APEAdvances in Physical Education2164-0386Scientific Research Publishing10.4236/ape.2016.61004APE-63403ArticlesMedicine&Healthcare Social Sciences&Humanities Motivation, Learning Strategies, and Performance in Physical Education at Secondary School veinOlav Ulstad1HallgeirHalvari2ØysteinSørebø2EdwardL. Deci3Department of Physical Education and Sport Science, North University, Levanger, NorwayDepartment of Clinical and Social Sciences in Psychology, University of Rochester, Rochester, NY, USASchool of Business and Social Sciences, University College of Buskerud and Vestfold, Honefoss, Norway040220160601274123 November 2015accepted 11 February 14 February 2016© Copyright 2014 by authors and Scientific Research Publishing Inc. 2014This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/

Field studies investigating self-determined motivation in relation to learning strategy use and its educational outcomes in physical education are lacking. The purpose of the present study was therefore to test a Self-Determination Theory (SDT; Deci & Ryan, 2000) process model of learning strategy use as it related to participation and performance in physical education courses in eighth through tenth grades. In this model, autonomy support from teachers was hypothesized to be positively related to basic psychological need satisfaction. In turn, need satisfaction was expected to be positively related to autonomous motivation and perceived competence, both of which should be positively related to learning strategy use. Finally, learning strategy use was hypothesized to be positively related to the level of participation and the performance (i.e., grades) in physical education courses. Structural equation modeling supported the SDT process model. All indirect links in the structural model were also significant.

Self-Determination Theory Need Satisfaction Motivation Performance Autonomy Support Learning Strategies Physical Education1. Introduction

The aim of the present article is to study the role of learning strategies in the relation between motivation and outcomes such as participation and performance in physical education. Abilities and skills are important, although not sufficient for achievement in school. Self-regulated motivation and learning strategies are also important (Schunk, 2005) . In physical education, one of the main purposes is to facilitate students’ understanding and acceptance of the importance of effort in reaching their goals, and to facilitate their experience of joy and coping by being actively engaged with others. A precondition in physical education is that all the students participate and contribute to each other’s learning. Competence and effort are the bases for assigning grades in physical education. If students show persistence, trying to solve challenges without giving up, and work with others, contributing to their learning, it can enhance their grades. Learning strategies such as effort regulation, peer learning, and help seeking may not only help students get better grades but may also help them reach the main goals presented in the curriculum.

In the present research, learning strategies include effort regulation, help seeking, and peer learning (Nisbet & Shucksmith, 1986; Pintrich, 2000) , as well as task absorption (Elliot, Murayama, & Pekrun, 2011) . These learning strategies are important because they can enhance students learning and competence development (Weinstein & Mayer, 1986) , and the use of learning strategies has been found to be positively related to academic achievement (Pintrich, Smith, Garcia, & McKeachie, 1993) .

Self-Determination Theory (SDT; Deci & Ryan, 2000 ) provides a potential perspective on the student-motiv- ational antecedents of learning-strategy use and performance-related outcomes. The SDT motivation constructs of autonomous motivation and perceived competence have been found to predict a range of behavior change and learning outcomes (e.g., Williams & Deci, 1996; Williams, Saizow, Ross, & Deci, 1997 ), as well as participation and performance in physical education (Moreno, González-Cutre, Martín-Albo, & Cervelló, 2010; Sas-No- wosielski, 2008; Ntoumanis, 2005). Ntoumanis & Standage (2009) present an overview of studies from school physical education that has used SDT. Furthermore, many studies have shown relations from both authority figures’ autonomy support and participants’ need satisfaction to autonomous motivation and perceived competence (Bagøien, Halvari, & Nesheim, 2010; Cheon, Reeve, & Moon, 2012; Koka & Hagger, 2010; Moreno-Murcia, Lacarcel, & Alvarez, 2010) , as well as to engagement and performance in physical activity (Chatzisarantis & Hagger, 2009) or physical education (Tessier, Sarrazin, & Ntoumanis, 2010) . Thus, it seems that the antecedents of learning strategies in our model have received support from past studies. Because it is sensible to predict that autonomy support and need satisfaction will predict autonomous motivation and perceived competence, and that autonomous motivation and perceived competence will predict the learning strategies and outcomes. Learning strategy research from a SDT perspective is scarce. However, motivational constructs similar to autonomous motivation such as mastery goals have been positively related to learning strategy use (Hofer, Yu, & Pintrich, 1998) , and both autonomous motivation and perceived competence have been positively linked to the more specific learning strategy effort regulation (Miserandino, 1996; Vallerand & Bissonnette, 1992) . In addition, learning strategies have been positively linked to educational outcomes (Crede & Phillips, 2011) . This may indicate a mediating role of learning strategies in the relation between SDT motivation constructs and physical education outcomes, because both needs satisfaction and autonomous motivation have been positively linked to engagement and performance in physical education (Cheon, Reeve, & Moon, 2012) . In addition, in accordance with the SDT process model (Deci & Ryan, 2000) , we include perceived autonomy support from teachers and psychological needs satisfaction as antecedents of autonomous motivation and perceived competence in the model tested. This resulted in the following three questions: Would need satisfaction mediate the link between autonomy support and the two motivational constructs (viz., autonomous motivation and perceived competence)? Would the two motivational constructs mediate the links between needs satisfaction and the use of learning strategies? And would learning-strategy use mediate the relation between the two motivation variables and performance and participation in physical education?

The purpose of this study was to test the fit of a process model in which perceived autonomy support from teachers would positively predict students’ need satisfaction, and that need satisfaction would positively predict both autonomous motivation and perceived competence, each of which in turn would be positively linked to learning strategy use, which again would positively predict both participation and performance (see Figure 1).

1.1. Autonomy Support and Need Satisfaction

In the educational domain autonomy support is defined as interpersonal sentiments and behaviors teachers provide during instructions to identify, nurture, and develop students’ inner motivational resources (Reeve, 2009) . To nurture inner motivational resources by providing explanatory rationales, relying on non-controlling and

Results from the structural equation analysis. Note. All coefficients are standardized. χ<sup>2</sup> (df = 182) = 431.89, p < .001, RMSEA (90% CI) = .069 (.060 - .077), CFI = .93, TLI = .92, SRMR = .059, ***p < .001

informational language, displaying patience to allow time for self-paced learning, and acknowledging and accepting expressions of negative affect (Reeve, 2009) , teachers may be able to foster greater need satisfaction in students.

Teachers providing autonomy support have been shown both to nurture satisfaction of the needs for competence, relatedness, and autonomy in physical education (Cheon et al., 2012; Standage, Duda, & Ntoumanis, 2006) , and to predict perceived competence and autonomous motivation in high school students (Hardre & Reeve, 2003) .

1.2. Need Satisfaction, Autonomous Motivation, and Perceived Competence

Self-determination theory emphasizes that three inner needs are central to human growth and development, the needs for autonomy, competence, and social relatedness (Ryan & Deci, 2002) . Autonomy refers to volition and the experience of freedom (Deci & Ryan, 2000) . Competence is about feeling effective and confident in pursuing an activity (Ryan & Deci, 2002) , and relatedness is about being accepted by others and feeling connected to others in a secure environment (Ryan & Deci, 2002) . An autonomy supportive learning environment plays a key role in the satisfaction of these needs. According to the theory, satisfaction of these needs supports intrinsic motivation, internalization, and autonomous motivation (Ryan, Williams, Patrick, & Deci, 2009) . In an educational setting, students’ often encounter activities they do not enjoy or that they find of little interest. Internalization of extrinsic motivation is therefore important for the students to maintain volition for those activities (Niemiec & Ryan, 2009) . By supporting the needs for competence, relatedness, and autonomy in physical activities, teachers can enable the process of internalization and integration of motivation (Ryan, Williams, Patrick, & Deci, 2009) . By supporting students’ inner needs, teachers’ can facilitate their autonomous self-regulation for learning and academic performance (Niemiec & Ryan, 2009) . Research in physical education has shown that satisfaction of each of the three needs predicts autonomous motivation independently (Koka & Hagger, 2010; Standage, Duda, & Ntoumanis, 2006) as does the sum of the three needs (Ntoumanis, 2005) . Further, the need satisfactions correlated strongly positively with students’ perceived competence for physical activity (Bagøien, Halvari, & Nesheim, 2010) . Other research in schools indicated that the needs for competence and autonomy are most important in relation to autonomous motivation (Barkoukis, Hagger, Lambropoulos, & Tsorbatzoudis, 2010; Standage & Gillison, 2007; Standage, Gillison, Ntoumanis, & Treasure, 2012) . Thus, because autonomy support has been directly linked to both autonomous motivation (Cheon, Reeve, & Moon, 2012) and perceived competence (Moreno-Murcia, Lacarcel, & Alvarez, 2010) , we expected that satisfaction of the basic needs in physical education would mediate the positive links between autonomy support and both autonomous motivation and perceived competence.

1.3. Autonomous Motivation, Perceived Competence, and Learning Strategies

Self-determined forms of extrinsic motivation (identified and integrated regulation) have been combined with intrinsic regulation to form autonomous motivation (Ryan & Deci, 2000) . SDT views the quality of motivation as more important than the amount of motivation for predicting outcomes, and a central distinction in SDT, namely, the degree to which motivation is autonomous versus controlled, is a critical differentiation in terms of quality of motivation. Autonomous motivation is when people have identified with the value of the activities and have integrated the internalizations into their own sense of self (Deci & Ryan, 2008) . Autonomous motivation is expected to lead to many positive outcomes such as long-term persistence, healthier behavior, and more effective performance (Deci & Ryan, 2008) . Empirical evidence based on self-determination theory research shows that autonomous motivation and intrinsic motivation are important for engagement and optimal learning in school (Niemiec & Ryan, 2009) . Autonomous motivation and perceived competence are believed to be critical preconditions for maintaining a behavior change over time (Ryan & Deci, 2000) , which is significantly less achieved when the motivation is controlled. Several studies of pupils and students from early elementary school to college and university have supported the hypothesis that changes in autonomous motivation and perceived competence would predict positive changes in: (1) classroom engagement, perceived skill, and performance in physical education (Cheon et al., 2012) ; (2) remaining in school and not dropping out (Vallerand & Bissonnette, 1992) ; (3) the degree of conceptual learning and better memory of learned materials (Grolnick, Ryen, & Deci, 1991) ; (4) improved academic achievement (Grolnick, Ryan, & Deci, 1991; Miserandino, 1996) ; and (5) involvement in physical activity (Bagøien & Halvari, 2005) .

Learning strategies, in the present study, are operationalized as a composite of effort regulation, help seeking, and peer learning from the resource management strategies in the MSLQ manual (Pintrich, Smith, Garcia, & McKeanchie, 1991) , as well as task absorption. All variables are hypothesized to mediate between each of the two motivation variables and educational outcomes. In particular effort regulation seems to be of importance as significant relations have been reported for: (1) both autonomous motivation and/or perceived competence among students, in relation to persistence (i.e., effort when things become difficult) and involvement in class (Miserandino, 1996; Vallerand & Bissonnette, 1992) ; (2) both autonomous motivation and perceived competence as predictors of continued effort at difficult tasks (viz., action orientation after failure) (Halvari, Ulstad, Bagøien, & Skjesol, 2009) ; (3) both autonomous types of motivation and/or perceived competence and effort (Noels, Clement, & Pelletier, 1999; Ntoumanis, 2001; Ntoumanis, 2002) ; (4) both autonomous motivation and need satisfaction in physical education and increases in effort over time (Taylor, Ntoumanis, Standage, & Spray, 2010) ; and (5) autonomous motivation (both intrinsic and identified regulation) for goals and sustained effort over time in two studies of undergraduate students in psychology classes (Sheldon & Elliot, 1998) . Further, the strategy of task absorption (or concentration) represents cognitive immersion in an activity (Cury, Elliot, Sarrazin, Da Fonseca, & Rufo, 2002) , and has been positively correlated with autonomous motivation and participation (Martin & Jackson, 2008) . However, physical education research on peer learning and help seeking in a physical education context using self-determination theory seem scarce. Thus, autonomous motivation and perceived competence were expected to be positively linked to learning strategies, in particular to effort regulation and task absorption or concentration.

Because the use of learning strategies has been shown to be more evident among students with high normative ability in the academic classroom (Ames & Archer, 1988) , we also tested the relative contribution of normative ability (viz. grades/performance), autonomous motivation, and perceived competence in relation to the use of learning strategies. If motivation affects the use of learning strategies independent of ability this would be important, because there is evidence that it is much easier to influence students’ motivation than their relatively more-stable abilities (Dweck, 1999) .

1.4. Links from Learning Strategies to Participation and Performance

Effort regulation is important to academic success because it not only signifies goal commitment, but also regulates the continued use of learning strategies (Pintrich, Smith, Garcia, & McKeanchie, 1991) . Effort regulation is one of the resource management strategies that work as motivational beliefs that promote and sustain different aspects of self-regulated learning (Pintrich, 1999) .

Peer learning has been found to have positive relations to achievement, and dialogue can help clarify material and reach insights one may not have attained on one’s own (Pintrich, Smith, Garcia, & McKeanchie, 1991) . Help seeking from peers and the instructor is another important aspect of the environment. There is a lot of research that indicates that peer help, peer tutoring, and individual teacher assistance facilitate student achievement (Pintrich, Smith, Garcia, & McKeanchie, 1991) .

Task absorption helps people concentrate on an activity. It is a type of mental focus shown to be positively related to performance and enjoyment for students (Lee, Sheldon, & Turban, 2003) . Task absorption or involvement has been shown to be positively associated with intrinsic motivation and to lead to more free-choice puzzle solving, more time spent on the activity, and enjoyment (Cury, Elliot, Sarrazin, Da Fonseca, & Rufo, 2002; Elliot & Harackiewicz, 1996) . A positive correlation between absorption and participation in art education was reported from university students (Wild, Kuiken, & Schopflocher, 1995) . An experience of absorption on the internet was shown to be more important than extrinsic factors regarding consuming behavior on the net (Shang, Chen, & Shen, 2005) .

A study among medical students reported significant positive associations between study effort and academic performance (grades) for males (Kusurkar, Ten Cate, Vos, Westers, & Croiset, 2012) . Another study report that effort-regulation strongly predicted course grades for freshman and upper level college students (Lynch, 2006) . Two studies done by Sheldon & Elliot (1998) showed that effort promotes goal attainment for students in a psychology class. A meta-analytic review of learning strategies, based on 67 independent samples indicates that effort-regulation was the one positively predicting grades most strongly (true score correlation = .40) (Crede & Phillips, 2011) . Analysis indicated that effort-regulation partially mediated the relationship between self-efficacy and grades. As self-efficacy is a similar construct, although more task specific, but related to perceived competence, this finding indicates that effort regulation may mediate the link between perceived competence and outcomes in the present study. Together with help-seeking and self-efficacy, effort regulation predicted 18% of the variance in grades for undergraduates (Komarraju & Nadler, 2013) . Effort as a learning strategy predicted final grades and performance in the lab among college students (Lynch, 2010) .

1.5. Model and Hypotheses

Based on the theory and research described above, we tested a SDT (Deci & Ryan, 2000) process model of participation and performance in physical education at school (see Figure 1). In the model, the hypothesized mediators are: (1) needs satisfaction would mediate the positive links between perceived autonomy support and each of the two motivation variables (autonomous motivation and perceived competence); (2) autonomous motivation and perceived competence would separately mediate the positive link between needs satisfaction and use of learning strategies; and (3) learning strategies would mediate the positive links between each of the two motivation variables and each of the two outcomes (viz., participation and performance in physical education).

We also tested the relative contribution of normative ability (grades) together with autonomous motivation and perceived competence in relation to the use of learning strategies.

2. Method2.1. Participants

Participants were 290 students (162 boys and 128 girls) attending the 8th, 9th, or 10th grade (Mage = 14.0, SD = .9). The students were distributed among four schools in Nord-Trøndelag, Norway, and they represented 14 classes and 12 teachers. Students responded to a questionnaire package (see appendix) measuring autonomysupport, need satisfaction, autonomous motivation perceived competence, effort regulation, absorption, help- seeking, peer-learning, performance and participation in late February, just after that they had received their semester grades. The questionnaire was completed in class with one teacher reading the questions for the students.

2.2. Measures

The scales for measuring motivational and learning strategy variables were translated to Norwegian from English following recommended procedures (Beaton, Bombardier, Guillemin, & Ferraz, 2000) . The measures were found reliable in previous research in Norway as well as in the present study. In a past study, α for perceived teacher autonomy support was .96 (Bagøien, Halvari, & Nesheim, 2010) and in the current study α was .89. For psychological need satisfaction: in a past study the range of α was .78 - .83 for the autonomy need; .78 - .84 for the competence need; and .82 - .88 for the relatedness need (Solberg, Hopkins, Ommundsen, & Halvari, 2012) . In the current study, α = .85 for the autonomy need, α = .88 for the competence need, and α = .87 for the relatedness need. In a past study, the autonomous motivation for learning had an α = .92 (Bagøien et al., 2010) ; and in the current study, α = .80 (with α’s = .93 and .88 for the intrinsic and identified motivation sub-scales, respectively). For perceived competence, α = .95 (Bagøien et al., 2010) ; and in the current study α = .89.

Regarding the learning strategy scales, they were found acceptably reliable in the current study (α’s = .73 for effort regulation, .73 for peer learning, and with a borderline estimate of .64 for help seeking). This pattern of internal consistency is the same as initially reported for these scales, with α’s = .69 for effort regulation, .76 for peer learning, and .52 for help-seeking (Pintrich, Smith, Garcia, & McKeanchie, 1991) . For absorption, α = .72 in the current study.

2.3. Data Analysis

Before we tested the hypothesized SDT process model and because students were nested within teachers, we used multilevel hierarchical linear modeling (HLM, Version 7.00; Raudenbush, Bryk, & Congdon, 2010 ) to test whether teacher differences affected students’ self-reported perceptions of autonomy support, needs satisfaction, motivation, learning strategies, and performance. The percentage of the total variance explained by teacher was low for all student indicators, except for the two performance indicators, which exceeded the 10% cutoff value as reflected by the intraclass correlation coefficient (ICC; see the first column in Table 1). Due to the low number of between-teacher differences on the indicator level (i.e., 2 out of 21) and the low number of clusters (i.e., 12 teachers), we decided to perform two structural equation tests with Mplus (Version 7.3; Muthén & Muthén, 1998-2012 ). First, we tested the complete SDT process model, with its seven latent variables, as an ordinary covariance-based structural equation model. Next, we utilized multilevel structural equation modeling on a reduced model that included only two latent variables, namely learning strategies and performance. The decision to test only a reduced multilevel model was based on the fact that the number of clusters to analyze (i.e., 12) was relatively low for the performance of a valid multilevel analysis (McNeish & Stapleton, 2014) . As emphasized above, the ICC from the HLM analysis revealed that the performance indicators were the only indicators that were exposed to a between-teacher effect. This suggests that it is only necessary to test the relations between learning strategies and performance as a multilevel model. Testing two different models, namely, one ordinary and one multilevel model, makes it possible to compare the influence of between-teacher effects on the relations between learning strategies and performance.

The model fit in Mplus was evaluated by using the chi-square likelihood ratio (X²), the Tucker Lewis Index (TLI), the Comparative Fit Index (CFI), the standardized root-mean-square residual (SRMR), and the root mean square error of approximation (RMSEA). TLI and CFI values should be close to .95 or higher to be adequate, and the values for SRMR and RMSEA should be equal to or lower than .08 (Hu & Bentler, 1999) . If the values are close to these recommendations, the fit of the hypothesized model to the data would be considered adequate. These values for model evaluation are also reported in other studies describing good or acceptable fit (Schermelleh-Engel, Moosbrugger, & Muller, 2003) .

3. Results3.1. Descriptive Statistics and Reliability

In Table 2, observed ranges, standard deviations, and means are presented together with reliabilities for all the variables. All of the variables yielded good reliability estimates exceeding the value of .70, except the help seeking variable with an alpha value = .64. Pintrich et al. (1993) reported an alpha value = .52 for help seeking, arguing that it can be because the items ask about seeking help both from peers and instructors, and that students tend to seek help from only one of these sources.

3.2. Measurement Model

We tested the measurement model with all the variables and found an adequate fit. [X² = 448.36, df = 174, p < .001; TLI = .91; CFI = .93; SRMR = .058; RMSEA = .074]. One out of twenty-two indicators was dropped (cf., Table 1) based on reported standardized residuals. This means that this indicator showed a significant degree of shared nonspecified variance with other measurement items. After removing this indicator, the model fit

Interclass correlation coefficients (ICC), standardized beta (β) weights and t-values for all 22 observed indicators
Observed variableICC (%)βt-value
Perceived autonomy support indicators
1. Teacher provides choices and options0.00.7121.47***
2. Feel understood by my teacher0.02.8131.36***
3. Teacher conveys confidence in me0.02.7828.44***
4. Teacher encourages questions0.00.6718.38***
5. Teacher listens…0.04.7928.80***
6. Teacher understands how I see things¹0.03.7524.57***
Needs satisfaction indicators
1. Competence need0.00.9580.76***
2. Social relatedness need0.00.7223.34***
3. Autonomy need0.00.8441.36***
Autonomous motivation indicators
1. Intrinsic motivation0.06.9240.54***
2. Identified motivation0.02.8028.37***
Perceived competence indicators
1. PC10.00.8032.33***
2. PC20.00.8543.39***
3. PC30.00.7324.27***
4. PC40.00.8851.61***
Learning strategy indicators
1. Effort regulation0.02.6818.20***
2. Absorption0.06.6114.36***
3. Peer learning0.02.6716.54***
4. Help seeking0.00.5210.19***
Performance indicators
1. Actual grade0.20.7823.07***
2. Expected grade0.11.8729.71***
Participation indicator
1. How often participating0.01----

*** p < .001. 1Removed item.

improved slightly [X2² = 375.05, df = 155, p < .001; TLI = .92; CFI = .94; SRMR = .051; RMSEA = .070].

3.3. Structural Equation Model

The theoretical model with all the hypothesized paths was tested as a structural equation model based on the hypothesized relations between latent variables. In the theoretical structural model, all paths were significant, and the model yielded an adequate fit [X2 = 431.89, df = 182, p < .001; TLI = .92; CFI = .93; SRMR = .059; RMSEA = .069].

 3.4. Test of Indirect Links

We used Mplus to simultaneously test the indirect links in the structural model presented in Figure 1: (1) Autonomy support was indirectly positively associated with both autonomous motivation (E = .45, SE = .04, Z = 10.53) and perceived competence (E = .50, SE = .04, Z = 11.82) through need satisfaction; (2) need satisfaction

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