performance task for physical education

What is a Performance Task? (Part 1)

Defined Learning

Performance Task PD with Jay McTighe — Blog

A performance task is any learning activity or assessment that asks students to perform to demonstrate their knowledge, understanding and proficiency. Performance tasks yield a tangible product and/or performance that serve as evidence of learning. Unlike a selected-response item (e.g., multiple-choice or matching) that asks students to select from given alternatives, a performance task presents a situation that calls for learners to apply their learning in context.

Performance tasks are routinely used in certain disciplines, such as visual and performing arts, physical education, and career-technology where performance is the natural focus of instruction. However, such tasks can (and should) be used in every subject area and at all grade levels.

Characteristics of Performance Tasks

While any performance by a learner might be considered a performance task (e.g., tying a shoe or drawing a picture), it is useful to distinguish between the application of specific and discrete skills (e.g., dribbling a basketball) from genuine performance in context (e.g., playing the game of basketball in which dribbling is one of many applied skills). Thus, when I use the term performance tasks, I am referring to more complex and authentic performances.

Here are seven general characteristics of performance tasks:

• Performance tasks call for the application of knowledge and skills, not just recall or recognition.

In other words, the learner must actually use their learning to perform . These tasks typically yield a tangible product (e.g., graphic display, blog post) or performance (e.g., oral presentation, debate) that serve as evidence of their understanding and proficiency.

2. Performance tasks are open-ended and typically do not yield a single, correct answer.

Unlike selected- or brief constructed- response items that seek a “right” answer, performance tasks are open-ended. Thus, there can be different responses to the task that still meet success criteria. These tasks are also open in terms of process; i.e., there is typically not a single way of accomplishing the task.

3. Performance tasks establish novel and authentic contexts for performance.

These tasks present realistic conditions and constraints for students to navigate. For example, a mathematics task would present students with a never-before-seen problem that cannot be solved by simply “plugging in” numbers into a memorized algorithm. In an authentic task, students need to consider goals, audience, obstacles, and options to achieve a successful product or performance. Authentic tasks have a side benefit — they convey purpose and relevance to students, helping learners see a reason for putting forth effort in preparing for them.

4. Performance tasks provide evidence of understanding via transfer.

Understanding is revealed when students can transfer their learning to new and “messy” situations. Note that not all performances require transfer. For example, playing a musical instrument by following the notes or conducting a step-by-step science lab require minimal transfer. In contrast, rich performance tasks are open-ended and call “higher-order thinking” and the thoughtful application of knowledge and skills in context, rather than a scripted or formulaic performance.

5. Performance tasks are multi-faceted.

Unlike traditional test “items” that typically assess a single skill or fact, performance tasks are more complex. They involve multiple steps and thus can be used to assess several standards or outcomes.

6. Performance tasks can integrate two or more subjects as well as 21st century skills.

In the wider world beyond the school, most issues and problems do not present themselves neatly within subject area “silos.” While performance tasks can certainly be content-specific (e.g., mathematics, science, social studies), they also provide a vehicle for integrating two or more subjects and/or weaving in 21st century skills and Habits of Mind. One natural way of integrating subjects is to include a reading, research, and/or communication component (e.g., writing, graphics, oral or technology presentation) to tasks in content areas like social studies, science, health, business, health/physical education. Such tasks encourage students to see meaningful learning as integrated, rather than something that occurs in isolated subjects and segments.

7. Performances on open-ended tasks are evaluated with established criteria and rubrics.

Since these tasks do not yield a single answer, student products and performances should be judged against appropriate criteria aligned to the goals being assessed. Clearly defined and aligned criteria enable defensible, judgment-based evaluation. More detailed scoring rubrics, based on criteria, are used to profile varying levels of understanding and proficiency.

Let’s look at a few examples of performance tasks that reflect these characteristics:

Botanical Design (upper elementary)

Your landscape architectural firm is competing for a grant to redesign a public space in your community and to improve its appearance and utility. The goal of the grant is to create a community area where people can gather to enjoy themselves and the native plants of the region. The grant also aspires to educate people as to the types of trees, shrubs, and flowers that are native to the region. Your team will be responsible for selecting a public place in your area that you can improve for visitors and members of the community. You will have to research the area selected, create a scale drawing of the layout of the area you plan to redesign, propose a new design to include native plants of your region, and prepare educational materials that you will incorporate into the design.

Check out the full performance task from Defined STEM , here: Botanical Design Performance Task . Defined STEM is an online resource where you can find hundreds of K-12 standards-aligned project based performance tasks.

Evaluate the Claim (upper elementary/ middle school)

The Pooper Scooper Kitty Litter Company claims that their litter is 40% more absorbent than other brands. You are a Consumer Advocates researcher who has been asked to evaluate their claim. Develop a plan for conducting the investigation. Your plan should be specific enough so that the lab investigators could follow it to evaluate the claim.

Moving to South America (middle school)

Since they know that you have just completed a unit on South America, your aunt and uncle have asked you to help them decide where they should live when your aunt starts her new job as a consultant to a computer company operating throughout the region. They can choose to live anywhere in the continent.

Your task is to research potential home locations by examining relevant geographic, climatic, political, economic, historic, and cultural considerations. Then, write a letter to your aunt and uncle with your recommendation about a place for them to move. Be sure to explain your decision with reasons and evidence from your research.

Accident Scene Investigation (high school)

You are a law enforcement officer who has been hired by the District Attorney’s Office to set-up an accident scene investigation unit. Your first assignment is to work with a reporter from the local newspaper to develop a series of information pieces to inform the community about the role and benefits of applying forensic science to accident investigations.

Your team will share this information with the public through the various media resources owned and operated by the newspaper.

Check out the full performance task from Defined STEM here: Accident Scene Investigation Performance Task

In sum, performance tasks like these can be used to engage students in meaningful learning. Since rich performance tasks establish authentic contexts that reflect genuine applications of knowledge, students are often motivated and engaged by such “real world” challenges.

When used as assessments, performance tasks enable teachers to gauge student understanding and proficiency with complex processes (e.g., research, problem solving, and writing), not just measure discrete knowledge. They are well suited to integrating subject areas and linking content knowledge with the 21st Century Skills such as critical thinking, creativity, collaboration, communication, and technology use. Moreover, performance-based assessment can also elicit Habits of Mind, such as precision and perseverance.

For a collection of authentic performance tasks and associated rubrics, see Defined STEM : https://www.definedstem.com

For a complete professional development course on performance tasks for your school or district, see Performance Task PD with Jay McTighe : http://www.performancetask.com

For more information about the design and use of performance tasks, see Core Learning: Assessing What Matters Most by Jay McTighe: http://www.schoolimprovement.com

Article originally posted: URL: http://performancetask.com/what-is-a-performance-task | Article Title: What is a Performance Task? | Website Title:PerformanceTask.com | Publication date: 2015–04–12

Written by Defined Learning

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Educators Blog

What is a Performance Task?

By Jay McTighe,

A performance task is any learning activity or assessment that asks students to perform to demonstrate their knowledge, understanding and proficiency. Performance tasks yield a tangible product and/or performance that serve as evidence of learning. Unlike a selected-response item (e.g., multiple-choice or matching) that asks students to select from given alternatives, a performance task presents a situation that calls for learners to apply their learning in context.

Performance tasks are routinely used in certain disciplines, such as visual and performing arts, physical education, and career-technology where performance is the natural focus of instruction. However, such tasks can (and should) be used in every subject area and at all grade levels.

 Performance tasks can be used to engage students in meaningful learning. Since rich performance tasks establish authentic contexts that reflect genuine applications of knowledge, students are often motivated and engaged by such “real world” challenges.

When used as assessments, performance tasks enable teachers to gauge student understanding and proficiency with complex processes (e.g., research, problem-solving, and writing), not just measure discrete knowledge. They are well suited to integrating subject areas and linking content knowledge with the 21st Century Skills such as critical thinking, creativity, collaboration, communication, and technology use.   New research shows that such performance tasks lead to deeper understanding and can improve student achievement up +39%.

To learn how educators can create and implement effective performance tasks that drive student achievement, visit www.PerformanceTask.com .

  Jay McTighe is a nationally recognized educator and author of the award-winning and best-selling Understanding by Design series with Grant Wiggins.

Editors Note: This is an excerpt from the article " What is a Performance Task ( Part  1)" published on the PerformanceTask.com blog. 

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Educating the Student Body: Taking Physical Activity and Physical Education to School (2013)

Chapter: 4 physical activity, fitness, and physical education: effects on academic performance.

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.

A lthough 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.

PHYSICAL FITNESS AND PHYSICAL ACTIVITY: RELATION 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).

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

FIGURE 4-1 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.

FIGURE 4-2 Effects of a single session of exercise in preadolescent children. SOURCE: Hillman et al., 2009. Reprinted with permission.

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.

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 ).

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

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 group ( N = 86) were significant ( p <.01). SOURCE: Donnelly et al., 2009. Reprinted with permission.

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 DEVELOPING bRAIN, PHYSICAL ACTIVITY, AND BRAIN HEALTH

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 dur-

ing 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.

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

FIGURE 4-4 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.

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.

LIMITATIONS

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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Physical inactivity is a key determinant of health across the lifespan. A lack of activity increases the risk of heart disease, colon and breast cancer, diabetes mellitus, hypertension, osteoporosis, anxiety and depression and others diseases. Emerging literature has suggested that in terms of mortality, the global population health burden of physical inactivity approaches that of cigarette smoking. The prevalence and substantial disease risk associated with physical inactivity has been described as a pandemic.

The prevalence, health impact, and evidence of changeability all have resulted in calls for action to increase physical activity across the lifespan. In response to the need to find ways to make physical activity a health priority for youth, the Institute of Medicine's Committee on Physical Activity and Physical Education in the School Environment was formed. Its purpose was to review the current status of physical activity and physical education in the school environment, including before, during, and after school, and examine the influences of physical activity and physical education on the short and long term physical, cognitive and brain, and psychosocial health and development of children and adolescents.

Educating the Student Body makes recommendations about approaches for strengthening and improving programs and policies for physical activity and physical education in the school environment. This report lays out a set of guiding principles to guide its work on these tasks. These included: recognizing the benefits of instilling life-long physical activity habits in children; the value of using systems thinking in improving physical activity and physical education in the school environment; the recognition of current disparities in opportunities and the need to achieve equity in physical activity and physical education; the importance of considering all types of school environments; the need to take into consideration the diversity of students as recommendations are developed.

This report will be of interest to local and national policymakers, school officials, teachers, and the education community, researchers, professional organizations, and parents interested in physical activity, physical education, and health for school-aged children and adolescents.

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Physical Education

Physical education is the foundation of a Comprehensive School Physical Activity Program. 1, 2 It is an academic subject characterized by a planned, sequential K–12 curriculum (course of study) that is based on the national standards for physical education. 2–4 Physical education provides cognitive content and instruction designed to develop motor skills, knowledge, and behaviors for physical activity and physical fitness. 2–4 Supporting schools to establish physical education daily can provide students with the ability and confidence to be physically active for a lifetime. 2–4

There are many benefits of physical education in schools. When students get physical education, they can 5-7 :

• Increase their level of physical activity.
• Improve their grades and standardized test scores.
• Stay on-task in the classroom.

Increased time spent in physical education does not negatively affect students’ academic achievement.

Strengthen Physical Education in Schools [PDF – 437 KB] —This data brief defines physical education, provides a snapshot of current physical education practices in the United States, and highlights ways to improve physical education through national guidance and practical strategies and resources. This was developed by Springboard to Active Schools in collaboration with CDC.

Secular Changes in Physical Education Attendance Among U.S. High School Students, YRBS 1991–2013

The Secular Changes in Physical Education Attendance Among U.S. High School Students report [PDF – 3 MB] explains the secular changes (long-term trends) in physical education attendance among US high school students over the past two decades. Between 1991 and 2013, US high school students’ participation in school-based physical education classes remained stable, but at a level much lower than the national recommendation of daily physical education. In order to maximize the benefits of physical education, the adoption of policies and programs aimed at increasing participation in physical education among all US students should be prioritized. Download the report for detailed, nationwide findings.

Physical Education Analysis Tool (PECAT)

The  Physical Education Curriculum Analysis Tool (PECAT) [PDF – 6 MB] is a self-assessment and planning guide developed by CDC. It is designed to help school districts and schools conduct clear, complete, and consistent analyses of physical education curricula, based upon national physical education standards.

Visit our PECAT page  to learn more about how schools can use this tool.

• CDC Monitoring Student Fitness Levels1 [PDF – 1.64 MB]
• CDC Ideas for Parents: Physical Education [PDF – 2 MB]
• SHAPE America: The Essential Components of Physical Education (2015) [PDF – 391 KB]
• SHAPE America: Appropriate Instructional Practice Guidelines for Elementary, Middle School, and High School Physical Education [PDF – 675 KB]
• SHAPE America: National Standards and Grade-Level Outcomes for K–12 Physical Education 2014
• SHAPE America: National Standards for K–12 Physical Education (2013)
• SHAPE America Resources
• Youth Compendium of Physical Activities for Physical Education Teachers (2018) [PDF – 145 KB]
• Social Emotional Learning Policies and Physical Education
• Centers for Disease Control and Prevention. A Guide for Developing Comprehensive School Physical Activity Programs . Atlanta, GA: Centers for Disease Control and Prevention, US Department of Health and Human Services; 2013.
• Centers for Disease Control and Prevention. School health guidelines to promote healthy eating and physical activity. MMWR . 2011;60(RR05):1–76.
• Institute of Medicine. Educating the Student Body: Taking Physical Activity and Physical Education to School . Washington, DC: The National Academies Press; 2013. Retrieved from  http://books.nap.edu/openbook.php?record_id=18314&page=R1 .
• SHAPE America. T he Essential Components of Physical Education . Reston, VA: SHAPE America; 2015. Retrieved from   http://www.shapeamerica.org/upload/TheEssentialComponentsOfPhysicalEducation.pdf  [PDF – 392 KB].
• Centers for Disease Control and Prevention. The Association Between School-Based Physical Activity, Including Physical Education, and Academic Performance . Atlanta, GA; Centers for Disease Control and Prevention, US Department of Health and Human Services; 2010.
• Centers for Disease Control and Prevention. Health and Academic Achievement. Atlanta: US Department of Health and Human Services; 2014.
• Michael SL, Merlo C, Basch C, et al. Critical connections: health and academics . Journal of School Health . 2015;85(11):740–758.

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Physical Education Assessment Ideas

Assessment in physical education is more important than ever. It is a great way to see if students are really learning in our physical education classes. Written assessments are a terrific medium for showcasing what students have learned to administrators and parents. The following resources and ideas are presented to help teachers incorporate assessment into their programs.

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Learn the advantages of using performance-based assessments

This is an excerpt from performance-based assessment for middle and high school physical education-2nd edition by jacalyn lund & mary fortman kirk..

Many of the things that physical educators do during an instructional unit can be easily turned into performance-based assessments. By making a few modifications, writing out criteria for the performance, and gradually including performance-based assessments throughout a unit, a teacher can begin to transform current assessment practices into performance-based assessments.

Performance-based assessments provide several instructional advantages in physical education and can greatly increase the effectiveness of instruction and evaluation systems. This section considers some advantages of using performance-based assessments.

Direct Observations of Student Learning

Performance-based assessments allow teachers to assess areas of learning that traditional assessments do not address. Many traditional assessments do not directly measure progress toward the teacher's final learning objectives. For example, at the secondary level, a physical educator's goal is usually to teach a student how to play a game or do an activity. However, while skill tests may evaluate performance of discrete skills in a fairly closed (unchanging) environment, they do not evaluate a student's ability to use these skills and “put it all together” during game play. Additionally, game play, involves making decisions about which skill to use and thus requires students to evaluate a complex environment. Skill tests are merely an approximation of what a student must be able to do. Although they do represent a first step in learning, obtaining high scores on a skill test is usually not the teacher's ultimate goal for the unit.

Direct observation of students performing in a real-world setting provides a powerful way to measure both their knowledge and their ability to apply it. Traditional assessments are designed to measure students' learning indirectly. For example, when students take a test about tennis rules, the teacher assumes that the test measures the degree to which a student knows the rules, and if the questions are valid then this is a reasonable assumption. However, a student might know the rules of tennis and demonstrate that knowledge on a written test yet be unable to apply them during a game. Skill tests and written tests give teachers a useful way to sample students' learning during instruction, but actual assessment of game play allows teachers to see whether students can combine the pieces into a meaningful entity.

Thus performance-based assessments allow teachers to access information not available through traditional testing. Assessments must measure how well students meet the teacher's goals or targets for the unit. When a teacher's goals include game play or some type of student performance, then performance-based assessments provide an excellent way to determine whether students have achieved those goals.

Good Instructional Alignment

Put simply, instructional alignment means that teachers test what they teach. Cohen's research (1987) revealed the power of instructional alignment strategies. Teachers in his study demonstrated a significant difference in student learning when their assessments matched student learning. When applying instructional alignment principles, teachers decide on a target, then test what they teach. This approach may seem logical, but the fact is that not all teachers use it. Some teachers use written tests to evaluate learning for activity units. Too often, the material covered by a test comes from a one- or two-page handout on the history or rules of a game or sport, which means that the test ignores all the skill and game-play instruction involved in the unit. In performance-based assessment, in contrast, the assessment can be the instructional task. Students know exactly what is expected of them and are given multiple opportunities to meet preannounced teacher expectations and criteria. Thus instruction and assessment work together in performance-based assessments, which leads to strong instructional alignment and enhances students' learning.

Interesting Assessments

Since performance-based assessments usually involve real-world tasks, students tend to find them more engaging and challenging. Rather than studying just enough to get a good grade on a test, students spend many hours engaged in their projects and often explore and use sources beyond the teacher and textbook. In addition, when an assessment simulates what a person in the field might do, students have several role models to emulate (e.g., announcing a game like Harry Caray, doing basketball analysis like Pat Summitt, or dancing like Michael Flatley or Julianne Hough). When an assessment results in a product or performance, students accomplish something they can be proud of.

Instructional Feedback

Because they have a formative component, performance-based assessments provide high-quality feedback to students throughout the assessment. Since students have access to the rubric that is used to judge the final product, they can self-assess and peer-assess as they move through the assessment and receive additional feedback. The overall purpose of assessment should be to enhance learning, and the primary reason to assess should be to give feedback to students about their progress. The second reason for doing assessments is to provide information to the teacher that can be used to shape instruction. Thus, instead of doing assessment at the end of the unit, teachers can enhance students' learning by integrating assessment throughout the instructional process.

Measurement of Multiple Objectives and Concepts

These days, physical education is often squeezed into an instructional curriculum loaded with classes that students were not required to take 10 years ago. As a result, physical education teachers must make every minute count. Because performance-based assessments are linked with instruction, the two can be accomplished simultaneously, thus increasing instructional efficiency. Game play provides opportunities for teachers to assess students' skill, use of strategy, knowledge of rules, and affective-domain attributes. Additionally, physical education teachers can often work with other teachers to do assessments that display competence in multiple areas. For example, written assessments could be used to evaluate learning in both English and physical education, and fitness assessments could also be used to measure biology content knowledge. Assessments involving other subject areas can be completed outside the gym, which maximizes time available for activity.

Active Student Learning

Performance-based assessments can empower students by giving them freedom to make choices, within parameters set by teachers, about the direction that their learning should take. Giving students this kind of ownership of their learning process can be a powerful motivator. In addition, because students understand what their learning should look like, students are more likely to experience success with performance-based assessments. Not only do the lessons have a more lasting effect—performance-based assessments require students to do something, which makes them more likely to retain the knowledge they use—but also may lead students to other projects and activities. Indeed, whether they involve writing or the use of psychomotor skills, performance-based assessments should encourage students to go outside the confines of the class for additional learning. As a result, an assessment may not be the end or culmination of learning so much as it is the beginning of engagement with a newfound area of interest.

Higher-Order Thinking Skills

Higher-order thinking skills, which are important for success as an adult, must be nurtured and developed throughout a student's school career. Performance-based assessments prompt students to use higher-order thinking skills such as analysis, synthesis, and evaluation. The more opportunities students are given to practice these skills, the more proficient they become at using them. For example, a teacher might call on students to use higher-order thinking skills in physical education by giving them a scouting assignment in which they analyze the skills and strategies of future opponents in a badminton tournament. Another option would be to have students create a dance for an upcoming performance or design a play for use in an upcoming game.

Multiple Chances to Get It Right

Some educators see assessment in a purely evaluative light: students have one chance to prove that they have learned the required material. In contrast, because of its formative focus, performance-based assessments give students multiple chances to succeed. Indeed, in life outside the classroom, people often have multiple chances to demonstrate competence without penalty. Did you pass your lifesaving exam the first time you took it? If you didn't, that setback did not mean that you could never become a lifeguard. It just meant that more work was necessary before you met the criteria. In much the same way, performance-based assessments allow students multiple opportunities to meet the criteria or standard of excellence set by the teacher.

When game-play assessments are used during a tournament, the grade should be determined not by averaging a student's early performance with that from later games but by using results from his or her best performance. Errors made during a game in the early stages of learning should not be held against the student because improvement with experience is the expectation. When dancers make errors while performing for their video recording, they can do another take. When a student's written work misses the mark, he or she is allowed to rewrite. Educators who administer an assessment only once must recognize that in the world outside the classroom people often have multiple chances to demonstrate proficiency. Athletes compete in many contests, dancers put on many shows, and skaters perform in numerous competitions. Thus, giving students multiple opportunities to achieve success provides more of a real-world experience than a one-shot evaluation provides.

Students' Enjoyment

Because assessments are challenging and simulate real-world experiences, students find them interesting and engaging. Time on task in class tends to be high and students are willing to spend additional time outside of class to complete their projects. Afterward, when students consider their accomplishments, they have a strong sense of satisfaction and pride, since the product or performance provides a tangible, concrete demonstration of their achievement.

This is an excerpt from Performance-Based Assessment for Middle and High School Physical Education, Second Edition .

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Subject Knowledge >

Performance Tasks: Physical Education

* Evaluated Practicum

Performance Tasks revised 21 Jul 09

Other Portfolio Pages: Introduction - Teaching Philosophy - Subject Knowledge - Instructional Strategies Assessment - Adaptive Instruction - Credentials

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The Effects of Physical Activity on Academic Performance in School-Aged Children: A Systematic Review

Associated data.

The data presented in this study are available in the article.

Schools offer a unique environment to influence children’s physical activity (PA) levels positively. This study aims to systematically review the evidence surrounding how PA affects academic performance by analysing how the frequency, intensity, time, and type of PA mediate academic performance outcomes. This review was conducted using the PRISMA framework. Keyword searches were conducted in Science Direct, PubMed, and SPORTDiscus. Children that were obese, typically developing, typical weight, disabled, with a developmental disability, from a low socio-economic background, or an ethnic minority were included. A total of 19 studies were included, with a total of 6788 participants, a mean age of 9.3 years (50.2% boys, and 49.8% girls). Overall, 63.2% were nondisabled, while 36.8% were diagnosed with a disability. Two authors met, reviewed papers with regard to the inclusion criteria, and agreed on outputs to be included. Evidence suggests that associations between PA and academic performance were primarily positive or nonsignificant. PA levels of 90 min plus per week were associated with improved academic performance, as was PA performed at moderate to vigorous intensity. The optimal duration of PA was 30–60 min per session, whilst various sports induced positive academic effects. Importantly, findings support that PA does not have a deleterious effect on academic performance but can enhance it.

1. Introduction

It is widely acknowledged that regular physical activity (PA) is inextricably linked to a plethora of health benefits [ 1 ]. Extensive research advocates PA’s role in improving a person’s physiological wellbeing [ 2 ]. Conversely, numerous studies have documented the ill effects physical inactivity can have on one’s physiological health [ 1 , 3 ]; most notably, Warburton et al. [ 1 ] recognised that physical inactivity is a modifiable risk factor for a diverse range of diseases, which include cardiovascular diseases, bone and joint diseases, and chronic diseases such as cancer (colon and breast), obesity, and hypertension. Regarding psychological health, PA has also been identified as an effective means of alleviating mild to moderate depression, improving mood, and reducing anxiety symptoms [ 1 , 4 ]. It is also well established that regular participation in PA facilitates a child’s physical, psychological, and social development [ 5 ]. Vaqnguero-Solis et al. [ 6 ] stated that childhood participation in PA positively affects body mass index (BMI), morphology, fundamental movement skill competence, self-esteem, and social behaviours. These findings are consistent with the literature [ 7 , 8 , 9 , 10 , 11 ].

Physical inactivity prevalence in children across the UK is concerning; in 2018/2019, less than half (47%) of children aged 5–18 years met the current PA guidelines of 60 min of moderate PA per day [ 12 ]. Accordingly, it can be inferred that strategies to improve PA levels in children across the UK are an irrefutable necessity, not only to improve children’s current health status, but also to decrease the likelihood of obesity and other inactivity-related conditions. Given the compulsory attendance of children at schools and the significant amount of time children spend there each day, schools offer a unique environment to positively influence PA levels among children so that recommended PA levels are achieved [ 13 ]. Nevertheless, opportunism to increase PA levels within schools is increasingly finite [ 11 ]. In fact, some schools are decreasing time spent on non-academic subjects such as physical education (PE) to allocate more time to academic subjects such as mathematics or English [ 14 ]. This decline in PA opportunities in schools is primarily influenced by ever-increasing academic pressures placed on schools and educators to achieve within an attainment-focused curriculum [ 14 ]. However, research indicates such declines in PA are detrimental to the child, their physiological and psychological health, and potentially, their academic performance.

A growing body of literature has investigated the effects of PA (school-based, class-based, and extracurricular PA) on academic performance, and the results are widely debated. Notably, several studies advocate PA to improve academic and/or cognitive performance [ 15 , 16 , 17 , 18 , 19 ]. De Greeff et al. [ 20 ] supported this positive effect of PA on executive functions (inhibition, working memory, cognitive flexibility, and planning) and academic performance, and stated that largest effects are seen with interventions that implement continuous regular PA over several weeks. This was similar to findings by Barbosa et al. [ 21 ] who found a medium positive effect of PA on academic achievement as opposed to acute PA which demonstrated no benefits. Further research [ 22 ] saw deviations from this as they reported acute PA interventions significantly improved processing speed, inhibition and attention, whereas chronic PA interventions significantly improved processing speed, attention, cognitive flexibility, working memory, and language skills. However, studies conducted by Esteban-Cornejo et al. [ 23 ] found that the association between PA and academic performance was negative and very weak. Similarly, Daley and Ryan [ 24 ] reported no correlations between increased PA and academic performance; these findings are consistent with the literature [ 25 , 26 , 27 ]. Contrasting results across the literature suggest that future research within this area is necessary to bring clarity to the field. If it was evidenced that PA could be implemented in schools without being a detriment to academic performance; policymakers and schoolteachers may be inclined to implement a policy of regular PA within the school context. This would ensure children meet their recommended PA guidelines (60 min or more per day) for most of the week.

Several authors have recognised the uncertainty surrounding PA’s effect on academic performance. Rasberry et al. [ 28 ] explored the association between four school-based PA contexts (PE, recess, classroom PA breaks, and extracurricular PA) and academic performance across 50 peer-reviewed articles. The review concluded that positive or no associations between the interventions and academic performance were reported across the studies that assessed PE, recess, and classroom-based PA. Whereas extracurricular PA interventions differentiated from the aforementioned contexts, mainly reporting positive or no associations but some negative associations (2%). Overall, this review strengthens the idea that PA within schools is vital, with PA enhancing academic performance rather than detracting from it. Likewise, a study conducted by Singh et al. [ 29 ] investigated the relationship between PA interventions and academic and cognitive performance and reported inconclusive results. Notably, of the 11 high-quality studies included in the synthesis, 60% reported a significant beneficial effect of PA on academic performance, and 48% reported a significant beneficial effect on cognitive performance. Sember et al. [ 30 ] also reported mixed results between PA and academic performance; specifically, of the 44 articles included in the synthesis, 20 reported significant, positive effects, and 24 reported adverse or null effects on academic performance. More recently Peiris et al. [ 31 ] reported physical activity had mixed effectiveness on academic performance, e.g., a positive effect on spelling performance ( p < 0.05) and foreign language learning ( p < 0.01) but no significant effect on mathematics and reading, and no effect on cognitive outcomes. The mixed results reported across the aforementioned reviews reiterate the necessity for further research to contextualise the causes of such diversity in findings, and further extend the understanding of the mediators for associated outcomes, whether positive, negative, or insignificant. Barisic et al. [ 32 ] stated PA is a multifaceted behaviour encompassing frequency, intensity, time, and type (FITT). These domains individually affect physiological processes differently. Therefore, it is crucial to explore the domains of FITT, individually and combined, to understand the underlying mechanisms behind the associations [ 32 ]. Consequently, it is suggested that FITT should be incorporated in future reviews to elucidate the cause of associated effects and improve the applicability of results if utilised to inform future interventions.

The applicability of the reviews is also problematic. Rasberry et al. [ 28 ], Singh et al. [ 29 ], and Sember et al. [ 30 ] only included children or adolescents that were nondisabled, and Marques et al. [ 14 ] did not specify the characteristics of the included population. This has significant implications for the applicability of the results, as subsequent findings will be unrepresentative of the school community. Notably, schools are heterogeneous environments characterised by a diverse range of individuals, subcommunities, and cultures [ 33 ]. To ensure results are applicable and relevant to those wishing to utilise them (school communities and policymakers), authors should not exclude participants on the basis of specific characteristics (disabled, nondisabled, culture, background, race, religion, sex, gender reassignment, and socioeconomic status). Instead, it is suggested that future research should only exclude participants on the basis of age (too old/young), as this is genuinely representative of what occurs in the schools’ heterogeneous communities.

Although several published reviews explore PA’s effect on academic performance, the above-indicated inadequacies in study designs suggest that further research is necessary to bring clarity to the field [ 28 , 29 , 30 , 32 ]. Therefore, the primary aim of this current study is to conduct a broad examination of the literature surrounding PA’s effect on academic performance. However, unlike other systematic reviews of this nature, this study aims to extend the understanding of the causal factors related to associated effects, recognising a heterogeneous school community. This is achieved through documenting the FITT of PA intervention designs. Findings are used to disseminate an optimal frequency, intensity, type, and time of PA for improved academic performance.

2. Materials and Methods

2.1. protocol.

This review was carried out according to the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework; we did attempt to register with PROPSERO, but they did not accept it as it was looking at the effect of physical activity on academic performance, and they did not support research looking at academic performance. We felt that the review has great importance and implications; hence, although not approved by the PRISMA process, we performed the review following the PRISMA guidelines to see if there is any effect of PA on academic performance.

2.2. Eligibility Criteria

The literature synthesis was carried out according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework. The criteria for selecting studies for inclusion in this review were as follows: published in the English language (although origin was preferably diverse to draw generalisable results); peer-reviewed, longitudinal, experimental studies published between March 2012 and June 2022; studies that focus on school-aged children aged 6–14 years of age; incorporated a PA intervention as the dependant variable; examined outcome variables related to academic performance using one or more outcome measure (e.g., performance on standardised tests, on-task behaviours, and performance on executive functioning tests). Diversity between study cohorts was also a prerequisite for the literature synthesis; studies were screened and chosen on the basis of their applicability to provide diverse findings that are relevant to and representative of the heterogeneous school community; groups to be included were children that were obese, typically developing, typical weight, with physical disabilities, with a developmental disability, from a low socioeconomic background, or an ethnic minority. Moreover, only studies that detailed the frequency, volume, and type of PA of their intervention were included in this review. However, studies that also included the intensity of PA were most desired. These predetermined measures were essential for two reasons. Firstly, clear and measurable dependant variable(s) ensure that documented interventions can be applied and repeated if later utilised to inform future practice. Secondly, through a clear understanding of intervention protocol and its outcomes, authors can reach an informed conclusion surrounding optimal intervention design.

Several terms relating to academic performance were included in this review under the encompassing term, academic performance ( Table 1 ). It is recognised that a number of these terms are independent entities that are not inextricable to academic performance itself. Nevertheless, they are included in this review due to their well-established association/link with academic performance. Most notably, academic performance has been found to have a strong association with intelligence [ 34 ], cognitive functioning [ 35 ], and executive functioning [ 36 ]. It is recognised that only including these outcome variables would be insufficient to determine exactly how PA affects academic performance. However, their incorporation in the study design alongside standard outcome measures related to academic performance (mathematics score, reading score, standardised test scores, and academic achievement) allows for a more comprehensive analysis of PA’s effects on academic performance, whereby the direct and indirect effects of PA on academic performance are evaluated. Publications were excluded from this review if they were unable to meet the eligibility criteria discussed above or if they focused on the effects of PA alongside other independent variables (such as nutrition interventions or workshops). If the study did not explicitly state the participating cohort, the intervention, outcome measures, or results, it was excluded. Moreover, experimental studies that did not incorporate a control group were excluded from the study (the necessity for a control group was pre-established to gain valid and objective conclusions from the data/studies provided). Studies that focused on the immediate effects of antecedent PA on academic performance were deemed ineligible. Meta-analyses, case studies, systematic literature reviews, review articles, and observational studies were excluded from this article. Studies that did not include significance values to support findings were also excluded from this review.

Databases searched and search terms employed.

2.3. Study Selection

The initial literature search using three electronic databases (Science Direct, PubMed and Sport Discus) yielded 425 results (the predetermined search terms used for this search can be found in Table 1 ). A total of 357 articles were immediately excluded on the basis of the title. Following this, duplicates were removed, and the abstracts of the remaining 60 studies were assessed for eligibility. Among the 60 articles, 18 articles were deemed ineligible. Accordingly, 42 articles remained for the full-text screening; 19 articles were considered eligible after the full-text screening and, therefore, included in the final synthesis. Conversely, 23 full-text articles were excluded for a variety of reasons; most commonly, articles were excluded because the intervention design did not adhere to the eligibility criteria (lacked longitude and mainly focused on the immediate effects of antecedent PA on academic tasks), outcome measures were either subjective (observational) or unavailable, methodology or intervention design was unclear and, thus, unsuitable for analysis, the study did not incorporate a control group/condition, or p -values were not provided to support relevant outcomes. See Figure 1 for a visual illustration of the study selection process discussed.

Visual depiction of academic performance (AP) and physical activity (PA) searches using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses flow diagram.

2.4. Identification of Studies

See Figure 1 for a depiction of the search strategy employed. Published studies were independently identified and assessed using three electronic databases (Science Direct, PubMed and Sport Discus) up to 9 March 2022. These databases were searched using pre-determined search terms related to PA, academic performance, and the target population ( Table 1 ). Filters applied were concerning the year of publication (2012–2022) and study design (experimental studies, clinical trials, and randomised control trials). On completion of the initial search, the process of screening based on article titles was carried out. The titles were assessed on the basis of congruence with the eligibility criteria, and articles with ineligible titles were excluded from further screening. Duplicates were then removed, and the abstracts of the remaining articles were assessed for eligibility. When the article abstracts were screened, each article was evaluated and chosen for further assessment according to its ability to meet the eligibility criterion specified. However, if a study’s eligibility (based on reading of the abstract) was inconclusive, it was also included in the final screening. Lastly, full-text articles were screened for eligibility, and all articles that did not meet the inclusion criterion were removed. Subsequently, the remaining studies met the inclusion criteria and were included in the synthesis.

2.5. Data Extraction and Synthesis

An independent reviewer extracted the following data from the studies eligible for synthesis: author(s); study design; country of origin; sample (sample size, mean age of participants, and participant characteristics); the independent variable of interest (relating to PA) and intervention characteristics (FITT); dependent variable of interest and outcome measures (related to academic performance); relevant findings pertaining to academic performance and PA. Notably, there was no pre-established outcome measure sought. Instead, all outcome measures relating to academic performance-related keywords ( Table 2 ) were documented. This holistic approach was adopted to ensure the different aspects of academia and in that academic performance was accounted for. The difference in curricula across the UK alone supports the necessity for this method, with differing pedagogies, subjects, and means of assessment from country to country [ 37 , 38 , 39 ]. It was evident that there was no encompassing measure to assess academic performance. Therefore, this article did not want to discredit or overlook any potentially significant/relevant outcome measures and their consequent findings due to stringent specificity that would not be exemplary of academia and academic performance itself. Due to the article’s narrative nature, any outcome or finding relevant to achieving this study’s objectives is documented and discussed. However, significance values are provided for each study to support statements regarding the significance of effects observed, if any. Moreover, no assumptions were made if a study did not include relevant data or findings in the text. Consequently, any study that did not provide relevant data or findings suitable for analysis was excluded from this article.

Academic performance-related keywords.

* Cognitive and executive functioning are broad terms encompassing numerous mental processes involved in multiple cognitive tasks. Therefore, if appropriate, any keywords relating to these domains were also included when documenting outcome measures and findings (e.g., working memory, on-task behaviour, decision making, and selective attention).

2.6. Analysis

A narrative analysis of the literature was adopted due to the diversity of populations, outcome measures, and multiple methods included. Moreover, at the time of the study, little literature surrounding PA’s effect on academic performance adopted a narrative approach; therefore, a narrative analysis was utilised to make a novel contribution to the field. A meta-analysis was not chosen due to the genuine differences between groups, interventions, and outcome measures that would otherwise not be considered if combined for meta-analysis. Instead, a narrative approach was most appropriate so that overall effects could be examined alongside providing opportunism to gain deeper insight into the intricacies and reasons for associated effects. Consequently, a comprehensive review could be achieved that, firstly, informs the reader of the overall effect PA has on academic performance and, secondly, objectively concludes the reasons for these effects.

3.1. General Study Characteristics

A detailed description of the included studies, their characteristics, methodological processes, and key findings are summarised in Table S1 . Of the 19 articles that met the eligibility criteria, the countries with the highest number of articles included were the Netherlands ( n = 3), followed by the USA ( n = 2) and Norway ( n = 2). Then, the remaining articles represented one country of origin each, namely, Spain, Switzerland, Denmark, Chile, Australia, Taiwan, South Africa, Italy, China, Canada, and Germany. Figure 2 presents a visual representation of each study’s country of origin.

Visual representation of each article’s country of origin. Key: green shading— n = 3 articles; red shading— n = 2 articles; blue shading— n = 1 article.

The total number of participants for the included studies combined was 6788. The average number of participants was 357, ranging from 22 to 1181. Of the 19 articles, 16 reported the mean age of the participants at baseline, which ranged from 8.01 to 11.35 years old, although the average age across the studies was 9.26 years. Moreover, among the 6788 participants that took part in the study combined, many were characteristically diverse. Most notably, 50.2% of the participants were boys, and 49.8% girls. Furthermore, 63.2% of the articles included participants that were nondisabled, whilst 36.8% included participants that were diagnosed with a disability. Specifically, the disabilities presented were autism spectrum disorder (ASD; n = 3), foetal alcohol syndrome ( n = 1), and attention-deficit/hyperactivity disorder (ADHD; n = 3). Furthermore, a small number of the nondisabled studies presented stringent eligibility criteria related to participant characteristics; notably, Gall et al.’s [ 40 ] study only included participants from a low-socioeconomic background, whilst Reed et al. [ 41 ] only included participants from an ethnic minority.

Across the 19 interventions, PA was implemented through the following forms of PA; physically active academic lessons [ 40 , 41 , 42 , 43 , 44 , 45 , 46 ], PA lesson breaks [ 40 , 44 , 46 , 47 ], moderate intensity PA [ 48 ], moderate- to vigorous-intensity PA [ 42 , 43 , 45 , 47 , 49 , 50 ], high-intensity PA [ 48 , 51 ], cognitively engaging PA [ 47 , 49 , 51 ], aerobic exercise [ 51 ], mixed martial arts [ 52 , 53 ], table tennis [ 54 ], team games [ 51 ], PE lessons [ 40 , 41 , 44 , 46 , 48 , 49 , 51 , 55 ], PA homework [ 44 ], multi-activity sport [ 41 , 46 , 50 , 56 , 57 ], and PA that emphasises fundamental movement skill development [ 41 ]. Notably, several studies were categorised into various types of PA due to their multifactorial intervention design. For example, Ardoy et al. [ 48 ] implemented a multifaceted intervention design to compare cognitive and academic performance across three intervention conditions (group 1 received four 55 min periods of moderate-intensity PE per week; group 2 received four 55 min periods of high-intensity PE per week; control group received two 55 min periods of regular PE lessons per week); therefore, this study fell into various categories: moderate-intensity PA, high-intensity PA, and PE lessons.

3.2. Measurements of Academic and Cognitive Performance

Measurements of academic performance differentiated profusely across each of the included studies. However, this review categorised each study’s primary dependant variables into two encompassing domains: academic performance and cognitive performance. Notably, nine studies measured domains of academic performance, while 14 studies measured indicators of cognitive performance. Of the eight studies that analysed the effects on academic performance, four used grades in academic subjects [ 40 , 48 , 49 , 50 ]; meanwhile, three studies utilised standardised test results [ 43 , 49 , 55 ], one took measurements of the student’s mastery of the basic facts test [ 47 ], and one analysed mathematics and reading performance with the speed test arithmetic and the 1 min test [ 45 ]. Conversely, the majority of studies evaluating PA’s effects on cognitive performance reported outcome measures related to the domains of executive functioning ( n = 10), namely, cognitive flexibility (shifting), working memory, inhibition, updating, and behavioural and emotional control. However, some studies assessed selective attention ( n = 2), intelligence ( n = 2), and speed of information processing ( n = 1).

3.3. Physical Activities Effect on Academic Performance

Results varied across the academic performance related studies ( n = 9); two reported positive, significant effects, two reported insignificant effects, and five reported mixed conclusions. A brief description of intervention designs associated with the aforementioned effects is reported below. Furthermore, detailed descriptions of included studies, their characteristics, methodological processes, and key findings are summarised in Table S1 . A study conducted by Gall et al. [ 40 ] increased PA through a multifaceted PA intervention design, incorporating PE lessons, active breaks, and active academic lessons. The intervention had a significant ( p = 0.032), positive effect on academic performance compared to children receiving PE lessons in isolation. Likewise, a study conducted by García-Hermoso et al. [ 50 ] reported that increased moderate to vigorous PA has a significant ( p < 0.001), positive effect on academic performance. Ardoy et al. [ 48 ] compared academic performance across three intervention conditions: a moderate-intensity group (moderate-intensity PE lesson for 55 min, four times weekly), a high-intensity group (high-intensity PE lesson for 55 min, four times weekly), and a control group (regular PE lessons for 55 min, twice weekly). Interestingly, the high-intensity group had a significant ( p < 0.001), positive effect on academic performance compared to the control condition. However, no significant ( p > 0.05) difference was observed between the moderate-intensity and control groups. Similarly, Mavilidi et al. [ 47 ] and De Bruijn et al. [ 49 ] compared the effects of different types of increased PA on academic performance and reported mixed conclusions. Mavilidi et al. [ 47 ] reported a significant ( p = 0.045), positive relationship between active breaks and academic performance, but reported an insignificant ( p > 0.05) relationship between cognitively engaging, active breaks and PA. In contrast, De Bruijn et al. [ 49 ] reported that both increased cognitively engaging, moderate to vigorous PE and increased moderate to vigorous PE had no significant ( p > 0.05) overall effect on academic performance (spelling, mathematics, and reading) compared to the control condition. However, the study reported a significant ( p ≤ 0.05) dose–response relationship between increased moderate to vigorous PA and mathematics score, and a significant ( p ≤ 0.05) dose–response relationship between moderate to vigorous, cognitively engaging PA and mathematics and spelling performance.

Mullender-Wijnsma et al. [ 45 ] and Resaland et al. [ 46 ] also reported mixed results. The study conducted by Mullender-Wijnsma et al. [ 45 ] found no significant difference between the overall academic performance of children receiving active academic lessons and those receiving regular academic lessons ( p > 0.05). However, a significant interaction between grade and reading and mathematics performance was reported. Interestingly, the third-grade (8–9 years) children receiving active academic lessons scored significantly ( p < 0.01) higher than those receiving regular academic lessons for mathematics and reading performance. In contrast, the active academic lessons had no significant ( p > 0.05) effect on second-grade (7–8 years) students’ reading scores and a significant ( p < 0.01), negative effect on mathematics scores compared with those receiving regular academic lessons. Similarly, Resaland et al. [ 46 ] reported no significant ( p > 0.358) intervention effect on overall academic performance but a significant ( p = 0.005) effect between subgroup and numeracy score. Notably, the intervention group with the lowest baseline numeracy score significantly improved its post-test numeracy score compared to the control condition. The study included a multifaceted intervention design (active breaks, active academic lessons, and active homework) incorporating 165 min per week of additional PA.

Bugge et al. [ 55 ] compared the academic performance of a group receiving PE 6 days per week (4.5 h per week) and a group receiving PE 2 days per week (1.5 h). The study found no significant ( p > 0.5) difference between academic performance of both groups following the intervention. Likewise, a study conducted by Donnelly et al. [ 43 ] compared academic performance across a group receiving a moderate to vigorous PA intervention and a group that followed the regular curriculum and found no significant ( p > 0.5) intervention effects on mathematics, reading, and spelling performance. However, improvements were reported for both groups across all three academic performance indicators.

3.4. Physical Activities Effect on Cognitive Performance

Of the 14 studies that examined the relationship between PA and domains of cognitive performance: six reported positive, significant effects, while four reported insignificant effects, and four reported mixed conclusions. Succinct descriptions of intervention designs associated with these effects are provided below. Moreover, detailed descriptions of the studies, their characteristics, methodological processes, and key findings are provided in Table S1 .

Studies conducted by Ronzi and Greco [ 52 ] and Phung and Goldberg, [ 53 ] found that increased participation in PA through combat sports (karate and mixed martial arts) significantly ( p ≤ 0.05) improved executive functioning test scores when compared to the control condition. Similarly, Pan et al. [ 54 ] investigated the effects of increased PA through the medium of a specific sport (table tennis) and reported a significant ( p < 0.01), positive intervention effect on executive functioning compared to the control condition. Kvalø et al. [ 44 ] found that children who participated in 460 min of PA per week performed significantly ( p = 0.001) better on an executive functioning test than a group participating in 135 min of PA per week. Notably, 460 min of PA per week in Kvalø et al. [ 44 ] study was achieved through a multifaceted intervention design, incorporating active academic lessons, active breaks, PE, and active homework.

Ziereis and Jansen, [ 5 ] compared executive functioning across three conditions: a general sports group (60 min of PA, 1 day per week for 12 weeks, with an emphasis on nonspecific sporting movements), a specific sports group (60 min of PA, 1 day per week for 12 weeks, with an emphasis on specific sports), and a control group (a group that did not receive a PA intervention). Both interventions had a significant ( p ≤ 0.05), positive effect on executive functioning compared to the control condition. However, no significant ( p > 0.5) difference between the general and specific sports groups was reported following the 12 weeks. Moreover, Reed et al. [ 41 ] found that children participating in 45 min of generalised sport (multiactivity sport or fundamental movement skill development) five times per week performed significantly ( p ≤ 0.05) better in eight out of 26 cognitive performance indictors than a group receiving regular PE for 30 to 50 min, once weekly.

Ardoy et al. [ 48 ] found that increased levels of moderate-intensity PE per week had no significant (all p ≥ 0.2) effect on cognitive performance compared to the control condition. However, increased levels of high-intensity PE per week had a positive, significant ( p ≤ 0.001) effect on cognitive performance compared to the control condition. Congruently, Schmidt et al. [ 51 ] also compared cognitive performance (executive functioning) across three conditions: a high-intensity, cognitively engaged group (45 min of high-intensity PA, 2 days per week for 6 weeks, with an emphasis on team games with a high degree of cognitive engagement), high-intensity group (45 min of high-intensity PA, 2 days per week for 6 weeks, with an emphasis on aerobic exercise with a low degree of cognitive engagement), and a control group (45 min of low-intensity PA, 2 days per week for 6 weeks) and reported mixed results. Interestingly, cognitive flexibility (shifting) significantly ( p ≤ 0.05) improved in the high-intensity, cognitively engaged group compared with the high-intensity and control groups. However, there was no significant ( p > 0.5) difference between the updating and inhibition performance across the three groups.

Pan et al. [ 56 ] compared cognitive performance (executive functioning) across two conditions: an intervention group (70 min of PA, twice per week for 12 weeks; see Table S1 for session design) and a control group (a group that did not receive any form of PA intervention). The study reported mixed results; an insignificant ( p > 0.5) main effect of group and time on all indices of the executive functioning test was reported. However, the intervention had a significant ( p < 0.01), positive effect on three indices of the executive functioning test compared to the control condition, namely, total correct, conceptual level response, and preservative response. Similarly, Pritchard et al. [ 57 ] reported an insignificant ( p = 0.173) intervention effect on the first component of an executive functioning test but a significant ( p = 0.014), positive effect on the second component of the test compared to the control condition. Notably, the intervention group received 90 min of PA (see session design in Table S1 ), 2 days per week for 8 weeks, whilst the control condition did not receive any form of PA intervention during the study.

Mavilidi et al. [ 47 ] and de Greeff et al. [ 42 ] investigated the effects of active breaks on cognitive performance. Mavilidi et al. [ 47 ] reported that active breaks had no significant ( p > 0.5) effect on executive functioning compared to the control condition, whilst de Greeff et al. [ 42 ] found no significant ( p > 0.5) intervention effect on shifting performance. Likewise, studies conducted by Gall et al. [ 40 ] and García-Hermoso et al. [ 50 ] found no significant ( p > 0.5) intervention effect on cognitive performance compared to a control condition (group receiving regular PE lessons). Notably, Gall et al.’s [ 40 ] intervention included 180 min of additional PA, whilst the García-Hermoso et al.’s [ 50 ] study included 150 min of additional PA per week.

4. Discussion

This article aimed to examine the literature surrounding PA’s effect on academic performance in school children. To the author’s knowledge, this is the first study to assess PA’s effect on academic performance to include a heterogeneous participant group that is truly representative of the school community. Moreover, the authors aimed to investigate the causal factors related to the associated effects. Following the research, it can be said with confidence that a key finding in this study is that PA does not diminish academic performance in school children and potentially enhances it. Altogether, the results across the studies varied considerably. However, studies predominantly reported that PA is either positively associated with academic performance, or that there is no significant relationship between the two variables in either direction. Interestingly, Mullender-Wijnsma et al. [ 45 ] was the only article to report a negative, significant association between PA and academic performance, whilst the other articles either reported positive, significant associations (50% reported positive, significant associations) or insignificant associations (47% reported insignificant). Nevertheless, the results reported reflect those of Marques et al. [ 14 ], Ericsson and Karlsson [ 15 ], Aadland et al. [ 25 ] and Rasberry et al. [ 28 ].

An important finding to emerge from the synthesis was that various frequencies of PA were associated with improved academic performance. For example, 4 days of PA a week improved academic performance in the De Bruijn et al. [ 49 ] study, as did 5 days a week in the Reed et al. [ 41 ] study. These results are consistent with that of Rasberry et al. [ 28 ], who also reported a positive or insignificant effect of PA on academic performance irrespective of the frequency implemented. A possible explanation for this might be that the total amount of PA is more important than the accrual pattern [ 58 ]. Thus, if participants accumulated a total amount of PA that is adequate to elicit improved academic performance, how they accumulated this may not matter. However, a downfall of the De Bruijn et al. [ 49 ] and Reed et al. [ 41 ] studies is that effect size was not reported; thus, several questions surrounding this remain. Notably, future research should note the effect size so that the dose–response relationship between frequency of PA and academic performance is better understood. Moreover, further research should be undertaken to investigate if the pattern of accrual has a mediating effect on the relationship between the total amount of PA and academic performance.

The duration of PA implemented across individual studies differentiated profusely, ranging from 15 min of PA per week to 325 min of PA per week. However, of the studies that reported positive intervention effects between PA and academic performance, most implemented PA that lasted 30–60 min. These results are significant as they collaborate with an array of literature that suggests children and adolescents should receive at least 60 min of PA per day to improve health outcomes [ 2 , 59 , 60 , 61 ], suggesting that schools can facilitate a child’s physical, mental, and cognitive health without concern that such endeavours deter academic performance. However, it is imperative to note that several of the included studies derived their conclusions on the basis of subjective rather than objective measures of PA. This has significant implications for the validity and reliability of their results, as subjective measures of PA are less accurate and reliable than objective measures [ 62 ]. Therefore, it is recommended that future research utilises an objective measure of PA, such as an accelerometer, so that conclusions surrounding PA’s effect on academic performance are informed by accurate data that is representative of the PA levels that took place.

Regarding the total amount of PA, a significant finding across several studies was that increased volume of PA (total amount of PA accumulated over 1 week, frequency × duration) either did not affect academic performance or positively affected academic performance. Notably, of the studies that reported positive associations between PA and academic performance, the majority reported positive effects when the volume of PA was ≥90 per week. These findings further support the idea that the total amount of PA is a more critical factor than the frequency of PA for improved academic performance. Since most positive associations occurred when the volume of PA was ≥90 per week, irrespective of how individual studies accrued this.

No clear patterns were observed regarding the most favourable volume of PA to improve academic or cognitive performance. Therefore, on the basis of the findings in this study, the authors recommend that children receive at least 90 min of PA per week, but most desirably, their recommended levels of 60 min of PA per day, as this does not detract from academic performance and is associated with a vast amount of positive health effects [ 63 ]. Nevertheless, future research should be carried out to establish an optimal volume of PA for the improvement of academic performance. Further research could also explore the implementation of varying PA interventions and assess the differentiating effects this can have on a participants individualised academic needs.

Moreover, it is recognised that many studies manipulate independent variables such as intensity, volume, and type of PA cohesively when implementing a PA intervention design. One of the issues that emerge from this is that the actual effects of each independent variable are difficult to establish. Thus, future research should investigate the effects of volume, intensity, and type of PA in isolation so that the actual effects of each independent variable on academic performance are better understood.

It is also interesting to note that the intensity of PA had a significant effect on academic performance outcomes. Notably, across all the studies that reported moderate- to vigorous-intensity PA, 57.1% reported a positive intervention effect between moderate to vigorous PA and at least one academic performance indicator. Among the studies that reported on high-intensity PA, 100% reported a positive intervention effect between high-intensity PA and at least one academic performance indicator. These results suggest that high-intensity PA is most effective in eliciting improved academic performance. These results are significant for the implementation of increased PA in schools as it can be assumed shorter bouts of high intensity PA will be more feasible to implement alongside classroom activities than the more traditional, longer-duration, low-intensity PA interventions. These results are consistent with those attained by Mekari et al. [ 64 ], who found that high-intensity PA had a significant, positive effect on cognitive performance compared to moderate-intensity PA. A possible explanation for this might be that PA at a higher intensity causes more substantial and more enduring neurobiological changes that consequently lead to more significant improvements in academic performance [ 65 ]. Moreover, high-intensity PA was recognised in a study by Hannan et al. [ 66 ] to be more effective than moderate-intensity PA for improving aerobic fitness and cardiovascular health. This is significant as several studies state that aerobic fitness is a predictor of academic performance [ 67 , 68 , 69 ]. Therefore, it can be inferred that the high-intensity PA implemented by Ardoy et al. [ 48 ] and Schmidt et al. [ 51 ] improved aerobic fitness and, as a result, academic performance Improved congruently. Moreover, it can, thus, be suggested that specific PA may not be the single most crucial factor for improving academic performance but rather the physiological changes PA elicits. Therefore, the lens through which we view PA must be much broader. Nevertheless, it is recognised that the validity of these conclusions is questionable as they are derivative of only two studies. Thus, more research in this area is required to increase the statistical power of these results.

Interestingly, positive associations were observed across several studies that implemented a variety of different types of PA, such as karate, table tennis, mixed martial arts, team games, and cognitively engaging PA. These results are significant as they further reiterate the idea that the specific PA may not be the single most crucial factor in improving academic performance, but rather the physiological changes the PA elicits. Therefore, if the appropriate physiological changes happen, it does not matter what type of PA induces the response, as long as the response takes place. For example, aerobic fitness has been associated with academic performance outcomes [ 70 ]. Therefore, any type of PA that improves aerobic fitness may have a positive effect. Moreover, an apparent similarity across many of the efficacious types of PA was that they require a high degree of agility. For example, Pal et al. [ 71 ] stated that karate requires maximum levels of agility. Likewise, table tennis is associated with agility [ 72 ], as are many team games [ 73 ] and mixed martial arts [ 74 ]. Accordingly, it can be assumed that levels of agility may have a significant effect on academic performance. Nevertheless, future research is recommended to explore this relationship further. Regarding the optimal type of PA to improve academic performance, the authors recommend implementing various types of PA that improve agility and aerobic fitness. This is based on evidence supporting the positive relationship between these types of PA and academic performance.

4.1. Limitations

This present study systematically searched, reviewed, and collated the literature surrounding PA’s effect on academic performance and provided a clear and comprehensive overview of the available evidence. Moreover, 10 years of research were covered, specific eligibility criteria were followed, and a broad range of studies were considered. Nevertheless, as with most studies, the design of this current review is subject to limitations that could be addressed in future research. Most notably, the effect size was ill-reported throughout the available literature. Thus, few conclusions were made surrounding the strength of the relationship between the independent and dependent variables. Nevertheless, to the authors’ knowledge, this current review is one of the first studies to examine the relationship between FIIT of PA and academic performance. Despite effect size being ambiguous, this review enhances our understanding of the causal factors related to the associated effects and offered many areas for future research to explore; this insight into intervention design considerations is, therefore, a strength of the study. Study designs, outcome measures, and PA varied considerably across individual studies. Thus, these inconsistencies limited the number of objective conclusions and comparisons that could be made. Nevertheless, the scope of this review was deliberately broad to ensure all relevant literature was considered. Moreover, measures of academic performance differentiate profusely from country to country [ 37 , 38 , 39 ]. Therefore, we included a broad scope of academic measures to eradicate bias towards a particular country or place. Outcome measures related to academic and cognitive performance are described throughout this current review under the encompassing term “academic performance”. A possible limitation to doing this is that the intricacies of effects are not fully explored. For example, cognitive performance is indirectly associated with academic performance, whilst reading score is directly associated with academic performance; however, describing the results of these outcome measures under the encompassing term “academic performance” does not allude to this. Nevertheless, due to the range of outcome measures implemented by the individual studies, the authors decided to utilise an encompassing term such as “academic performance” to ensure the reader can easily interpret the results.

4.2. Practical Implications

Participant heterogeneity is one of the significant advantages of this current review. Specifically, the inclusion of differentiated participant groups ensured that this review is relevant and applicable to the school community, in which many individuals are characteristically diverse. If future research is performed, then it would be advantageous to assess a subgroup analysis to look at the academic effects of PA in specific subgroups. Nevertheless, this present study lays the groundwork for future research in this area. The findings of this research will be shared with our local and regional physical activity and public health networks so that learning from this study can benefit practitioners and policymakers as part of their programme delivery and planning. Moreover, because PA has been shown to improve and not deter academic performance, it can only be thought that such findings will influence educational reform, allowing teachers and educational leaders to integrate increased amounts of PA into the school day and national curriculum subjects. Consequently, pertinent issues such as childhood physical inactivity and childhood obesity can be addressed in schools without concern that such practices deter children’s intellectual development. This research also sheds light on optimal PA protocols for improved academic performance; accordingly, it can be utilised by teachers, policymakers, and parents as a foundational set of guidelines or benchmark of best practices to strive towards when developing their PA interventions.

5. Conclusions

To the authors’ knowledge, this is the first study to review the literature surrounding PA’s effect on academic performance and provide a contextualisation of the causal factors related to the associated effects. This study established that PA is either positively associated with academic performance, or that there is no significant relationship between the two variables in either direction. This study could not establish an optimal frequency of PA to improve academic performance; however, it was observed that total volume, duration, intensity, and type of PA may have a significant effect. Notably, PA levels of 90 min or more per week were associated with improved academic performance, as was PA performed at moderate to vigorous and high intensity. The optimal duration of PA was found to be 30–60 min per session, whilst a variety of efficacious sports made determining an optimal type of PA less clear, although evidence indicated that aerobic and agility-based sports were most favourable with several academic performance indicators. Moreover, several studies reported that increased time allocated to PA did not have a deleterious effect on academic performance. In fact, quite contrarily, many studies reported that increased time allocated to PA was positively associated with academic performance. We aim for this study’s findings to help inform evidence-based interventions and policies surrounding the implementation of PA in schools, whereby health promotion and optimal academic performance should be a priority. We will disseminate the outcomes of this study through our local, regional and national PA and public health networks. Nevertheless, given that investigation into the causal factors of the associated effects is in its infancy, further research is recommended to address the limitations of this current study and explore the gaps that were identified throughout. Most notably, the authors recommend investigations into the relationship between PA and academic performance by subgroup (e.g., disabled, gender, and race), an examination of the relationship between agility and academic performance, and further research that explores the effects of the FITT of PA on academic performance outcomes.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/children10061019/s1 ; Table S1. Academic/cognitive performance and physical activity, and article descriptive results.

Funding Statement

This research received no external funding.

Author Contributions

Conceptualisation, J.J. and C.M.P.R.; methodology, J.J. and C.M.P.R.; software, J.J.; validation, J.J. and C.M.P.R.; formal analysis, J.J. and C.M.P.R.; investigation, J.J. and C.M.P.R.; resources, J.J. and C.M.P.R.; data curation, J.J.; writing—original draft preparation, J.J.; writing—review and editing, J.J., A.P., S.M. and C.M.P.R.; visualisation, J.J. and C.M.P.R.; supervision, C.M.P.R.; project administration, J.J. and C.M.P.R. All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

Ethical review and approval were waived for this study as it was a systematic literature review and no data from participants were collected; this is in line with the institutional review board at the host university.

Informed Consent Statement

Patient consent was waived as it was a systematic literature review and no data from participants was collected.

Data Availability Statement

Conflicts of interest.

The authors declare no conflict of interest.

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