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Peter A. Hastie and Tristan Wallhead

Purpose:

This paper provides a potential roadmap for the future development of research on Sport Education. In the first part of the paper, research on each of the elements of competence, literacy and enthusiasm are reviewed, with the aim of providing evidence to support the idea that the model can achieve its goals. For each of these goals we provide some potential directions which we believe are important for moving research on Sport Education forward.

Development:

These avenues include more attention to appropriate practices for enhancing student-coach effectiveness, ways to enhance the development of more equitable and inclusive class environments within the model, as well as the potential transfer of Sport Education experiences to physical activity environments beyond physical education.

Design:

Research designs need to include how teachers and students give value and significance to what they teach and what they learn, respectively. This could be achieved through researchers considering more prolonged action-based research designs that allow a close monitoring of the implementation of pedagogical approaches. These case studies can provide guidance for future pedagogical iterations of the model that can be applied within more generalizable group designs.

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Jacob Szeszulski, Kevin Lanza, Erin E. Dooley, Ashleigh M. Johnson, Gregory Knell, Timothy J. Walker, Derek W. Craig, Michael C. Robertson, Deborah Salvo, and Harold W. Kohl III

on models and frameworks to guide research agendas, surveillance, and program planning/evaluation. Researchers have proposed 4 key domains of adult physical activity: leisure time, occupational time, transportation time, and household time. 7 This 4-domain classification system, however, is not

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Karl M. Newell and Paola Cesari

Smeets and Brenner provide a very clear and useful statement of the work that has been stimulated by Jeannerod's 1984 paper but seem more concerned about the viability of model fitting than model assumptions. The theoretical and practical limitations of viewing “grasping as nothing more than pointing” are noted. We reemphasize the importance in prehension of the union of the hand with the object in the act of realizing a task goal.

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Janaina Lima Fogaca, Sam J. Zizzi, and Mark B. Andersen

publish articles and book chapters about sport psychology supervision (e.g.,  Andersen, Van Raalte, & Brewer, 1994 ). These publications included important recommendations such as using models of supervision similar to the ones found in counseling supervision (e.g.,  Andersen & Williams-Rice, 1996

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Kobe Vermeire, Michael Ghijs, Jan G. Bourgois, and Jan Boone

in the 70s, the impulse-response model, more commonly known as the fitness–fatigue model, was developed. 1 In this fitness–fatigue model, performance is considered the resultant of both a fitness and a fatigue component that are both induced to a different extent from a training session. Although

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Marius Pokolm, Robert Rein, Daniel Müller, Stephan Nopp, Marie Kirchhain, Karl Marius Aksum, Geir Jordet, and Daniel Memmert

to complete their passes. A Bayesian hierarchical model, accounting for individual player differences and pass difficulty, was used to examine the influence of scanning on performance. The results showed that scanning had a positive, albeit small, influence on performance when controlling for

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Philip Friere Skiba and David C. Clarke

cycling, the availability of bike-mounted power meters enables the power–duration relationship to be computed as best-power-for-duration efforts, which may also be extracted from the maximal mean power profile. 1 Various mathematical models have been proposed to express the power–duration relationship in

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Brock Laschowski, Naser Mehrabi, and John McPhee

skeletal muscles (ie, dynamometry) is invasive and therefore unpractical in sport environments. 3 With modern advancements in computer science, biomechanical modeling presents a viable method of approximating the dynamics of multibody movements. 3 Considering the emergent interests in determining the

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Keith R. Lohse, Jincheng Shen, and Allan J. Kozlowski

descriptors for mixed-effect regression models (viz., “mixed-effect”, “multilevel model” or “MLM”, “hierarchical linear model” or “HLM”). Of the 15 articles that employed mixed-effects regression only two were longitudinal designs ( Angell et al., 2018 ; Cantin, Ryan, & Polatajko, 2014 ), while the remainder

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Jeff M. Barrett, Colin D. McKinnon, Clark R. Dickerson, and Jack P. Callaghan

activity levels (∼15% Maximum Voluntary Contraction), with most users adopting postures at neck flexion angles smaller than those required to elicit a flexion-relaxation response. 5 Despite these alarming statistics, there are few biomechanical models focused on studying the physical risk factors that