospatial STM (r = -0.102); and object control skills and visuospatial STM (r = 0.094).

Table 23:

The Results of Pearson Correlation (r) of the Relationship Between FMS (Total FMS,

Locomotor Skills, and Object Control Skills) and Verbal STM and Visuospatial STM

Correlations

FMS LOS OCS VSTM VSSTM

FMS Pearson Correlation 1 .890** .767** .119 -.019 Sig. (2-tailed) .000 .000 .360 .882 N 61 61 61 61 61 LO-Skills Pearson Correlation 1 .459** -.037 -.102

Sig. (2-tailed) .000 .776 .432

N 61 61 61 61 OC-Skills Pearson Correlation 1 .291* .094

Sig. (2-tailed) .023 .473

N 61 61 61 VSTM Pearson Correlation 1 .311* Sig. (2-tailed) .015 N 61 61 VSSTM Pearson Correlation 1 Sig. (2-tailed) N 61 **Correlation is significant at the 0.01 level (2-tailed) * Correlation is significant at the 0.05 level (2-tailed) LOS (locomotor skills), OCS (object control skills), VSTM (verbal STM), VSSTM (visuospatial STM)

Table 24 presents the results of the simple linear regression to predict verbal STM of fourth grade children through using FMS raw scores (total FMS, locomotor skills, and object control skills) as independent predictor variables. The values of R2, and adjusted R2 revealed that the independent variables (total FMS, locomotor skills, and object control skills) did not provide a significant contribution to explain the variance (verbal STM): Locomotor scores explained .1% of the variance, F(2,58) = .082, p < .776; object control scores explained 8.5% of the variance F(2,58) = 5.465, p < .023; and total FMS explained 1.4% of the variance, F(2,58) =

.853, p < .360. However, object control scores significantly predicted verbal STM, F(2,58) =

5.465, p < .023.

Table 24:

Results of Overall Fit Statistics of the Simple Linear Regressions to Predict Verbal STM

R R2 Adjusted R2 F p-value 1. Locomotor score .037 .001 -.016 .082 .776

2. Object control score .291 .085 .069 5.465 .023

3. Total FMS score .119 .014 -.002 .853 .360 Notes: R2= the proportion of the total variance, which is accounted to explain the dependent variable by the regression equation. Adjusted R2= a modified version of R-squared that has been adjusted for the number of predictors in the model. F-test= overall significance test P-value= statistically significant at the p < .05 level to predict verbal STM

Table 25 presents the results of the coefficient of the simple linear regression to predict verbal STM of fourth grade children through using FMS raw scores (total FMS, locomotor skills, and object control skills) as independent predictor variables. The results of the unstandardized coefficients (β and Std. Error) and the significant p-value indicated that only object control skills significantly predicted verbal STM, F(2,58) = 5.465, p < .023 (see Table 25). This result supports the first research hypothesis in terms of the relationship between object control skills and verbal STM.

Table 25:

Results of Coefficient of the Simple Linear Regression to Predict Verbal STM

β Std. Error Βeta p-value Intercept 113.758 15.248 .000 Locomotor skills -109 .379 -037 .776 Intercept 61.136 20.734 .005 Object control skills 1.113 .476 .291 .023 Intercept 90.193 20.911 .000 Total FMS .230 .249 .119 .360 Notes: β= Unstandardized coefficients Βeta= standardized coefficients Std. Error= the standard error of the estimate (how close the predicted values are to the observed values).

Table 25 contains the results of the simple linear regression to predict visuospatial STM of fourth graders using FMS raw scores (total FMS, locomotor skills, object control skills) as independent predictor variables. The values of R2, adjusted R2 revealed that the independent variables (total FMS, locomotor skills, and object control skills) did not provide a significant contribution to explain the variance (visuospatial STM): Locomotor scores explained 1.0% of the variance, F(2,58) = .625, p < .432,object control scores explained .9% of the variance, F(2,58) =

.522, p < .473, and total FMS explained 0.0% of the variance, F(2,58) = .022, p < .882. The significant values of F(2,58) and p-values indicated that none of the independent variables was a statistically significant predictor of visuospatial STM.

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Table 26:

Results of Overall Fit Statistics of the Simple Linear Regression to Predict Visuospatial STM

R R2 Adjusted R2 F p-value 1. Locomotor score .102 .010 -.006 .625 .432

2. Object control score .103 .009 -.008 .522 .473

3. Total FMS score .019 .000 -.033 .022 .882 Notes: R2= the proportion of the total variance, which is accounted to explain the dependent variable by the regression equation. Adjusted R2= a modified version of R-squared that has been adjusted for the number of predictors in the model. F-test= overall significance test P-value= statistically significant at the p < .05 level to predict visuospatial STM

Table 27 presents the results of the coefficient of the simple linear regression to predict visuospatial STM of the fourth graders through using FMS raw scores (total FMS, locomotor skills, and object control skills) as independent predictor variables. The results of the unstandardized coefficients (β and Std. Error) and the significant p-value indicated that the predictor variables (total FMS, locomotor skills, and object control) were not statistically significant predictors of the visuospatial STM, p < .05 (see Table 27). This result did not support the first research hypothesis in terms of the relationship between FMS (total FMS, locomotor skills, and object control skills) and visuospatial STM.

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Table 27:

Results of Coefficient of the Simple Linear Regressions to Predict Visuospatial STM

β Std. Error Βeta p-value Intercept 126.409 12.662 .000 Locomotor skills -.249 .315 -.102 .432 Intercept 103.517 18.00 .000 Object control skills .299 .413 .094 .463 Intercept 119.084 17.566 .000 Total FMS -.031 .209 -.019 .882 Notes: β= Unstandardized coefficients Βeta= standardized coefficients Std. Error= the standard error of the estimate (how close the predicted values are to the observed values).

Exploratory analyses: FMS, Verbal STM and Visuospatial STM, Gender, and Covariate

Variables

In order to explore how other variables, such as gender, BMI, ethnicity, regions, and mother’s and father’s education levels, affect the relationship between FMS and verbal STM and visuospatial STM, partial correlations and six multiple linear regressions were conducted. Table

28 presents the results of the partial correlations to examine the potential influence of the covariate variables (gender, BMI, ethnicity, regions, and mother’s and father’s education levels) on the study variables. Six separate partial correlations were conducted (Appendix G) including locomotor skills, verbal STM, and covariate variables (Table 34); object control skills, verbal

STM, and covariate variables (Table 35); total FMS, verbal STM, and covariate variables (Table

36); Locomotor skills, visuospatial STM, and covariates (Table 37); object control skills, visuospatial STM, and covariate variables (Table 38); and total FMS, visuospatial STM, and covariate variables (Table 39). The results of the partial correlations indicated no effect of the covariate variables on the correlation between FMS (total FMS, locomotor skills, and object control skills) and WMC (verbal STM and visuospatial STM).

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Table 28:

Partial Correlations Between FMS and Verbal STM (VSTM) and Visuospatial STM (VSSTM) and Controlling for Gender, BMI, Region, Ethnicity, and Mother's and Father's Educational

Levels

Partial Correlation between FMS and Verbal STM and Visuospatial STM Before adding the After adding the covariate variables covariate variables Correlation p-value Correlation p-value Locomotor skills and VSTM -.037 .776 -.008 .954

Object control skills and VSTM .291 .023 .292 .031

Total FMS and VSTM .119 .360 .069 .616

Locomotor skills and VSSTM -.102 .432 .022 .875

Object control skills and VSSTM .094 .473 .039 .779 Total FMS and VSSTM -.019 .882 -.015 .915

Table 29 presents the results of the overall fit statistics of the multiple linear regressions to predict verbal STM of fourth grade children using FMS raw scores, separately by FMS category with covariates. The values of R2, and adjusted R2 revealed that the independent variables (total FMS, locomotor skills, and object control skills) did not provide a significant contribution to explain the variance in verbal STM, locomotor scores explained 18.9% of the variance F(2,58) = 2.634, p < .021, object control scores explained 25.8% of the variance F(2,58)

= 2.634, p < .021, and total FMS explained 19.3% of the variance F(2,58) = 2.634, p < .021.

Object control scores significantly predicted verbal STM, F(2,58) = 2.634, p < .021 (see Table

29), even after adding the covariate variables.

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Table 29:

Results of Overall Fit Statistics of the Multiple Linear Regressions (Predictor, Gender, and

Covariate Variables) to Predict Verbal STM

R R2 Adjusted R2 F p-value

1. Locomotor scores .435 .189 .082 1.764 .114

2. Object control scoresa .508 .258 .160 2.634 .021* 3. Total FMS scores .439 .193 .086 1.809 .105 Notes: *= Statistically significant at the p < .05 level to predict verbal STM aOverall model was significant, F(2,58) = 2.634, p < .021, R2 = .258, adj. R2 = .160 R2= the proportion of the total variance, which is accounted to explain the dependent variable by the regression equation. Adjusted R2= a modified version of R-squared that has been adjusted for the number of predictors in the model. F-test= overall significance test P-value= statistically significant at the p < .05 level to predict verbal STM

Table 30 presents the results of the coefficient of the multiple linear regressions to predict verbal STM of fourth grade children using FMS raw scores, separately by FMS category with gender and covariates. The results of the unstandardized coefficients (β and Std. Error) and the significant p-value indicated that only object control scores, F(2,58) = 2.634, p < .013, and region (covariate) were statistically significant predictors of verbal STM, p < .05. The results showed that there is no significant role of gender to predict verbal STM. Region is the only covariate that was a statistically significant predictor of verbal STM in all three regression models, F(2,58) = 1.764, p < .017, F(2,58) = 2.634, p < .031, and F(2,58) = 1.809, p < .013.

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Table 30:

Results of the Coefficient of the Multiple Linear Regressions (Predictor, Gender, and Covariate

Variables) to Predict Verbal STM

β Std. Error Βeta p-value Intercept 143.912 27.180 .000 Locomotor skills -.023 .402 -.008 .954 Gender -.715 3.759 -.025 .850 BMI -1.987 1.069 -.238 .069 Regiona -10.924 4.451 -.359 .017* Ethnicity 2.270 3.857 .075 .559 Mothers’ education level 5.283 4.677 .182 .264 Fathers’ education level 6.069 5.121 .197 .241 Intercept 85.008 32.340 .011 Object Control skillsb 1.182 .532 .309 .031* Gender 3.690 4.082 .129 .370 BMI -1.948 1.009 -.234 .059 Regiona -8.867 4.227 -.291 .041* Ethnicity 1.357 3.658 .045 .712 Mothers’ education level 4.057 4.331 .140 .353 Fathers’ education level 4.056 4.981 .131 .419 Intercept 130.325 31.870 .000 Total FMS .135 .267 .072 .616 Gender .069 4.021 .002 .986 BMI -1.945 1.055 -.233 .071 Regiona -11.094 4.300 -.364 .013* Ethnicity 2.037 3.813 .067 .595 Mothers’ education level 4.704 4.596 .162 .311 Fathers’ education level 5.783 5.141 .187 .266 Notes: β= Unstandardized coefficients Βeta= standardized coefficients Std. Error= the standard error of the estimate (how close the predicted values are to the observed values). * = statistically significant at the p < .05 level to predict verbal STM aRegion was statistically significant predictor, F(2,58) = 1.764, p < .017, F(2,58) = 2.634, p <.041, and F(2,58) = 1.809, p < .013. bObject control scores were statistically significant predictor, F(2,58) = 2.634, p < .031.

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Table 31 presents the results of the overall fit statistics of the multiple linear regressions to predict viusospatial short-term memory of fourth grade children using FMS raw scores, separately by FMS category with covariates. The values of R2, and adjusted R2 revealed that the independent variables (total FMS, locomotor skills, and object control skills) did not provide a significant contribution to explain the variance in visuospatial STM after adding the covariate variables. Locomotor scores explained 18.7% of the variance; object control scores explained

18.8% of the variance; and total FMS explained 18.7% of the variance. The significant p-value of the locomotor scores, F(2,58) = 1.743, p < .119, object control scores, F(2,58) = 1.753, p <

.117, and total FMS, F(2,58) = 1.741, p < .119 indicated that these variables are not statistically significant predictors of the visuospatial STM even after adding the covariate variables.

Table 31:

Results of Overall Fit Statistics of the Multiple Linear Regressions (Predictor, Gender, and

Covariate Variables) to Predict Visuospatial STM

Adjusted R R2 F p-value R2 1. Locomotor scores .433 .187 .080 1.743 .119a 2. Object control scores .434 .188 .081 1.753 .117b 3. Total FMS scores .432 .187 .080 1.741 .119c Notes: *= Statistically significant at the p < .05 level to predict visuospatial STM R2= the proportion of the total variance, which is accounted to explain the dependent variable by the regression equation. Adjusted R2= a modified version of R-squared that has been adjusted for the number of predictors in the model. F-test= overall significance test P-value= statistically significant at the p < .05 level to predict visuospatial STM

Table 32 presents the results of the coefficient of the multiple linear regressions to predict visuospatial STM of fourth grade children using FMS raw scores, separately by FMS category with gender and covariates. The results of the unstandardized coefficients (β and Std. Error) and

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the significant p-value indicated that in all three-regression models, only region was a significant predictor of the visuospatial STM, F(2,58) = 1.743, p < .006, F(2,58) = 1.753, p < .008, and

F(2,58) = 1.741, p < .006.

Table 32:

Results of the Coefficient of the Multiple Linear Regressions (Predictor, Gender, and Covariate

Variables) to Predict Visuospatial STM

β Std. Error Βeta p-value Intercept 130.850 22.699 .000 Locomotor skills .053 .336 .023 .875 Gender -.915 3.139 -.038 .772 BMI -.794 .893 -.114 .377 Regiona -10.563 3.717 -.416 .006* Ethnicity 3.485 3.221 .137 .284 Mothers’ education level -3.036 3.906 -.125 .440 Fathers’ education level 6.311 4.277 .245 .146 Intercept 126.849 28.224 .000 Object Control skills .131 .464 .041 .779 Gender -.482 3.562 -.020 .893 BMI -.814 .881 -.117 .360 Regiona -10.178 3.689 -.401 .008* Ethnicity 3.474 3.192 .137 .281 Mothers’ education level -2.994 3.780 -.124 .432 Fathers’ education level 6.081 4.347 .236 .168 Intercept 135.489 26.683 .000 Total FMS -.024 .224 -.015 .915 Gender -1.104 3.366 -.046 .744 BMI -.823 .883 -.118 .356 Regiona -10.395 3.600 -.409 .006* Ethnicity 3.606 3.192 .142 .264 Mothers’ education level -2.777 3.848 -.115 .474 Fathers’ education level 6.356 4.304 .247 .146 Notes: β= Unstandardized coefficients Βeta= standardized coefficients Std. Error= the standard error of the estimate (how close the predicted values are to the observed values). * = statistically significant at the p < .05 level to predict visuospatial STM aRegion was statistically significant predictor, F(2,58) = 1.743, p < .006, F(2,58) = 1.753, p < .008, and F(2,58) = 1.741, p < .006.

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Summary of Findings

The level of FMS performance

- Based on FMS raw scores, boys and girls scored higher in object control skills than

locomotor skills. There were significant differences between groups; boys scored higher in

total FMS and object control skills than girls.

- Within six levels of FMS (superior, above average, average, below average, poor, and very

poor), higher percentage of both boys and girls was in the average level of total FMS,

locomotor skills, and object control skills. .

- Within two levels of FMS performance (level 1 and level 2), higher percentage of both boys

and girls was in level 1 of total FMS, locomotor skills, and object control skills. .

- No statistical differences were found between boys and girls in any of six or two FMS levels

(total FMS, locomotor skills, and object control skills).

The level of Verbal STM and Visuospatial STM performance

- The majority of the sample for both boys and girls were in the average level of verbal STM

and visuospatial STM

- No statistical differences were found between boys and girls in the verbal STM and

visuospatial STM or in any sub-components.

The level of

The level of FMS Across Regions

- Significant differences in the level of total FMS occurred across regions.

- Significant differences in the level of locomotor skills across regions

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The level of Verbal STM and Visuospatial STM Across Regions

- No statistical differences were found in the level of verbal STM and visuospatial STM across

five regions.

Findings of the first hypothesis: FMS, Verbal STM and Visuospatial STM

- No statistically significant existed of a relationship between FMS and verbal STM and

visuospatial STM in terms of:

 Total FMS and verbal STM

 Locomotor skills and verbal STM

 Object control skills and verbal STM

 Total FMS and visuospatial STM

 Locomotor skills and visuospatial STM

 Object control skills and visuospatial STM

Findings of the second hypothesis: FMS, Verbal STM and Visuospatial STM and gender

- No statistically significant existed of a relationship between FMS and verbal STM and

visuospatial STM across gender in terms of:

 Total FMS and verbal STM and gender

 Locomotor skills and verbal STM and gender

 Object control skills and verbal STM and gender

 Total FMS and visuospatial STM and gender

 Locomotor skills and visuospatial STM and gender

 Object control skills and visuospatial STM and gender

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Findings of the exploratory analyses: FMS and Verbal STM and Visuospatial STM, and

Covariate Variables

- A significant relationship was found between object control skills and verbal STM, Pearson’s

r = 0.291.

- In all regression models to predict verbal STM, only object control scores and region were

statistically significant predictors of verbal STM, p < .05.

- In all regression models to predict visuospatial STM, only region was a statistically

significant predictor of visuospatial STM.

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CHAPTER 5: DISCUSSION

The purpose of this present study was to explore the relationships between FMS and verbal STM and visuospatial STM for children aged 9-10 years. The study was based on the understanding that the mind and body are one entity composed of inter-related subsystems. Any malfunction in one subsystem will impact the entire system, including physical state, mental development, and emotional health. It is important to understand how these systems relate to each other and how this relation can be improved by change in one or more factors. For example, can the WMC of children be improved through practicing FMS? Or, can children control their body systems more readily by enhancing their WMC?

Previous research examined the relationship between motor skills and cognitive functions by using neuroimaging studies in children with specific disorders such as ADHD (Piek & Dyck,

2004), DCD and dyslexia (Piek, Dyck, Francis, & Conwell, 2007; Viholainen, Ahonen, Cantell,

Lyytinen, & Lyytinen, 2002), or in children with motor difficulties and problems in learning, language, reading, math, and spelling (Alloway, 2007; Archibald & Alloway, 2008).

Investigations also focused on typically developing children (Davis, Pitchford, & Limback,

2011) and broadly on the relationship between FMS, cognitive functions, and physical activity in children and adults (Rokicka-Hebel, 2013; Iverson, 2010).

Little attention has been devoted to exploring the relationship between FMS and cognitive functions, especially WMC for school-aged children. Thus, the purpose of this chapter is to discuss the findings of the current experimental study that was conducted on children aged

9-10 years to identify the relationship between FMS and verbal STM and visuospatial STM. The discussion includes interpretation of the findings in terms of the two research hypotheses and

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exploratory analysis of data. This chapter provides a summary of the findings, explanations for the results, and suggestions for the future directions.

Hypothesis 1

“Children, who have higher levels of FMS (total FMS, locomotor skills, and object control skills), will show better verbal STM, and visuospatial STM compared to children who have lower levels of FMS.”

The study’s findings did not support the first research hypothesis. The results showed that there is no strong evidence of a relationship between FMS and WMC. These insignificants results may be due to several possible explanations. First, the sample size was based on 61 participants from five different regions in Michigan. Even though the number of participants was slightly lower than the number that was determined by the power analysis, but is still considered small. The power analysis was based on the medium effect size (f2 = .25; n= 66) that was used to determine the number of participants compared with the small effect size (f2 = .2; n= 90). The small sample size of participants may impact the analysis in term of increasing bias and the amount of error and decreasing the accuracy of the results in explaining and predicting the outcome (Timberlake, 2011). The sample size may also influence the statistical and practical significance in both types of errors (Type I and Type II) (Maxwell, 2000). In addition, the small number of participants impacts the analyses by gender, ethnicity, region, etc. Consequently, it is difficult to generalize results (Thomson, Watt, & Liukkonen, 2015; Knofczynski & Mundfrom,

2008). Further investigation is needed to check if the sample size affected the current results through using a larger number of participants.

The second explanation is the children’s lack of development in some of the FMS. The results showed that may children did not do well in two of six locomotor skills (leaping and

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jumping) and in two of six object control skills (throwing and striking). Children also did not do well in locomotor skills compared with object control skills, which may impact their overall performance. Normative data from the TGMD-2 would suggest that children of age 9 – 10 should be at the higher levels of performance. The typically developing children in this study should have been physically and intellectually capable of developing their motor skills. Thus, environmental factors (i.e. learning and practicing skills with or without equipment) may have affected their performance. This explanation is supported by Weiss (2011) who wrote that children do not acquire FMS automatically as a consequence of their maturation and physical development. Children can develop these skills by the interaction between biology and environmental factors. These factors will change over time, which may cause changes in child's motor development (Gabbard, 2009). Therefore, children need effective instruction and adequate opportunity to learn FMS in the early years of primary school. During the early years, children are ready physically and intellectually to learn motor skills and highly motivated and enthusiastic to acquire and develop FMS physically and cognitively (Weiss, 2011). It is very important to provide children, especially during the early years, opportunities and experiences to acquire and practice motor skills (Cools, Martelaer, Samaey & Andries, 2011; Williams, Pfeiffer, O'Neill,

Dowda, McIver, Brown, et al., 2008) and to refine these skills to perform more complex skills in sports and daily activities (Weiss, 2011). Based on data from this cross-sectional study, some children had not mastered all of their FMS by age 10, as would normally be expected. Thus, intervention studies related to teaching and improving FMS across different age groups is needed for further understanding the relationship between FMS and verbal STM and visuospatial STM.

Longitudinal evidence across different ages would provide better information on the evaluation of level of FMS and improvement in verbal STM and visuospatial STM.

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In this study, a high percentage of children were in an average level of their FMS (n=36;

59%) and verbal STM (n= 43; 70.5%) and visuospatial STM (n=33; 54.1%) development.

However, there is no significant relationship between FMS and the storage components of the

WMC or in any sub-components (see Table 5 and 6). Therefore, a third possible explanation of the study results could be the potential role of the teaching methods used by the physical educators of these participants. While the specific methodologies of the physical education teachers were not measured in this investigation, best practices would be characterized by skill presentation, corrective and positive feedback on the performance and individual practice

(Ayers, Housner, Gurvitch, Pritchard, Dell'Orso, Dietrich, et al., 2005). These characteristics are important for children’s cognitive development. Children benefit from learning skills through task exploration during early learning. Understanding the skills and receiving corrective and positive feedback during task presentation plays a crucial role in improving FMS and cognitive functions. Metzler (2005) believes that there is little emphasis on cognitive learning during physical education class due to lack of time to ensure that all children understand and learn the skills. Evidence in supporting the role of the teaching method in the development of FMS and

WMC was supported by Thomson, Watt, and Liukkonen (2015) and Liu and Chepyator-

Thomson (2008). They found positive connections between acquisition of FMS, cognitive style, and teaching approach. They concluded that cognitive restructuring plays an essential role in

FMS development at an early age. Children, especially independent learners, benefit from tasks that require internal processing of kinesthetic information, proprioception detail, and spatial awareness. This information supports the role of cognitive style and analytic teaching protocol in learning and developing FMS, especially for kinesthetic learners (Thomson, Watt, & Liukkonen,

2015; Liu & Chepyator-Thomson, 2008). Focusing on cognitive learning during FMS acquisition

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may help children improve their FMS and cognitive functions (e.g., WMC) to reach an above average level in both FMS and verbal STM and visuospatial STM. Intervention studies are needed to address the impact of the teaching method in the relationship between FMS and verbal

STM and visuospatial STM.

A fourth possible explanation for the findings may relate to the ages of the participants.

The relationship between FMS and verbal STM and visuospatial STM may be better understood by testing several different age groups of children. The findings of the current study did not show a wide range of different FMS and verbal STM and visuospatial STM abilities or in any subcomponents of these two variables (see Table 5 and 6) among fourth graders. Typically developing children at the same age and grade often mature at similar rates, as they share the same developmental characteristics as well as environmental experiences. They also share the same critical and developmental mental ages to develop FMS and cognitive skills between the ages of 5 and 10 years (van der Fels, te Wierike, Hartman, Elferink-Gemser, Smith, & Visscher,

2015). These factors may help children of similar age build their cognitive structure to similar levels (Gabbard, 2009). Testing children in different age groups may help identify different motor skills levels and WM abilities. Research shows that children at different ages use different mental planning and strategies to improve cognitive and motor skills. Older children exhibit increasing desire for autonomy and less verbalizations to learn motor and cognitive skills compared with younger children, who need to express their inability to learn these skills.

Younger children need more instructions to learn the skills compared with older children. The cognitive processes in older children seem to become automatic, because the interaction between learning motor skills and mental planning (verbal operations) is more developed in older children than younger. Older children are able to realize what they are doing, pay more attention, and

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select the right approach to reach their goals; while younger children do not have a symbolic representation of these processes. Therefore, younger children have less developed motor and cognitive systems (e.g., inhibitory control and working memory) compared with older children, resulting from lack of experiences (Franchin, 2011; Malloy-Diniz, Cardoso-Martins, Pacheco

Nassif, Levy, Fuentes, & Borges Leite, 2008; Brocki & Bohlin, 2004; Bunker, 1991). Consistent with this finding, Davis, Pitchford, and Limback (2011) indicated that the nature of interrelation between motor and cognitive skills changes over time. Not all motor skills mature at the same time, which affects the rate of development of cognitive skills.

Evidence of the link between motor and cognitive skills varies across studies and ages.

Ackerman (1988) showed that the correlation between motor and cognitive skills declined with age. Ackerman concluded that level of attention decreases as children practice motor skills; whilst Ahnert, Bos, and Schneider (2003) reported that a correlation between the motor and cognitive skills (for specific sub-skills) increases with age towards the end of the school years. In addition, the varied non-linear correlations between motor skills and cognitive functions develop across age from 3-14 years (Dyck, Piek, Kane, & Patrick, 2009). Thus, evidence is needed to support the relationship between motor skills and verbal STM and visuospatial STM across age.

This evidence may help to understand how children acquire FMS and develop verbal STM and visuospatial STM over developmental time. It also may help in designing specific intervention programs to increase children's cognitive and motor skills during the school years.

Overall, the possible explanations of the relationship between FMS and verbal STM and visuospatial STM highlight the need for intervention programs and further investigations into the relationship between FMS and verbal STM and visuospatial STM across different age groups of children. The current findings of no significant relationship between motor and verbal STM and

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visuospatial STM were consistent with the work of Rigoli, Piek, Kane, and Oosterlaan (2012), who reported no evidence of the role of motor coordination in children's WM and academic achievement. Roebers and Kauer (2009) and Wassenberg, Feron, Kesseles, Hendtiksen, Kalff,

Kroes, et al. (2005) also reported that no significant relationship was found between overall cognitive and motor skills in children aged 5-7 years. The current study produced inconsistent findings with Davis, Pitchford, & Limback (2011) and Dyck, Piek, Kane, and Patrick (2009) studies. Both studies showed a moderate and strong correlation between motor and cognitive skills across different age groups (4–14 years) and gender. Thus, evidence of the relationship between FMS and verbal STM and visuospatial STM remains equivocal, especially in typically developing children. Broader research is needed to draw a conclusion about the nature of the interrelation between motor skills and cognitive functions. Specifically there is need to study these factors longitudinally through the early, middle, and late childhood years to more thoroughly understand the process and identify changing relationships between FMS and verbal

STM and visuospatial STM.

Hypothesis 2

" Boys will have better verbal STM, and visuospatial STM compared to girls in all levels of FMS."

The findings of this study did not support the second hypothesis. There are no gender differences between boys and girls in terms of the relationship between FMS (total FMS, locomotor skills, and object control skills) and verbal STM and visuospatial STM. A significant gender difference was expected in which boys would do better in total FMS, object control skills, and visuospatial short-term memory. Whilst, girls were expected to do better on verbal STM as these tests are language based. These expectations were based on evidence from other studies

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(True, 2014; Hume, Okely, Bagley, Telford, Booth, Crawford et al., 2008; Morgan, Okely, Cliff,

Jones, & Baur, 2008; Rudisill, Mahar, & Meaney, 1993). The expectations were also based on neurophysiology and functional neuroimaging data, which showed evidence of the differences between boys and girls in relying on different networks to produce the same behavior on working memory tasks (Hill, Laird, & Robinsona, 2014). Research found higher activation in the areas of the brains of males associated with visuospatial skills and planning; whereas, the higher activation in the females' brain areas were associated with language and social awareness

(Leisman, Moustafa, & Shafir, 2016; Lowe, Mayfield, & Reynolds, 2003; Robinson, Abbott,

Berninger, & Busse, 1996; Temple & Cornish, 1993; Huang, 1993). Studies showed that males were advantaged in spatial ability in processing WM, whilst females were ahead in verbal ability

(Palmiero, Nori, Rogolino, D’amico, & Piccardi, 2016; Quaiser-Pohl & Lehmann, 2002; Tzuriel, p& Egozi, 2010; Casey, Nuttall, Pezaris, & Benbow, 1995). They indicated that males depend on the right hemisphere more prominently than females, while females depend on the left hemisphere more prominently.

The possible explanation of the current findings is that both boys and girls seem to have the same opportunities or barriers to develop FMS and verbal STM and visuospatial STM to the same level, as the majority of participants were in an average level of both FMS and verbal STM and visuospatial STM. The results of FMS were consistent with the criteria indicated by Ulrich

(2000) that children should reach the intermediate or advanced level of FMS development by age

10 or 11 years. These results were consistent with DeWan’s (2006) study, which showed no significant differences in the development of executive function (i.e. working memory, inhibition and shifting) between boys and girls across different age groups (9-10 years, 9-11 years, and 10-

12 years). DeWan outlined that it is possible that boys and girls grow in similar ways as they

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follow comparable courses over childhood into young adulthood (DeWan, 2006). Holmes,

Gathercole and Dunning (2009) and Thorell, Lindqvist, Nutley, Bohlin, Klingberg, Humanistisk, et al. (2009) showed that gender differences in WMC are relatively constant over time. Likewise,

Alloway, Gathercole, and Pickering (2006), Ullman, McKee, Campbell, Larrabee, and Trahan,

(1997) and Forrester and Geffen (1991) showed no gender differences existed between boys and girls aged 10 years in WMC. However, children improved their WM ability via training programs during childhood. The training programs increased WM ability in children by increasing their brain activity, specifically in the frontal and parietal cortices, which serve WM

(Holmes, Gathercole, & Dunning, 2009; Westerberg & Klingberg, 2007).

Another possible explanation for the findings is that the FMS and verbal STM and visuospatial STM testing instruments are not robust enough to distinguish differences in both boys and girls at age 10. Changing testing to increase task difficulty matched to the children’s

FMS and WM abilities may help to differentiate results. For example, Gimenez, Manoel, de

Oliveira, Dantas, and Marques (2012) increased the complexity by combining two skills of FMS

(running and overarm throwing) in order to identify the efficiency of performing these skills and to increase diversity between children at different ages and by gender. Such evidence emphasizes the importance of checking the stability of acquiring FMS by testing children in different circumstances to determine the mature stage of developing FMS across ages and gender. Another way that may lead to more robust findings is to test children in all WMC components. Testing children in the processing components of WMC (verbal WM and visuospatial WM) instead of the storage components of WMC (verbal STM and visuospatial STM), or even using a comprehensive AWMA test, may lead to different results of the relationship between FMS and

WMC across gender. For example, Holmes, Gathercole, and Dunning (2009) tested children

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aged 8-11 years on the processing and storage WMC components using AWMA. The study findings showed both boys and girls were below the average of their verbal WM ability. Based on these results, unclear evidence of the gender differences in the relationship between FMS and verbal STM and visuospatial STM still existed. The current results show the need of the continual exploration using different methods to explore factors in the relationship between FMS and WMC among different age groups and gender.

Exploration Data for FMS and Verbal STM and Visuospatial STM

The results of the multiple linear regressions showed no significant relationships between

FMS and verbal STM and visuospatial STM. However, the only significant relationship was found between object control skills and verbal STM. Object control significantly predicted verbal STM (see Tables 20 through 24). The possible explanation of the result is that participants had a sufficient opportunity to practice and learn object control skills compared to locomotor skills. These skills are considered complex and difficult skills, which require more structures and practices in order to be learned and mastered compared with locomotor skills (Westendorp-

Haverdings, Houwen, Hartman, Mombarg, Smith, & Visscher, 2014). Through practicing object control skills, children need to control and manipulate an object and to mobilize muscles and body segments to perform, especially in the receptive skills such as catching and dribbling.

Receptive skills require perception and coordination skills to receive the object by moving the body. Conversely, propulsive skills such as throwing, kicking, striking, and rolling only require force to send an object (Borodina & Sisolyatina, 2014). The mechanism underpinning learning object control skills requires higher order cognitive skills to process visual and verbal incoming stimuli from objects, skill structure, and moving body parts. Therefore, children acquire an intermediate or advanced level of object control skills at 10-11 years compared with locomotor

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skills that children acquire by 7-8 years (Ture, 2014; Ulrich, 2000). Results from this study are supported by the neuropsychological research, which showed co-activation of the cerebellum and the prefrontal cortex through processing motor and cognitive tasks (Westendorp-Haverdings et al., 2014). They were consistent with the findings of Rigoli, Piek, Kane, and Oosterlaan (2012) who found a positive association between verbal WM and visuospatial WM and motor coordination in adolescents aged 12-16. Conversely, several studies showed insignificant relationships between motor skills and working memory (van der Fels et al. 2015, Wassenberg,

Feron, Kessels, Hendriksen, Kalff, Kroes et al., 2005). Further evidence is needed to understand more fully the relationship between motor and cognitive skills. However, it appears that focusing on development of object control skills may be most helpful.

Exploration Data for FMS and Verbal STM and Visuospatial STM and Covariate

Variables

The results of the multiple linear regressions analyses showed object control scores significantly predicted verbal STM even after adding the covariate variables (gender, BMI, regions, ethnicity, and mother's and father's education levels). Even though the current study found significant differences between gender in the total FMS and object control scores, as boys showed better performance than girls (see Table 3), gender differences did not emerge in the regression model. The findings also showed region was the only covariate that significantly predicted both verbal STM and visuospatial STM. These results may be due to the role of school environment in each region in children’s FMS and verbal STM and visuospatial STM development. Current data did not show any impact of other variables (gender, BMI, ethnicity, and mother's and father's education levels) in the regression model.

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The results of the current study correspond with those of Clarke, Ailshire, House,

Morenoff, King, Melendez, et al. (2012). They investigated how the surrounding neighborhood impacted individuals’ cognitive functions (memory and executive functioning). They compared individuals from advantaged and disadvantaged neighborhoods. Individuals who were living in advantaged regions (e.g., high household income, education, and greater density of physical and institutional resources) had better cognitive functions compared with individuals in disadvantaged regions (Clarke, et al., 2012). Another study by Malloy-Diniz, et al. (2008) showed different mental planning abilities between Brazilian children aged 5-8 years enrolled in public or private schools. Children at the private school did significantly better than public school children on the Tower of London (TOL: mental planning) and Raven’s Colored Matrices

(RCM: fluid intelligence) task. They indicated that school environment had an important impact on children’s mental planning development, possibly by impacting the neurocognitive development of the children. The impact of the school environment on children’s FMS development was also reported by Goodway and Branta (2003). They found that children aged 4 years who were raised in disadvantaged environments had less opportunity to develop FMS compared with children in the typical preschool program from the same community. The researchers emphasized the importance of providing quality programs at the school and effective instruction in physical education class to improve FMS and academic achievement (Goodway &

Branta, 2003). The same results and conclusions were supported by Goodway, Robinson, and

Crowe (2010), Goodway and Rudisill (1997), Branta and Goodway (1996), and Connor-Kuntz and Dummer (1996) who reported different levels of FMS of children from different regions.

Likewise, Bakhtiar (2014) found different motor skill proficiencies in children age 6-years-old

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from rural and urban regions. Children in the urban region did better on FMS than children in the rural region.

In this study, children in region 1 were enrolled in a more affluent school, with more highly educated parents, than children in the other regions. These differences impacted the specific environments in which the children were reared with those in region 1 having more enriched environments. They had more opportunities for skill development programs both within and outside of school compared to participants in the other regions. Because 1/3 of participants in the study came from region 1, the overall effect of this enriched environment may have influenced the results.

Based on this finding, it is essential to do further investigation to explore the relationship between children’s FMS and verbal STM and visuospatial STM across different regions with a larger sample size and different age groups. This process will help to identify important factors related to FMS and verbal STM and visuospatial STM in children across different regions. In addition, intervention programs that provide equal opportunity to improve children’s FMS and

WMC in different schools and regions should be developed.

Conclusions & Future Directions

In summary, in this cross sectional study of children aged 9-10 years, no significant relationships were found between FMS and verbal STM and visuospatial STM across gender.

Significant relationships were found between object control skills and verbal STM. Object control skills significantly predicted verbal STM. Moreover, region was significantly predictive of both verbal STM and visuospatial STM. Thus, FMS and region seem to be involved in development of WMC in children aged 9-10 years. Further investigation, such as longitudinal and intervention studies is needed on the relationship between FMS and verbal STM and

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visuospatial STM with larger sample sizes across different age groups, gender, and regions.

Intervention programs in early childhood might play a role in improving children’s FMS and

WMC. Key components of such programs should include equal opportunities, appropriate instruction proper equipment, and the necessary verbal and visual stimuli for learning motor skills and improving WMC.

Our findings suggest the need for longitudinal research to explore the relationship between FMS and verbal STM and visuospatial STM over time. Realizing the changes in developing FMS and cognitive functions (e.g., verbal and visual perception, planning, and regulation of movement) helps to understand the emerging sequence of cognitive ability. Future research should include a comprehensive WMC battery and increase the complexity of testing

FMS (e.g., testing two or three skills together) to more accurately test the relationship between

FMS and verbal STM and visuospatial STM. Moreover, it might be beneficial to find or develop one assessment to test both motor and working memory abilities together instead of assessing them separately, as these complex systems depend upon each other to make small steps forward in development.

Strengths and Limitations

The Limitations of the Study

This study has a number of limitations. First, the small sample size limits the generalizability of the findings and highlights the need for a larger sample size. In addition, this study did not address the relationship between FMS and verbal STM and visuospatial STM over a range of ages. A wider range of ages might help discover any variation in motor skills, verbal

STM and visuospatial STM abilities, and gender differences. Secondly, testing children on only the storage components of WMC may not have been enough to fully capture WMC in these 9-10

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year old participants. Third, testing children in different settings including time (before or after school program, morning, noon, evening), places (school gym and tennis court), and order of assessment of both FMS and verbal STM and visuospatial STM may have affected the accuracy and could bias the results.

The strengths of the study

This is the first study to find direct evidence of the relationship between object control skills and verbal STM. It provides a framework for future research in terms of (a) improving children’s WMC through learning and practicing specific motor skills and (b) enhancing FMS through providing children specific verbal and visual structures that match brain functions of girls and boys, especially in early childhood. Appropriate verbal and visual structures facilitate processing information cognitively and improving learning from practicing motor skills. Such considerations may help increase the percentage of children in the above average level compared with other levels in both FMS and verbal STM and visuospatial STM.

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APPENDICES

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APPENDIX A

Parental Consent Form

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Informed Consent to Participate in a Research Study

Project Title: The Relationship of Motor Skills Development to Working Memory Capacity of Children Aged 9-10 years

Principal Investigator: Florian Kagerer, PhD. Secondary Investigator: Fadya Mahrous Jerojeis, PhD student Michigan State University/ Department of Kinesiology

Description You and your child are invited to participate in a research study. Researchers are required to provide a consent form to inform parents and children about the research study. Participation is completely voluntary. This consent form provides information about the research study to help you and your child make a decision. In order to participate in the study, you will be asked to complete a questionnaire about your child’s physical, mental, and emotional health, and information about your education level. Your child will be asked to participate in some motor skills activities and complete some memory measures. Please feel free to ask the researchers any questions you may have.

Who is Eligible? 1. Children who are between the ages of 9-10 years old, without a history of emotional behaviors and/or learning disabilities. 2. Parents of the children.

Purpose of the Study The purpose this study is to examine fundamental motor skills of children (i.e., by observing the child running, jumping throwing, and kicking), with cognitive development (i.e., a child’s memory) in relation to their gender.

What you will do If you and your child agree to participate: 1. Parents will fill out a survey. It will take about 5 minutes. 2. We would like to video tape your child while they are running, jumping, throwing, kicking, etc., Then we will ask your child to work at a computer station using a program which measures their ability to memorize information and/or respond to prompts. Your child’s participation will take approximately 50 minutes. You may start the research today or come back at another time.

Benefits The researchers don’t know if you or your child will directly benefit from your participation. However, we hope that the information gained will benefit others in the future.

Risks The potential risks of participating in the exercise portion of the study are the possibility that your child may be injured during the exercise portion of the study. We will not ask your child to do strenuous exercises, and if they are uncomfortable with any of the movement tasks, they may stop. The study team does not anticipate that the computer task will pose any harm. If your child

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is uncomfortable with a question, or a computer task, they may skip it. We don’t anticipate any risks with the parents portion of the study.

Privacy and Confidentiality All research records in this study will be kept confidential. Data will be available to the research staff only by using a personal code, in order to maximize confidentiality. Data will be kept in a locked office at MSU and will be used for research purposes only. No reference to participants will be made in publications or presentations. Data will be kept for at least three (3) years after the close of the study and may be accessed by the MSU HRPP (Human Research Protection Program) and members of the study team.

Your Rights Participation is completely voluntary. Refusal to participate will cause no penalty or loss of benefits to which you or your child are otherwise entitled. Participants may discontinue involvement in this study at any time without penalty or loss of benefits to which you are otherwise entitled. You and your child have the right to say no. You or your child may change your mind at any time and withdraw. You or your child may choose not to answer specific questions, or to stop participating at any time. Choosing not to participate or withdrawing from this study will have no effect on you or your child's grades or relationship at their school.

Cost and Compensation There are no costs to participate in this study. We are providing a $10 Meijer gift card as an incentive for participation.

Injuries If your child is injured as a result of participation in this research project, Michigan State University will assist you in obtaining emergency medical care, if necessary, for your child’s research related injuries. If you have insurance for medical care, your insurance carrier will be billed in the ordinary manner. As with any medical insurance, any costs that are not covered or are in excess of what are paid by your insurance, including deductibles, will be your responsibility. The University’s policy is not to provide financial compensation for lost wages, disability, pain or discomfort, unless required by law to do so. This does not mean that you are giving up any legal rights you may have. You may contact Dr. Florian Kagerer, principal investigator, at (517)-432-9907, with any questions or to report an injury.

Contact Information If you (or your child) have concerns or questions about this study, such as scientific issues, how to do any part of it, or to report an injury, please contact Fadya Mahrous Jerojeis, the secondary investigator, at (517) 574-6652, or via email at [email protected], or the PI, Dr. Florian Kagerer at (517)-432-9907, or via email at [email protected].

If you have questions or concerns about your role (or your child’s role) and rights as a research participant, or would like to obtain information or offer input, or would like to register a complaint about this study, you may contact, anonymously if you wish, the Michigan State University's Human Research Protection Program at 517-355-2180, Fax 517-432-4503, or e-mail

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[email protected] or regular mail at Olds Hall, 408 West Circle Drive #207, MSU, East Lansing, MI 48824.

Documentation of Informed Consent Please feel free to ask any questions about the study. You may contact the researcher if you have any questions later. By signing this document, you are voluntarily agreeing for your child to participate in this research study:

Parent signature: ______

Child’s Name ______

Child’s Date of Birth ______

Name of Parent______

Email address ______

Parent’s address ______

I agree to allow videotaping of my child Yes No

------Your signature below means that you voluntarily agree to participate in this research study by completing the questionnaire.

Parent’s Signature ______Date ______

Investigator’s Signature ______Date ______

You will be given a copy of this document for your records, and one copy will be kept with the study records.

If a second session is necessary, please indicate when and where you would like to meet:

Location: ______

Day: ______

Time: ______

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APPENDIX B

Participant Assent Form

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Assent Form for Children 9-10 years old

The Relationship of Motor Skills Development to Working Memory Capacity

You are being asked to participate in a research study. Before we begin, we would like to explain the purpose of the study and the procedures you will be following.

Procedures: The study examines your physical activity level, such as running, catching, throwing, rolling, and your memory, such as how many numbers, words, and sentences you can remember.

What you will do: We will test your level of motor skills. We will also do a memory test (30 minutes).

We would like to see you one or two times. During the first visit, we will test your motor skills during your normal physical education class, or wherever you and your parents decide. During the second visit, we will measure your memory. We can do both tests in one time based on your and your family available time.

Your Rights: You do not have to be in the study if you do not want to, and you can stop anytime for any reason. If you want to participate, you should know that you would not be in any danger of anything bad to happen to you while you are taking part. All data we collect from you are available to the researchers working on this study, and may need to be seen by the Human Research Protection Program and/or the agency that is funding the research. Your research records will be kept secret and will be stored in locked cabinets in our laboratory at Michigan State University until at least three years after the close of the study.

Risks: You may feel a little tired while performing the tasks or afterwards. It’s okay to ask for a break. You might feel a little bored because you will be asked to concentrate in order to do your best. You can ask questions at any time.

Compensation: If you participate in both sessions, you will get a $10 Meijer gift card.

Question: If you have any questions now, or later, please ask any of the researchers working with you. If you agree to participate, print your name below. I agree to participate in this study. Name of Child: ______Name of Researcher: ______Phone and/or email: ______

You will be offered a copy of this form to keep

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APPENDIX C

Questionnaire

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Demographic Information Questionnaire

Project Title: The Relationship of Motor Skills Development to Working Memory Capacity of

Children Aged 9-10 years

Thank you for showing an interest in being part of our study relating to your child’s physical and cognitive development. Please complete the following questions about your child’s health. Your answers are confidential and will help us in our analyses of the data.

Child’s name ______.

Child’s gender (Female/Male) ______.

Child’s birth date (Month/Day/Year) ______.

Child’s height to the nearest 1/2 inch or 0.1 centimeter______.

Child’s weight to the nearest decimal fraction (for example, 55.5 pounds or 25.1 kilograms)

______.

Ethnicity of the child (check all that apply):

African- American Asian Caucasian Hispanic Other

Parental education levels: Check the highest degree

- Mother/ guardian ------

GED , High School , Some College , Associate’s Degree , Bachelor’s Degree , Post Graduate Degree . - Father/ guardian ------

GED , High School , Some College , Associate’s Degree , Bachelor’s Degree , Post Graduate Degree .

Please continue to page 2

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Please check the appropriate response for each of the following conditions:

1. Does your child take medication for:

Depression or anxiety: YES NO Seizures or epilepsy: YES NO Neuromuscular problems: YES NO Neurological issues: YES NO Attention Deficit Hyperactivity Disorder (ADD/ADHD) YES NO Other disruptive behavior disorders YES NO

2. Does your child have an Individualized Educational Plan with the school?

YES NO

3. Does your child have a diagnosis of learning difficulty or learning disability in these

areas?

Reading: YES NO

Writing: YES NO

Math: YES NO

Reasoning: YES NO

Listening: YES NO

Speaking: YES NO

Printed name of parent/guardian ______

Signature of parent/guardian ______

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APPENDIX D

Flyers

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Figure 23: $10 for Children

Are you a child between the ages of 9 -10 years old? Do you like to run, jump, throw or kick a ball? Do you like to play games on the computer?

If so, you and your parent(s) may be eligible to participate in a research study through Michigan State University!

Study team members will meet with you and your parents at a convenient location (i.e., on MSU campus, at your home or another location) to give you more details about the study.

If you agree to participate, your participation will take about 50 minutes and we have a $10 Meijer gift card for those who participate in our research study.

For more information please contact:

Fadya Mahrous Jerojeis Crystal Branta Florian Kagerer [email protected] [email protected] [email protected] (517) 574-6652 (517) 420-2384 (517) 432-9907

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APPENDIX E

The Test of Gross Motor Development, Second edition (TGMD–2)

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Figure 24: The Test of Gross Motor Development, Second Edition (TGMD-2)

TGMD–2 is a norm-referenced discriminative test to assess children fundamental motor skills aged 3-to-11 years. It consists of 12 skills divided into two subtests:

 Locomotor skills include running, galloping, hopping, leaping, horizontal jumping, and sliding  Object control skills include striking, dribbling, catching, kicking, overhand throwing, and underhand rolling The performance of each skill is evaluated quantitatively on three to five criteria depending on the skill. Criteria are coded (1) if met and “0” if not. If the examiner’s performance met the criterion, they received 1 and zero if the criterion not met. Two trials are scored and added together for a total raw skill score. The total maximum raw score of all the FMS is 48. Evaluating examinees’ levels of FMS will be obtained by dividing the total raw scores for all FMS and both subtests into two levels: high and middle (> 90), and low (<89) based on TGMD-2 standard protocols (TGMD-2, Ulrich, 2000).

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Table 33:

Example of Evaluating Running

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APPENDIX F

Alloway Working Memory Assessment (AWMA)

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Alloway Working Memory Assessment (AWMA)

AWMA is a Computer-Based Standardized Battery to assess Working Memory Capacity. It consists of four components:  Verbal short-term memory, Verbal working memory, Visual-spatial short-term memory and visual-spatial working memory. • Verbal short-term memory and verbal working memory are for measuring the activity in the phonological loop, verbal central executive, and episodic buffer. • Visual-spatial short-term memory and visual-spatial working memory are for measuring visuospatial sketchpad, visuospatial central executive and episodic buffer.  In these four components, participants’ level will be determined by twelve subtests - The verbal short-term memory will be tested by digit recall, word recall, and nonword recall subtest. - The verbal short-term memory will be tested by digit recall, word recall, and nonword recall subtest. - The verbal working memory will be tested by listening recall, counting recall, and backwards digit recall subtest. - The visual-spatial short-term memory will be tested by dot matrix, mazes memory, and block recall subtests. - The visual-spatial working memory will be tested by odd one out, miser X, and spatial recall backwards subtest.  Each of twelve subtests consists of a series of practice trials before the test trials. The test trials are presented as a series of blocks; each block consists of six trials. In each case, the child has to remember a piece of information and then recall it back immediately  The full form requires 45 minutes to complete.  The score and report form is automatically provided at the end of the test. This form of testing offers a practical and convenient way for teachers and psychologists to identify individuals’ working memory levels.

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Figure 25: AWMA Administration

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APPENDIX G

Partial Correlation

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Table 34:

Partial Correlations Between Locomotor Skills (LOS) and Verbal STM (VSTM) Controlling for

Gender (G), BMI, Region (R), Ethnicity (Eth), and Mother's (M) and Father's (F) Education

Levels (EL)

M F LOS VSTM G BMI R Eth Control Variables EL EL -none-a LOS Correlation 1.000 .033 -.068 -.157 .373 .140 .381 .285 Sig. (2-tailed) . .801 .603 .226 .003 .281 .002 .026 df 0 59 59 59 59 59 59 59 VSTM Correlation 1.000 .090 -.216 -.192 .101 .173 .163 Sig.(2-tailed) . .492 .095 .138 .437 .181 .209 df 0 59 59 59 59 59 59 G Correlation 1.000 -.175 -.057 -.057 .099 .193 Sig. (2-tailed) . .177 .660 .660 .449 .136 df 0 59 59 59 59 59 BMI Correlation 1.000 -.101 -.012 -.018 -.076 Sig. (2-tailed) . .438 .929 .888 .561 df 0 59 59 59 59 R Correlation 1.000 -.041 .341 .435 Sig.(2-tailed) . .751 .007 .000 df 0 59 59 59 Eth Correlation 1.000 -.014 .058 Sig. (2-tailed) . .915 .656 df 0 59 59 MEL Correlation 1.000 .591 Sig. (2-tailed) . .000 df 0 59 FEL Correlation 1.000 Sig. (2-tailed) . df 0 Gender LOS Correlation 1.000 -.008 & BMI & R Sig. (2-tailed) . .954 & Ethnic df 0 53 & M-EL V Correlation -.008 1.000 & F-EL STM Sig. (2-tailed) .954 . df 53 0 a. Cells contain zero-order (Pearson) correlations.

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Table 35:

Partial Correlations Between Object Control Skills (OCS) and Verbal STM (V-STM)

Controlling for Gender (G), BMI, Region (R), Ethnicity (Eth), and Mother's (M) and Father's (F)

Education Levels (EL)

Control Variables OCS VSTM G BMI R Eth MEL FEL -none-a OCS Correlation 1.000 .291 -.431 .078 -.064 .141 .126 .100 Sig. (2-tailed) . .023 .001 .548 .623 .277 .332 .445 df 0 59 59 59 59 59 59 59 VSTM Correlation 1.000 .090 -.216 -.192 .101 .173 .163 Sig.(2-tailed) . .492 .095 .138 .437 .181 .209 df 0 59 59 59 59 59 59 G Correlation 1.000 -.175 -.057 -.057 .099 .193 Sig. (2-tailed) . .177 .660 .660 .449 .136 df 0 59 59 59 59 59 BMI Correlation 1.000 -.101 -.012 -.018 -.076 Sig. (2-tailed) . .438 .929 .888 .561 df 0 59 59 59 59 R Correlation 1.000 -.041 .341 .435 Sig.(2-tailed) . .751 .007 .000 df 0 59 59 59 Eth Correlation 1.000 -.014 .058 Sig. (2-tailed) . .915 .656 df 0 59 59 MEL Correlation 1.000 .591 Sig. (2-tailed) . .000 df 0 59 FEL Correlation 1.000 Sig. (2-tailed) . df 0 Gender OCS Correlation 1.000 .292 & BMI & R Sig. (2-tailed) . .031 & Eth df 0 53 & MEL V- Correlation .292 1.000 & FEL STM Sig. (2-tailed) .031 . df 53 0 a. Cells contain zero-order (Pearson) correlations.

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Table 36:

Partial Correlations between Total FMS, Verbal Short-Term Memory, and Controlling for

Gender (G.), BMI, Region (R.), Ethnicity (Eth), and Mother’ (M) and Father’ (F) education level

(EL)

Control Variables TFMS VSTM G BMI R. Eth MEL FEL -none-a TFMS Correlation 1.000 .096 -.320 -.009 .210 .114 .299 .232 Sig. (2-tailed) . .462 .012 .947 .104 .383 .019 .071 df 0 59 59 59 59 59 59 59 VSTM Correlation 1.000 .090 -.216 -.192 .101 .173 .163 Sig. (2-tailed) . .492 .095 .138 .437 .181 .209 df 0 59 59 59 59 59 59 G Correlation 1.000 -.175 -.057 -.057 .099 .193 Sig. (2-tailed) . .177 .660 .660 .449 .136 df 0 59 59 59 59 59 BMI Correlation 1.000 -.101 -.012 -.018 -.076 Sig. (2-tailed) . .438 .929 .888 .561 df 0 59 59 59 59 R Correlation 1.000 -.041 .341 .435 Sig. (2-tailed) . .751 .007 .000 df 0 59 59 59 Eth Correlation 1.000 -.014 .058 Sig. (2-tailed) . .915 .656 df 0 59 59 MEL Correlation 1.000 .591 Sign (2-tailed) . .000 df 0 59 FEL Correlation 1.000 Sig. (2-tailed) . df 0 Gender Total Correlation 1.000 .069 & BMI FMS & R Sig. (2-tailed) . .616 & Eth df 0 53 & MEL V Correlation .069 1.000 & FEL STM Sign (2-tailed) .616 . df 53 0 a. Cells contain zero-order (Pearson) correlations.

147

Table 37:

Partial Correlations Between Locomotor Skills (LOS) and Visuospatial STM (VS-STM)

Controlling for Gender (G), BMI, Region (R), Ethnicity (Eth), and Mother's (M) and Father's (F)

Education Levels (EL)

Control Variables LOS VSSTM G BMI R Eth MEL FEL -none-a LOS Correlation 1.000 -.070 -.068 -.157 .373 .140 .381 .285 Sig. (2-tailed) . .591 .603 .226 .003 .281 .002 .026 df 0 59 59 59 59 59 59 59 VS Correlation 1.000 .031 -.087 -.335 .177 -.117 .006 STM Sig. (2-tailed) . .811 .505 .008 .172 .369 .964 df 0 59 59 59 59 59 59 G Correlation 1.000 -.175 -.057 -.057 .099 .193 Sig. (2-tailed) . .177 .660 .660 .449 .136 df 0 59 59 59 59 59 BMI Correlation 1.000 -.101 -.012 -.018 -.076 Sig. (2-tailed) . .438 .929 .888 .561 df 0 59 59 59 59 R Correlation 1.000 -.041 .341 .435 Sig. (2-tailed) . .751 .007 .000 df 0 59 59 59 Eth Correlation 1.000 -.014 .058 Sig. (2-tailed) . .915 .656 df 0 59 59 MEL Correlation 1.000 .591 Sig. (2-tailed) . .000 df 0 59 FEL Correlation 1.000 Sig. (2-tailed) . df 0 Gender LOS Correlation 1.000 .022 & BMI & R Sig. (2-tailed) . .875 & Eth df 0 53 & MEL VS Correlation .022 1.000 & FEL STM Sig. (2-tailed) .875 . df 53 0 a. Cells contain zero-order (Pearson) correlations.

148

Table 38:

Partial Correlations Between Object Control Skills (OCS) and Visuospatial STM (VS-STM)

Controlling for Gender (G), BMI, Region (R), Ethnicity (Eth), and Mother's (M) and Father's (F)

Education Levels (EL)

Control Variables OCS VSSTM G BMI R Eth MEL FEL -none-a OCS Correlation 1.000 .094 -.431 .078 -.064 .141 .126 .100 Sig. (2-tailed) . .473 .001 .548 .623 .277 .332 .445 df 0 59 59 59 59 59 59 59 VS Correlation 1.000 .031 -.087 -.335 .177 -.117 .006 STM Sig. (2-tailed) . .811 .505 .008 .172 .369 .964 df 0 59 59 59 59 59 59 G Correlation 1.000 -.175 -.057 -.057 .099 .193 Sig. (2-tailed) . .177 .660 .660 .449 .136 df 0 59 59 59 59 59 BMI Correlation 1.000 -.101 -.012 -.018 -.076 Sig. (2-tailed) . .438 .929 .888 .561 df 0 59 59 59 59 R Correlation 1.000 -.041 .341 .435 Sig.(2-tailed) . .751 .007 .000 df 0 59 59 59 Eth Correlation 1.000 -.014 .058 Sig. (2-tailed) . .915 .656 df 0 59 59 MEL Correlation 1.000 .591 Sig. (2-tailed) . .000 df 0 59 FEL Correlation 1.000 Sig. (2-tailed) . df 0 Gender OCS Correlation 1.000 .039 & BMI & R Sig. (2-tailed) . .779 & Eth df 0 53 & MEL VS Correlation .039 1.000 & FEL STM Sig. (2-tailed) .779 . df 53 0 a. Cells contain zero-order (Pearson) correlations.

149

Table 39:

Partial Correlations Between Total FMS (TFMS) and Visuospatial STM (VSSTM) Controlling for Gender (G), BMI, Region (R), Ethnicity (Eth), and Mother's (M) and Father's (F) Education

Levels (EL)

Control Variables TFMS VSSTM G BMI R Eth MEL FEL -none-a TFMS Correlation 1.000 -.046 -.320 -.009 .210 .114 .299 .232 Sig. (2-tailed) . .723 .012 .947 .104 .383 .019 .071 df 0 59 59 59 59 59 59 59 VS Correlation 1.000 .031 -.087 -.335 .177 -.117 .006 STM Sig. (2-tailed) . .811 .505 .008 .172 .369 .964 df 0 59 59 59 59 59 59 G Correlation 1.000 -.175 -.057 -.057 .099 .193 Sig. (2-tailed) . .177 .660 .660 .449 .136 df 0 59 59 59 59 59 BMI Correlation 1.000 -.101 -.012 -.018 -.076 Sig. (2-tailed) . .438 .929 .888 .561 df 0 59 59 59 59 R Correlation 1.000 -.041 .341 .435 Sig.(2-tailed) . .751 .007 .000 df 0 59 59 59 Ethnic Correlation 1.000 -.014 .058 Sig. (2-tailed) . .915 .656 df 0 59 59 MEL Correlation 1.000 .591 Sig. (2-tailed) . .000 df 0 59 FEL Correlation 1.000 Sig. (2-tailed) . df 0 Gender TFMS Correlation 1.000 -.015 & BMI & R Sig. (2-tailed) . .915 & Eth df 0 53 & MEL VS Correlation -.015 1.000 & FEL STM Sig. (2-tailed) .915 . df 53 0 a. Cells contain zero-order (Pearson) correlations.

150

APPENDIX H

Regions for Data Collection

151

Table 40:

Regions for Data Collection

The name Places where the FMS and FMS Assessment Place to test Participants Region of the verbal STM and visuospatial Number of camera verbal STM & (N=61) Place Region STM were conducted used visuospatial STM 4/ 4 station A quite room at Region1 Okemos 20 (32.8%) Hiawatha Elementary School Gymnasium Each station the school included 3 skills 1/ 1 station East Department of Kinesiology, A quite room at Region 2 15 (24.3%) Gymnasium For testing all Lansing Michigan State University the department FMS Tennis court 1/ 1 station A quite room at Region 3 Lansing 13 (21.3%) Parents’ home close to For testing all the parent’s home parents’ home FMS Tennis court 1/ 1 station Grand St. Paul Chaldean Catholic A quite room at Region 4 6 (9.8%) close to For testing all Blanc Church the church church FMS Our Lady of Lebanon Tennis court 1/ 1 station A quite room at Region 5 Flint 6 (9.8%) Maronite close to For testing all the church Catholic Church church FMS

152

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