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Committee on Physical Activity and Physical Education in the School Environment; Food and Nutrition Board; Institute of Medicine; Kohl HW III, Cook HD, editors. Educating the Student Body: Taking Physical Activity and Physical Education to School. Washington (DC): National Academies Press (US); 2013 Oct 30.

Cover of Educating the Student Body

Educating the Student Body: Taking Physical Activity and Physical Education to School.

  • Hardcopy Version at National Academies Press

4 Physical Activity, Fitness, and Physical Education: Effects on Academic Performance

Key messages.

  • Evidence suggests that increasing physical activity and physical fitness may improve academic performance and that time in the school day dedicated to recess, physical education class, and physical activity in the classroom may also facilitate academic performance.
  • Available evidence suggests that mathematics and reading are the academic topics that are most influenced by physical activity. These topics depend on efficient and effective executive function, which has been linked to physical activity and physical fitness.
  • Executive function and brain health underlie academic performance. Basic cognitive functions related to attention and memory facilitate learning, and these functions are enhanced by physical activity and higher aerobic fitness.
  • Single sessions of and long-term participation in physical activity improve cognitive performance and brain health. Children who participate in vigorous- or moderate-intensity physical activity benefit the most.
  • Given the importance of time on task to learning, students should be provided with frequent physical activity breaks that are developmentally appropriate.
  • Although presently understudied, physically active lessons offered in the classroom may increase time on task and attention to task in the classroom setting.

Although academic performance stems from a complex interaction between intellect and contextual variables, health is a vital moderating factor in a child's ability to learn. The idea that healthy children learn better is empirically supported and well accepted ( Basch, 2010 ), and multiple studies have confirmed that health benefits are associated with physical activity, including cardiovascular and muscular fitness, bone health, psychosocial outcomes, and cognitive and brain health ( Strong et al., 2005 ; see Chapter 3 ). The relationship of physical activity and physical fitness to cognitive and brain health and to academic performance is the subject of this chapter.

Given that the brain is responsible for both mental processes and physical actions of the human body, brain health is important across the life span. In adults, brain health, representing absence of disease and optimal structure and function, is measured in terms of quality of life and effective functioning in activities of daily living. In children, brain health can be measured in terms of successful development of attention, on-task behavior, memory, and academic performance in an educational setting. This chapter reviews the findings of recent research regarding the contribution of engagement in physical activity and the attainment of a health-enhancing level of physical fitness to cognitive and brain health in children. Correlational research examining the relationship among academic performance, physical fitness, and physical activity also is described. Because research in older adults has served as a model for understanding the effects of physical activity and fitness on the developing brain during childhood, the adult research is briefly discussed. The short- and long-term cognitive benefits of both a single session of and regular participation in physical activity are summarized.

Before outlining the health benefits of physical activity and fitness, it is important to note that many factors influence academic performance. Among these are socioeconomic status ( Sirin, 2005 ), parental involvement ( Fan and Chen, 2001 ), and a host of other demographic factors. A valuable predictor of student academic performance is a parent having clear expectations for the child's academic success. Attendance is another factor confirmed as having a significant impact on academic performance ( Stanca, 2006 ; Baxter et al., 2011 ). Because children must be present to learn the desired content, attendance should be measured in considering factors related to academic performance.


State-mandated academic achievement testing has had the unintended consequence of reducing opportunities for children to be physically active during the school day and beyond. In addition to a general shifting of time in school away from physical education to allow for more time on academic subjects, some children are withheld from physical education classes or recess to participate in remedial or enriched learning experiences designed to increase academic performance ( Pellegrini and Bohn, 2005 ; see Chapter 5 ). Yet little evidence supports the notion that more time allocated to subject matter will translate into better test scores. Indeed, 11 of 14 correlational studies of physical activity during the school day demonstrate a positive relationship to academic performance ( Rasberry et al., 2011 ). Overall, a rapidly growing body of work suggests that time spent engaged in physical activity is related not only to a healthier body but also to a healthier mind ( Hillman et al., 2008 ).

Children respond faster and with greater accuracy to a variety of cognitive tasks after participating in a session of physical activity ( Tomporowski, 2003 ; Budde et al., 2008 ; Hillman et al., 2009 ; Pesce et al., 2009 ; Ellemberg and St-Louis-Deschênes, 2010 ). A single bout of moderate-intensity physical activity has been found to increase neural and behavioral concomitants associated with the allocation of attention to a specific cognitive task ( Hillman et al., 2009 ; Pontifex et al., 2012 ). And when children who participated in 30 minutes of aerobic physical activity were compared with children who watched television for the same amount of time, the former children cognitively outperformed the latter ( Ellemberg and St-Louis-Desêhenes, 2010 ). Visual task switching data among 69 overweight and inactive children did not show differences between cognitive performance after treadmill walking and sitting ( Tomporowski et al., 2008b ).

When physical activity is used as a break from academic learning time, postengagement effects include better attention ( Grieco et al., 2009 ; Bartholomew and Jowers, 2011 ), increased on-task behaviors ( Mahar et al., 2006 ), and improved academic performance ( Donnelly and Lambourne, 2011 ). Comparisons between 1st-grade students housed in a classroom with stand-sit desks where the child could stand at his/her discretion and in classrooms containing traditional furniture showed that the former children were highly likely to stand, thus expending significantly more energy than those who were seated ( Benden et al., 2011 ). More important, teachers can offer physical activity breaks as part of a supplemental curriculum or simply as a way to reset student attention during a lesson ( Kibbe et al., 2011 ; see Chapter 6 ) and when provided with minimal training can efficaciously produce vigorous or moderate energy expenditure in students ( Stewart et al., 2004 ). Further, after-school physical activity programs have demonstrated the ability to improve cardiovascular endurance, and this increase in aerobic fitness has been shown to mediate improvements in academic performance ( Fredericks et al., 2006 ), as well as the allocation of neural resources underlying performance on a working memory task ( Kamijo et al., 2011 ).

Over the past three decades, several reviews and meta-analyses have described the relationship among physical fitness, physical activity, and cognition (broadly defined as all mental processes). The majority of these reviews have focused on the relationship between academic performance and physical fitness—a physiological trait commonly defined in terms of cardiorespiratory capacity (e.g., maximal oxygen consumption; see Chapter 3 ). More recently, reviews have attempted to describe the effects of an acute or single bout of physical activity, as a behavior, on academic performance. These reviews have focused on brain health in older adults ( Colcombe and Kramer, 2003 ), as well as the effects of acute physical activity on cognition in adults ( Tomporowski, 2003 ). Some have considered age as part of the analysis ( Etnier et al., 1997 , 2006 ). Reviews focusing on research conducted in children ( Sibley and Etnier, 2003 ) have examined the relationship among physical activity, participation in sports, and academic performance ( Trudeau and Shephard, 2008 , 2010 ; Singh et al., 2012 ); physical activity and mental and cognitive health ( Biddle and Asare, 2011 ); and physical activity, nutrition, and academic performance ( Burkhalter and Hillman, 2011 ). The findings of most of these reviews align with the conclusions presented in a meta-analytic review conducted by Fedewa and Ahn (2011) . The studies reviewed by Fedewa and Ahn include experimental/quasi-experimental as well as cross-sectional and correlational designs, with the experimental designs yielding the highest effect sizes. The strongest relationships were found between aerobic fitness and achievement in mathematics, followed by IQ and reading performance. The range of cognitive performance measures, participant characteristics, and types of research design all mediated the relationship among physical activity, fitness, and academic performance. With regard to physical activity interventions, which were carried out both within and beyond the school day, those involving small groups of peers (around 10 youth of a similar age) were associated with the greatest gains in academic performance.

The number of peer-reviewed publications on this topic is growing exponentially. Further evidence of the growth of this line of inquiry is its increased global presence. Positive relationships among physical activity, physical fitness, and academic performance have been found among students from the Netherlands ( Singh et al., 2012 ) and Taiwan ( Chih and Chen, 2011 ). Broadly speaking, however, many of these studies show small to moderate effects and suffer from poor research designs ( Biddle and Asare, 2011 ; Singh et al., 2012 ).

Basch (2010) conducted a comprehensive review of how children's health and health disparities influence academic performance and learning. The author's report draws on empirical evidence suggesting that education reform will be ineffective unless children's health is made a priority. Basch concludes that schools may be the only place where health inequities can be addressed and that, if children's basic health needs are not met, they will struggle to learn regardless of the effectiveness of the instructional materials used. More recently, Efrat (2011) conducted a review of physical activity, fitness, and academic performance to examine the achievement gap. He discovered that only seven studies had included socioeconomic status as a variable, despite its known relationship to education ( Sirin, 2005 ).

Physical Fitness as a Learning Outcome of Physical Education and Its Relation to Academic Performance

Achieving and maintaining a healthy level of aerobic fitness, as defined using criterion-referenced standards from the National Health and Nutrition Examination Survey (NHANES; Welk et al., 2011 ), is a desired learning outcome of physical education programming. Regular participation in physical activity also is a national learning standard for physical education, a standard intended to facilitate the establishment of habitual and meaningful engagement in physical activity ( NASPE, 2004 ). Yet although physical fitness and participation in physical activity are established as learning outcomes in all 50 states, there is little evidence to suggest that children actually achieve and maintain these standards (see Chapter 2 ).

Statewide and national datasets containing data on youth physical fitness and academic performance have increased access to student-level data on this subject ( Grissom, 2005 ; Cottrell et al., 2007 ; Carlson et al., 2008 ; Chomitz et al., 2008 ; Wittberg et al., 2010 ; Van Dusen et al., 2011 ). Early research in South Australia focused on quantifying the benefits of physical activity and physical education during the school day; the benefits noted included increased physical fitness, decreased body fat, and reduced risk for cardiovascular disease ( Dwyer et al., 1979 , 1983 ). Even today, Dwyer and colleagues are among the few scholars who regularly include in their research measures of physical activity intensity in the school environment, which is believed to be a key reason why they are able to report differentiated effects of different intensities. A longitudinal study in Trois-Rivières, Québec, Canada, tracked how the academic performance of children from grades 1 through 6 was related to student health, motor skills, and time spent in physical education. The researchers concluded that additional time dedicated to physical education did not inhibit academic performance ( Shephard et al., 1984 ; Shephard, 1986 ; Trudeau and Shephard, 2008 ).

Longitudinal follow-up investigating the long-term benefits of enhanced physical education experiences is encouraging but largely inconclusive. In a study examining the effects of daily physical education during elementary school on physical activity during adulthood, 720 men and women completed the Québec Health Survey ( Trudeau et al., 1999 ). Findings suggest that physical education was associated with physical activity in later life for females but not males ( Trudeau et al., 1999 ); most of the associations were significant but weak ( Trudeau et al., 2004 ). Adult body mass index (BMI) at age 34 was related to childhood BMI at ages 10-12 in females but not males ( Trudeau et al., 2001 ). Longitudinal studies such as those conducted in Sweden and Finland also suggest that physical education experiences may be related to adult engagement in physical activity ( Glenmark, 1994 ; Telama et al., 1997 ). From an academic performance perspective, longitudinal data on men who enlisted for military service imply that cardiovascular fitness at age 18 predicted cognitive performance in later life (Aberg et al., 2009), thereby supporting the idea of offering physical education and physical activity opportunities well into emerging adulthood through secondary and postsecondary education.

Castelli and colleagues (2007) investigated younger children (in 3rd and 5th grades) and the differential contributions of the various subcomponents of the Fitnessgram ® . Specifically, they examined the individual contributions of aerobic capacity, muscle strength, muscle flexibility, and body composition to performance in mathematics and reading on the Illinois Standardized Achievement Test among a sample of 259 children. Their findings corroborate those of the California Department of Education ( Grissom, 2005 ), indicating a general relationship between fitness and achievement test performance. When the individual components of the Fitnessgram were decomposed, the researchers determined that only aerobic capacity was related to test performance. Muscle strength and flexibility showed no relationship, while an inverse association of BMI with test performance was observed, such that higher BMI was associated with lower test performance. Although Baxter and colleagues (2011) confirmed the importance of attending school in relation to academic performance through the use of 4th-grade student recall, correlations with BMI were not significant.

State-mandated implementation of the coordinated school health model requires all schools in Texas to conduct annual fitness testing using the Fitnessgram among students in grades 3-12. In a special issue of Research Quarterly for Exercise and Sport (2010), multiple articles describe the current state of physical fitness among children in Texas; confirm the associations among school performance levels, academic achievement, and physical fitness ( Welk et al., 2010 ; Zhu et al., 2010 ); and demonstrate the ability of qualified physical education teachers to administer physical fitness tests ( Zhu et al., 2010 ). Also using data from Texas schools, Van Dusen and colleagues (2011) found that cardiovascular fitness had the strongest association with academic performance, particularly in mathematics over reading. Unlike previous research, which demonstrated a steady decline in fitness by developmental stage ( Duncan et al., 2007 ), this study found that cardiovascular fitness did decrease but not significantly ( Van Dusen et al., 2011 ). Aerobic fitness, then, may be important to academic performance, as there may be a dose-response relationship ( Van Dusen et al., 2011 ).

Using a large sample of students in grades 4-8, Chomitz and colleagues (2008) found that the likelihood of passing both mathematics and English achievement tests increased with the number of fitness tests passed during physical education class, and the odds of passing the mathematics achievement tests were inversely related to higher body weight. Similar to the findings of Castelli and colleagues (2007) , socioeconomic status and demographic factors explained little of the relationship between aerobic fitness and academic performance; however, socioeconomic status may be an explanatory variable for students of low fitness ( London and Castrechini, 2011 ).

In sum, numerous cross-sectional and correlational studies demonstrate small-to-moderate positive or null associations between physical fitness ( Grissom, 2005 ; Cottrell et al., 2007 ; Edwards et al., 2009; Eveland-Sayers et al., 2009 ; Cooper et al., 2010 ; Welk et al., 2010 ; Wittberg et al., 2010 ; Zhu et al., 2010 ; Van Dusen et al., 2011 ), particularly aerobic fitness, and academic performance ( Castelli et al, 2007 ; Chomitz et al., 2008 ; Roberts et al., 2010 ; Welk et al., 2010 ; Chih and Chen, 2011 ; London and Castrechini, 2011 ; Van Dusen et al., 2011 ). Moreover, the findings may support a dose-response association, suggesting that the more components of physical fitness (e.g., cardiovascular endurance, strength, muscle endurance) considered acceptable for the specific age and gender that are present, the greater the likelihood of successful academic performance. From a public health and policy standpoint, the conclusions these findings support are limited by few causal inferences, a lack of data confirmation, and inadequate reliability because the data were often collected by nonresearchers or through self-report methods. It may also be noted that this research includes no known longitudinal studies and few randomized controlled trials (examples are included later in this chapter in the discussion of the developing brain).

Physical Activity, Physical Education, and Academic Performance

In contrast with the correlational data presented above for physical fitness, more information is needed on the direct effects of participation in physical activity programming and physical education classes on academic performance.

In a meta-analysis, Sibley and Etnier (2003) found a positive relationship between physical activity and cognition in school-age youth (aged 4-18), suggesting that physical activity, as well as physical fitness, may be related to cognitive outcomes during development. Participation in physical activity was related to cognitive performance in eight measurement categories (perceptual skills, IQ, achievement, verbal tests, mathematics tests, memory, developmental level/academic readiness, and “other”), with results indicating a beneficial relationship of physical activity to all cognitive outcomes except memory ( Sibley and Etnier, 2003 ). Since that meta-analysis, however, several papers have reported robust relationships between aerobic fitness and different aspects of memory in children (e.g., Chaddock et al., 2010a , 2011 ; Kamijo et al., 2011 ; Monti et al., 2012 ). Regardless, the comprehensive review of Sibley and Etnier (2003) was important because it helped bring attention to an emerging literature suggesting that physical activity may benefit cognitive development even as it also demonstrated the need for further study to better understand the multifaceted relationship between physical activity and cognitive and brain health.

The regular engagement in physical activity achieved during physical education programming can also be related to academic performance, especially when the class is taught by a physical education teacher. The Sports, Play, and Active Recreation for Kids (SPARK) study examined the effects of a 2-year health-related physical education program on academic performance in children ( Sallis et al., 1999 ). In an experimental design, seven elementary schools were randomly assigned to one of three conditions: (1) a specialist condition in which certified physical education teachers delivered the SPARK curriculum, (2) a trained-teacher condition in which classroom teachers implemented the curriculum, and (3) a control condition in which classroom teachers implemented the local physical education curriculum. No significant differences by condition were found for mathematics testing; however, reading scores were significantly higher in the specialist condition relative to the control condition ( Sallis et al., 1999 ), while language scores were significantly lower in the specialist condition than in the other two conditions. The authors conclude that spending time in physical education with a specialist did not have a negative effect on academic performance. Shortcomings of this research include the amount of data loss from pre- to posttest, the use of results of 2nd-grade testing that exceeded the national average in performance as baseline data, and the use of norm-referenced rather than criterion-based testing.

In seminal research conducted by Gabbard and Barton (1979) , six different conditions of physical activity (no activity; 20, 30, 40, and 50 minutes; and posttest no activity) were completed by 106 2nd graders during physical education. Each physical activity session was followed by 5 minutes of rest and the completion of 36 math problems. The authors found a potential threshold effect whereby only the 50-minute condition improved mathematical performance, with no differences by gender.

A longitudinal study of the kindergarten class of 1998–1999, using data from the Early Childhood Longitudinal Study, investigated the association between enrollment in physical education and academic achievement ( Carlson et al., 2008 ). Higher amounts of physical education were correlated with better academic performance in mathematics among females, but this finding did not hold true for males.

Ahamed and colleagues (2007) found in a cluster randomized trial that, after 16 months of a classroom-based physical activity intervention, there was no significant difference between the treatment and control groups in performance on the standardized Cognitive Abilities Test, Third Edition (CAT-3). Others have found, however, that coordinative exercise ( Budde et al., 2008 ) or bouts of vigorous physical activity during free time ( Coe et al., 2006 ) contribute to higher levels of academic performance. Specifically, Coe and colleagues examined the association of enrollment in physical education and self-reported vigorous- or moderate-intensity physical activity outside school with performance in core academic courses and on the Terra Nova Standardized Achievement Test among more than 200 6th-grade students. Their findings indicate that academic performance was unaffected by enrollment in physical education classes, which were found to average only 19 minutes of vigorous- or moderate-intensity physical activity. When time spent engaged in vigorous- or moderate-intensity physical activity outside of school was considered, however, a significant positive relation to academic performance emerged, with more time engaged in vigorous- or moderate-intensity physical activity being related to better grades but not test scores ( Coe et al., 2006 ).

Studies of participation in sports and academic achievement have found positive associations ( Mechanic and Hansell, 1987 ; Dexter, 1999 ; Crosnoe, 2002 ; Eitle and Eitle, 2002 ; Stephens and Schaben, 2002 ; Eitle, 2005 ; Miller et al., 2005 ; Fox et al., 2010 ; Ruiz et al., 2010 ); higher grade point averages (GPAs) in season than out of season ( Silliker and Quirk, 1997 ); a negative association between cheerleading and science performance ( Hanson and Kraus, 1998 ); and weak and negative associations between the amount of time spent participating in sports and performance in English-language class among 13-, 14-, and 16-year-old students ( Daley and Ryan, 2000 ). Other studies, however, have found no association between participation in sports and academic performance ( Fisher et al., 1996 ). The findings of these studies need to be interpreted with caution as many of their designs failed to account for the level of participation by individuals in the sport (e.g., amount of playing time, type and intensity of physical activity engagement by sport). Further, it is unclear whether policies required students to have higher GPAs to be eligible for participation. Offering sports opportunities is well justified regardless of the cognitive benefits, however, given that adolescents may be less likely to engage in risky behaviors when involved in sports or other extracurricular activities ( Page et al., 1998 ; Elder et al., 2000 ; Taliaferro et al., 2010 ), that participation in sports increases physical fitness, and that affiliation with sports enhances school connectedness.

Although a consensus on the relationship of physical activity to academic achievement has not been reached, the vast majority of available evidence suggests the relationship is either positive or neutral. The meta-analytic review by Fedewa and Ahn (2011) suggests that interventions entailing aerobic physical activity have the greatest impact on academic performance; however, all types of physical activity, except those involving flexibility alone, contribute to enhanced academic performance, as do interventions that use small groups (about 10 students) rather than individuals or large groups. Regardless of the strength of the findings, the literature indicates that time spent engaged in physical activity is beneficial to children because it has not been found to detract from academic performance, and in fact can improve overall health and function ( Sallis et al., 1999 ; Hillman et al., 2008 ; Tomporowski et al., 2008a ; Trudeau and Shephard, 2008 ; Rasberry et al., 2011 ).

Single Bouts of Physical Activity

Beyond formal physical education, evidence suggests that multi-component approaches are a viable means of providing physical activity opportunities for children across the school curriculum (see also Chapter 6 ). Although health-related fitness lessons taught by certified physical education teachers result in greater student fitness gains relative to such lessons taught by other teachers ( Sallis et al., 1999 ), non-physical education teachers are capable of providing opportunities to be physically active within the classroom ( Kibbe et al., 2011 ). Single sessions or bouts of physical activity have independent merit, offering immediate benefits that can enhance the learning experience. Studies have found that single bouts of physical activity result in improved attention ( Hillman et al., 2003 , 2009 ; Pontifex et al., 2012 ), better working memory ( Pontifex et al., 2009 ), and increased academic learning time and reduced off-task behaviors ( Mahar et al., 2006 ; Bartholomew and Jowers, 2011 ). Yet single bouts of physical activity have differential effects, as very vigorous exercise has been associated with cognitive fatigue and even cognitive decline in adults ( Tomporowski, 2003 ). As seen in Figure 4-1 , high levels of effort, arousal, or activation can influence perception, decision making, response preparation, and actual response. For discussion of the underlying constructs and differential effects of single bouts of physical activity on cognitive performance, see Tomporowski (2003) .

Information processing: Diagram of a simplified version of Sanders's (1983) cognitive-energetic model of human information processing (adapted from Jones and Hardy, 1989). SOURCE: Tomporowski, 2003. Reprinted with permission.

For children, classrooms are busy places where they must distinguish relevant information from distractions that emerge from many different sources occurring simultaneously. A student must listen to the teacher, adhere to classroom procedures, focus on a specific task, hold and retain information, and make connections between novel information and previous experiences. Hillman and colleagues (2009) demonstrated that a single bout of moderate-intensity walking (60 percent of maximum heart rate) resulted in significant improvements in performance on a task requiring attentional inhibition (e.g., the ability to focus on a single task). These findings were accompanied by changes in neuroelectric measures underlying the allocation of attention (see Figure 4-2 ) and significant improvements on the reading subtest of the Wide Range Achievement Test. No such effects were observed following a similar duration of quiet rest. These findings were later replicated and extended to demonstrate benefits for both mathematics and reading performance in healthy children and those diagnosed with attention deficit hyperactivity disorder ( Pontifex et al., 2013 ). Further replications of these findings demonstrated that a single bout of moderate-intensity exercise using a treadmill improved performance on a task of attention and inhibition, but similar benefits were not derived from moderate-intensity exercise that involved exergaming ( O'Leary et al., 2011 ). It was also found that such benefits were derived following cessation of, but not during, the bout of exercise ( Drollette et al., 2012 ). The applications of such empirical findings within the school setting remain unclear.

Effects of a single session of exercise in preadolescent children. SOURCE: Hillman et al., 2009. Reprinted with permission.

A randomized controlled trial entitled Physical Activity Across the Curriculum (PAAC) used cluster randomization among 24 schools to examine the effects of physically active classroom lessons on BMI and academic achievement ( Donnelly et al., 2009 ). The academically oriented physical activities were intended to be of vigorous or moderate intensity (3–6 metabolic equivalents [METs]) and to last approximately 10 minutes and were specifically designed to supplement content in mathematics, language arts, geography, history, spelling, science, and health. The study followed 665 boys and 677 girls for 3 years as they rose from 2nd or 3rd to 4th or 5th grades. Changes in academic achievement, fitness, and blood screening were considered secondary outcomes. During a 3-year period, students who engaged in physically active lessons, on average, improved their academic achievement by 6 percent, while the control groups exhibited a 1 percent decrease. In students who experienced at least 75 minutes of PAAC lessons per week, BMI remained stable (see Figure 4-3 ).

Change in academic scores from baseline after physically active classroom lessons in elementary schools in northeast Kansas (2003–2006). NOTE: All differences between the Physical Activity Across the Curriculum (PAAC) group ( N = 117) and control (more...)

It is important to note that cognitive tasks completed before, during, and after physical activity show varying effects, but the effects were always positive compared with sedentary behavior. In a study carried out by Drollette and colleagues (2012) , 36 preadolescent children completed two cognitive tasks—a flanker task to assess attention and inhibition and a spatial nback task to assess working memory—before, during, and after seated rest and treadmill walking conditions. The children sat or walked on different days for an average of 19 minutes. The results suggest that the physical activity enhanced cognitive performance for the attention task but not for the task requiring working memory. Accordingly, although more research is needed, the authors suggest that the acute effects of exercise may be selective to certain cognitive processes (i.e., attentional inhibition) while unrelated to others (e.g., working memory). Indeed, data collected using a task-switching paradigm (i.e., a task designed to assess multitasking and requiring the scheduling of attention to multiple aspects of the environment) among 69 overweight and inactive children did not show differences in cognitive performance following acute bouts of treadmill walking or sitting ( Tomporowski et al., 2008b ). Thus, findings to date indicate a robust relationship of acute exercise to transient improvements in attention but appear inconsistent for other aspects of cognition.

Academic Learning Time and On- and Off-Task Behaviors

Excessive time on task, inattention to task, off-task behavior, and delinquency are important considerations in the learning environment given the importance of academic learning time to academic performance. These behaviors are observable and of concern to teachers as they detract from the learning environment. Systematic observation by trained observers may yield important insight regarding the effects of short physical activity breaks on these behaviors. Indeed, systematic observations of student behavior have been used as an alternative means of measuring academic performance ( Mahar et al., 2006 ; Grieco et al., 2009 ).

After the development of classroom-based physical activities, called Energizers, teachers were trained in how to implement such activities in their lessons at least twice per week ( Mahar et al., 2006 ). Measurements of baseline physical activity and on-task behaviors were collected in two 3rd-grade and two 4th-grade classes, using pedometers and direct observation. The intervention included 243 students, while 108 served as controls by not engaging in the activities. A subgroup of 62 3rd and 4th graders was observed for on-task behavior in the classroom following the physical activity. Children who participated in Energizers took more steps during the school day than those who did not; they also increased their on-task behaviors by more than 20 percent over baseline measures.

A systematic review of a similar in-class, academically oriented, physical activity plan—Take 10!—was conducted to identify the effects of its implementation after it had been in use for 10 years ( Kibbe et al., 2011 ). The findings suggest that children who experienced Take 10! in the classroom engaged in moderate to vigorous physical activity (6.16 to 6.42 METs) and had lower BMIs than those who did not. Further, children in the Take 10! classrooms had better fluid intelligence ( Reed et al., 2010 ) and higher academic achievement scores ( Donnelly et al., 2009 ).

Some have expressed concern that introducing physical activity into the classroom setting may be distracting to students. Yet in one study it was sedentary students who demonstrated a decrease in time on task, while active students returned to the same level of on-task behavior after an active learning task ( Grieco et al., 2009 ). Among the 97 3rd-grade students in this study, a small but nonsignificant increase in on-task behaviors was seen immediately following these active lessons. Additionally, these improvements were not mediated by BMI.

In sum, although presently understudied, physically active lessons may increase time on task and attention to task in the classroom setting. Given the complexity of the typical classroom, the strategy of including content-specific lessons that incorporate physical activity may be justified.

It is recommended that every child have 20 minutes of recess each day and that this time be outdoors whenever possible, in a safe activity ( NASPE, 2006 ). Consistent engagement in recess can help students refine social skills, learn social mediation skills surrounding fair play, obtain additional minutes of vigorous- or moderate-intensity physical activity that contribute toward the recommend 60 minutes or more per day, and have an opportunity to express their imagination through free play ( Pellegrini and Bohn, 2005 ; see also Chapter 6 ). When children participate in recess before lunch, additional benefits accrue, such as less food waste, increased incidence of appropriate behavior in the cafeteria during lunch, and greater student readiness to learn upon returning to the classroom after lunch ( Getlinger et al., 1996 ; Wechsler et al., 2001 ).

To examine the effects of engagement in physical activity during recess on classroom behavior, Barros and colleagues (2009) examined data from the Early Childhood Longitudinal Study on 10,000 8- to 9-year-old children. Teachers provided the number of minutes of recess as well as a ranking of classroom behavior (ranging from “misbehaves frequently” to “behaves exceptionally well”). Results indicate that children who had at least 15 minutes of recess were more likely to exhibit appropriate behavior in the classroom ( Barros et al., 2009 ). In another study, 43 4th-grade students were randomly assigned to 1 or no days of recess to examine the effects on classroom behavior ( Jarrett et al., 1998 ). The researchers concluded that on-task behavior was better among the children who had recess. A moderate effect size (= 0.51) was observed. In a series of studies examining kindergartners' attention to task following a 20-minute recess, increased time on task was observed during learning centers and story reading ( Pellegrini et al., 1995 ). Despite these positive findings centered on improved attention, it is important to note that few of these studies actually measured the intensity of the physical activity during recess.

From a slightly different perspective, survey data from 547 Virginia elementary school principals suggest that time dedicated to student participation in physical education, art, and music did not negatively influence academic performance ( Wilkins et al., 2003 ). Thus, the strategy of reducing time spent in physical education to increase academic performance may not have the desired effect. The evidence on in-school physical activity supports the provision of physical activity breaks during the school day as a way to increase fluid intelligence, time on task, and attention. However, it remains unclear what portion of these effects can be attributed to a break from academic time and what portion is a direct result of the specific demands/characteristics of the physical activity.


The study of brain health has grown beyond simply measuring behavioral outcomes such as task performance and reaction time (e.g., cognitive processing speed). New technology has emerged that has allowed scientists to understand the impact of lifestyle factors on the brain from the body systems level down to the molecular level. A greater understanding of the cognitive components that subserve academic performance and may be amenable to intervention has thereby been gained. Research conducted in both laboratory and field settings has helped define this line of inquiry and identify some preliminary underlying mechanisms.

The Evidence Base on the Relationship of Physical Activity to Brain Health and Cognition in Older Adults

Despite the current focus on the relationship of physical activity to cognitive development, the evidence base is larger on the association of physical activity with brain health and cognition during aging. Much can be learned about how physical activity affects childhood cognition and scholastic achievement through this work. Despite earlier investigations into the relationship of physical activity to cognitive aging (see Etnier et al., 1997 , for a review), the field was shaped by the findings of Kramer and colleagues (1999) , who examined the effects of aerobic fitness training on older adults using a randomized controlled design. Specifically, 124 older adults aged 60 and 75 were randomly assigned to a 6-month intervention of either walking (i.e., aerobic training) or flexibility (i.e., nonaerobic) training. The walking group but not the flexibility group showed improved cognitive performance, measured as a shorter response time to the presented stimulus. Results from a series of tasks that tapped different aspects of cognitive control indicated that engagement in physical activity is a beneficial means of combating cognitive aging ( Kramer et al., 1999 ).

Cognitive control, or executive control, is involved in the selection, scheduling, and coordination of computational processes underlying perception, memory, and goal-directed action. These processes allow for the optimization of behavioral interactions within the environment through flexible modulation of the ability to control attention ( MacDonald et al., 2000 ; Botvinick et al., 2001 ). Core cognitive processes that make up cognitive control or executive control include inhibition, working memory, and cognitive flexibility ( Diamond, 2006 ), processes mediated by networks that involve the prefrontal cortex. Inhibition (or inhibitory control) refers to the ability to override a strong internal or external pull so as to act appropriately within the demands imposed by the environment ( Davidson et al., 2006 ). For example, one exerts inhibitory control when one stops speaking when the teacher begins lecturing. Working memory refers to the ability to represent information mentally, manipulate stored information, and act on the information ( Davidson et al., 2006 ). In solving a difficult mathematical problem, for example, one must often remember the remainder. Finally, cognitive flexibility refers to the ability to switch perspectives, focus attention, and adapt behavior quickly and flexibly for the purposes of goal-directed action ( Blair et al., 2005 ; Davidson et al., 2006 ; Diamond, 2006 ). For example, one must shift attention from the teacher who is teaching a lesson to one's notes to write down information for later study.

Based on their earlier findings on changes in cognitive control induced by aerobic training, Colcombe and Kramer (2003) conducted a meta-analysis to examine the relationship between aerobic training and cognition in older adults aged 55-80 using data from 18 randomized controlled exercise interventions. Their findings suggest that aerobic training is associated with general cognitive benefits that are selectively and disproportionately greater for tasks or task components requiring greater amounts of cognitive control. A second and more recent meta-analysis ( Smith et al., 2010 ) corroborates the findings of Colcombe and Kramer, indicating that aerobic exercise is related to attention, processing speed, memory, and cognitive control; however, it should be noted that smaller effect sizes were observed, likely a result of the studies included in the respective meta-analyses. In older adults, then, aerobic training selectively improves cognition.

Hillman and colleagues (2006) examined the relationship between physical activity and inhibition (one aspect of cognitive control) using a computer-based stimulus-response protocol in 241 individuals aged 15-71. Their results indicate that greater amounts of physical activity are related to decreased response speed across task conditions requiring variable amounts of inhibition, suggesting a generalized relationship between physical activity and response speed. In addition, the authors found physical activity to be related to better accuracy across conditions in older adults, while no such relationship was observed for younger adults. Of interest, this relationship was disproportionately larger for the condition requiring greater amounts of inhibition in the older adults, suggesting that physical activity has both a general and selective association with task performance ( Hillman et al., 2006 ).

With advances in neuroimaging techniques, understanding of the effects of physical activity and aerobic fitness on brain structure and function has advanced rapidly over the past decade. In particular, a series of studies ( Colcombe et al., 2003 , 2004 , 2006 ; Kramer and Erickson, 2007 ; Hillman et al., 2008 ) of older individuals has been conducted to elucidate the relation of aerobic fitness to the brain and cognition. Normal aging results in the loss of brain tissue ( Colcombe et al., 2003 ), with markedly larger loss evidenced in the frontal, temporal, and parietal regions ( Raz, 2000 ). Thus cognitive functions subserved by these brain regions (such as those involved in cognitive control and aspects of memory) are expected to decay more dramatically than other aspects of cognition.

Colcombe and colleagues (2003) investigated the relationship of aerobic fitness to gray and white matter tissue loss using magnetic resonance imaging (MRI) in 55 healthy older adults aged 55-79. They observed robust age-related decreases in tissue density in the frontal, temporal, and parietal regions using voxel-based morphometry, a technique used to assess brain volume. Reductions in the amount of tissue loss in these regions were observed as a function of fitness. Given that the brain structures most affected by aging also demonstrated the greatest fitness-related sparing, these initial findings provide a biological basis for fitness-related benefits to brain health during aging.

In a second study, Colcombe and colleagues (2006) examined the effects of aerobic fitness training on brain structure using a randomized controlled design with 59 sedentary healthy adults aged 60-79. The treatment group received a 6-month aerobic exercise (i.e., walking) intervention, while the control group received a stretching and toning intervention that did not include aerobic exercise. Results indicated that gray and white matter brain volume increased for those who received the aerobic fitness training intervention. No such results were observed for those assigned to the stretching and toning group. Specifically, those assigned to the aerobic training intervention demonstrated increased gray matter in the frontal lobes, including the dorsal anterior cingulate cortex, the supplementary motor area, the middle frontal gyrus, the dorsolateral region of the right inferior frontal gyrus, and the left superior temporal lobe. White matter volume changes also were evidenced following the aerobic fitness intervention, with increases in white matter tracts being observed within the anterior third of the corpus callosum. These brain regions are important for cognition, as they have been implicated in the cognitive control of attention and memory processes. These findings suggest that aerobic training not only spares age-related loss of brain structures but also may in fact enhance the structural health of specific brain regions.

In addition to the structural changes noted above, research has investigated the relationship between aerobic fitness and changes in brain function. That is, aerobic fitness training has also been observed to induce changes in patterns of functional activation. Functional MRI (fMRI) measures, which make it possible to image activity in the brain while an individual is performing a cognitive task, have revealed that aerobic training induces changes in patterns of functional activation. This approach involves inferring changes in neuronal activity from alteration in blood flow or metabolic activity in the brain. In a seminal paper, Colcombe and colleagues (2004) examined the relationship of aerobic fitness to brain function and cognition across two studies with older adults. In the first study, 41 older adult participants (mean age ~66) were divided into higher- and lower-fit groups based on their performance on a maximal exercise test. In the second study, 29 participants (aged 58-77) were recruited and randomly assigned to either a fitness training (i.e., walking) or control (i.e., stretching and toning) intervention. In both studies, participants were given a task requiring variable amounts of attention and inhibition. Results indicated that fitness (study 1) and fitness training (study 2) were related to greater activation in the middle frontal gyrus and superior parietal cortex; these regions of the brain are involved in attentional control and inhibitory functioning, processes entailed in the regulation of attention and action. These changes in neural activation were related to significant improvements in performance on the cognitive control task of attention and inhibition.

Taken together, the findings across studies suggest that an increase in aerobic fitness, derived from physical activity, is related to improvements in the integrity of brain structure and function and may underlie improvements in cognition across tasks requiring cognitive control. Although developmental differences exist, the general paradigm of this research can be applied to early stages of the life span, and some early attempts to do so have been made, as described below. Given the focus of this chapter on childhood cognition, it should be noted that this section has provided only a brief and arguably narrow look at the research on physical activity and cognitive aging. Considerable work has detailed the relationship of physical activity to other aspects of adult cognition using behavioral and neuroimaging tools (e.g., Boecker, 2011 ). The interested reader is referred to a number of review papers and meta-analyses describing the relationship of physical activity to various aspects of cognitive and brain health ( Etnier et al., 1997 ; Colcombe and Kramer, 2003 ; Tomporowski, 2003 ; Thomas et al., 2012 ).

Child Development, Brain Structure, and Function

Certain aspects of development have been linked with experience, indicating an intricate interplay between genetic programming and environmental influences. Gray matter, and the organization of synaptic connections in particular, appears to be at least partially dependent on experience (NRC/IOM, 2000; Taylor, 2006 ), with the brain exhibiting a remarkable ability to reorganize itself in response to input from sensory systems, other cortical systems, or insult ( Huttenlocher and Dabholkar, 1997 ). During typical development, experience shapes the pruning process through the strengthening of neural networks that support relevant thoughts and actions and the elimination of unnecessary or redundant connections. Accordingly, the brain responds to experience in an adaptive or “plastic” manner, resulting in the efficient and effective adoption of thoughts, skills, and actions relevant to one's interactions within one's environmental surroundings. Examples of neural plasticity in response to unique environmental interaction have been demonstrated in human neuroimaging studies of participation in music ( Elbert et al., 1995 ; Chan et al., 1998 ; Münte et al., 2001 ) and sports ( Hatfield and Hillman, 2001 ; Aglioti et al., 2008 ), thus supporting the educational practice of providing music education and opportunities for physical activity to children.

Effects of Regular Engagement in Physical Activity and Physical Fitness on Brain Structure

Recent advances in neuroimaging techniques have rapidly advanced understanding of the role physical activity and aerobic fitness may have in brain structure. In children a growing body of correlational research suggests differential brain structure related to aerobic fitness. Chaddock and colleagues (2010a , b ) showed a relationship among aerobic fitness, brain volume, and aspects of cognition and memory. Specifically, Chaddock and colleagues (2010a) assigned 9- to 10-year-old preadolescent children to lower- and higher-fitness groups as a function of their scores on a maximal oxygen uptake (VO 2 max) test, which is considered the gold-standard measure of aerobic fitness. They observed larger bilateral hippocampal volume in higher-fit children using MRI, as well as better performance on a task of relational memory. It is important to note that relational memory has been shown to be mediated by the hippocampus ( Cohen and Eichenbaum, 1993 ; Cohen et al., 1999 ). Further, no differences emerged for a task condition requiring item memory, which is supported by structures outside the hippocampus, suggesting selectivity among the aspects of memory that benefit from higher amounts of fitness. Lastly, hippocampal volume was positively related to performance on the relational memory task but not the item memory task, and bilateral hippocampal volume was observed to mediate the relationship between fitness and relational memory ( Chaddock et al., 2010a ). Such findings are consistent with behavioral measures of relational memory in children ( Chaddock et al., 2011 ) and neuroimaging findings in older adults ( Erickson et al., 2009 , 2011 ) and support the robust nonhuman animal literature demonstrating the effects of exercise on cell proliferation ( Van Praag et al., 1999 ) and survival ( Neeper et al., 1995 ) in the hippocampus.

In a second investigation ( Chaddock et al., 2010b ), higher- and lower-fit children (aged 9-10) underwent an MRI to determine whether structural differences might be found that relate to performance on a cognitive control task that taps attention and inhibition. The authors observed differential findings in the basal ganglia, a subcortical structure involved in the interplay of cognition and willed action. Specifically, higher-fit children exhibited greater volume in the dorsal striatum (i.e., caudate nucleus, putamen, globus pallidus) relative to lower-fit children, while no differences were observed in the ventral striatum. Such findings are not surprising given the role of the dorsal striatum in cognitive control and response resolution ( Casey et al., 2008 ; Aron et al., 2009 ), as well as the growing body of research in children and adults indicating that higher levels of fitness are associated with better control of attention, memory, and cognition ( Colcombe and Kramer, 2003 ; Hillman et al., 2008 ; Chang and Etnier, 2009 ). Chaddock and colleagues (2010b) further observed that higher-fit children exhibited increased inhibitory control and response resolution and that higher basal ganglia volume was related to better task performance. These findings indicate that the dorsal striatum is involved in these aspects of higher-order cognition and that fitness may influence cognitive control during preadolescent development. It should be noted that both studies described above were correlational in nature, leaving open the possibility that other factors related to fitness and/or the maturation of subcortical structures may account for the observed group differences.

Effects of Regular Engagement in Physical Activity and Physical Fitness on Brain Function

Other research has attempted to characterize fitness-related differences in brain function using fMRI and event-related brain potentials (ERPs), which are neuroelectric indices of functional brain activation in the electro-encephalographic time series. To date, few randomized controlled interventions have been conducted. Notably, Davis and colleagues (2011) conducted one such intervention lasting approximately 14 weeks that randomized 20 sedentary overweight preadolescent children into an after-school physical activity intervention or a nonactivity control group. The fMRI data collected during an antisaccade task, which requires inhibitory control, indicated increased bilateral activation of the prefrontal cortex and decreased bilateral activation of the posterior parietal cortex following the physical activity intervention relative to the control group. Such findings illustrate some of the neural substrates influenced by participation in physical activity. Two additional correlational studies ( Voss et al., 2011 ; Chaddock et al., 2012 ) compared higher- and lower-fit preadolescent children and found differential brain activation and superior task performance as a function of fitness. That is, Chaddock and colleagues (2012) observed increased activation in prefrontal and parietal brain regions during early task blocks and decreased activation during later task blocks in higher-fit relative to lower-fit children. Given that higher-fit children outperformed lower-fit children on the aspects of the task requiring the greatest amount of cognitive control, the authors reason that the higher-fit children were more capable of adapting neural activity to meet the demands imposed by tasks that tapped higher-order cognitive processes such as inhibition and goal maintenance. Voss and colleagues (2011) used a similar task to vary cognitive control requirements and found that higher-fit children outperformed their lower-fit counterparts and that such differences became more pronounced during task conditions requiring the upregulation of control. Further, several differences emerged across various brain regions that together make up the network associated with cognitive control. Collectively, these differences suggest that higher-fit children are more efficient in the allocation of resources in support of cognitive control operations.

Other imaging research has examined the neuroelectric system (i.e., ERPs) to investigate which cognitive processes occurring between stimulus engagement and response execution are influenced by fitness. Several studies ( Hillman et al., 2005 , 2009 ; Pontifex et al., 2011 ) have examined the P3 component of the stimulus-locked ERP and demonstrated that higher-fit children have larger-amplitude and shorter-latency ERPs relative to their lower-fit peers. Classical theory suggests that P3 relates to neuronal activity associated with revision of the mental representation of the previous event within the stimulus environment ( Donchin, 1981 ). P3 amplitude reflects the allocation of attentional resources when working memory is updated ( Donchin and Coles, 1988 ) such that P3 is sensitive to the amount of attentional resources allocated to a stimulus ( Polich, 1997 ; Polich and Heine, 2007 ). P3 latency generally is considered to represent stimulus evaluation and classification speed ( Kutas et al., 1977 ; Duncan-Johnson, 1981 ) and thus may be considered a measure of stimulus detection and evaluation time ( Magliero et al., 1984 ; Ila and Polich, 1999 ). Therefore the above findings suggest that higher-fit children allocate greater attentional resources and have faster cognitive processing speed relative to lower-fit children ( Hillman et al., 2005 , 2009 ), with additional research suggesting that higher-fit children also exhibit greater flexibility in the allocation of attentional resources, as indexed by greater modulation of P3 amplitude across tasks that vary in the amount of cognitive control required ( Pontifex et al., 2011 ). Given that higher-fit children also demonstrate better performance on cognitive control tasks, the P3 component appears to reflect the effectiveness of a subset of cognitive systems that support willed action ( Hillman et al., 2009 ; Pontifex et al., 2011 ).

Two ERP studies ( Hillman et al., 2009 ; Pontifex et al., 2011 ) have focused on aspects of cognition involved in action monitoring. That is, the error-related negativity (ERN) component was investigated in higher- and lower-fit children to determine whether differences in evaluation and regulation of cognitive control operations were influenced by fitness level. The ERN component is observed in response-locked ERP averages. It is often elicited by errors of commission during task performance and is believed to represent either the detection of errors during task performance ( Gehring et al., 1993 ; Holroyd and Coles, 2002 ) or more generally the detection of response conflict ( Botvinick et al., 2001 ; Yeung et al., 2004 ), which may be engendered by errors in response production. Several studies have reported that higher-fit children exhibit smaller ERN amplitude during rapid-response tasks (i.e., instructions emphasizing speed of responding; Hillman et al., 2009 ) and more flexibility in the allocation of these resources during tasks entailing variable cognitive control demands, as evidenced by changes in ERN amplitude for higher-fit children and no modulation of ERN in lower-fit children ( Pontifex et al., 2011 ). Collectively, this pattern of results suggests that children with lower levels of fitness allocate fewer attentional resources during stimulus engagement (P3 amplitude) and exhibit slower cognitive processing speed (P3 latency) but increased activation of neural resources involved in the monitoring of their actions (ERN amplitude). Alternatively, higher-fit children allocate greater resources to environmental stimuli and demonstrate less reliance on action monitoring (increasing resource allocation only to meet the demands of the task). Under more demanding task conditions, the strategy of lower-fit children appears to fail since they perform more poorly under conditions requiring the upregulation of cognitive control.

Finally, only one randomized controlled trial published to date has used ERPs to assess neurocognitive function in children. Kamijo and colleagues (2011) studied performance on a working memory task before and after a 9-month physical activity intervention compared with a wait-list control group. They observed better performance following the physical activity intervention during task conditions that required the upregulation of working memory relative to the task condition requiring lesser amounts of working memory. Further, increased activation of the contingent negative variation (CNV), an ERP component reflecting cognitive and motor preparation, was observed at posttest over frontal scalp sites in the physical activity intervention group. No differences in performance or brain activation were noted for the wait-list control group. These findings suggest an increase in cognitive preparation processes in support of a more effective working memory network resulting from prolonged participation in physical activity. For children in a school setting, regular participation in physical activity as part of an after-school program is particularly beneficial for tasks that require the use of working memory.

Adiposity and Risk for Metabolic Syndrome as It Relates to Cognitive Health

A related and emerging literature that has recently been popularized investigates the relationship of adiposity to cognitive and brain health and academic performance. Several reports ( Datar et al., 2004 ; Datar and Sturm, 2006 ; Judge and Jahns, 2007 ; Gable et al., 2012 ) on this relationship are based on large-scale datasets derived from the Early Child Longitudinal Study. Further, nonhuman animal research has been used to elucidate the relationships between health indices and cognitive and brain health (see Figure 4-4 for an overview of these relationships). Collectively, these studies observed poorer future academic performance among children who entered school overweight or moved from a healthy weight to overweight during the course of development. Corroborating evidence for a negative relationship between adiposity and academic performance may be found in smaller but more tightly controlled studies. As noted above, Castelli and colleagues (2007) observed poorer performance on the mathematics and reading portions of the Illinois Standardized Achievement Test in 3rd- and 5th-grade students as a function of higher BMI, and Donnelly and colleagues (2009) used a cluster randomized trial to demonstrate that physical activity in the classroom decreased BMI and improved academic achievement among pre-adolescent children.

Relationships between health indices and cognitive and brain health. NOTE: AD = Alzheimer's disease; PD = Parkinson's disease. SOURCE: Cotman et al., 2007. Reprinted with permission.

Recently published reports describe the relationship between adiposity and cognitive and brain health to advance understanding of the basic cognitive processes and neural substrates that may underlie the adiposity-achievement relationship. Bolstered by findings in adult populations (e.g., Debette et al., 2010 ; Raji et al., 2010 ; Carnell et al., 2011 ), researchers have begun to publish data on preadolescent populations indicating differences in brain function and cognitive performance related to adiposity (however, see Gunstad et al., 2008 , for an instance in which adiposity was unrelated to cognitive outcomes). Specifically, Kamijo and colleagues (2012a) examined the relationship of weight status to cognitive control and academic achievement in 126 children aged 7-9. The children completed a battery of cognitive control tasks, and their body composition was assessed using dual X-ray absorptiometry (DXA). The authors found that higher BMI and greater amounts of fat mass (particularly in the midsection) were related to poorer performance on cognitive control tasks involving inhibition, as well as lower academic achievement. In follow-up studies, Kamijo and colleagues (2012b) investigated whether neural markers of the relationship between adiposity and cognition may be found through examination of ERP data. These studies compared healthy-weight and obese children and found a differential distribution of the P3 potential (i.e., less frontally distributed) and larger N2 amplitude, as well as smaller ERN magnitude, in obese children during task conditions that required greater amounts of inhibitory control ( Kamijo et al., 2012c ). Taken together, the above results suggest that obesity is associated with less effective neural processes during stimulus capture and response execution. As a result, obese children perform tasks more slowly ( Kamijo et al., 2012a ) and are less accurate ( Kamijo et al., 2012b , c ) in response to tasks requiring variable amounts of cognitive control. Although these data are correlational, they provide a basis for further study using other neuroimaging tools (e.g., MRI, fMRI), as well as a rationale for the design and implementation of randomized controlled studies that would allow for causal interpretation of the relationship of adiposity to cognitive and brain health. The next decade should provide a great deal of information on this relationship.


Despite the promising findings described in this chapter, it should be noted that the study of the relationship of childhood physical activity, aerobic fitness, and adiposity to cognitive and brain health and academic performance is in its early stages. Accordingly, most studies have used designs that afford correlation rather than causation. To date, in fact, only two randomized controlled trials ( Davis et al., 2011 ; Kamijo et al., 2011 ) on this relationship have been published. However, several others are currently ongoing, and it was necessary to provide evidence through correlational studies before investing the effort, time, and funding required for more demanding causal studies. Given that the evidence base in this area has grown exponentially in the past 10 years through correlational studies and that causal evidence has accumulated through adult and nonhuman animal studies, the next step will be to increase the amount of causal evidence available on school-age children.

Accomplishing this will require further consideration of demographic factors that may moderate the physical activity–cognition relationship. For instance, socioeconomic status has a unique relationship with physical activity ( Estabrooks et al., 2003 ) and cognitive control ( Mezzacappa, 2004 ). Although many studies have attempted to control for socioeconomic status (see Hillman et al., 2009 ; Kamijo et al., 2011 , 2012a , b , c ; Pontifex et al., 2011 ), further inquiry into its relationship with physical activity, adiposity, and cognition is warranted to determine whether it may serve as a potential mediator or moderator for the observed relationships. A second demographic factor that warrants further consideration is gender. Most authors have failed to describe gender differences when reporting on the physical activity–cognition literature. However, studies of adiposity and cognition have suggested that such a relationship may exist (see Datar and Sturm, 2006 ). Additionally, further consideration of age is warranted. Most studies have examined a relatively narrow age range, consisting of a few years. Such an approach often is necessary because of maturation and the need to develop comprehensive assessment tools that suit the various stages of development. However, this approach has yielded little understanding of how the physical activity–cognition relationship may change throughout the course of maturation.

Finally, although a number of studies have described the relationship of physical activity, fitness, and adiposity to standardized measures of academic performance, few attempts have been made to observe the relationship within the context of the educational environment. Standardized tests, although necessary to gauge knowledge, may not be the most sensitive measures for (the process of) learning. Future research will need to do a better job of translating promising laboratory findings to the real world to determine the value of this relationship in ecologically valid settings.

From an authentic and practical to a mechanistic perspective, physically active and aerobically fit children consistently outperform their inactive and unfit peers academically on both a short- and a long-term basis. Time spent engaged in physical activity is related not only to a healthier body but also to enriched cognitive development and lifelong brain health. Collectively, the findings across the body of literature in this area suggest that increases in aerobic fitness, derived from physical activity, are related to improvements in the integrity of brain structure and function that underlie academic performance. The strongest relationships have been found between aerobic fitness and performance in mathematics, reading, and English. For children in a school setting, regular participation in physical activity is particularly beneficial with respect to tasks that require working memory and problem solving. These findings are corroborated by the results of both authentic correlational studies and experimental randomized controlled trials. Overall, the benefits of additional time dedicated to physical education and other physical activity opportunities before, during, and after school outweigh the benefits of exclusive utilization of school time for academic learning, as physical activity opportunities offered across the curriculum do not inhibit academic performance.

Both habitual and single bouts of physical activity contribute to enhanced academic performance. Findings indicate a robust relationship of acute exercise to increased attention, with evidence emerging for a relationship between participation in physical activity and disciplinary behaviors, time on task, and academic performance. Specifically, higher-fit children allocate greater resources to a given task and demonstrate less reliance on environmental cues or teacher prompting.

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Review article, cooperative learning in physical education lessons - literature review.

literature review physical education

  • 1 Levinsky-Wingate Academic College, Wingate Campus, Netanya, Israel
  • 2 Medical Education, University of New South Wales, Sydney, NSW, Australia
  • 3 University of Auckland, Auckland, New Zealand

Cooperative learning in physical education classes is perceived as beneficial. The aim of this article was to examine whether field studies that include cooperative learning in their physical education intervention programs provide applicable data—to allow teachers to choose the optimal teaching strategy in line with their teaching goals. A systematic review of 44 research studies, published between 2000 and 2020, was conducted. Data related to teaching strategies and outcomes were compiled and discriminant function analysis was conducted, to classify the articles according to positive outcomes reported/not reported. Our results suggest a partial association between a range of cooperative teaching strategies (including Jigsaw, Learning Team, Complex, and Complex Instruction, as well as the cooperative learning model and combined strategies) and learning outcomes in four domains (social, physical, affective, and cognitive). Our literature review reveals that while the published data is valuable, additional research is needed to complete the picture.


Field studies that examine the impact of educational intervention programs are referred to as applied studies, seeking to reveal what content, conditions, means, and methods lead to significant teaching. As such, their main purpose is to help teachers improve their educational endeavor (e.g., Pulgar et al., 2019 ; Ghanbari and Abdolrezapour, 2020 ).

Cooperative Learning (CL) is an active learning model in which students work in small groups to achieve shared learning goals. The Cooperative Learning Model (CLM) aspires to raise the level of student involvement in the learning, while encouraging social relationships that lead to improved achievements in the taught subject and in the students’ affective and cognitive skills ( Chiu et al., 2014 ). This approach is based on meaningful theory, validated by research that presents outcomes in a variety of human dimensions, school ages, and study fields ( Dzemidzic Kristiansen et al., 2019 ). During the second half of the 20th century, CL evolved not only as an effective approach to teaching but also as a means for addressing social tension caused by the juxtaposition between socio-cultural status and achievements ( Slavin, 2011 ). As this issue continues to be central to education systems, CL is especially meaningful in contemporary societies, where cooperation between and within groups has become an important means for facing scientific and technological challenges that are too complex to be solved by individuals ( Capar and Tarim, 2015 ).

While expectations from the CLM are high, its application to teaching processes is complex, especially as it is not always in line with the more intuitive and associative manner in which many teachers teach ( Page, 2017 ). Moreover, teachers testify that the organization of the CL class is complex and expresses concerns that the time needed to manage such learning may come at the expense of the learning itself ( Buchs et al., 2017 ). Although teachers acknowledge the benefits of CL goals and outcomes, they usually lack the practical knowledge that is required for constructing a comprehensive teaching strategy that addresses students’ norms and behaviors ( Johnson et al., 2000 ). In this paper, we analyze the existing body of published research on applying CL in PE, to provide PE teachers with more focused data regarding the reported outcomes of this model. Our focus was on two topics: (1) the outcomes of applying the CLM; and (2) the relationship between teaching strategies and these outcomes. By analyzing the outcomes, PE teachers will be able to easily access and recognize the variety of teaching goals that are achievable via CL. As such, in order to examine CL methods and techniques that could lead to the desired outcomes, we begin by reviewing theoretical academic articles that laid the foundation for the CLM in PE, as well as articles that review and summarize research on CL in PE. Next, we review practical CL intervention articles, to analyze and present the range of strategies and their outcomes. Finally, we discuss the data that could serve PE teachers who are interested in teaching according to the CL teaching model.

The outcomes of CL in PE

Over the past two decades, the theoretical and review articles on CL in the field of PE have dealt extensively in both the goals and the outcomes of the CL model. Casey and Goodyear (2015) , who analyzed 27 articles that aimed at exploring the empirical research on the use of CL in PE, reported on learning achievements in the physical, cognitive, and social domains, and even in the affective domains albeit to a lesser extent. The researchers reported that CL enhances academic learning through the physical and cognitive learning domains, as students acquire a certain level of physical competence and develop an understanding of movement techniques and tactics as a result of their engaging in CL activities. They claimed that one explanation for this enhanced academic learning is the increased opportunity for discussions and face-to-face interactions between students, which increases their opportunities for engaging in higher order thinking skills. The researchers also found social learning outcomes to include the development of interpersonal skills, interpersonal relations, the ability to listen and to speak coherently, while sharing ideas and constructing a new understanding together. Finally, they found that social learning outcomes also encompass students’ ability to exhibit caring, empathy, respect, and support.

Bores-García et al. (2021) , who later reviewed 15 studies that were conducted during 2014–2019, pointed to the contribution of CL to all dimensions of the human personality, while stating that the affective domain, however, had been inadequately addressed in the examined studies. Both studies ( Casey and Goodyear, 2015 ; Bores-García et al., 2021 ) assert that short implementation durations would not yield sustainable learning outcomes, and claim that teachers struggle with implementing the model because of its complexity, and that more time is needed to assimilate it in school. Chiu et al. (2014) conducted content analysis on 15 articles that dealt with CL in the physical education curriculum. In line with the findings of Bores-García et al. (2021) and Casey and Goodyear (2015) , they demonstrate that the main educational value that CL brings to the physical education curriculum is social responsibility. However, a slightly different point of view is expressed in a recent theoretical article ( Montoya et al., 2020 ), where motivation was found to be the main educational value that arises from CL. In addition to presenting the varied outcomes of CL, researchers are concerned that a significant proportion of interventions are short-lived, and that in some interventional studies, the specific intervention plan is unclear ( Casey and Goodyear, 2015 ; Bores-García et al., 2021 ), rendering the fidelity of the study of CL in PE somewhat obscure ( Casey et al., 2015 ).

Strategies employed in CL in PE

The terms teaching model and teaching strategy are not synonymous. A teaching model presents achievable didactic teaching principles and defined teaching goals that are rooted in a defined educational approach ( Joyce et al., 2015 ). A teaching strategy, on the other hand, is subject to the chosen teaching model and presents teaching methods, i.e., ways of teaching and techniques that makes it possible to comply with the didactic principles of the model ( Joyce et al., 2015 ). Indeed, the CL model was originally created to deal with learning gaps in the heterogeneous classroom; its principles include creating a positive dependence on members of the cooperative group, creating a proactive interaction that allows each participant to contribute to the group, etc. One CL strategy is the Jigsaw model, in which the teacher divides the class into small heterogeneous home groups of four-seven children. For each topic, a different representative from each group is taught the material, so that they can then return to the home group and teach their new specialty to the other group members, thereby increasing the participation of each and every student in the group.

Bores-García et al. (2021) specify the CL teaching strategies used in the reviewed research studies (Jigsaw, Joint Action Studies in Didactics, and Learning Teams), yet most do not present such detailed data (e.g., Chiu et al., 2014 ; Casey and Quennerstedt, 2020 ; Montoya et al., 2020 ). Several researchers in the field of CL (e.g., Hastie and Casey, 2014 ; Casey et al., 2015 ; Dyson and Casey, 2016 ) present five fundamental CLM principles: (1) positive interdependence; (2) individual accountability; (3) group processing; (4) promoting face-to-face interaction; and (5) small groups and interpersonal skills. However, they claim that as implementing all five elements is too complex for teachers, the specific steps while applying the model should be further examined, to understand the outcomes. This argument, which points to the difficulty of applying CL principles, justifies the vast efforts that have been made by numerous researchers in designing detailed and interwoven teaching strategies in a manner that allows for expected outcomes to be achieved. The current study therefore strives to specifically examine the teaching strategies that are implemented in CL intervention studies in PE, their outcomes, and the relationships between the two.

Search sources

In this study, we conducted a systematic review of 44 research studies (from 2,576 initial studies) that were published over a 20-year period, from January 2000 to April 2020. The search for sources focused on field research articles in which there was an examination of the impact of CL intervention programs that entailed physical activity on processes and achievements. Our review included quantitative studies, qualitative studies, and mixed-method studies. The search was conducted via seven electronic databases, including ERIC, Google Scholar, SPORTDiscus, EBSCO host, and Web of Science, ProQuest, and ScienceDirect. The descriptors used for the search included “cooperative learning” or “collaborative learning”; “school” or “class”; and “physical education,” “physical activity,” or “movement.”

Exclusion criteria

The exclusion criteria included the following: (1) duplicated articles, (2) articles that were not published in journals that are indexed in the Journal Citation Report (JCR) or in the Scimago Journal Rank (SJR); (3) articles written in languages other than English; (4) articles that do not address an intervention program; and (5) articles that address an intervention program yet do not mention any of the CL teaching or learning process examined in this study. The search summary, using the Prisma framework ( Page M. J. et al., 2020 ; Page M. et al., 2020 ), is presented in Figure 1 as flow chart.


Figure 1 . Flow chart of studies identification via databases.

The article sorting process resulted in our identifying 44 articles that met all of our inclusion criteria. As past PE teachers, we chose to gather data that could help teachers understand how CL research might help them while considering this method for their purposes. Therefore, the data were examined in relation to: (1) outcomes in social, physical, affective, and cognitive domains ; and (2) type of CL teaching strategy – (a) Jigsaw (JIG); (b) Learning Team (LT); (c) Complex Instruction (CI); (d) Student Team – Achievement Division (STAD); (e) Performer and Coach Earn Rewards (PACER); (f) Cooperative Learning Model Teaching Strategy (CLM); and (g) combined teaching strategies (Combined). Data were also examined regarding the learning process , including the intervention duration and students’ previous experience in CL. Finally, we also examined the research method (qualitative, quantitative, or mixed methods) and the participants in the article (students vs. teachers; individual vs. group level).

Given the nature of the data that was reported in the reviewed articles, whereby conducting a meta-analysis was not suitable due to inconsistency of reported data between studies, we decided to focus on the presence or absence of various key features. As such, we recorded the data in a binary manner. The outcome of each intervention served as the dependent variable, whereby when the reported outcome was positive and statistically significant, the variable received a value of 1. When the reported outcome was either negative, not significant, or no outcome was reported, the variable received the value of 0. In addition, teaching strategies and additional discrete variables (e.g., type of study, class, grade, etc.) that may have impacted the outcome were similarly recorded, whereby their presence was marked with a value of 1 and their absence was marked with a value of 0. Compiling the data in this manner enabled us to address the following important generic question: Which teaching strategies that were reported as having been implemented in the studies are associated with the reported positive outcomes? Moreover, applying this type of analytical approach in research is the best option in cases where conducting a meta-analysis is not a possible option ( Garson, 2012 ). Finally, the advantage of applying this approach is that it minimizes the number of articles that are excluded from the analysis due to missing data.

Data analysis

Discriminant Function Analysis (DFA) ( Haas et al., 2004 ; Garson, 2012 ) was used to identify the possibility of classifying (or discriminating between) articles that report positive outcomes and those that do not report such outcomes through features of the interventions or relating to the specific studies. The DFA was conducted separately for each of the four domains of outcomes (social, physical, affective, and cognitive). The predictors applied in our analysis included: (1) type of research method (qualitative, quantitative, or mixed); (2) the level at which the student data and the teacher data were reported (individual or group average); (3) teaching strategy reported (yes or no); (4) duration of the intervention in academic hours (≥24 h, yes or no); and (5) whether the students had previously experienced CL prior to the study (yes or no). The results of the DFA in this review paper are reported using a standardized and unstandardized linear function for each outcome, the two centroids and the cut-off point for classification. We also report the percentage of correct classification, thereby indicating the predictive power of each DF.

It is important to note that the analysis reported in this paper is of articles (i.e., research reports) rather than of the actual studies . As such, most independent variables are classified as being present or lacking. Regarding the dependent variable of outcomes, we assumed that positive outcomes are more likely to be reported while negative or non-significant outcomes are more likely to be omitted ( Marks-Anglin and Chen, 2020 ; Page M. J. et al., 2020 ; Page M. et al., 2020 ).

Table 1 presents each of the 44 articles reviewed in this article in chronological order. Of all the articles, 21 were quantitative studies, 21 were qualitative articles, and two used mix methods. In 21 studies, the number of subjects reported was less than 50, which is a relatively low number of participants. Moreover, about a quarter of the studies that had a low number of subjects were quantitative. Only four studies reported that the students had previous experience in CL. In 20 studies, the duration of the intervention program was at least 24 academic hours (i.e., lessons).


Table 1 . Studies on CL in PE conducted during 2000–2020.

Outcomes of CL in PE

The prevalence of the four examined domains was similar among the articles. Some studies examined variables from two different domains, while a number of qualitative articles only examined processes, not outcomes. Among those that presented positive outcomes, 14 articles presented positive social outcomes, including seven relating to behavioral changes, two dealing with attitudes toward friends and the class, and two dealing with both behavioral changes and attitude changes. Ten articles addressed the physical domain, with a focus on motor abilities in skills, fitness, and games. In the affective domain there were a total of 12 articles, of which seven dealt with improving motivation for coping or succeeding and five dealt with changes in perceptions and attitudes. Finally, in the cognitive domain, 10 articles were identified, of which four showed improvements in academic achievements and six showed improvement in thinking skills.

Associations between CL strategies in PE and outcomes

When examining the strategies that were applied in the review research studies, only three teaching strategies were addressed in more than one article. Of the 44 articles reviewed, the JIG strategy was applied in five studies, LT was applied in five studies, and CI was applied in two studies. Ten articles applied general CLM principles, while 20 intervention programs (almost half of all programs) employed the Combined strategy. Moreover, in several studies, the researchers incorporated principles of non-CL strategies, such as the Sport Education Strategy ( Montoya et al., 2020 ) or the Self-Learning Strategy ( Benkhaled et al., 2015 ).

Table 2 shows that overall, the DFA yielded acceptable-to-high levels of correct classification (68.2–81.8%). The positive DF coefficients were found to be associated with four positive outcomes in the affective and cognitive domains, while negative DF coefficients were associated with positive outcomes in the social and physical domains. Meaningful results were those that yielded a medium or larger effect size.


Table 2 . Discriminant function coefficients: predictors of reported positive outcomes.

When the JIG strategy was implemented, positive outcomes were reported in the affective domain, and to a lesser degree in the cognitive and social domains (standardized coefficients = 0.734, 0.404, and −0.403, respectively). When the LT teaching strategy was implemented, positive outcomes were reported in the physical and affective domains, yet with a low-medium effect size (standardized coefficients = 0.377 and 0.360, respectively). When the CI teaching strategy was reported, positive outcomes were seen in the cognitive domain (standardized coefficient = 0.586). When CLM was reportedly implemented, positive outcomes were reported in the affective domain, and to a lesser degree in the cognitive domain (standardized coefficients = 1.160 and 0.421, respectively). Finally, when Combined teaching strategies were reported, positive outcomes were seen in the affective domain (standardized coefficient = 0.797).

When the duration of the intervention was examined as being ≥24 h in terms of academic lessons, a negligible impact was seen on the positive outcomes, with the exception of positive outcomes being reported in the social domain (standardized coefficient = −0.367, i.e., low-medium effect).

When examining the students’ previous experience in CL that was reported in the reviewed articles, no significant associations were found with any positive outcomes, thereby suggesting that this variable has no impact on the positive outcomes reviewed in this study. However, student data that was reported on the individual level was associated with positive outcomes in the cognitive and social domains (standardized coefficients = 0.691 and −0.592, respectively).

It is important to note that the DFA for the affective domain only yielded 68.2% correct classification. Such levels are estimated to be equivalent to a medium effect in comparison to the DFA of the other three domains (i.e., social, physical, and cognitive) that yielded 79.5–81.8% correct classification, which is estimated to be equivalent to a high effect ( Coe, 2002 ).

The motivation for conducting this article review stemmed from the importance of understanding how PE teachers can benefit from implementing CL in their classes, based on the corpus of articles that have been published in academic journals. Based on our systematic review, diversified studies have been conducted across a wide range of classrooms and durations, and have resulted in a range of outcomes regarding social, physical, affective, and cognitive domains. While such a large pool of data is important and beneficial, in this case it makes it harder for PE teachers to make an educated decision regarding the type of CL that they should apply in their classroom in order to achieve optimal outcomes.

Further to our findings, some associations were seen between certain teaching strategies and outcomes. The social domain was found to be weakly associated with the JIG model, while the physical domain was found to be weakly associated with the LT strategy. The affective domain was found to be associated with JIG, CLM, and Combined strategies, and to a lesser effect with LT. Finally, the cognitive domain was found to be associated with the CI strategy, and to a lesser degree with JIG and CLM. As such, we cannot fully recommend a certain teaching strategy for teachers who wish to achieve social and physical goals through CL in their PE classes.

In more than half the studies, the intervention duration was relatively short. However, we did not find a relationship between the length of the intervention program and its outcomes. This differs from previous findings, whereby researcher suggest that teachers must invest time and effort in order to conduct effective CL in small groups ( Baloche and Brody, 2017 ). Moreover, Bjørke and Mordal Moen (2020) argued that children who embark on CL, approach it with skepticism at first, only gradually developing a positive attitude toward the process, understanding its benefits, and actually beginning to learn through it. In our research, no association was found between the reported duration of the intervention programs and outcomes on physical, affective, and cognitive domains, yet a small impact was seen, however, on social outcomes.

Only four of the reviewed research studies in this paper addressed students’ previous CL experience and this aspect was not associated with any positive outcomes. Previous studies (e.g., Ghaith, 2018 ) mention that students who have learned to listen to each other in small group lessons, in classes such as math or language, may apply this CL skill in PE classes as well. In other words, when experiencing CL in one field, students could be expected to transfer this capability to other fields, thereby achieving more meaningful learning. It is therefore recommended that future research examine this aspect of previous CL experience among children.

A range of CL strategies are analyzed in the literature and applied in various teaching professions (e.g., Felder, 2001 ). Yet in our review, only the following three strategies—JIG, LT, and CLM—were found to have been used as intervention programs in more than one article. The question is therefore, what makes each of these strategies special and what is their contribution to the intervention outcomes in the various dimensions? To answer this, we will now present the main concept of these three teaching strategies and their unique association with PE classes.

The JIG strategy

This strategy is based on the recognition that it is of the utmost importance to maximize the learning potential of each and every student in the classroom, which can be achieved by creating motivation to learn among the students. To do so, the teacher must conduct meticulous and structured planning that encourages children’s involvement in the learning through social processes ( Aronson et al., 1978 ).

The principles that enable this relate to the cultivating and nurturing of students’ self-esteem while decreasing their anxiety that could prevent them from participating in class. Self-esteem improves as those involved become more experienced and enthusiastic, and achieve mastery of the learned topic. As such, students must have mutual goals and agree to share their ideas and solutions with their classmates. It is also important to create in children a sense that they are needed and that they can teach and contribute to the class ( Marhamah and Mulyadi, 2013 ). The teacher must serve as a mediator or facilitator, helping the children to take responsibility for their own learning and for that of their peers ( Lee and Kim, 2015 ).

Applying this strategy entails four steps: (1) dividing the class into small heterogeneous home groups of students and assigning a different sub-topic to each member of the group; (2) the students then study their allocated sub-topics; (3) in turn, each student teaches the other group members about the specific sub-topic; (4) the group and the teacher summarize and evaluate the learning process. Specifically in PE classes, JIG has the potential to improve the affective domain, i.e., the students’ attitude toward PE ( Casey and Fernandez-Rio, 2019 ; Walad et al., 2019 ), and facilitate social communications, as the stronger students cannot take over and prevent the quieter ones from participating. Instead, it provides an opportunity for all students to participate and be partners to the lesson. Indeed, our literature review confirms that the JIG strategy has a positive impact on the affective domain, and to some extent on the social domain.

The LT strategy

This strategy is based on the assumption that there is inequality in education—due to the discrimination of children with disabilities, from different racial or ethnic backgrounds, and from different socio-economic statuses ( Johnson and Johnson, 1999 )—which in turn leads to inequality in their integration and achievements in the future.

The principles that enhance equality in learning require the enhancing of students’ positive interdependence, individual accountability, and ability to conduct face-to-face interactions. In addition, they require the appropriate use of group skills and processing that are necessary for achieving the best group results by means of mutual assistance among the group members. All group members know that they must work together on the task and are aware of their individual contribution to the success or failure of the group as a whole ( Rimmerman, 2004 ). In order to realize these principles, teachers need to teach interpersonal skills and impart self-regulating behavior capabilities, while conducting the classroom in a structured framework that enables cooperation ( Hobri and Hossain, 2018 ).

Applying this strategy entails four steps: (1) prior to embarking on group learning, the teacher must build up the students’ ability to work in collaboration; (2) Students are divided into small heterogeneous groups and must work together to define the purpose of the group; (3) while performing activities in the group setting, discussions are held within the group as well as, ongoing self-assessment of the cooperation in the group; (4) Each member of the group has to perform tasks in pairs (one performs while the other assists), and the tasks constantly change ( Bayraktar, 2011 ). In this strategy, the teacher fills the role of environment organizer, supporter, and assistant.

Specifically in PE, this strategy enables students to apply the social skills that are needed in face-to-face interactions ( Hannon and Ratliffe, 2004 ). Moreover, this strategy makes solving problems and giving feedback much easier, as the students’ movements are visible, demonstrating and enabling trial and error ( Huang et al., 2017 ). However, evidence regarding outcomes of applying this strategy in PE classes on the physical and affective domains is weak, and no evidence can be seen for positive outcomes on students’ social and cognitive domains.

The CI strategy

The goal of the CI strategy is to provide students with equal accessibility to the teacher and to the learning ( Cohen and Lotan, 1997 ). To break the cycle of discrimination whereby students from a lower socio-economy status have less access to education, the teacher must ensure that optimal student-teacher contact conditions exist. This strategy entails four contact conditions: (1) institutional support provided by the school principal and the teachers to encourage social rapprochement between different groups; (2) equal status and equal division of roles between the group members when performing the tasks; (3) cooperation and mutual assistance between group members for achieving the common goals; and (4) an intimate, pleasant, and rewarding environment when working as a group.

Applying this strategy encompasses six basic requirements: (1) maintaining equal access to each interaction; (2) addressing each group as an independent entity; (3) implementing cooperative behavior as the norm; (4) treating children as multidimensional; (5) setting norms and maintaining a consistent framework; and (6) ensuring an intimate and pleasant environment. Each of these six principles includes a methodical breakdown of the learning structure, the teacher and students’ behavioral norms. Every little detail is specific and accurate, pieces of a puzzle that together provide a comprehensive picture.

Specifically in terms of PE lessons, the CI strategy could serve as a special aid that allows the teacher to implement the contact conditions in the classroom ( Ben Ari, 2002 ; Shoval, 2011 ), thereby enhancing both learning and social relationships between students. Indeed, our literature review confirms the impact of the CI strategy on the cognitive domain, whereby adherence to the rules of communication and equality between children has an impact on their learning. However, evidence is lacking about the impact of CI on other dimensions.

Table 3 is a summary of missing and existing evidences to serve physical education teachers who are interested in applying CL as was reported in the existing body of research.


Table 3 . Summary of existing and missing evidences to serve physical education teachers who are interested in applying CL.

Non-specific strategy intervention programs

Of the 44 research studies reviewed in this article, 10 were not based on a detailed or structured teaching strategy, but rather implemented the more general CLM that is based on five principles (positive interdependence; individual accountability; group processing; face-to-face interaction; and small groups and interpersonal skills). When examining the outcomes of this more general model, our results indicate positive outcomes in the affective domain and a positive yet weaker outcome on the cognitive domain. Yet to maintain fidelity and enable other researchers to replicate research findings, the methodology must be more detailed than it is in these 10 articles ( Casey et al., 2015 ). As such, PE teachers who wish to implement CLM may find it difficult to do so. Future research could therefore benefit from specifying the CLM methodology and comparing studies that employ the same techniques.

Moreover, 20 studies combined principles from different strategies. These studies, which we referred to as Combined, presented outcomes in the affective domain. However, here too, PE teachers may find it difficult to replicate these studies, due to the inability to replicate the methodologies employed. Many studies with identical combination and comparison between different combinations and between different well-defined CL’s teaching strategies may change the picture.

Our literature review of 44 articles that address CL strategies employed in PE classes indicates a lack of data regarding the specific strategy and methodology employed and their outcomes on four domains: Social, physical, cognitive, and affective. It is therefore important to further explore CL so as to provide PE teachers with applicable methodologies for achieving desired outcomes. Researchers and teachers could benefit from applying specific existing strategies based on known principles and pedagogical theories that are specially interwoven as a means for achieving defined outcomes. In turn, such research could serve as scaffolding for providing teachers with solid grounds for teaching. Research should consider the time children acquire the ability to act in collaborative groups, and the time they use CL to achieve meaningful outcomes as two separate procedures.


As the articles reviewed in this study were only written in English, articles in other languages such as Spanish and Portuguese were excluded. Therefore, the review may be culture biased. Moreover, throughout this reviewed, we classified each article according to type of teaching strategy employed and outcomes on four domains. With regards to outcomes, our classification differentiated positive outcomes and all other outcomes (negative, unclear, or not reported)—based on the assumption that negative outcomes are less likely to be reported ( Torgerson, 2006 ). That being said, this limitation does not compromise the quality of this literature review, and may even strengthen it, as we acknowledge the possible (or likely) bias that some of the literature may be subject to.

Author contributions

SZ: Investigation, Methodology, Project administration, Visualization, Writing – original draft, Writing – review & editing. ES: Visualization, Writing – original draft, Writing – review & editing, Conceptualization, Investigation, Project administration, Supervision. BS: Data curation, Formal analysis, Methodology, Software, Validation, Writing – original draft, Writing – review & editing.

The author(s) declare that no financial support was received for the research, authorship, and/or publication of this article.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

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Keywords: discriminant function analysis, cooperative learning, teaching strategies, learning outcomes, physical education, intervention studies, field research

Citation: Zach S, Shoval E and Shulruf B (2023) Cooperative learning in physical education lessons - literature review. Front. Educ . 8:1273423. doi: 10.3389/feduc.2023.1273423

Received: 06 August 2023; Accepted: 03 October 2023; Published: 19 October 2023.

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Copyright © 2023 Zach, Shoval and Shulruf. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Sima Zach, [email protected]

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  • Published: 25 February 2008

Physical education, school physical activity, school sports and academic performance

  • François Trudeau 1 &
  • Roy J Shephard 2  

International Journal of Behavioral Nutrition and Physical Activity volume  5 , Article number:  10 ( 2008 ) Cite this article

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The purpose of this paper is to review relationships of academic performance and some of its determinants to participation in school-based physical activities, including physical education (PE), free school physical activity (PA) and school sports.

Linkages between academic achievement and involvement in PE, school PA and sport programmes have been examined, based on a systematic review of currently available literature, including a comprehensive search of MEDLINE (1966 to 2007), PSYCHINFO (1974 to 2007), SCHOLAR.GOOGLE.COM, and ERIC databases.

Quasi-experimental data indicate that allocating up to an additional hour per day of curricular time to PA programmes does not affect the academic performance of primary school students negatively, even though the time allocated to other subjects usually shows a corresponding reduction. An additional curricular emphasis on PE may result in small absolute gains in grade point average (GPA), and such findings strongly suggest a relative increase in performance per unit of academic teaching time. Further, the overwhelmingly majority of such programmes have demonstrated an improvement in some measures of physical fitness (PF). Cross-sectional observations show a positive association between academic performance and PA, but PF does not seem to show such an association. PA has positive influences on concentration, memory and classroom behaviour. Data from quasi-experimental studies find support in mechanistic experiments on cognitive function, pointing to a positive relationship between PA and intellectual performance.

Given competent providers, PA can be added to the school curriculum by taking time from other subjects without risk of hindering student academic achievement. On the other hand, adding time to "academic" or "curricular" subjects by taking time from physical education programmes does not enhance grades in these subjects and may be detrimental to health.

The purpose of this paper is to review relationships between physical education (PE), school physical activity (PA), school sports and academic performance. These relationships have been the subject of extensive discussion between advocates and skeptics of PE, school PA and school sports programmes. Both elements of this discussion (academic achievement and physical activity) are independent determinants of a child's health. Our intent in this article is to assess the effects on academic achievement of school PA programmes (including PE and school sports), in both elementary and high schools. Previous reviews have examined relationships between PA and academic achievement. [ 1 – 4 ] Recent research results, echoed in the media, suggest that such activity may have a positive impact on learning and memory. It is now fairly well-recognized that PA is associated with the maintenance of cognitive function in older adults [ 5 ] and offers some protection against Alzheimer's disease. [ 6 ] Cognitive dysfunctions in older adults is becoming an urgent public health problem, given the ever-rising average life expectancy and the associated growth in the proportion of old and very old individuals in most societies. A positive association between PA and cognitive health is also suspected in younger subjects, but is not as well documented in this age group. Nevertheless, any positive influence of PA on the cognitive functions of children is important for at least 2 reasons: 1) It is a potential argument for increasing PE and/or other types of school PA without risk of decreasing academic progress, and 2) It may offer a way to reduce disruptive behaviour at school and the drop-out from educational programmes. Furthermore, an important by-product of an increased participation to school PA would be an enhanced level of physical fitness.

Search methods

The databases searched included MEDLINE (1966 to 2007), PSYCHINFO (1974 to 2007), SCHOLAR.GOOGLE.COM, and ERIC, as well as the extensive personal databases of the authors. The reference lists of the articles thus identified were also consulted to identify additional potentially-relevant research. Publications in languages other than English were considered where appropriate. For the purpose of this review, we use the term academic achievement to encompass academic success, school performance and all combinations of these terms.

The outcomes of school PA/PE and academic achievement, success or performance were actual or self-reported grade point average (GPA) and determinants of GPA that could potentially be changed by the interventions (concentration, learning, classroom behaviour, engagement in learning, self-esteem, etc.). The terms physical education, physical activity and sports are, for the purposes of this review, restricted to programmes offered within the school context (i.e. instructional physical education and extracurricular physical activity, including in-school physical activity programmes, intraschool and intramural sport).

Quasi-experimental and longitudinal studies

It is not surprising that no randomized controlled trials were identified, as they are not practicable in this type of research setting. Quasi-experimental protocols are usually indicated when causality cannot be tested by a random controlled trial in milieux such as the school setting. Seven quasi-experimental studies were identified (Table 1 ). Cross-sectional studies were also considered, as well as experimental or laboratory experiments on the determinants of academic performance (i.e. learning concentration, classroom behaviour, etc.).

The first documented quasi-experimental study relevant for to this paper was the Vanves (France) investigation; this involved a small group of schoolchildren tested during the 1950's. [ 7 ] Schoolchildren who spent mornings in the classroom and afternoons doing PE were said to perform better academically than children from a control class, but no further details were given. [ 7 ] Unfortunately, the specifics of these observations were not described in peer reviewed journals.

A second quasi-experimental study conducted in the Trois-Rivières region (Québec) between 1970 and 1977 involved 546 primary school students; this noted that students involved in an experimental 5 hours of physical education per week had a higher academic performance than their control counterparts who were enrolled in the normal school program for 40 min per week [ 8 ]. The supplemental 260 minutes allocated to PE was necessarily taken from time for other academic teaching (i.e. an average 14% curtailment of academic instruction). Despite this curricular change, during the last 5 years of primary school, the overall academic performance of the experimental students improved relative to the controls. During standardized Provincial examinations, children receiving the 5 hours/week of PE had higher scores in mathematics, but lower scores in English (their second language), despite the fact that 33 minutes were removed from mathematics instruction and none from English. [ 3 ]

A 2-year quasi-experimental study followed 759 Californian children in the 5th and 6th grades. [ 9 ] Subgroups of children were taught PE by either a professional physical educator (n = 178), a trained homeroom teacher (n = 312), or in the normal programme (n = 165). The professional physical educators, the trained teachers, and normal programmes offered, respectively, 80, 65, and 38 minutes per week of PE. As expected, those taught by the professional physical educators achieved greater fitness (cardiovascular and muscle endurance). [ 10 ] Also, the groups taught by the professional physical educators and trained teachers had smaller declines in academic performance despite allocating more time to PE. Four of 8 statistical comparisons disclosed an advantage for students in the experimental groups; one comparison was advantageous to control students, while the remaining 3 were equal. The group who spent the most time on PE (i.e. those with a professional physical educator) showed no negative effects on academic achievement and indeed the decline of academic results during the 2 years of the intervention was smaller than that observed in the control subjects. [ 9 ]

In South Australia, the 500-student SHAPE trial added 1.25 hours per day of endurance fitness training to the curriculum of 10-year-old primary school students. [ 11 ] Over the first 14 weeks of the study, the experimenatl group showed gains in physical work capacity and decreases in body fat relative to controls. Arithmetic and reading scores were not adversely affected by the substantial reallocation of curricular time in favour of PE. These physical benefits appeared to be maintained over the succeeding 2 years in a follow-up of 216 participants. These follow-up evaluations showed (non-significant) trends for better arithmetic and reading grades in experimental students, as well as beneficial changes in teachers' ratings of classroom behaviour. [ 12 ]

The 16-month Action School BC! project involved a population of 287 British Columbian primary school children (4th and 5th years: 9–11-years olds). PA was delivered by classroom teachers, amounting to 47 minutes more per week in interventional than in control schools (139 ± 62 vs. 92 ± 45 minutes, P < 0.001). [ 13 ] Despite a corresponding decrease in academic time, the academic performance of the experimental group, as measured by the Canadian Achievement Test, remained unchanged; indeed, data analysis revealed a trend towards an enhanced academic performance in the intervention schools (the average score rising from 1,595 to 1,672 units).

Another interventional study of 6 th grade (11 year-old) students covered a single school term. Fifty-five minutes/day of PE were included in the curriculum, vs. the same allocation of time for arts or computer sciences; the two groups performed equally well in mathematics, sciences and English. [ 14 ] Finally, an intervention in Israel involved 92 preschool and 266 first grade children. [ 15 ] The experimental manipulation here was a school-based movement education programme, and children in the experimental group showed greater reading skills and arithmetic scores than controls. [ 15 ]

Taken together, these quasi-experimental data suggest that the enriched PE programmes demanded a substantial reduction in the time allocated for academic tuition. Since the children achieved at least equally despite the reduced teaching time, the evidence seems strong that the efficiency of learning was enhanced. [ 3 ] Despite the variety of programme durations and locations, a common and valuable by-product was a significant increase in various measures of physical fitness (PF).

Cross-sectional studies

Cross-sectional studies commonly have difficulty in controlling for potential biases, particularly socio-economic status (SES). SES remains the strongest predictor of academic achievement [ 16 ] and is also one of the strongest predictors of PA participation in children (e.g. in Canada [ 17 ]; Italy [ 18 ] and Estonia [ 19 ]). Cross-sectional studies generally indicate a positive association with academic achievement. Some of these studies did control for confounders such as SES, and still most of them found a positive association between physical activity and academic achievement (Table 2 ).

Positive results on GPA

Nelson and Gordon-Larsen [ 20 ] analyzed results from the US National Longitudinal Study of Adolescent Health; they observed that adolescents who were active in school were more likely to have high grades. Even after adjustment for demographics and SES, the risk ratio of higher grades was 1.20 for mathematics and 1.21 for English among adolescents who were active at school. Within middle to upper middle SES categories, a cross-sectional study of suburban high school seniors (52 girls and 37 boys) found that the more active group had higher GPA. [ 21 ]

4,690 Hong Kong children from primary 5 to secondary 7 (i.e. grades 5 to 12) completed a pre-validated questionnaire relating their sports and exercise participation to perceived academic performance. [ 22 ] Low correlations were seen for the whole sample (r = 0.10, P < 0.01; r = 0.17, P < 0.01 for females; r = 0.06, NS for males). GPA was not a significant correlated with PA participation when all school bands were confounded; however, the high band showed a positive link between GPA and PA participation, whereas students in the low band showed a negative relationship between PA participation and GPA. [ 23 ] These reports suggest that the relationship between PA and academic performance is influenced by the type of students and/or the school that they attend. Deliberate stratification of students by learning ability is by no means universal, but we cannot exclude the possibility that spontaneous, unplanned banding may also influence the strength of observed relationships.

Dwyer et al. [ 24 ] made a cross-sectional survey of 9000 Australian schoolchildren between the ages of 7 and 15 years (500 in each age/sex stratum drawn from 109 schools, i.e. 10 girls and 10 boys per school). Depending on the group, a linear regression analysis with good control of confounding variables demonstrated a significant association between academic achievement and PA (a combination of lunchtime PA and minutes of PA the preceding week). In all subjects aged 9–12 years, school performance was positively associated with ratings of PA during the preceding week. In girls 10–15 years old and boys 8–15 years old, academic achievement was also positively associated with the estimates of lunchtime PA. The correlation coefficients between PA and academic achievement, although low (r = 0.08 to 0.19) were statistically significant, suggesting that PA was contributing to academic achievement in both boys and girls. Data from the Youth Risk Behavior Survey likewise showed that a perception of little or no involvement in PA was associated with a perception of low academic performance. [ 25 ] Another cross-sectional study from England also controlled for SES; this again reported a positive association between school sports participation and academic achievement. [ 26 ]

Researchers from Iceland designed a study included other health behaviours. [ 27 ] They found small but significantly positive univariate associations of PA with self-reported school performance (r = -0.11 with absenteeism and r = 0.09 with grades). When confounders were considered, these associations were further weakened, but nevertheless remained statistically significant predictors if selected health behaviours and psychological variables were included in the prediction model. [ 27 ]

Negative or null outcomes on GPA

In 6,923 grade 6 New Brunswick children (age 11 years), PA showed a weak inverse association with academic achievement, but a positive association with self-esteem. [ 28 ] A study on 232 English boys and girls (13–16 years old) found no relationship between self-reported PA and GPA. Moreover, in children aged 13, 14, or 16 years, the durartion of PA was negatively correlated with marks for English (r = -0.29 to -0.30). [ 29 ] To our knowledge, these are the only 2 studies to observe negative associations between PA (but not PE) and academic achievement.

A survey of 117 Australian primary schools found no deterioration of literacy and numeracy results in primary school grades 3, 5 and 7 when more time was allocated to PE. [ 30 ] SES was the strongest predictor of both literacy and numeracy scores. A recent analysis of Hong Kong pre-adolescent boys reported that a high level of PA at school was associated with high self-esteem, but not with academic achievement. [ 31 ]

Even studies that failed to find a positive relationship between PA/PE and GPA have generally found no decrease in academic achievement as a consequence of increased participation in PA (Table 2 ). Clearly, the absence of an elevation in GPA should not be interpreted as a negative outcome. This is well illustrated by a survey conducted in Virginia's primary schools. [ 32 ] A reduction in the time allocated for PE (or the arts) did not improve performance in other subjects like mathematics or reading. Moreover, increasing the time allocated to PE (or the arts) at the expense of other academic subjects was not detrimental to test scores in these subjects. [ 32 ] Taken together, these observations suggest that if academic achievements are maintained while spending less time on a specific discipline, the intervention has increased academic efficacy.

Effects of PA on elements considered to favour academic performance

Many factors like classroom behaviour, self-esteem, self-image, school satisfaction and school connectedness have been postulated as determinants of academic achievement.

Classroom behaviour

Self-identification as a school athlete vs. a «jock» is associated with a lower rate of reported misconduct at school [ 33 ], with the exception of binge drinking. [ 34 ] In the American linguistic context, the word "jock" refers to an individual whose life is oriented toward sport; it is not necessarily a pejorative term. However, it should not be confused with the focused and planned life of a typical athlete.

In the Trois-Rivières study, competencies linked to behaviour were similar overall in the experimental vs. the control group. [ 35 ] A German cross-sectional study (CHILT) compared 12 intervention schools (n = 668) vs. 5 control schools (n = 218), finding that PF was associated with concentration in 6–7 years old children. [ 36 ]

Evans et al. [ 37 ] reported a lower rate of inappropriate talking among emotionally, or behaviourally-disturbed children who were participating in a jogging and football exercise programme. Furthermore, a meta-analysis on the effect of exercise prior to classes led to the conclusion that most exercise interventions significantly reduced disruptive behaviours in disturbed students. [ 38 ] These effects could reflect in part better teacher attitudes towards these children, as seen in the Trois-Rivières [ 3 ] and the Australian [ 1 ] quasi-experimental studies.

Other psychosocial effects

Better self-esteem or self-image [ 20 , 39 ] and body image [ 40 ] are commonly associated with high levels of PA. Many studies have also linked school sport or PA programmes with other psychosocial outcomes, such as school satisfaction and school connectedness, regardless of ethnic group [ 41 ]. Both school connectedness and school satisfaction are factors preventing drop-out from school. [ 42 ]

A recent analysis of data from the National Longitudinal Study of Adolescent Health [ 20 ] found evidence of a positive association between PA and components of mental health, including self-esteem, emotional well-being, spirituality, and future expectations. When participation in PA/sports also included parental involvement, the behavioural risk profile became even more positive.

A cross-sectional questionnaire study of 245 Finnish adolescents [ 43 ] observed no association between PA level and school satisfaction and the trend to a weak correlation between PA level and problems at school was not statistically significant. However, PA was correlated with global school satisfaction (r = -0.21 for boys) and absence of a depressive mood state (-0.20 and -0.26 for girls and boys, respectively).

What are the acute effects of PA on cognitive function?

Many authors have documented the acute effects of PA on cognitive function. Three recent reviews and/or meta-analyses examined these studies. [ 44 – 46 ] In a meta-analysis of 44 studies, Sibley and Etnier [ 45 ] concluded that PA was positively associated with better cognitive functioning in children. Some groups, particularly middle school students (grades 6–8, aged 11–13 years) and younger, seemed to benefit more from PA. Sibley and Etnier [ 45 ] noted that unpublished studies had a higher effect size than published reports, suggesting that no bias had occurred from a failure to publish non-significant results.

Brisswalter et al. [ 44 ] reviewed published studies into the effects of exercise on various tasks. They concluded that the optimal intensity for decisional tasks covered a wide range (~40–80% VO 2 max). An exercise duration of more than 20 minutes was most efficient in increasing the performance of perceptual and decisional tasks. [ 44 , 46 ] Tomporowki [ 47 ] suggested an upper limit of 60 minutes might arise from the adverse effects of dehydration on cognitive functions.

The literature generally suggests a positive effect of acute physical exercise on cognition. Other activities, like involvement in music also have the potential to increase reading skills, although in this case there is no positive influence on PF. [ 48 ]

Relationship of PF with academic achievement

What is the effect of a high level of PF on academic performance? Is good cognitive functioning associated with above average PF? If so, is this a consequence of PF per se, or of better overall physical health? When analyzed globally, the literature does not indicate any clear linkage between PF and either academic achievement or intellectual performance. As early as 1969, Railo found no relationship between PF and either of these outcomes. [ 49 ] More recently, Etnier et al. [ 50 ] concluded from a meta-regression analysis that the empirical literature did not support a link between cardiovascular PF and academic achievement. However, this meta-analysis revealed a weakness in the literature: there was little data on the relationship between PF and academic achievement in school-aged children. Indeed, only 1 of the 37 studies identified included this age group.

When the definition of PF includes aspects other than cardiovascular fitness, there seems evidence of positive correlations between various measures of psychomotor performance, cognitive abilities and academic achievement. [ 51 , 52 ] Psychomotor performance shares many common neurological mechanisms with cognitive functions.

A 2001 cross-sectional study on California children disclosed a positive relationship between reading and mathematics results (as measured by Stanford Achievement Test-9) and results on a field test of physical fitness (the Fitnessgram). Despite a huge sample of students from grades 5, 7 and 9 (n = 954,000), potential selection biases were not considered, making it difficult to conclude that PA was linked to increased academic performance. [ 53 ] When found, any effects of PF were small. Another weak association between PF and academic achievement was observed in South Korean children (grades 5, 8, and 11); in this study, the association was much smaller than that between academic achievement and regular meal eating. [ 54 ] Dwyer et al. [ 24 ] measured muscle fitness in 9,000 Australian students. They found significant but weak associations, ranging from r = -0.10 to -0.19 for running distances of 50 m and 1.6 km, and from r = 0.10 to 0.22 for sit-ups and standing long jump, respectively.

School sports and academic achievement

The connection between school sports and intellectual achievement has been a long-standing issue since Davis and Cooper [ 55 ] first reported a positive association between school sports participation and academic achievement. It remains the subject of recent investigations. The competitive dimension of most sports introduces particular problems, even in the school context, as the educational dimension tends to be relegated to a secondary level. The literature comprises mainly cross-sectional data and the results are more equivocal than for PA; unfortunately, most of the earlier studies did not control for biases common to athletic and academic achievements. [ 56 , 57 ]

Data from the longitudinal Maryland Adolescent Development in Context Study included 67% African-Americans and 33% European-Americans; it found that participation in extracurricular PA was a significant predictor of better academic results and of higher academic expectations. [ 58 ] Furthermore, sports participation by 8th grade African-American males resulted in aspirations to continue their studies toward college, with less likelihood of acting inappropriately in school. [ 59 ] In their female counterparts, sports participation also resulted in higher aspirations and in a reduction of absenteeism.

Cooper et al. [ 60 ] found that even after eliminating confounding factors, extracurricular activities, including sports and PA were predictors of better academic achievement in 2,200 American high school students. Their conclusion is in line with the point that Marsh made in 1992, that such activities may have an effect on academic achievement by increasing motivation and investment in school. [ 61 ] Another study of 11,957 American adolescents found that even after standardization for SES, sports participation with parental presence was associated with an increased probability of good grades in English and mathematics, the Adjusted Relative Risk being 1.23 for both subjects. [ 20 ] Dexter [ 62 ] examined the relationship between sports knowledge, sport performance and academic ability, the last being measured by scores on the British General Certificate of Secondary Education (GCSE). They observed a small but significant positive correlation between sports performance and GCSE score for both mathematics and English.

Melnick et al. [ 63 ] detected no relationship between academic achievement and sports participation in 3,686 African-American and Hispanic students from the "High-school and Beyond Study". However, sports participation was associated with a lower drop-out rate. Therefore, they suggested that if sports participation contributes to academic achievement, it may do so indirectly, by encouraging retention in school. Fisher et al. [ 64 ] also observed no association between sports involvement and self-reported grades in an ethnic mix of 838 grade 9 to 12 students (predominantly 63% African-American and 27% Hispanic).

Harvard students involved in varsity teams had a slightly lower GPA than their peers, but reported a higher degree of satisfaction with their university experience. [ 65 ] This also seemed the case in other institutions examined by Light. Athletes have more friends and a stronger sense of belonging to their institution. They are, according to Light, "the happiest on campus". Generally, this same trend is seen among high-school athletes. Students engaged in extracurricular PAs do not achive different academic scores than their peers, but they feel a greater engagement with their institution. [ 66 , 67 ] This may reflect in part the greater attention directed towards these specific students. Indeed, participants in extracurricular activities (including sports) have more interactions with significant adults than non-participants. [ 66 ]

Sport is a very complex phenomenon. There are many cultures within school sports, and any effect on academic achievement is influenced by gender, race, type of sport, type and level of athletic involvement. White and McTeer [ 68 ] suggested that the status of a given sport may influence its effect on academic achievement. Their results showed that high-status sports had a positive influence on English grades but they saw no evidenceof an effect of such sports on mathematics grades. They suggested that academic performance was more likely to be affected by cultural factors in subjective subjects like English than in mathematics. Any influence of school sports participation may also differ between girls and boys [ 33 ], and between various ethnic and cultural groups. [ 69 ]

In conclusion, the available literature suggests that sport is more likely to benefit academic achievement if offered in school rather than in other sport contexts, given the proximity of educational resources and environment. This may be particularly important for team sports, which often seem associated with risky behaviours, particularly binge drinking of alcohol. [ 70 ] When sports-involved students identify themselves as athletes rather than «jocks», such risky behaviours seem less prevalent. [ 67 ] Greater academic coaching of school athletes could be a factor favouring their academic achievement. [ 67 ] School sports should be monitored closely, with the intent of avoiding a drift away from educational objectives. It appears that satisfaction with sports vs. satisfaction with school work is predicted by a differing psychological domain (perceived ability vs. task orientation). [ 71 ] It may be helpful to create an environment where both types of endeavour find common ground, i.e. school may be the best setting in which sports can be directed towards task orientation and skills acquisition, without decreasing the pleasure and satisfaction of being good at sports and PA. As noted in various long-term follow-ups, elite and varsity level athletes later tend to experience greater educational and labour market success than non athletes. [ 34 , 67 , 72 , 73 ] Current evidence suggests that this effect may be mediated by racial group. [ 74 ]

Populations with special educational needs

Academic integration of children with various behavioural and developmental problems is a growing trend in industrialized countries. The question arises in terms of their academic achievement. Reviews of exercise programmes for children with learning disabilities [ 75 , 76 ] have suggested that in order to increase the likelihood of positive outcomes, such programmes should have a low student-instructor ratio. Benefits (with the exception of increased PF) may reflect increased attention toward the participants.

In hyperactive impulsive children, PA is associated with global satisfaction in boys and an absence of depressive emotions in both sexes. [ 77 ] An outdoor education programme also decreased behavioural problems in children with attention deficit hyperactivity disorder. [ 78 ]

In children with reading disabilities, a school-based programme of balance and coordination training, throwing, catching, and stretching produced significant improvements in both reading and semantics. [ 79 ] Positive changes were maintained for at least 18 months following the programme, reducing the likelihood of a Hawthorne effect. [ 80 ]

Four pupils with emotional and behavioural disorders were directly studied before and after a 10-week PE intervention. Back in class, there was an increase (13.8%, or a little more than 23 minutes) in the amount of time spent focused on the tasks they were supposed to be performing. [ 81 ] A 10-week PA intervention in children with learning disabilities improved classroom behaviour and the perception of academic competence was increased. [ 76 ] However, a similar outcome was seen in the control group, indicating that there had been no specific effect from the programme.

The effects of school PA upon children with learning problems thus remains an open field for research.

Is the potential beneficial effect of PE, school PA and sport supported by fundamental research?

The positive association observed between PA and intellectual performance among children in quasi-experimental studies should be supported by mechanistic, experimental evidence. No one can deny the important role of neurosciences in the comprehension of academic achievement. [ 82 ] Most research on the relationships between PA and cognition has centered on the hippocampus, a brain region that mediates memory and learning in mammals, and on changes in the cerebral circulation. The hippocampus has an important role in the consolidation of memory. One major mechanism essential to its functions is long-term potentiation, or LTP. LTP leads to an enhancement of nervous influx following a first series of stimuli.

Exercise and learning mechanisms

Hippocampal LTP is the most credible physiological explanation for learning and memory in mammals, including humans. [ 83 ] LTP leads to an increase of synaptic efficacy following an increase of synaptic traffic. [ 83 ] It was shown recently that PA favours hippocampal LTP. [ 84 ] Chronic exercise favourably influences the hippocampus through 3 mechanisms:

1) Heightened neurogenesis, i.e. an increased formation of new neurons after chronic PA, as demonstrated in the adult mouse [ 85 , 86 ],

2) Augmented LTP itself, i.e. enhanced neuronal transmission in the hippocampus. Different methods employed to measure cognitive functions, and scores on these tasks are well correlated with a better performing hippocampus [ 87 ]. Radial maze learning, i.e. an hippocampal spatial learning, is increased in both male and female rats exercised by voluntary running. The performance of this task does not seem to be influenced by changes in fitness of the animal, as is the case for the Morris water maze. However, if the water maze is used, it remains possible to control for an animal's level of fitness. Other studies using the Morris water maze have also reported improved performance. [ 85 , 88 ] Exercise has no effect on glutamate receptors in the hippocampus in aged rats [ 89 ], reinforcing the view that post-receptor mechanisms are responsible for stronger LTP in active animals. However, this point remains to be confirmed in the hippocampus of younger animals,

3) Chronic exercise creates a favourable environment for LTP by increasing the hippocampal concentrations of neuroprotective factors like brain-derived neurotrophic factor (BDNF) [ 90 ] and of other growth factors such as insulin-like growth factor (IGF-1), nerve growth factor, and fibroblast growth factor 2 (FGF-2).

The brain concentration of some antioxidants is also increased in trained animals, thus protecting hippocampal cells from oxidative damage. [ 91 ] Radak et al. [ 92 ] studied the acute effects of exercise (2 hours). Oxidative damage to macromolecules was reduced through an increase of glutathion synthetase activity and a reduction in the deleterious, inactivity-related efflux of glutamate (the neurotransmitter of learning in the hippocampus). Acute exercise also normalized certain memory functions, particularly orientation time to novelty and passive avoidance reactions.

To our knowledge, these mechanisms of enhanced learning and memory have never been explored in animals at a developmental stage corresponding to school-age children. We hypothesize that, given the higher brain plasticity of childhood, the changes seen in older brains may have an even greater magnitude in the developing brain. The data suggest that the brain structures involved in learning and memory, although more complex, function much like skeletal muscle. To enhance function (i.e. increase memory and learning), periods of stimulation must be followed by a recovery period when supercompensation can take place, and the new proteins associated with learning and memory consolidation can be synthesized.

Discussion and Conclusion

Available data suggest that school PA (PE instruction, free time PA or school sport) could become a consistent component of PA to meet current guidelines for children and adolescents without impairing academic achievement, even if curricular time for so-called academic subjects is curtailed. In his classical work "The Adolescent Society," James S. Coleman advanced the concept of a zero-sum model. [ 93 ] This hypothesized that if time was taken from academic programmes to allow other pursuits, academic achievement would suffer. This concept may be applicable if time is spent in paid employment while attending school [ 94 ], but it does not seem to apply to extracurricular activities like sports or curricular PE. [ 95 ] In contrast, such activities are likely to increase attachment to school and self-esteem which are indirect but important factors in academic achievement.

Parents concerned about decreases in study and homework time may be better advised to question the time their children spend on TV and computer games rather than the time that they devote to PE, PA or sports in school. Indeed, the more children watch TV, the greater the decline in their academic results. [ 96 ] At least one Canadian study found that the time devoted to PA was positively associated with the time that school-aged children spent in reading. [ 97 ] Parents interested in the health and academic success of their offspring should focus on the increased prevalence of various metabolic pathologies in which sedentary behaviour plays a key etiologic role, for example, obesity and type 2 diabetes, both of which are beginning at an ever younger age. [ 98 ] Such pathologies have the potential to affect school performance adversely, although this is an area where more research is needed. [ 99 ] In one recent article, obese 3 rd grade girls (8 years old) did not have poorer academic results after control for SES, but relative to normal weight girls they exhibited more displaced behaviours like arguing and fighting, as well as more depressive symptoms like loneliness and sadness [ 100 ].

Engagement in PE instruction would probably be increased if grades were allocated for performance in PE, particularly in high school. The engagement of girls, particularly, decreases when PE is not considered incalculating their GPA. [ 101 , 102 ] However, between grade 8 and 12, the school drop-out rate for adolescents of both sexes is reduced by sport participation [ 103 ]

Another problem that remains to be resolved, despite a call for action from the Surgeon General in 1996, is the heterogeneity in provision of PE [ 104 ], extracurricular sports and other school PA programmes [ 105 ], schools with a low SES being particularly disadvantaged. School sport would appeal to more students if emphasis was placed on its educational potential rather than its competitive side. Potential drifting of objectives should be monitored to avoid a «subversion» of the educational mission and ensure a maximisation of positive effects such as academic achievement and long term adherence to physical activity. The current emphasis on a limited range of team sports should be modified to provide opportunities for students who are interested in and have the skills relevant to other sport ventures, thus attracting a wider range of students.

Many questions remain to be clarified on the relationship between academic performance, PE, school PA and sports. However, to paraphrase Eccles et al. [ 67 ], "We now know enough about the kinds of programs likely to have positive effects on children and adolescents' development." The literature strongly suggests that the academic achievement, physical fitness and health of our children will not be improved by limiting the time allocated to PE instruction, school PA and sports programmes.

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F. Trudeau is holder of a joint initiative grant from Social Science and Humanity Research Council/Sport Canada. R. J. Shephard is collaborator on the same grant.

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Trudeau, F., Shephard, R.J. Physical education, school physical activity, school sports and academic performance. Int J Behav Nutr Phys Act 5 , 10 (2008). https://doi.org/10.1186/1479-5868-5-10

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The effect of the Sport Education Model in physical education on student learning attitude: a systematic review

  • Junlong Zhang 1 ,
  • Wensheng Xiao 2 ,
  • Kim Geok Soh 1 ,
  • Gege Yao 3 ,
  • Mohd Ashraff Bin Mohd Anuar 4 ,
  • Xiaorong Bai 2 &
  • Lixia Bao 1  

BMC Public Health volume  24 , Article number:  949 ( 2024 ) Cite this article

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Evidence indicates that the Sport Education Model (SEM) has demonstrated effectiveness in enhancing students' athletic capabilities and fostering their enthusiasm for sports. Nevertheless, there remains a dearth of comprehensive reviews examining the impact of the SEM on students' attitudes toward physical education learning.

The purpose of this review is to elucidate the influence of the SEM on students' attitudes toward physical education learning.

Employing the preferred reporting items of the Systematic Review and Meta-analysis (PRISMA) statement guidelines, a systematic search of PubMed, SCOPUS, EBSCOhost (SPORTDiscus and CINAHL Plus), and Web of Science databases was conducted in mid-January 2023. A set of keywords associated with the SEM, attitudes toward physical education learning, and students were employed to identify relevant studies. Out of 477 studies, only 13 articles fulfilled all the eligibility criteria and were consequently incorporated into this systematic review. The validated checklist of Downs and Black (1998) was employed for the assessment, and the included studies achieved quality scores ranging from 11 to 13. The ROBINS-I tool was utilized to evaluate the risk of bias in the literature, whereby only one paper exhibited a moderate risk of bias, while the remainder were deemed to have a high risk.

The findings unveiled significant disparities in cognitive aspects ( n  = 8) and affective components ( n  = 12) between the SEM intervention and the Traditional Teaching (TT) comparison. Existing evidence suggests that the majority of scholars concur that the SEM yields significantly superior effects in terms of students' affective and cognitive aspects compared to the TT.


Nonetheless, several issues persist, including a lack of data regarding junior high school students and gender differences, insufficient frequency of weekly interventions, inadequate control of inter-group atmosphere disparities resulting from the same teaching setting, lack of reasonable testing, model fidelity check and consideration for regulating variables, of course, learning content, and unsuitable tools for measuring learning attitudes. In contrast, the SEM proves more effective than the TT in enhancing students' attitudes toward physical learning.

Systematic review registration

( https://inplasy.com/ ) (INPLASY2022100040).

Peer Review reports


In recent years, the "student-centered" teaching model, as a more effective alternative to the traditional "teacher-centered" teaching model, has gained increasing attention and recognition from education scholars and departments worldwide [ 1 , 2 ]. Metzler [ 3 ] identified a series of "student-centered" teaching models based on constructivism and social learning theories, each developed for specific course objectives [ 4 , 5 ]. Furthermore, it is widely acknowledged that instructional models are in a constant state of development, involving the generation, testing, refinement, and further testing processes under different educational objectives. These instructional models are designed to enable students to acquire a depth and breadth of knowledge in physical education [ 6 ]. In this regard, a series of instructional models have been identified as effective means to achieve specific objectives. Consequently, numerous studies have established that placing students at the center of the instructional process is the most effective approach [ 7 ], allowing for the assessment of the impact of these models on students' learning in physical education. For instance, Cooperative Learning (CL), rooted in the idea of learning together with others, through others, and for others [ 8 ], aims to promote five essential elements [ 9 ]: interpersonal skills, processing, positive interdependence, promoting interaction, and individual responsibility. The underlying concept of Teaching Game for Understanding (TGFU) involves shifting the focus from technical aspects of gameplay to the context (tactical considerations) through modification of representation and exaggeration [ 4 , 10 ]. Emphasizing placing learners in game situations where tactics, decision-making, and problem-solving are non-negotiable features, despite incorporating skill practice to correct habits or reinforce skills [ 11 ], TGFU is structured around six steps: game, game appreciation, tactical awareness, decision-making, skill execution, and performance. Teaching for Personal and Social Responsibility (TPSR), designed by Hellison [ 12 ], aims to cultivate personal and social responsibility in young people through sports activities, defining four major themes: integration, transfer, empowerment, and teacher-student relationships. It revolves around five responsibility goals: respecting the rights and feelings of others, effort (self-motivation), self-direction, caring (helping), and transferring beyond the "gym" [ 13 ]. The SEM comprises six key structural features: season, affiliation, formal competition, culminating events, record-keeping, and festivity. SEM seeks to provide students with authentic, educationally meaningful sporting experiences within the school sports context, aiming to achieve the goal of developing capable, cultured, and enthusiastic individuals [ 14 ]. This suggests a subtle intersection between SEM's developmental goals and enhancing students' learning attitudes (cognitive and emotional), laying the foundation for the selection of teaching model types in this study.

In previous SEM-centered reviews, the focus primarily centered on the model's positive impact on students' personal and social skills [ 15 , 16 ], motor and cognitive development [ 16 ], motivation [ 17 , 18 ], basic needs [ 18 ], prosocial attitudes [ 18 ], and learning outcomes [ 19 ], and it is concluded that the implementation of SEM has a positive effect on improving students' performance in these aspects. While these reviews contribute valuable insights, they exhibit certain limitations, such as a lack of comprehensive exploration of the model's impact on the cognitive and emotional dimensions in the context of school-based physical education. Therefore, our study attempts to bridge this gap by delving into the nuanced intersection between SEM and students' learning attitudes, aiming to provide a more comprehensive understanding of its impact on educational environments.

In the field of education, a focus on practical application and scholarly discourse is crucial and commendable [ 20 , 21 ]. From a practical perspective, research should offer valuable resources for curriculum designers, educators, and policymakers [ 22 , 23 , 24 , 25 ]. In theoretical terms, the contribution of research lies in addressing gaps in the literature by elucidating dimensions within physical education that remain insufficiently explored [ 26 ]. Our study is dedicated to significantly impacting physical education teaching through the practical application and scholarly discourse surrounding SEM. By revealing the subtle interactions between SEM and attitudes, we aim to provide valuable curriculum implementation recommendations for designers, practitioners, and policymakers, filling the gaps in how SEM shapes learning attitudes in educational environments.

In the realm of attitude research, scholars have traditionally classified attitude components into three types: single-component, two-component, and three-component. Advocates of the single-component view contend that attitudes are confined to the emotional dimension. For example, Fazio and Zanna [ 27 ] define attitude as "an evaluative feeling caused by a given object" (p. 162). Two-component researchers posit that attitudes comprise cognition and emotion, with the affective component measuring emotional attraction or feelings toward the object, and the cognitive component representing beliefs about the object's characteristics [ 28 , 29 ]. Bagozzi and Burnkrant [ 30 ] compared the effectiveness of one-component and two-component attitude models, concluding that incorporating both cognitive and emotional dimensions enhances attitude effectiveness. On the contrary, proponents of the three-component perspective argue that attitudes encompass cognition, emotion, and behavior, suggesting that cognitive and emotional responses to an object influence behavior. However, the three-component view has faced skepticism, with some researchers finding that attitude measurement explains only about 10% of behavior variance. Studies reporting higher correlations often focus on attitudes and behavioral intent rather than explicit behavior itself [ 31 , 32 , 33 ]. Our research places a deliberate emphasis on investigating the intersection between the SEM and attitudes to address a noticeable gap in the existing scholarly landscape. While none of the reviewed literature approached the subject from an attitude theory perspective, we prioritize this theoretical framework, acknowledging that attitudes significantly influence student learning [ 16 , 34 ]. Consequently, the exploration of the interplay between SEM and attitudes is considered indispensable for attaining a thorough comprehension of SEM's potential impact in educational contexts. By integrating attitude theory into this inquiry, there is an aspiration to unveil nuanced insights into the cognitive and emotional dimensions influenced by SEM, thereby enriching the understanding of the model's pedagogical implications.

The chosen systematic review approach in this study aims to enhance the reader's understanding of the research methodology, thereby strengthening the overall scientific rigor of the study [ 35 ].

Protocol and registration

This review adheres to the guidelines set forth by the Preferred Reporting Project for Systematic Review and Meta-Analysis (PRISMA). The review has been registered on the International Registry Platform for Systematic Review and Meta-Analysis Programmes (INPLASY) under the registration number INPLASY2022100040. More information about the review can be found at the following link: https://inplasy.com/ .

Search strategy

In October 2004, Siedentop initiated SEM workshops, attracting widespread attention from scholars both domestically and internationally, marking the beginning of SEM practices [ 36 , 37 ]. Subsequently, in many advanced countries such as the United States, New Zealand, Australia, and the United Kingdom, SE has become a mainstream approach in physical education instruction [ 38 ]. Therefore, the retrieval period for this review is set from October 2004 to December 2023, encompassing relevant articles published during this timeframe. A systematic search of four electronic databases was conducted for relevant articles: SCOPUS, PubMed, EBSCOhost (SPORT Discus and CINAHL Plus), and Web of Science. The search aimed to identify studies on the effects of SEM on attitudes toward physical education learning. We employed advanced search methods and added the following search terms: ("Sport Education Model" OR "Sport Education" OR "Sport season") AND ("learning attitude" OR "sports attitude" OR "cognitive" OR "cognition" OR "usefulness" OR "importance" OR "perceptions" OR "affective" OR "emotional" OR "enjoyment" OR "happiness" OR "well-being" OR "Blessedness" OR "subjective well-being") AND ("student" OR "pupil" OR "scholastic" OR "adolescent" OR "teenager"). The search expressions were combined using logical operators. We also sought assistance from librarians in the field to ensure comprehensive results. Furthermore, we manually examined the reference lists of the included studies to identify additional relevant literature and validate the effectiveness of our search strategy.

Eligibility criteria

We employed the Picos framework, encompassing Population, Intervention, Comparison, Outcomes, and Study Design, as the inclusion criteria for this systematic review (Table  1 ). Furthermore, the selected literature adhered to the following additional criteria: (i) it comprised full English texts published in peer-reviewed journals; (ii) the interventions were conducted within the context of physical education, with a comprehensive description of the intervention process and content; (iii) the effects of the SEM and TT on students' learning attitudes (cognitive and emotional) were compared on at least one dimension; (iv) quasi-experimental designs employing objective tests and measurements, along with studies presenting evaluation results, were considered. Exclusion criteria encompassed studies that combined physical education models with other teaching methods or models (hybrid or invasive). Initially, the search strategy was guided by a librarian, and duplications were eliminated by importing the retrieved literature into Mendeley reference management software. Subsequently, decisions regarding literature exclusion and retention were made through the screening of titles and abstracts. Ultimately, articles deemed highly relevant were read in full. The primary outcome aimed to assess attitudes (cognitive and affective) toward physical learning based on the SEM.

The search strategy was guided by a librarian, and the obtained literature was imported into Mendeley reference management software for duplicate removal. Decisions regarding literature inclusion and exclusion were made based on the screening of titles and abstracts. Articles that were deemed highly relevant were read in their entirety. The primary focus of this review was to assess attitudes (cognitive and affective) toward physical learning, specifically based on the SEM. The designation "not relevant" is employed to characterize articles subjected to thorough scrutiny, which fail to make substantive contributions to the fundamental focus of our research. More precisely, those articles deemed irrelevant were those that omitted consideration of the pivotal variables under examination, namely, cognitive and emotional dimensions. Furthermore, they were not situated within the milieu of a scholastic educational framework for physical education (SEM). This methodological approach has been instituted to uphold the establishment of a centralized and cohesive dataset requisite for subsequent analytical procedures [ 39 ] (See Fig.  1 ).

figure 1

PRISMA summary of the study selection process

Study selection

Prior to conducting the search, consultation with an experienced librarian was sought to develop an effective retrieval strategy. Following this, two independent reviewers conducted the literature search. All retrieved studies were imported into Mendeley literature management software to identify and eliminate duplicates. Initially, the literature was screened based on the titles by two independent evaluators, who excluded irrelevant studies. Subsequently, the abstracts of the initially selected literature were reviewed against pre-established inclusion criteria to determine their eligibility for inclusion in the study. Finally, the full text of the included literature was reviewed by two authors, who extracted relevant information. In the case of any disagreements, a third author (K.G.S.) was involved in the review process.

Data extraction and quality assessment

The data extraction process involved collecting the following information: (1) author and year of publication; (2) research design, including the type of experiment or teaching project; (3) population details, such as student category, total number of students, age range, and gender distribution, as well as group size; (4) intervention characteristics, including the total number of interventions, weekly frequency of interventions, duration of each intervention, and consistency of intervention location; (5) a comparison group, typically involving the TT and country information; (6) results, which encompassed the measurement tools used, specific indicators measured, and the research findings. The collected data were independently summarized and reviewed by two authors, with the involvement of a third author to resolve any discrepancies or disagreements.

The methodological quality of the selected articles in this systematic review was assessed using the validated checklist developed by Downs and Black [ 40 ]. The checklist consisted of 27 items, which were categorized into three domains: reporting (items 1–10), validity (external validity: items 11–13; internal validity: items 14–26), and statistical power (item 27). Each item was scored, resulting in a total score ranging from 0 to 27, with higher scores indicating higher methodological quality.

In this review, the cross-sectional and longitudinal surveys were scored in detail using the Downs and Black checklist to evaluate the strengths and weaknesses of each study [ 40 ]. The scoring process involved two primary assessors independently assessing the selected studies. In case of any ambiguity or disagreement, a resolution was reached through reconciliation. If disagreements persisted, the assessment was conducted by one of the co-authors until a consensus was reached.

The classification criteria for the scores were as follows: studies with a score below 11 were considered to have low methodological quality, scores ranging from 11 to 19 indicated medium quality, and scores higher than 20 indicated high methodological quality [ 41 ]. Upon assessment, it was found that all selected articles in this review fell within the medium-quality range (see Table  2 ).

The studies risk of bias

The Risk of Bias in Non-randomized Studies-of Interventions (ROBINS-I) tool encompasses seven evaluation areas, which are further divided into three distinct stages: pre-intervention, intervention, and post-intervention. The pre-intervention stage includes two evaluation areas: confounding bias and selection bias of participants. The intervention stage focuses on the evaluation of bias in the classification of interventions. The post-intervention stage comprises four evaluation areas: bias due to deviations from intended interventions, bias due to missing data, bias in the measurement of outcomes, and bias in the selection of reported results. Each evaluation area is composed of multiple signaling questions, amounting to a total of 34 signaling questions.

Methodical quality

The articles underwent assessment using the validated checklist developed by Downs and Black (1998): 11–13 (mean = 12.38; median = 12; mode = 12 & 13). All the articles demonstrated a medium level of quality, indicating their suitability for inclusion in this review. Furthermore, it suggests the potential for higher-quality articles in future studies. Among the thirteen included articles, five were published within the last three years, constituting one-third of the included literature. This observation highlights the ongoing research interest and significance of the SEM in the investigation of various teaching models. In terms of the Hypothesis/aim/objective, participant characteristics, interventions, main findings, data variability, probability values, statistical tests, detailed intervention descriptions, reliable outcome measures, participant source ( n  = 12), participant grouping ( n  = 11), and random allocation ( n  = 3) were adequately addressed. However, aspects such as reporting measurement outcomes in the introduction or methods section, confounder distribution, adverse events following the intervention, characterization of lost-to-follow-up patients, data analysis, blinding of participants and assessors, adjustment for confounding, and identification of chance results with a probability less than 5% ( n  = 0) were not thoroughly addressed. Although the implementation of blind subjects, therapists, and assessors in teaching experiments poses challenges, future research should strive for higher quality and stronger levels of evidence [ 23 ].

After a detailed reading of the literature that meets the inclusion criteria of this review and the extraction and sorting of important information, it is presented in Table  3 .

The bias risk assessment results are summarized in Table  4 , which includes information such as author/date, field of study, study type, risk assessment tool, and overall rating. The main sources of bias identified were confounding factors and outcomes measurement. The evaluation revealed that only two experimental studies in the Confounders field had a moderate risk of bias, while the rest had a high risk of bias. All included literature demonstrated low risk in terms of subject selection, classification of recommended interventions, and deviation from established interventions. Furthermore, one-third of the literature showed low-risk missing data [ 23 , 42 , 50 , 51 ], while other studies did not provide relevant information. Lastly, nearly a third of the literature showed missing data for low-risk.

Overview of sports and experiment design

All thirteen papers included in this review utilized a pre-posttest design. The sports covered in these studies encompassed basketball, volleyball, soccer, ultimate Frisbee, table tennis, hockey, Polskie ringo, ball games, and body movements. Some studies examined two exercise programs [ 23 , 43 ], while the majority of research focused on basketball [ 44 , 52 , 53 ]. The participants in the course experiments were primarily college and high school students, with a limited number of studies investigating primary and junior high school students. The distribution of participants included college students (3), high school students (8), primary school students (1), and junior high school students (1). The sample sizes in these studies ranged from 40 to 508. Since the selected studies were teaching experiments, most of them involved mixed-sex classes, with four studies not specifying the gender of the students. Only one study established three experimental classes and two control classes [ 50 ], while the remaining studies had one experimental class and one control class. The number of interventions ranged from 8 to 25, with each intervention lasting between 45 and 90 min.

The majority of studies in the selected literature directly applied the SEM as the intervention. Five of the studies incorporated constructivism theory [ 48 ], self-determination theory [ 23 , 44 , 47 ], and ARCS learning motivation theory [ 52 ]. None of the literature investigated from the perspective of attitude theory. Furthermore, none of the selected studies mentioned the teaching standards or syllabus used to design the course content, nor did they provide explanations for the rationale behind the experimental teaching content. The number of interventions in the trials ranged from 8 to 25, with up to half of the studies using fewer than 18 interventions [ 42 , 47 , 48 , 49 , 50 , 52 , 53 ], the recommended class hours for large unit teaching are not met [ 54 ]. The duration of each intervention was most commonly reported as 45 or 60 min [ 42 , 43 , 44 , 47 , 49 , 50 , 51 , 52 , 53 ]. The frequency of weekly interventions varied from 1 to 5, but the majority of studies implemented interventions once a week [ 23 , 42 , 43 , 46 , 47 , 48 , 49 ]. The intervention frequency was generally low, and there was a scarcity of studies with higher intervention frequency. With the exception of one article that conducted the intervention in two schools without providing an explanation [ 50 ], the remaining studies were conducted within the same school.

The control classes in the selected literature implemented similar TT and forms, despite variations in naming used by scholars from different countries or even within the same country. The TT employed in the control classes were mainly Direct Instruction in Australia [ 43 , 46 , 47 , 51 , 52 ], Morocco [ 50 ], and Spain [ 42 , 43 , 44 ], In China, the traditional teaching models were referred to as TT [ 48 , 52 ] and Latent Growth Model [ 49 ]; Traditional Style in the United States and England [ 42 ], American Skill-drill-game [ 44 , 45 ], and multiactivity model [ 23 ].

Measuring instruments and main outcomes

The findings of this investigation were classified based on the impact of the SEM on various aspects of students' attitudes toward physical education: cognitive and affective domains. Through the segregation of subjects and constituents from prior research, the favorable and unfavorable indicators of affective and cognitive dimensions were predominantly derived from the existing body of literature.

The effect of SEM on student cognitive

In this literature review, it was evident that all the included studies reached a unanimous conclusion that the overall effectiveness of the SEM surpassed that of the TT. Among these studies, eight of them specifically evaluated students' cognitive performance [ 23 , 42 , 43 , 45 , 48 , 50 , 52 ]. Various assessment instruments were employed, such as the Intrinsic Motivation Inventory (IMI) [ 42 , 43 , 45 ], the Amotivation subscale of the Academic Motivation Scale (AMS) [ 23 ], the attitude questionnaire [ 48 ], the Spanish version of the Sport Satisfaction Instrument (SVSSI) [ 50 ], the ARCS Learning Motivation Scale, the Physical Education Affection Scale (PEAS) [ 52 ], and the ALT-PE data were collected using momentary time sampling for each team by trained coders [ 53 ].

The study participants encompassed junior high school students [ 43 ], high school students [ 23 , 42 , 45 , 48 , 50 ] and College students [ 52 , 53 ]. Most of these investigations revealed that following the intervention of the physical education course, the cognitive abilities of students in the intervention group exhibited significant improvement, surpassing those of the control group instructed through the TT. Conversely, no significant changes were observed within the control group before and after the experiment [ 23 , 42 , 48 , 50 ]. Nevertheless, one study reported a significant decrease in cognitive abilities among students in the control group before and after the experiment [ 54 ], the other two studies showed that both the experimental and control groups showed significant improvements, but the experimental group showed significantly greater improvements [ 52 , 53 ].

The effect of SEM on student's affective

In this comprehensive review, all the included studies examined students' affective aspects. The assessment instruments employed were as follows: Intrinsic Motivation Inventory (IMI) [ 42 , 43 , 44 , 45 , 47 ], Amotivation subscale of the Academic Motivation Scale (AMS) [ 23 ], Intention to be Physically Active Scale (IPAS) [ 46 ], the attitude questionnaire [ 48 ], Physical activity enjoyment scale (PACES) [ 49 ], the Spanish version of the Sport Satisfaction Instrument (SVSSI) [ 50 ], Positive and Negative Affect Scale (PANASN) [ 51 ] and the Physical Education Affection Scale (PEAS) [ 52 ].

The study participants encompassed primary school students [ 51 ], Junior high school students [ 43 ], high school [ 23 , 42 , 44 , 45 , 46 , 47 , 48 , 50 , 51 ] and College students [ 49 , 52 ]. Out of the 12 studies, four reported positive and/or negative interests or enjoyment among students. Among these, two studies indicated that the experimental group students exhibited significantly higher positive affect than the control group students [ 47 , 51 ]. However, the measurement results varied within the control group. One study reported no significant improvement [ 47 ], while another study showed significant improvement, but the effect was significantly greater in the experimental group compared to the control group [ 51 ]. Furthermore, one study demonstrated no significant difference between the two groups as the test indicators did not exhibit significant changes before and after the experiment [ 46 ].

Regarding the investigation of negative affect, three studies reported that the experimental group students exhibited significantly lower negative affect compared to the control group [ 47 , 51 ], with a significant decrease in negative affect observed in the experimental group while no significant change was noted in the control group. Additionally, one study showed no significant difference and no significant improvement in the test results between the two groups before and after the experiment [ 46 ].

Among the remaining eight studies, it was not specified whether the investigation focused on positive or negative effects. Among them, two studies solely compared the improvement effects between the experimental and control groups without conducting intra-group comparisons before and after the experiment, and the results revealed that the experimental group exhibited significantly better outcomes than the control group [ 45 , 49 ]; the remaining six studies conducted comparisons not only between groups before and after the experiment but also within each group. Five studies demonstrated a significant increase in the affected index of the experimental group, while the control group exhibited no significant change [ 23 , 42 , 44 , 48 , 52 ], and one study revealed that the experimental group displayed a significant improvement, while the control group experienced a significant decline [ 43 ].

This paper presents a comprehensive review of the effects of the SEM on students' attitudes towards physical education. Its aim is to distinguish this study from other published research on the application of the SEM interventions among students. The findings indicate that the SE model has the potential to enhance students' attitudes toward physical education in terms of cognition and affect. However, certain factors such as the lack of data on junior high school students and gender differences, the frequency and duration of intervention per week, the variation in the learning environment across groups taught in the same setting, the rationale behind the course content, and the selection of tools for measuring learning attitudes may influence the experimental outcomes. Nonetheless, considering the positive results observed in these studies, is SEM an effective way to interfere with students' attitudes toward physical education learning? In conjunction with the information presented in the " Results " section, this review offers a detailed analysis of the impact of various dimensions of student attitudes toward physical education learning.

As anticipated, eleven out of the thirteen studies included in this review focused on ball games, which aligns with the competitive nature of these sports [ 55 ]. This choice is well-suited to the seasonal characteristics of the Sports Education Model (SEM) [ 56 , 57 ]. When considering gender comparisons, incorporating gender research can enhance the reliability of experimental findings [ 58 , 59 ]. However, in all the studies included, the majority of researchers only used mixed experimental and control groups, without comparing gender distinctions. If significant differences exist in the effect of SEM on the learning attitudes of students of different genders, it would significantly impact the accuracy of the experimental results.

Regarding the frequency, number, and duration of each intervention, some scholars have suggested that these factors may have different effects on the experimental outcomes [ 60 ], However, among the thirteen studies reviewed, the largest number of interventions was only 25 [ 23 ], and most studies had fewer than 20 interventions. Most studies had fewer than 18 interventions. This deviates from the use of large unit teaching advocated by some scholars to enhance students' systematic cognition and learning experience of a sports event [ 54 , 61 ]. In the reform of the school curriculum, the State Council of China issued the Curriculum Standards for Physical Education and Health for Compulsory Education (2022 edition) for students, which also clearly mentioned that the length of class hours for large units should not be less than 18 lessons.

In terms of the rationality of classroom teaching form and content, Hastie et al. [ 62 ] developed an Instructional Checklist to evaluate the effectiveness of the SEM and TT. However, only four of the included studies addressed this aspect [ 46 , 47 , 50 ]. Regarding the selection of measurement tools, none of the studies examined students' learning attitudes using scales developed based on attitude theory. According to the two-component proponents of attitude, attitude theory defines attitude as the affective and cognitive (positive or negative) evaluation of individuals toward the object of attitude [ 28 , 29 , 30 , 63 ]. Failing to assess student attitudes using survey instruments developed based on the structural composition of attitudes is problematic, as these instruments may not accurately measure attitudes [ 64 ]. The critical concern regarding the assessment of student attitudes using survey instruments developed based on the structural composition of attitudes requires a more thorough explanation. This is particularly important because relying on instruments that do not align with the multi-dimensional nature of attitudes, encompassing affective, cognitive, and conative components, may lead to inaccurate measurements [ 64 ]. To elaborate further, historical quantitative investigations in physical education pedagogy often utilized instruments such as Kenyon's [ 65 ] or Simon and Smoll's [ 66 ], which might not capture the complete construct of attitude. For instance, Kenyon's instrument conceptualizes physical activity rather than attitude as a multidimensional construct, while Simon and Smoll's instrument, developed for adults, may not be entirely valid for children. This unidimensional perspective on attitude, focusing solely on the affective dimension, is problematic, as it overlooks the multi-component nature of attitude, as acknowledged in studies by Gonzàles [ 67 ], Mohsin [ 68 ], and Oppenheim [ 69 ]. Therefore, future research endeavors should delve into the intricacies of attitude assessment tools, considering the developmental differences and the multidimensional nature of attitudes to ensure comprehensive and accurate measurement in the context of physical education pedagogy.

The existing literature provides sufficient evidence to support the significant superiority of physical education courses over TT in enhancing students' cognition of physical education learning. The cognitive dimension refers to individuals' evaluation of concepts and beliefs related to specific people, things, and objects, forming a multi-perspective system [ 32 , 49 ]. The development of ideas and beliefs relies on a solid foundation of knowledge about people and things. Students' cognition of physical education learning serves as a prerequisite for fostering positive attitudes toward physical education [ 70 ]. However, among the eight studies included in this review that examined the cognitive components of attitudes, seven studies concluded that SEM and TT had a more significant impact on improving students' perception of attitudes toward physical education learning [ 23 , 42 , 43 , 45 , 48 , 50 , 53 ]. Most of these studies indicated that students' perception of physical education learning did not change significantly under TT. Only one study found that both SEM and TT showed significant improvements before and after the experiment, with no significant difference in the degree of improvement between them [ 52 ]. However, it is noteworthy that the study by Chu et al. [ 49 ] lacked a thorough examination of the model fidelity for both the SEM and TT. The absence of a robust fidelity check raises concerns about the reliability and validity of the observed improvements reported in both SEM and TT groups before and after the experiment. Without ensuring that the implemented instructional models were faithfully executed as intended, it becomes challenging to attribute the observed improvements solely to the effectiveness of the instructional methods. Consequently, the study reports significant improvements in both SEM and TT without a discernible difference in the degree of improvement between them. This underscores the importance of conducting comprehensive model fidelity checks to enhance the credibility and interpretability of research findings, particularly when comparing the effectiveness of different instructional models in educational settings. Although most studies support the significant superiority of the SEM in enhancing students' perception of physical education learning compared to traditional instruction, it is important to note that five out of seven studies were conducted with high school students, limiting the generalizability of the findings to broader populations. This represents a crucial gap in the existing literature regarding learning cognition in physical education. Furthermore, despite having mixed-gender classes, the studies did not include a comparative analysis of students from different genders. Therefore, it is necessary to conduct additional comparative studies on the SEM and TT, encompassing various learning stages and considering the cognition of physical education learning among students of different genders, to enrich the breadth of results.

The majority of sports scholars hold the view that the SEM is superior to the TT in fostering students' emotional experiences in sports learning. The affective dimension pertains to the emotions and emotional experiences of individuals based on cognitive factors related to specific people, things, or objects, such as interest or enjoyment [ 32 , 49 ]. By comparing SEM and TT, eleven out of the thirteen studies analyzing improvements in student physical education learning confirmed that SEM significantly outperformed TT in enhancing student interest or enjoyment [ 23 , 42 , 43 , 44 , 45 , 47 , 48 , 49 , 50 , 51 , 52 ]. Only one study found that both SEM and TT did not lead to significant improvements in student interest or enjoyment, as there were no significant changes in test results before and after the learning social work experiment in both groups [ 46 ]. Notably, three of the studies involved opposite outcomes of positive and negative effects [ 46 , 47 , 51 ], and one study exclusively reported negative affect [ 50 ]. These divergent results underscore the complexity of the relationship between instructional models and students' attitudes towards physical education. Future research endeavors should delve deeper into the factors contributing to such variations, exploring potential moderating variables, instructional nuances, or contextual influences that may elucidate the observed disparities. These findings not only deserve attention for their immediate implications but also emphasize the need for nuanced investigations that can inform the refinement and optimization of instructional approaches in the field of physical education.

Moreover, among the four studies involving 20 or more interventions, three studies conducted within-group comparisons of SEM and TT before and after the experiment [ 23 , 43 , 45 ], and the frequency of weekly interventions varied. One study with a low intervention frequency found a significant decrease in emotional aspects among students in the TT group before and after the experiment [ 43 ]. However, two studies with high intervention frequency found no significant changes in the emotional aspects of students in the TT group before and after the experiment [ 23 , 44 ]. These results contradict Chen's argument (2019) that prolonged treatment may lead to adverse emotions such as anxiety and depression. However, these limited findings do not provide strong evidence and require further validation in future studies with larger sample sizes.


In summary, this review presents substantial evidence supporting the superiority of the SEM over TT in enhancing students' attitudes toward physical education learning. However, there are several limitations to consider. Firstly, none of the included studies reported gender differences, which limits the richness and specificity of the research findings. Gender differences, if present, could potentially impact the accuracy of the overall results. Secondly, the studies did not address the influence of class size on teaching experiment outcomes. Determining the optimal number of students per group and the ideal number of groups is an important consideration for achieving optimal teaching effects. Inappropriate, insufficient, or excessive sample sizes can affect the quality and accuracy of experiments [ 71 ]. Thirdly, most studies did not account for the experimental environment or control participants' physical activities outside the experimental setting, which may influence students' attitudes toward physical education learning. Additionally, the studies generally did not consider the impact of factors such as climate and time on students' attitudes during the teaching experiments. Lastly, none of the studies included in this review conducted any short-term or long-term follow-up of students after the trial, making it challenging to determine the long-term effects of SEM on students' attitudes toward physical education learning.

The systematic review conducted provides compelling evidence supporting the positive impact of the SEM on students' attitudes toward physical education learning. However, it is important to note that most of the literature included in this review focused on high school and college students, while there were fewer findings for other school age groups. Urgently needed are comprehensive research initiatives that prioritize investigating the impact of the SEM on attitudes towards physical education learning across diverse age groups, including primary and middle school students. This will contribute to a more inclusive understanding of SEM's effectiveness, ensuring that its benefits are explored and validated across various educational stages, thus providing a solid foundation for evidence-based instructional practices in physical education. Additionally, although SEM is an established teaching model, recent research has shown an increase in its popularity in physical education, with five out of the thirteen studies published in the last three years. Nevertheless, it is crucial to approach the results with caution due to the limitations identified in this study.

To further deepen our understanding of the effectiveness of SEM in improving students' attitudes toward physical education learning, it is imperative to address the issue of model fidelity checks for both SEM and TT. The study highlighted the absence of a thorough examination of the model fidelity in certain investigations, which raises concerns about the reliability and validity of the observed improvements reported in both SEM and TT groups before and after the experiment. Future research should prioritize rigorous fidelity checks to enhance the credibility and interpretability of research findings when comparing the effectiveness of different instructional models.

Moreover, the identified divergent outcomes in some studies, including those with opposite positive and negative effects, as well as studies reporting exclusively negative affect, underscore the complexity of the relationship between instructional models and students' attitudes towards physical education. Therefore, future investigations should explore potential moderating variables, instructional nuances, or contextual influences contributing to such variations. This comprehensive approach will not only help refine our understanding of SEM's impact on attitudes but also aid in the selection of teaching models that align with the demands of contemporary times.

To optimize the study of SEM's influence on students' physical education learning attitudes, it is recommended to increase the number and frequency of interventions appropriately. Additionally, future research endeavors should consider demographic factors such as the gender and age of the students, contributing to a more nuanced understanding of SEM's impact across different populations. This continued exploration will not only verify the advantages of SEM in promoting students' physical education learning but also enrich the research outcomes concerning the influence of SEM on students' attitudes, addressing the identified gaps and fostering advancements in physical education pedagogy.

Availability of data and materials

The data set supporting the conclusions of this article is included within the article.

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Zhang, J., Xiao, W., Soh, K.G. et al. The effect of the Sport Education Model in physical education on student learning attitude: a systematic review. BMC Public Health 24 , 949 (2024). https://doi.org/10.1186/s12889-024-18243-0

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  2. A systematic review of the effectiveness of physical education and

    This article presents a systematic review of published literature on the effectiveness of physical education in promoting participation in physical activity, ... European Physical Education Review. 11(3): 257-285. Crossref. Google Scholar. Mosston M, Ashworth S (1986) Teaching physical education. Merill: Ohio.

  3. | Literature Review- Physical Education and Academic Achievement in

    For our literature review we will focus on the relationship between physical education and its effect on academic achievement in schools in urban areas. We will do this by addressing the importance of opportunities for physical education today, along with the following factors, health, testing scores, and amount of PE time.

  4. Personal and social development in physical education and sports: A

    This review provides an overview of the existing literature on school-aged children's and youth's (i.e. 6- to 18-year-olds) personal and social development within the context of physical education and sports.

  5. Physical Education and Sport in Schools: A Review of ...

    This paper explores the scientific evidence that has been gathered on the contributions and benefits of physical education and sport (PES) in schools for both children and for educational systems ...

  6. Didactics of health in physical education

    In recent years an increasing amount of research focusing on different aspects of health in physical education (PE) has been published (e.g. Cale and Harris 2013; Cale, Harris, and Chen 2014; ... Didactics of health in physical education - a review of literature. Hanne H. Mong Department of Physical Education, Norwegian School of Sport ...

  7. Physical Education Curriculum Interventions: A Review of Research

    Effective physical education (PE) may lead to positive student learning related to skill acquisition, ... (PE) curriculum interventions, and (b) to determine the efficacy of these interventions. We followed a pre-established literature review protocol to search, identify, screen, and analyze the scholarship related to PE curriculum ...

  8. Pedagogies of embodiment in physical education

    This article is a literature review of peer-reviewed empirical studies aiming to explore empirical research on pedagogies of embodiment in physical education. We ask what characterizes the empirical research literature on pedagogies of embodiment in physical education, and what implications for teaching and learning we can find in this literature.

  9. A Decade of Research Literature in Physical Education Pedagogy

    Papers represented all three focus areas: teaching (65.31%), curriculum (19.24%), and teacher education (15.45%). Research in physical education pedagogy has increased each year since 1995 ...

  10. Cooperative learning in physical education lessons

    Cooperative learning in physical education classes is perceived as beneficial. The aim of this article was to examine whether field studies that include cooperative learning in their physical education intervention programs provide applicable data—to allow teachers to choose the optimal teaching strategy in line with their teaching goals. A systematic review of 44 research studies, published ...

  11. PDF The impact of PE and sport on education outcomes: Literature review

    5.0 The impact of physical education, physical activity and sport on classroom behaviours that may impact on academic achievement. Physical activity has a positive effect on classroom behaviour according to the data presented in extensive reviews on the topic (Strong et al., 2005; Trudeau & Shephard, 2008).

  12. The physical education pedagogical approaches in nurturing physical

    To review the physical education and health curricula, the underlying learning objectives and the physical literacy approaches adopted in New Zealand ... Kirk, D. (2020), Pedagogies of embodiment in physical education - a literature review [Review; early access]. Sport Education and Society, 27(2), 1-13 doi: 10.1080/13573322.2020.1821182 ...

  13. Physical education, school physical activity, school sports and

    The purpose of this paper is to review relationships of academic performance and some of its determinants to participation in school-based physical activities, including physical education (PE), free school physical activity (PA) and school sports. Linkages between academic achievement and involvement in PE, school PA and sport programmes have been examined, based on a systematic review of ...

  14. The effect of the Sport Education Model in physical education on

    Evidence indicates that the Sport Education Model (SEM) has demonstrated effectiveness in enhancing students' athletic capabilities and fostering their enthusiasm for sports. Nevertheless, there remains a dearth of comprehensive reviews examining the impact of the SEM on students' attitudes toward physical education learning. The purpose of this review is to elucidate the influence of the SEM ...

  15. The association between physical education and academic achievement in

    A total of 5,599 unique articles were returned from the searches and alerts after duplicates were removed. Articles were then screened against inclusion and exclusion criteria with 88 articles identified for full text review. This literature review reports on the final 48 peer-reviewed research articles to meet the inclusion criteria.

  16. Inclusion in Physical Education: A review of literature

    The purpose of this review was to analyse empirical studies on inclusion in physical education (PE) over the past 20 years and then propose recommendations for future research. A systematic ...

  17. Physical literacy in the field of physical education

    This literature overview and analysis highlight a growing scholarly interest in the concept of physical literacy. It seems that physical literacy has been a "longed-for" concept. The literature, as the concept itself, has been developed, challenged, and re-formulated over a period of more than one decade.

  18. Literature review: Physical education in the covid-19 pandemic

    Meanw hile, most students stated that online learning f or physical education during. this pandemic was not y et fully effective. The purpose of this literature. study was to provide a review of ...

  19. Physical Education: Literature Reviews

    This tutorial from NCSU gives a good overview of the process of the literature review. Types of Literature Reviews. Completing Literature Reviews. Links to Further Help You... Purdue Online Writing Lab. ... Tags: Exercise, gym, PE, physical education, recreation, recreation and leisure studies, recreational, sports, working out.

  20. Inclusion in Physical Education: A review of literature

    A systematic process was used to search the literature for this review. First, a total of 75 research-based articles from computerised education databases were included in this review. Second, the publication descriptor data were summarised and analysed according to the geographic distribution, study period, research theme, and research method.

  21. Education Sciences

    A systematic literature review of 50 articles selected according to the PRISMA guidelines revealed that the focus of CL applications varied according to the age of the students and multicultural contexts. At the micro level, physical and social domains were emphasized, while cognitive domains received less attention.

  22. Full article: Primary physical education (PE): School leader

    1. Introduction. Physical education (PE) is described "as the only curriculum subject whose focus combines the body and physical competence with values-based learning and communication, [which] provides a learning gateway to grow the skills required for success in the 21st Century" (United Nations Educational, Scientific and Cultural Organisation [UNESCO], Citation 2015, p. 6).

  23. Financial Resource Management Knowledge, Skills, and Attitud

    cal education experiences (CEEs), and employers in addressing these KSAs. Review of Literature. FRM KSAs have been identified as components of professionalism and leadership and, as such, are a required element in student PTs (SPTs) educational preparation. Subjects. A purposive sampling of convenience strategy was employed by requesting a free mailing list for Ohio-licensed PTs. Methods. An ...

  24. "Physical education", "health and physical education", "physical

    Names used to represent physical education around the world include; physical literacy, health literacy and health and physical education (HPE). Literature suggests that many teachers lack confidence and competence when it comes to teaching physical education, subsequently adopting avoidance tactics and as a result children suffer.