Tony A. Pritchard

Effects of Two Instructional Approaches on Skill Development, Knowledge, and Game Performance

Two instructional approaches that have been of interest in promoting sport have been the Sport Education Model (SEM) and the Traditional Style (TS) of teaching physical education. The purpose of this study was to investigate how SEM and TS would affect skill development, knowledge, and game performance for volleyball at the secondary level. A 2 × 3 (group × time) research design was utilized on 47 secondary students testing volleyball skills, knowledge, and game performance. Participants were placed in either the SEM or the TS via stratified randomization, and then were tested pre, mid, and post intervention through the 20-lesson volleyball unit. The 2 × 3 repeated measures Analysis of Variances (ANOVAs) with Bonferroni correction revealed no significant difference between models for skills and knowledge, but there was for game performance for group [F(1, 45) = 10.27, p < .008, η2 = .19], time [F(2, 90) = 8.62, p < .008, η2 = .16], and group × time interaction [F(2, 90) = 8.43, p < .008, η2 = .16]. If the goal of the physical education program is to promote quality game play, the SEM may be more effective than the TS.

Physical activity, screen time, and school absenteeism: self-reports from NHANES 2005–2008

Abstract Objective The purpose of this study was to examine how lifestyle behaviors in the context of physical activity levels and screen time are associated with school absenteeism. Methods We analyzed 2005–2008 NHANES data of proxy interviews for 1048 children aged 6–11 years and in-person self-reports of 1117 adolescents aged 12–18 years. Missing 10% of school days during the past school year was defined as severe school absenteeism (SSA). Results Watching TV ≥2 hours a day was significantly associated with SSA among both children (OR = 3.51 [1.03–12.0]) and adolescents (OR = 3.96 [1.84–8.52]) compared with their peers watching <2 hours a day. A U-shaped association was identified between the level of physical activity and SSA among children. Both inactive children (OR = 12.4 [1.43–108]) and highly active children (14.8 [2.82–77.7]) had higher odds of SSA compared with children with medium levels of physical activity. No associations were observed for either children 0.57 ([0.16–1.99]) or adolescents (0.94 [0.44–2.03]) using a computer ≥3 hours a day. Limitations Cross-sectional study involving self-reports. Transportation to and from school not included in physical activity assessment. Absenteeism was not validated with report cards. Unable to account for the absence type or frequency of illness or injury. No psychometric properties provided for subjective measures regarding participants’ attitudes and characteristic traits towards physical activity, TV viewing, and school attendance. Conclusions Excessive TV watching among children and adolescents, and inactivity and high activity levels (≥7 times per week) among children are independently associated with severe school absenteeism.

The Sport Education Tactical Model

JOPERD • Volume 80 No. 9 • November/December 2009 A n instructional model is a “plan or pattern that can be used to shape curriculums (long-term courses of studies), to design instructional materials, and to guide instruction in the classroom or other settings” (Joyce & Weil, 1980, p. 1). Metzler (2005) described nine different instructional models that teachers can choose from to guide their teaching. Two instructional models that physical educators in middle and high schools often use are the sport education model (SEM) and the tactical games model (TGM). The SEM is a curriculum and instructional model that provides students with a more authentic sport experience in physical education (Siedentop, 1998). The SEM benefits teachers and students by increasing levels of responsibility and creating an environment that reinforces specific interpersonal behaviors (Hastie, 1998), increasing positive interactions and decreasing negative ones among students (Hastie & Sharpe, 1999), and providing more learning opportunities for lower-skilled students and girls (Hastie, 1998b; 1998c). Off-task behaviors also decrease (Hastie, 1996) as students get more opportunities to participate in moderate-to-vigorous physical activity (Hastie & Trost, 2002). Physical educators have also reported increased game performance (Hastie, 1998c; Ormond, Christie, Barbieri, & Schell, 2002; Pritchard, Hawkins, Wiegand, & Metzler, 2008) and skill development (Townsend et al., 2004). The TGM is an instructional model that promotes playing ability through interest and understanding of how to play games (Mitchell, Oslin, & Griffin, 2006). Research on the TGM has found that teachers preferred this model and that students were motivated by it (Berkowitz, 1996; Burrows, 1986; Griffin, Oslin, & Mitchell, 1995; Mitchell, Griffin, & Oslin, 1994). Other researchers have reported a transfer of learning from one sport to another (Mitchell & Oslin, 1999; Martin, 2004). If the teacher is teaching an invasion game (e.g., soccer), the tactics used in that activity can be transferred to other invasion sports like basketball or Ultimate. For example, the same or very similar learning task and objective of moving to open spaces would be taught, and therefore reinforced for transfer of learning, in each invasion sport. The same can be said about other categories of sports that are similar in tactics, such as badminton and tennis (i.e., net/wall games). When describing the TGM, Mitchell et al. (2006) suggested using the components of the SEM to “provide an effective framework through which a tactical games model can be implemented” (p. 487). The SEM and TGM have shown positive results, so why not combine both models to form a new sport education tactical model (SETM)? The purpose of this article is to describe the SETM and how it would be implemented at the middle and high school levels in order to promote lifetime engagement.

The Personalized System of Instruction in Fitness Education

JOPERD • Volume 82 No. 6 • August 2011 P ersonal fitness courses are required in many high schools in the United States and are offered by many colleges as physical activity courses. These courses are vital for the development of lifelong personal fitness behaviors in adolescents. The importance of these courses is compounded by the fact that only 54 percent of high school students attended physical education classes in 2007 (Centers for Disease Control and Prevention [CDC], 2008). These courses usually follow one of two instructional approaches. In teacherfocused fitness courses, students often follow the teacher’s example in group activities, whereas student-focused courses generally allow the student to choose among various activities in the hope of promoting enjoyment and personal meaning. However, the typical approaches to personal fitness have not translated into positive changes in the health status of today’s youths, as the obesity rate among adolescents has increased from 6.5 to 17.0% over the past three decades (Ogden, Carroll, & Flegal, 2008), and physical activity has decreased with age (National Center for Health Statistics, 2004). This is possibly due to physical education teachers’ inability to promote, in activitybased courses, the necessary fitness concepts that might lead to permanent lifestyle changes (Ross, 1994). Personal fitness courses must result in cognitive gains as well as enjoyment and personal application in order to produce lifestyle changes in high school students. To achieve this, physical education teachers need to meet the following guidelines to promote activity among their students: (1) provide planned, sequential physical education that promotes lifelong activity, (2) develop student knowledge and positive attitudes toward physical activity, and (3) develop mastery of skills and confidence in physical activity among students (CDC, 1997). One approach that physical education teachers could take to meet these guidelines is the personalized system of instruction (PSI; Keller & Sherman, 1974). Most physical education classes focus on student learning in the psychomotor domain, since teachers aim to increase the activity levels of students (Harrison, Blakemore, Buck, & Pellett, 1996). While students may experience direct benefits from such a narrow approach, it does not promote lifestyle changes. During a personal fitness course, students must engage in physical activity and develop the knowledge, motivation, and self-confidence to engage in fitness activities outside the physical education setting. This can be done only by making personal fitness “personal.” The PSI allows students to progress “as fast as they can or as slowly as they need” (Metzler, 2005, p. 217). Increasing the personal application of fitness content and improving student learning in all domains will make students more likely to continue to participate in the activity throughout life. An instructional model used in physical education settings, the PSI has been defined as a “plan or pattern that can be used to shape curriculums (long-term courses of studies), to design instructional materials, and to guide instruction in the classroom or other settings” (Joyce & Weil, 1980, p. 1). When selecting an instrucThe Personalized System of Instruction in Fitness Education

Using Sport Education to Teach the Lifetime Sport of Golf

Golf is a lifetime sport activity that can be taught in physical education classes. How one teaches golf in physical education could influence whether students will want to continue to participate outside of physical education. The sport education model (SEM) is an instructional model that promotes student learning in all three domains by ensuring students become competent, literate and enthusiastic in the activity being taught. The purpose of this article is to describe the steps necessary for teachers to utilize SEM when teaching golf in physical education.

Using the Personalized System of Instruction to Differentiate Instruction in Fitness

The purpose of this article is to provide an overview of how PE teachers can personalize learning to meet a variety of student needs. Differentiated instruction (DI) is a term frequently used in classroom-based learning to describe a method of personalization for individual students. The term can also describe a theoretical model for teaching and research, an instructional model, and a philosophy. Teachers must have a firm understanding of student readiness, interest, and learning profile to differentiate four areas of instruction: content, process, product, and the environment. Students in PE can benefit from DI, but there is a lack of formal methods to differentiate PE content. The Personalized System of Instruction (PSI) is an instructional model that provides a complete framework for PE teachers to personalize learning for all students. Fitness-related content such as resistance, plyometric, and agility training provides a context for applying the PSI model to DI in the secondary school setting. Subscribe to TPE

Letter to the Editor: Author Response

Thank you for sharing the recent letter commenting on our manuscript ‘‘Physical activity, screen time, and school absenteeism: self-reports from NHANES 2005–2008’’. We appreciate the opportunity to respond and provide clarification. We thank the author of the letter for his interest in our study and critical viewpoints. We believe there may have been a misinterpretation of our purpose and findings. The primary objective of our study, as stated briefly in the abstract, was ‘‘to examine how lifestyle behaviors in the context of physical activity levels and screen time are associated with school absenteeism’’. We did not make an effort to statistically compare the rates of absenteeism between children ages 6–11 and adolescents ages 12–18. We examined the associations between the variables in question for the two age groups separately, first, because of the unequal distribution stated in the letter and second, the adolescent surveys were self-reports and child surveys were proxy responses. We respect that self-reported data in most cases may not be comparable to proxy responses or direct observation. Lastly, obtaining accurate national estimates was not our objective due to the data limitations. Hence, for the sake of simplicity, we used two-year weighting variables for each two-year survey cycle. We also thank the author of the letter for pointing out a citation error. The citations indeed have been mismatched during multiple rounds of copy-editing. We apologize for this oversight. The more relevant citation, also in our reference list, is ‘‘Generation M2: media in the lives of 8 to 18-yearolds’’, a report of a series of large-scale, nationally representative surveys by the Kaiser Family Foundation about young people’s media use. The report found that the average amount of time spent watching TV in a typical day among 8 to 18 year old children and adolescents was 3:47, 3:51 and 4:29 hours respectively in the 1999, 2004 and 2009 surveys. The Ianotti and Wang study, referenced in the letter, observed 11–16 year old adolescents and provides another perspective on this important issue. It would be interesting to see what the findings would be if age ranges were similar between the two studies. The author of the letter also pointed out that we may have overstretched our observation with the statement ‘‘Reducing time on physical education and in turn reducing opportunities for physical activity is to ‘put the cart ahead of the horse’ since physical activity and fitness are associated with increased academic performance’’, and that this statement does not fit our finding that ‘‘Engaging in high levels of PA [physical activity] was significantly associated with increased odds of SSA [severe school absenteeism] among children, but not adolescents’’. We are confused by this concern and believe the letter does not address the other important finding that ‘‘The odds of SSA was more than ten times higher among physically inactive children than their peers with medium levels of PA, but no such relationship was observed with adolescents’’. As a result, our findings demonstrated a U-shaped curve in which physical inactivity and excessive activity were associated with increased odds of SSA among children aged 6–11 years. This U shaped curve is assessed at length in the discussion section and the statement regarding ‘‘Reducing time on physical education and in turn reducing opportunities for physical activity. . .’’ was strategically sequenced immediately after addressing the finding that physical inactivity is associated with increased odds of SSA.