1 Measurement in Physical Education and Exercise Science, 13: 34 51, 2009 Copyright Taylor & Francis Group, LLC ISSN: X print / online DOI: / Validating Coach-Athlete Relationship Measures with the Nomological Network HMPE X Measurement in Physical Education and Exercise Science, Vol. 13, No. 1, November 2008: pp Criterion JOWETTValidity of the CART-Q Sophia Jowett School of Sport & Exercise Sciences Loughborough University, United Kingdom The coach-athlete relationship is viewed as a multidimensional situational construct containing three factors: namely, closeness, commitment, and complementarity (3 Cs) that can be captured from a direct perspective and a meta-perspective. This conceptualization is primarily based on research conducted with samples that mix student and non-student athletes. This study aimed to examine the factorial structure of the direct and meta-perspective versions of the Coach-Athlete Relationship Questionnaire (CART-Q) in a sample of student athletes. Confirmatory factor analysis supported the validity of a model with separate yet correlated factors for the 3 Cs. Furthermore, the 3 Cs were found to be related in a conceptually coherent manner with such outcome variables as support from coach, significance of the relationship (depth), and the level of conflict experienced in the relationship. The results contribute further evidence to the utility of the CART-Q for the assessment of the quality of the coach-athlete relationship in student athletes. Key words: construct validity, nomological network, coach-athlete relationship INTRODUCTION Although the coach-athlete relationship has attracted limited empirical attention over the years, largely due to the lack of theoretical frameworks and measurement tools, progress has recently been noted (see Jowett & Wylleman, 2006). This surge of theoretical and empirical research may be due to the realization that the coach-athlete relationship is central to effective coaching (Lyle, 2002). The position that this article adopts regarding the practical significance of the coach-athlete relationship is that, while an athlete may have a chance in the sport by going it alone, the athlete and the coach in partnership have more and better chances of success. Clyde Hart and Michael Jackson (Olympic medalist and world record holder in 400 m), Bob Bowman and Michael Phelps (Olympic gold medalist in 100 m/200 m butterfly), Chris Carmichael and Lance Armstrong (7-time Tour de France winner), and Mary Lou Retton and Béla Karolyi (Olympic medalist in gymnastics) are just a few examples that demonstrate the impact a good working relationship can have on performance accomplishments. Correspondence should be sent to Sophia Jowett, Ph.D., School of Sport & Exercise Sciences, Loughborough University, Loughborough, Leicestershire, LE11 3TU, United Kingdom.
2 CRITERION VALIDITY OF THE CART-Q 35 Thus, studying the nature and content of the coach-athlete relationship as well as its functions would help discern what makes a coach-athlete relationship positive and successful. The generated knowledge will help design strategies for the development of effective, supportive, and successful athletic relationships. However, before this happens, scholars in this area need to give careful consideration to a number of critical issues, including defining and measuring the concept of the coach-athlete relationship, determining the construct validity of this concept, and identifying variables that act as outcomes (i.e., testing the concept s nomological network; see Cronbach & Meehl, 1955). THE NOMOLOGICAL NETWORK OF THE COACH-ATHLETE RELATIONSHIP The nomological network is a philosophical foundation that was developed by Lee J. Cronbach and Paul E. Meehl in 1955; it was their view of construct validity in psychological tests. The nomological network includes making clear what the concept is by setting forth the laws in which it occurs (i.e., establishing theoretical propositions), clarifying how the concept in question is going to be measured (e.g., operationalizing its theoretical construct/s), elaborating the nomological network by adding a construct or a relation to the theoretical framework, as well as specifying and establishing the empirical linkages of the theoretical and empirical frameworks. The central aspect to the nomological network (and ultimately to construct validity) of a psychological concept is the creation of a link between the conceptual/theoretical domain with the observable one. Cronbach and Meehl (1955) ascertained that a rigorous chain of inference is required to establish a test as a measure of a psychological concept. Based on the nomological network, the discussion that follows highlights efforts that have been made thus far to validate the claim that the developed psychological measures of the coach-athlete relationship assess its quality and content. A team of researchers over the last decade has concentrated on (a) developing a theoretical network involving propositions that concern the coach-athlete relationship, (b) linking the concept of the coach-athlete relationship and the constructs of which it is comprised to its developed questionnaires, and (c) relating the concept of the coach-athlete relationship to other relevant constructs (see, e.g., Jowett, 2003; Jowett & Chaundy, 2004; Jowett & Meek, 2000; Jowett & Ntoumanis, 2004). Based broadly on interdependence theory (Kelley & Thibaut, 1978), the concept of the coach-athlete partnership has been defined as the situation in which the coach and the athlete develop interconnected feelings, thoughts, and behaviors (see Jowett, 2005, 2007a). This definition has provided a platform from which an integrated conceptual model has been developed to represent the multifaceted nature of the dyadic coach-athlete relationship. The model is comprised of three interconnected constructs: closeness (emotions), commitment (thoughts), and complementarity (behaviors) (3 Cs; Jowett, 2007). The interpersonal construct of closeness represents coaches and athletes affective ties, such as liking, respecting, trusting, and appreciating each other. Commitment describes a cognitive attachment and a long-term orientation toward one another. Finally, complementarity reflects coaches and athletes behavioral transactions of cooperation, responsiveness, and affiliation. The postulated interconnections between these constructs imply that, not only, for example, a member s 3 Cs are interrelated (e.g., an athlete s closeness is linked to his/her commitment), but also a member s 3 Cs are interrelated to the other member s 3 Cs (e.g., an athlete s closeness is linked to his/her coach s closeness) in a dyadic relationship.
3 36 JOWETT A fourth construct has recently been introduced: namely, co-orientation (see Jowett, 2005, 2006, 2007). Co-orientation captures coaches and athletes intersubjective experiences and interperceptions. Jowett (2006) has explained that coaches and athletes are capable to perceive their relationship from two different perceptual perspectives, both of which can define the quality and, in turn, functions of the coach-athlete relationship. The direct perspective reflects a relationship member s (e.g., an athlete s) perception of personal feelings, thoughts, and behaviors relative to the other member (e.g., I like my coach ). Whereas the meta-perspective reflects a member s (e.g., an athlete s) perception of how the other member (e.g., coach) in the relationship feels, thinks, and behaves toward him/her (e.g., My coach likes me ). The different combinations of these perspectives can yield three distinct dimensions of co-orientation: (a) actual similarity (i.e., a combination of an athlete s or a coach s direct perspectives), (b) assumed similarity (i.e., a combination of an athlete s or a coach s direct perspective with their metaperspective), and (c) empathic understanding (i.e., a combination of an athlete s direct perspective with his/her coach s meta-perspective or a coach s direct perspective with his/her athlete s meta-perspective (see Jowett, 2007, for details). One basic goal in building the nomological network is to make sure all of the relevant constructs of the concept under study are identified. Toward that end, a series of qualitativebased research studies (e.g., Antonini Philippe & Seiler, 2006; Jowett, 2003, 2008b; Jowett & Cockerill, 2003; Jowett & Frost, 2007; Jowett & Meek, 2000; Jowett & Timson-Katchis, 2005) have provided evidence of the prevalence and content of the constructs of closeness, commitment, complementarity, and co-orientation (3 + 1 Cs model) in the coach-athlete relationship. This research has also revealed potential antecedent (e.g., social support, communication, relationship rules), moderating (e.g., race, gender, typical vs. atypical relationships), and dependent variables (e.g., satisfaction, conflict) that are associated with the coach-athlete relationship (i.e., its nomological network). The findings from the qualitative research contributed to creating an instrument that measures quantitatively the quality of the coach-athlete relationship. Two versions of the Coach- Athlete Relationship Questionnaire (CART-Q) have been developed (see Jowett, in press; Jowett & Ntoumanis, 2004). One version measures coaches and athletes direct closeness, direct commitment, and direct complementarity, while the other version measures coaches and athletes meta-closeness, meta-commitment, and meta-complementarity. Jowett and colleagues (e.g., Jowett, in press; Jowett & Clark-Carter, 2006; Jowett & Ntoumanis, 2004) studies tested the factorial validity of the CART-Q using confirmatory factor analyses. The findings provided evidence that the empirical relationships of the 3 Cs matched the theoretically postulated conceptual representation of the constructs, thus confirming that the 3 Cs are distinct entities yet interconnected aspects of the coach-athlete relationship. Guided by interdependence theory (Kelley & Thibaut, 1978), Jowett (2007) has hypothesized that coaches and athletes would experience more positive outcomes, such as personal and interpersonal satisfaction the more interdependent they are (i.e., the higher the levels of the 3 Cs). A number of studies have established links between the 3 Cs and satisfaction variables. For example, Jowett and Ntoumanis (2004) have revealed that athletes and coaches direct closeness (b = 0.37, p < 0.01) and direct complementarity (b = 0.36, p < 0.01) were predictive of satisfaction with the coach-athlete relationship. Moreover, Jowett (in press) has shown that athletes meta-closeness (b = 0.32, p < 0.04) and coaches meta-commitment (b = 0.36, p < 0.01) were predictive of satisfaction with performance, while athletes and coaches meta-complementarity (b = 0.25, p < 0.01
4 CRITERION VALIDITY OF THE CART-Q 37 for athletes and b = 0.34, p < 0.01 for coaches) were predictive of satisfaction with personal treatment. Jowett and Don Carolis (2003) have also found that direct commitment was a common relationship aspect that contributed to both male and female athletes satisfaction with training (b = 0.58, p < 0.01 for males and b = 0.30, p < 0.05 for females). However, direct complementarity was predictive of only female athletes satisfaction with performance accomplishments (b = 0.59, p < 0.01). These research studies highlight the role of coach-athlete relationships in terms of positive affective outcomes such as satisfaction and provide initial evidence for the unique contribution the 3 Cs make to specific dependent variable measures. Efforts continue to develop the nomological network of the coach-athlete relationship on the premise that an interdependent relationship is likely to produce positive outcomes as opposed to negative ones. Numerous studies have been conducted that establish links between the coachathlete relationship and such constructs as perceived coach motivational climate (Olympiou, Jowett, & Duda, in press), multiple achievement goals (Adie & Jowett, in press), physical selfconcept (Jowett, 2008a), interpersonal perceptions (Jowett & Clark-Carter, 2006), and team cohesion (Jowett & Chaundy, 2004). Research findings demonstrate positive links between interdependent coach-athlete relationships and positive outcomes (e.g., cohesion, task motivational climate) and negative links between interdependent relationships and negative ones (e.g., ego motivational climate, performance avoidance goals). Overall, this research program broadens the nomological network of the coach-athlete relationship while validating the various predictions set and, in turn, the claim that the CART-Q (both versions) measures the intended concept and its constructs. As Cronbach and Meehl (1955) would have put it, these findings provide a glimpse toward defending the judgment that the CART-Q (direct and meta-perspective versions) and its whole interpretative system is valid at some level of confidence. This research study aims to develop further the nomological network of the coach-athlete relationship. No research to date has focused on validating the direct and meta-perspective versions of the CART-Q using student-athlete participants. Thus, in this research, this issue of sampling was addressed in the context of establishing links between the 3 Cs and outcome variables that contain both positive and negative relationship aspects. The 3 Cs were measured via the direct and metaperspective versions of the CART-Q, and depth, support, and conflict representing positive and negative relationship aspects were measured via the Quality Relationship Inventory (QRI; Pierce, Sarason, Sarason, Solky-Butzel, & Nagle, 1997). Based on previous research, it is hypothesized that the 3 Cs would be (a) positively associated with the QRI s positive relationship aspects of depth and support, and (b) negatively associated with the QRI s negative relationship aspect of conflict. QRI has been extensively used with other types of relationships, including familial, romantic, and friendships; however, it has not been used to measure depth, support, and conflict in the coach-athlete relationship. Subsequently, this research study contained two studies, both of which employed independent samples of student athletes. Study 1 examined the psychometric properties (factorial validity and reliability) of the QRI, while Study 2 examined the degree to which the 3 Cs are associated with depth, support, and conflict in a conceptually coherent manner. STUDY 1 The Quality of Relationships Inventory (QRI; Pierce et al., 1997) has been developed to measure two positive and one negative relationship aspects: social support (provisions of support), depth
5 38 JOWETT (significance of relationship), and interpersonal conflict (expressions of anger and uncertainty that accompany conflict). The QRI has been developed as a measure that can be used for any interpersonal relationship type. Pierce et al. (1997) stated that in developing the QRI..., we sought to avoid linking the assessment of a particular facet of personal relationships to a specific relationship category (p. 355). Since its development, QRI has been extensively used to investigate such diverse personal and social relationships as parent-child, husband-wife, romantic relationships, and peer relationships (see, e.g., Pierce et al., 1997; Sarason, Pierce, Sarason, & Bannerman, 1993). Although Pierce et al. (1997) have claimed that the QRI has accumulated sufficient evidence over the years to make it a reliable and valid measure of diverse relationship contexts (Pierce et al., 1997), the QRI has never been used in the coach-athlete relationship context. Before the QRI s purported constructs of support, depth, and conflict can be used in relationship research in sport, its psychometric properties namely, reliability (internal consistency) and validity (factorial structure) need to be established. These were examined employing a sample of student athletes in Study 1. Methods Participants A total of 192 athlete-students (73 males and 119 females) from a large British University with a reputation for its sport achievements participated in the first study. The age of the participants ranged from 18 to 23 (M = 19.45, SD = ±1.01) years old. The participants reported to have a working partnership with their current coach that ranged between three months and 17 years (M = 2.23, SD = ±2.68). It was further reported that participants represented one of several team (N = 120) and individual (N = 72) sports, including athletics, badminton, basketball, canoe slalom, cricket, cycling, football, golf, gymnastics, hockey, lacrosse, martial arts, netball, rowing, rugby, swimming, tennis, and volleyball. Involvement with the specific sport ranged from 5 months to 19 years (M = 8.73, SD = ±3.88). Sport was played at different performance levels and varied from recreational (N = 5), university (N = 40), club (N = 30), county (N = 33), regional (N = 20), national (N = 30), and international (N = 33). (One participant did not report level of performance.) Instrumentation The Quality of Relationships Inventory (QRI; see Pierce et al., 1997) is a self-report instrument that was developed to assess the quality of different types of personal and social relationships along three dimensions: namely, support, conflict, and depth. The original QRI consists of 25 items of which 7 items measure social support defined as the general forthcomingness of the social environment, 6 items measure depth defined as the importance of the relationship in the participant s lives, and 12 items measure conflict defined by the angry and ambivalent feelings that frequently accompany conflict in relationships. A modified version of the QRI was employed for this study. A close examination of the original QRI items indicated that 7 items were irrelevant, inappropriate, or repetitive. For example, the item How much do you depend on this person (your coach)? is an item that represents the depth subscale and defines the significance of the
6 CRITERION VALIDITY OF THE CART-Q 39 relationship; thus, this item has positive connotations. However, in the context of the coachathlete relationship, this item can potentially be misconstrued as a negative item whereby depending on the coach is viewed as thwarting athletes autonomy, and so their actions are experienced as controlled by their coaches (cf. Deci & Ryan, 2000). In the conflict subscale, four items were eliminated. For example, How critical of you is this person (your coach)? and How often does this person try to control or influence your life (in sport)? are items that can be confused with positive characteristics of the coach-athlete relationship. It may be that coaches who are viewed as critical and influential by at least some of the athletes contribute to experiencing and perceiving the relationship dynamics as more positive and less negative or conflictual. Finally, two items, one from the support subscale and one from the conflict subscale, were not included because they appeared to repeat information covered in other items within their respective subscales (e.g., To what extent can you count on this person (your coach) to give you honest feedback, even if you might not want to hear it? and How much does this person (your coach) make you feel guilty? ). Subsequently, a total of 18 items were included in the modified QRI to represent the main dimensions of the coach-athlete relationship in terms of social support (e.g., To what extent could you turn to your coach for advice about problems? ), depth (e.g., How positive a role does your coach play in your sporting life? ), and conflict (e.g., How often do you need to work hard to avoid conflict with your coach? ). Each dimension contained 6 items and recorded satisfactory scores of internal consistency for social support 0.79, depth 0.83, and conflict The response scale ranged from 1 (not at all) to 4 (very much). Procedures A test administrator supplied brief descriptions of the main aims of the study to year-one and year-three students and highlighted the voluntary and confidential nature of the study. The two criteria for participation were then explained: (a) students had to participate regularly in a single sport, and (b) students had to have a coach. A pack was then administered to the students who met both criteria. The pack contained an informed consent form, instructions for completion of the questionnaire (e.g., express your thoughts relative to your relationship with your coach as honestly as you can), and the questionnaire itself. The questionnaire took, on average, 10 minutes to complete. The study received ethical approval from the University s Ethical Advisory Committee. Data Analysis Descriptive statistics were calculated to assess the mean and standard deviation values of each item and dimension. Confirmatory factor analysis was then conducted to assess the purported three-dimensional structure of the 18-item QRI. The analysis was conducted using EQS 6 (Bentler & Wu, 2002). The parameters were estimated by analyzing the covariance matrix with the robust maximum likelihood estimation method. Evaluation of the three-dimensional model that encompasses social support, depth, and conflict was conducted by utilizing the twoindex presentation strategy proposed by Hu and Bentler (1998). The two-index presentation strategy involves the use of the standardized root mean square residual (SRMR) alongside either the comparative fit index (CFI), the root mean square error of approximation (RMSEA), the Tucker-Lewis index (TLI), or relative non-centrality index (RNI).
7 40 JOWETT The SRMR and the CFI were selected. The use of the SRMR has been considered to be a superior index because it is able to discriminate well-fitting models (Hu & Bentler, 1998); the SRMR measures the discrepancy between observed and predicted covariances. The CFI was selected as the second goodness-of-fit index for this study because it has been viewed as fairly resistant against the violation of the assumption of multivariate normality (West, Finch, & Curran, 1995). The CFI has the capacity to indicate the level of the model fit when compared with a completely independent model (Bentler, 1990). For the SRMR, cutoff values of 0.08 have been recommended as acceptable (Hu & Bentler, 1999). A model with CFI above.90 is sufficient (Bentler & Bonett, 1980); however, an index above.95 is thought to be superior particularly when a single index is used for model evaluation (Hu & Bentler, 1999). In addition, the squared multiple correlation (R 2 ) for individual items was used to assess whether each item was measured adequately. Values R 2 less than 0.50 mean that more than half of an item s variance is unique and thus unexplained by the factor it is specified to measure; values can range from 0 (no effect) to 1 (all item variance is explained) (Kline, 1998). Results Descriptive Statistics Table 1 presents means and standard deviation scores. The correlations between the QRI subscales were as follows: social support and conflict was correlated negatively (r = 0.13, p = 0.04), while the correlation between social support and depth was positive (r = 0.70, p = 0.01). The correlation between depth and conflict was not significant (r = 0.02, p = 0.09). Assessment of overall model fit and individual items. Overall, both goodness-of-fit indices suggested that the data fit the three-dimensional model of social support, depth, and conflict well. (Alternative models were tested, including a unidimensional and a two-dimensional model, but these yielded unsatisfactory or inferior fit to the data.) Specifically, the CFI value was 0.94 and the SRMR value was 0.08 (χ 2 (129) = , p < 0.00), both of which reached the acceptable recommendations. Assessment of the fit of individual items, as examined by the R 2 (see Table 1), suggested that the majority of the items were adequately measured. However, there were some items that recorded low variances. For example, an item from the social support dimension was If you wanted to do something different in a training session, how confident are you that your coach would be willing to do something with you? an item from the depth dimension was How responsible do you feel for the happiness and satisfaction that your coach receives from coaching, or sport, more generally? and an item from the conflict dimension was How upset does your coach sometimes make you feel? Factor loadings were at least 0.40 and t-values (the parameter estimate divided by the standard error) were above 1.96, suggesting that each item was adequately measured with the exception of two items. The items with low factor loadings were How often do you need to work hard to avoid conflict with your coach? and If you wanted to do something different in a training session, how confident are you that your coach would be willing to do something with you? Factor loadings and errors are displayed in Table 1. Finally, significant correlations among the three dimensions of the model were recorded: social support and conflict 0.43, depth and social support 0.81, and conflict and depth
8 CRITERION VALIDITY OF THE CART-Q 41 TABLE 1 Means, Standard Deviations (Descriptive Statistics), Squared Multiple Correlation Values, and Factor Loadings for Confirmatory Factor Model Study 1 Study 2 QRI Items/Dimensions Mean SD Loadings (Errors) R 2 Mean SD Loadings (Errors) R 2 Social Support To what extent could you turn to your (.60) (.64) 0.59 coach for advice about problems? 2. To what extent could you count on your (.60) (.62) 0.62 coach forhelp with a problem? 3. To what extent can you count on your (.72) (.71) 0.49 coach to helpyou if a family member very close to you died? 4. If you wanted to do something different (.95) (.82) 0.32 in a trainingsession, how confident are you that your coach would be willing to do something with you? 5. To what extent can you count on your (.81) (.81) 0.43 coach to listento you when you are very angry at someone else? 6. To what extent can you really count on your coach todistract you from your worries when you feel under stress? (.79) (.55) 0.42 Depth How positive a role does your coach (.68) (.65) 0.58 play in yoursporting life? 8. How positive a role does your coach (.62) (.65) 0.57 play in your life generally? 9. How significant is this relationship (.66) (.69) 0.51 in your sportinglife? 10. How close will your relationship be (.75) (.83) 0.35 with your coachin two to three years? 11. How much would you miss your coach (.73) (.75) 0.45 if the two ofyou could not see or talk with each other for a month? 12. How responsible do you feel for the happiness (.90) (.91) 0.14 andsatisfaction that your coach receives from coaching, or sport, more generally? Conflict How often do you need to work hard (.96) (.91) 0.17 to avoid conflict with your coach? 14. How upset does your coach sometimes (.86) (.80) 0.35 make youfeel? 15. How much would you like your (.72) (.80) 0.36 coach to change? 16. How angry does your coach make you feel? (.40) (.51) How much do you argue with your coach? (.83) (.90) How often does your coach make you feel angry? (.50) (.55) 0.69
9 42 JOWETT Discussion The results of Study 1 highlight the modified QRI s merits as an appropriate instrument to investigate the three dimensions of depth, support, and conflict in the coach-athlete relationship. The internal consistency of the three dimensions were satisfactory, and its factorial structure, assessed by employing confirmatory factor analysis, illustrated its multidimensional nature. The three first-order factor models recorded satisfactory goodness-of-fit indices with significant factor loadings that ranged from moderate to high in size. It should be noted, however, that a small number of items recorded relatively low factor loadings and low squared multiple correlations (R 2 ), implying that these items variance is unique and unexplained by the dimension it is designated to measure. These findings may need to be monitored in subsequent studies. The CFA indicated that the associations among the three dimensions of the QRI were moderate to high. The associations between these dimensions are consistent with previous research studies that have shown that conflict is moderately and negatively related to both the availability of support and depth or the importance of the relationship in one s life, whereas support and depth are strongly and positively related constructs (see Pierce, Sarason, Sarason, 1991; Pierce et al., 1997). Overall, these results provide factorial validity evidence for the 18-item QRI in the context of the coach-athlete relationship. However, more validation studies are required to assess whether the constructs contained in the QRI are adequately represented, relevant, and practical. STUDY 2 The main aim of this study was to elaborate and extend the nomological network of the coachathlete relationship by demonstrating links between the 3 Cs using both versions of the direct and meta-perspective of the CART-Q and other variables of interest. In this study, the variables of interest were depth, support, and conflict of the QRI. First, the psychometric properties of the CART-Q and the QRI were examined with an independent sample of student athletes. Subsequently, the research aim was to investigate whether the 3 Cs of the CART-Q (both versions) are associated with the QRI dimensions of depth, support, and conflict in a conceptually meaningful way. Specifically, the hypotheses tested were as follows: (a) if student athletes perceive the relationship with the coach to be interdependent (the higher the levels of 3 Cs), they would attach more significance (depth) to the coach-athlete relationship and would feel more supported by the coach; and (b) if student athletes perceive the relationship with the coach to be interdependent (the higher the levels of 3 Cs), they would experience less anger and uncertainty in conflictual situations. Methods Participants British student athletes (N = 221; 115 males and 69 females) from a University that has a strong sport ethos participated in the study. The participants age ranged from 17 to 27 (M = 18.5, SD = ± 0.92) years. Sports represented included both team (N = 152) and individual (N = 69) sports, including athletics, badminton, basketball, boxing, cricket, football, hockey, lacrosse,
10 CRITERION VALIDITY OF THE CART-Q 43 netball, martial arts, rugby, swimming, tennis, and trampolining. It was reported that the participants involvement with their designated sport ranged from 1 month to 18 years (M = 18.14, SD = ± 3.74), while the duration of the relationship with their current coach ranged from 1 month to 15 years (M = 3.66, SD = ± 2.35). The level at which the participants performed was as follows: recreational (N = 16), university (N = 30), club (N = 53), county (N = 42), regional (N = 34), national (N = 30), and international (N = 16). Instrumentation The 18-item Quality of Relationships Inventory (QRI) for the coach-athlete relationship was employed to measure social support, depth, and conflict. The dimension of social support is measured by six items and is defined as the relationship that is characterized by such qualities as helpfulness, accommodativeness, and cooperativeness (e.g., To what extent could you count on your coach for help with a problem? ). The dimension of depth is also measured by six items and reflects the importance of the relationship in the athletes lives (e.g., How close will your relationship be with your coach in two to three years? ). Finally, the dimension of conflict is measured by another six items and is defined by the angry and ambivalent feelings that accompany interpersonal conflict between the athlete and his/her coach (e.g., How upset does your coach sometimes make you feel? ). The internal consistency with this sample was for social support 0.82, depth 0.80, and conflict The response scale ranged from 1 (not at all) to 4 (very much). The direct perspective version of the 11-item Coach-Athlete Relationship Questionnaire (CART-Q; Jowett & Ntoumanis, 2004) and its corresponding meta-perspective version (see Jowett, in press) were employed to measure three positive dimensions of the relationship: namely, closeness, commitment, and complementarity. Closeness measures the level to which the athlete likes and approves of his/her coach and the level to which the athlete trusts, respects, and appreciates the coach (e.g., I trust my coach ). Commitment measures the willingness to sacrifice and stick with the coach during ups and downs (e.g., I am committed to my coach ). Complementarity assesses the athletes behaviors that are corresponding, helpful, and supportive (e.g., In training, I am responsive ). Closeness contains 4 items, commitment 3 items, and complementarity 4 items. Athletes beliefs regarding how their coaches perceive them in the dyadic coach-athlete relationship are termed as meta-closeness (e.g., My coach likes me ), meta-commitment (e.g., My coach is committed to me ), and meta-complementarity ( In training, my coach is responsive ). These perceptual orientations can reveal diverse relationship dynamics and interpersonal situations (e.g., Jowett, 2006, 2007). The corresponding meta-perspective version of the CART-Q (Jowett, 2007) was used to measure student athletes beliefs. The internal consistency of the direct and meta-perspective subscales with this sample was direct closeness 0.87, direct commitment 0.78, direct complementarity 0.85, meta-closeness 0.90, meta-commitment 0.82, and metacomplementarity The response scales for the direct and meta-perspectives ranged from 1 (strongly disagree) to 7 (strongly agree). Procedures The procedures for recruitment and administration were similar to those outlined in Study 1. A test administrator supplied brief descriptions of the main aims of the study to year-one
11 44 JOWETT students, highlighted the voluntary and confidential nature of the study, and explained the criteria for participation. A pack was then administered to the students at the end of a lecture. The pack contained an informed consent form, instructions for completion of the questionnaire (e.g., express your thoughts relative to your relationship with your coach as honestly as you can), and the questionnaire itself. The questionnaire took, on average, 15 minutes to complete. The study received ethical approval from the University s Ethical Advisory Committee. Data Analysis Descriptive statistics were performed to assess the mean and standard deviation values of the dimensions of the two instruments. Following the descriptive statistical analyses, a confirmatory factor analysis was conducted to assess the purported three-dimensional structures of the QRI and the CART-Qs (direct and meta-perspectives). The analyses were conducted using EQS 6 (Bentler & Wu, 2002). As in Study 1, in Study 2 the model parameters were estimated by analyzing the covariance matrix with the robust maximum likelihood estimation method. Evaluation of the dimensionality of the QRI and CART-Qs was conducted by using the two-index presentation strategy (Hu & Bentler, 1998). Specifically, the standardized root mean square residual (SRMR) and the comparative fit index (CFI) were used. Models with CFI approaching.95 and SRMR below 0.08 were deemed acceptable. As in Study 1, squared multiple correlation (R 2 ) for individual items were used to assess whether each item was measured adequately. Subsequently, two sets of multiple regression analyses were conducted to assess the strength of association and the variance explained by the CART-Qs (predictor variables: direct perspective and meta-perspective subscales of 3 Cs) and the QRI (outcome variables: support, depth, and conflict). Results Means and standard deviations are presented in Tables 1 and 2. The intercorrelations of the QRI dimensions were social support and conflict r = 0.30 (p = 0.00), social support and depth r = 0.69 (p = 0.00), and depth and conflict r = 0.15 (p = 0.02). The intercorrelations of the CART-Q direct perspective version were closeness and commitment r = 0.77 (p = 0.00), commitment and complementarity r = 0.72 (p = 0.00), and closeness and complementarity r = 0.77 (p = 0.00). The intercorrelations of the CART-Q meta-perspective version were r = 0.83 (p = 0.00), commitment and complementarity TABLE 2 Means and Standard Deviations of the Direct and Meta-Perspectives of the CART-Q Subscales Subscales Mean SD CART-Qs subscales Direct closeness Direct commitment Direct complementarity Meta-closeness Meta-commitment Meta-complementarity
12 CRITERION VALIDITY OF THE CART-Q 45 TABLE 3 Intercorrelations Between the QRI Subscales and the Direct and Meta-Perspective CART-Q Subscales Direct Closeness Direct Commitment Direct Complementarity Meta Closeness Meta Commitment Meta Complementarity Social Support Depth Conflict Note: Correlations are significant at the 0.05 level (2-tailed). r = 0.75 (p = 0.00), and closeness and complementarity r = 0.86 (p = 0.00). Finally, the intercorrelations between the QRI and CART-Qs dimensions are displayed in Table 3. The three-dimensional structure of the QRI tested in Study 1 was tested again in Study 2 with an independent sample. Measurement modeling results were virtually the same. The three-factor model did reproduce the data well. The reported goodness-of-fit indices were CFI = 0.94 and SRMR = 0.08 (χ 2 (129) = , p < 0.00). Table 2 displays the R2 values, which, for the majority of the items, have reached the recommended value of around 0.50, and factor loadings for all items, which, with the exception of one, reached and exceeded values of 0.40 (t-values were above 1.96). The correlations between the three dimensions of QRI were significant and moderate to high: social support and conflict 0.31, depth and social support 0.83, and depth and conflict The three-dimensional factorial structure of the CART-Q direct and meta-perspective was supported. (Alternative models, including a unidimensional and two-dimensional model, did not yield as good fit indices as the three-dimensional model.) With respect to the three-dimensional model of the direct perspective CART-Q, both CFI = 0.93 and SRMR = 0.05 (χ 2 (39) = 80.59, p < 0.00), which suggested that the model fits the data well. Table 4 displays factor loadings, errors, and R 2 values. Two items (i.e., I feel that my sport career is promising with my coach and When I am coached by my coach, I am at ease ) recorded relatively low R 2 values. Nonetheless, all items had significant loadings that exceeded 0.40 (t-values were above 1.96). The correlations among the three dimensions were as follows: direct closeness and direct commitment 0.91, direct commitment and direct complementarity 0.86, and direct closeness and direct complementarity The three-dimensional factorial structure of the CART-Q meta-perspective displayed somewhat superior goodness-of-fit indices to those recorded by the direct perspective of the CART-Q (i.e., CFI = 0.94 and SRMR = 0.04; χ 2 (39) = 85.61, p < 0.00). The factor loadings, error, and R 2 were all in order (see Table 4). The correlations among the three dimensions were as follows: meta-closeness and meta-commitment 0.95; direct commitment and direct complementarity 0.90; and direct closeness and direct complementarity Two sets of multiple regression analyses were conducted that aimed to test whether the CART-Q subscales of both the direct and meta-perspective versions predict the QRI subscales. It was hypothesised that both direct and meta-perspectives of closeness, commitment, and complementarity will positively predict social support and depth and will negatively predict conflict. Table 5 reports the results of the multiple regression analyses. It was found that 37% and 40% of the variance in social support and in depth, respectively, were accounted for by all predictors of the direct perspective. Correspondingly, it was found that between 34% and 40% of the variance in social support and in depth were accounted for by all predictors of the meta-perspective.
13 46 JOWETT TABLE 4 Factor Loadings (Errors) and Squared Multiple Correlation Values for Confirmatory Factor Model of the Direct and Meta-Perspective CART-Q CART-Q Direct Perspective CART-Q Meta-Perspective Items (direct) (meta) Loadings Loadings (Errors) R 2 (Errors) R 2 Closeness 1. I like my coach (.62) (.51) 0.74 My coach likes me. 2. I trust my coach (.56) (.55) 0.69 My coach trusts me. 3. I respect my coach (.56) (.64) 0.59 My coach respects me. 4. I appreciate the sacrifices my coach 0.73 (.68) (.64) 0.59 has experienced to improve performance. My coach appreciates the sacrifices I have experienced to improve performance. Commitment 5. I am committed to my coach (.50) (.51) 0.74 My coach is committed to me. 6. I am close to my coach (.69) (.65) 0.57 My coach is close to me. 7. I think that my sport career is 0.65 (.75) (.66) 0.57 promising with my coach. My coach believes that his/her sport career is promising with me. Complementarity In training I am at ease with my coach (.73) (.67) 0.55 My coach is at ease. 9. I am responsive to his/her efforts (.56) (.64) 0.59 My coach is responsive to my efforts. 10. I am ready to do my best (.59) (.63) 0.60 My coach is ready to do his/her best. 11. I adopt a friendly stance (.67) (.71) 0.50 My coach adopts a friendly stance. For conflict, the variance accounted for by the direct and meta- perspective predictors was 12% and 15%, respectively. The variance inflation factor (VIF) was less than 10, and the tolerance value was greater than.10 in the two sets of regression analysis conducted. Both these indices suggest that there are not serious problems of multicollinearity in the regression equations. Discussion In Study 2, the multidimensional factorial structures of the 18-item QRI and the CART-Q (direct and meta-perspectives) were first examined using confirmatory factor analysis. The goodness-of-fit
14 CRITERION VALIDITY OF THE CART-Q 47 TABLE 5 Effects of the Direct and Meta Relationship Components of the CART-Q on Depth, Support, and Conflict Depth Support Conflict Predictor R 2 adj. F b R 2 adj. F b R 2 adj. F b CART-Q Direct * * * Direct closeness * Direct commitment 0.58* 0.67* 0.04 Direct complementarity CART-Q Meta * * * Meta-closeness Meta-commitment 0.45* 0.47* 0.24* Meta-complementarity 0.20** * *p < 0.05 **p = indices used were satisfactory, supporting the three-dimensional structures of both instruments. The reliability (internal consistency) scores of all subscales were also acceptable. This provides additional factorial validity evidence for the CART-Q and the QRI. The main aim of Study 2 was to examine whether the 3 Cs of the CART-Q (both versions) predict the variables of depth, support, and conflict in a conceptually coherent manner. The hypothesized relationships between the CART-Q dimensions of the 3 Cs (direct and meta-perspectives) and QRI dimensions of support, depth, and conflict were supported. Overall, the 3 Cs were associated with and predicted positively the relationship aspects of both support and depth and predicted negatively interpersonal conflict. The findings indicate that relationships that are committed (direct; e.g., I am committed to my coach ), (meta; e.g., My coach is committed to me ), and complementary (meta; My coach is responsive ) are more likely to be supportive and significant in the student athletes life. Whereas relationships that are affectively close (direct; e.g., I like my coach ) are more likely to prevent experiencing such feelings as anger and uncertainty in conflictual situations. Although conflict is inevitable in relationships, athletes who like, respect, trust, and appreciate their coaches are less likely to experience a great deal of negative feelings that come with conflict. Finally, the findings of this study support previous studies (Jowett & Don Carolis, 2003; Jowett & Ntoumanis, 2004) that demonstrate the importance of utilising the 3 Cs as distinct (albeit interconnected) constructs. This evidence highlights that the 3 Cs are capable to provide important and specific information that would have been lost if the 3 Cs were aggregated in a single dimension. SUMMARY AND GENERAL DISCUSSION Over the last decade, a team of researchers have focused on developing and elaborating the nomological network of the concept of the coach-athlete relationship. A nomological network surrounding the concept can assist in making validity claims that a psychological test measures a construct/s (Cronbach & Meehl, 1955). The concept of the coach-athlete relationship has been defined, operationalized, and measured (see Jowett, 2007). The coach-athlete relationship and
15 48 JOWETT the properties (3 + 1 Cs) that define it, measured by the CART-Q, have been embedded within a broader interpretative framework of interdependence theory (Kelley & Thibaut, 1978). Interdependence theory has enabled researchers to formulate hypotheses and make predictions. The coach-athlete relationship has been found to relate in theoretically meaningful ways to such constructs as personal and interpersonal satisfaction, social cohesion, and motivational climate. This accumulated evidence validates the claim that the CART-Q measures the concept of the coach-athlete relationship. This research aimed to extend this work by supplying further evidence of the degree of the validity of the CART-Q in a sample of student athletes. Based on interdependence theory, this study tested the hypothesis that the 3 Cs (both direct and meta-perspective) would positively affect the outcome variables of depth (importance of a relationship) and support (availability of support) and negatively affect the outcome variable of conflict (negative feelings generated by disputes). Because these variables were contained in an instrument that was never used before in sport settings, Study 1 was conducted to test the instrument s purported three-dimensional structure. The findings demonstrated that the 18-item QRI possess satisfactory factorial structure and internal consistency in the intercollegiate sport setting. Nonetheless, more validation studies are required to assess whether the constructs and items contained in both the original and modified QRI can adequately represent and assess the quality of the coach-athlete relationship. Subsequently, Study 2 provided further factorial validity evidence of both the QRI and the CART-Q with an independent sample of student athletes. Moreover, Study 2 revealed that the direct and meta-perspectives of the 3 Cs predict the outcome variables of depth, support, and conflict in a theoretically coherent manner. These findings are consistent with theoretical postulates that highly interdependent coach-athlete relationships are predictive of good outcomes (see Jowett, 2007). Subsequently, these findings place additional confidence in the CART-Q (both versions) because it has yet again produced appropriate and expected inferences. The present findings not only suggest that both versions of the CART-Q are promising measures with which to investigate the role of coach-athlete relationships in different collegiate sports, but also indicate the utility of the 18-item QRI. The original development of the QRI was based on the interactional-cognitive model of social support (see Pierce et al., 1997). Accordingly, QRI was developed to assess supportive and positive aspects of relationships through its subscales of support and depth as well as negative aspects through its subscale of conflict. Given that interpersonal conflict is an inevitable part of relationships and there is a lack of research in this area within sport settings, the QRI s subscale of conflict supplies researchers with a measurement tool to study interpersonal conflict in the coach-athlete relationship. The recommendations for future research discussed next underline ways for building and analyzing further the nomological network of the coach-athlete relationship. First, research should examine the coach-athlete relationship at other times or occasions (preparation season vs. competition season) using diverse methods (e.g., observations, diaries, experimental). Such evidence will strengthen our confidence by establishing the limits or boundaries beyond which the interpretation of the CART-Q can (cannot) be extended. In the collegiate sport setting, for example, it would be interesting to explore the CART-Qs over time, as the demands of different seasons change, while accounting for changes occurring in student athlete education (e.g., fresher vs. finalist student/athlete). Such future research directions will provide additional evidence of the stability of the multidimensional structure of the CART-Q. Second, the level of analysis must be specified. Research investigating the coach-athlete
16 CRITERION VALIDITY OF THE CART-Q 49 relationship will need to employ level-appropriate measures (e.g., corresponding measures for the athlete and the coach) and data analytic techniques (e.g., multilevel or dyadic analysis). Third, sampling should continue to be considered in terms of sport contexts (e.g., team vs. individual sports), performance levels (e.g., club vs. collegiate vs. national and international), gender composition of coach-athlete dyads, relationship length (e.g., newly developed coachathlete dyads vs. long-term, established dyads), and culture (e.g., what might be seen as an interdependent coach-athlete relationship in United Kingdom may be seen very differently in China). Finally, the development of positive and interdependent coach-athlete relationships and, in turn, the development of interventions is another research avenue. While some coaches will not need any guidance to become skilful in building satisfying relationships with their athletes, others may need help in developing and maintaining coach-athlete relationships that are positive. It is possible that training programs or interventions that involve a straightforward set of guidelines could help coaches create relationships that are effective and successful (see Jowett & Poczwardowski, 2007). It is proposed that the development of such positive and supportive relationships must be based upon an underlying theoretical model that is valid. The Cs model of the coach-athlete relationship could serve as a platform on which to base the design of development initiatives. ACKNOWLEDGMENTS I wish to thank Victoria Chaundy and Ross Lorimer for help with the collection of data. I would also like to thank Daniel Rhind and two anonymous reviewers for their helpful feedback. REFERENCES Adie, J., & Jowett, S. (in press). Athletes meta-perceptions of the coach-athlete relationship, multiple achievement goals, and intrinsic motivation among track and field athletes. Journal of Applied Social Psychology. Antonini Philippe, R., & Seiler, R. (2006). Closeness, co-orientation, and complementarity in coach-athlete relationships: What male swimmers say about their male coaches. Psychology of Sport and Exercise, 7, Bentler, P. M. (1990). Comparative fit indices in structural models. Psychological Bulletin, 107, Bentler, P. M., & Bonett, D. G. (1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychological Bulletin, 88, Bentler, P. M., & Wu, E. J. C. (2002). EQS 6 for Windows User s Guide. Encino, CA: Multivariate Software. Cronbach, L. J., & Meehl, P. E. (1955). Construct validity in psychological tests. Psychological Bulletin, 52, Deci, E. L., & Ryan, R. M. (2000). The What and Why of goal pursuits: Human needs and the self-determination of behavior. Psychological Inquiry, 11, Hu, L., & Bentler, P. M. (1998). Fit indices in covariance structure modeling: Sensitivity to underparameterized model misspecification. Psychological Methods, 3, Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indices in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6, Jowett, S. (2003). When the honeymoon is over: A case study of a coach-athlete relationship in crisis. The Sport Psychologist, 17, Jowett., S. (2005). On repairing and enhancing the coach-athlete relationship. In S. Jowett & M. Jones (Eds.), The psychology of coaching (pp ). Leicester, UK: The British Psychological Society, Sport and Exercise Psychology Division.
17 50 JOWETT Jowett, S. (2006). Interpersonal and structural features of Greek coach-athlete dyads performing in individual sports. Journal of Applied Sport Psychology, 18, Jowett, S. (2007). Interdependence analysis and the 3 + 1Cs in the coach-athlete relationship. In S. Jowett & D. Lavallee (Eds.), Social psychology in sport (pp ) Champaign, IL: Human Kinetics. Jowett, S. (in press). Factor structure and criterion validity of the meta-perspective version of the coach-athlete relationship questionnaire (CART-Q). Group Dynamics: Theory, Research, and Practice. Jowett, S. (2008a). Moderators and mediators of the association between the coach-athlete relationship and physical self-concept. International Journal of Coaching Science, 2, Jowett, S. (2008b). Outgrowing the familial coach-athlete relationship. International Journal of Sport Psychology, 39, Jowett, S., & Chaundy, V. (2004). An investigation into the impact of coach leadership and coach-athlete relationship on group cohesion. Group Dynamics: Theory, Research, and Practice, 8, Jowett, S., & Clark-Carter, D. (2006). Perceptions of empathic accuracy and assumed similarity in the coach-athlete relationship. British Journal of Social Psychology, 45, Jowett, S., & Cockerill, I. M. (2003). Olympic medallists perspective of the athlete-coach relationship. Psychology of Sport and Exercise, 4, Jowett, S., & Don Carolis, G. (2003, July). The coach-athlete relationship and perceived satisfaction in team sports. In R. Stelter (Ed.), XIth European Congress of Sport Psychology Proceedings (pp ). Copenhagen, Denmark: Det Samfundsvidenskabelige Fakultets. Jowett, S., & Frost, T. C. (2007). Race/ethnicity in the all male coach-athlete relationship: Black footballers narratives. Journal of International Sport and Exercise Psychology. 3, Jowett, S., & Meek, G. A. (2000). The coach-athlete relationship in married couples: An exploratory content analysis. The Sport Psychologist, 14, Jowett, S., & Ntoumanis, N. (2004). The Coach-Athlete Relationship Questionnaire (CART Q): Development and initial validation. Scandinavian Journal of Medicine and Science in Sports, 14, Jowett, S., & Poczwardowski, A. (2007). Understanding the coach-athlete relationship. In S. Jowett & D. Lavallee (Eds.), Social psychology in sport (pp. 3 14).Champaign, IL: Human Kinetics. Jowett, S., & Timson-Katchis, M. (2005). Social networks in sport: The influence of parents on the coach-athlete relationship. The Sport Psychologist, 19, Jowett, S., & Wylleman, P. (2006). Interpersonal relationships in sport and exercise: Crossing the chasm. Psychology of Sport and Exercise, 7, Kelley, H. H., & Thibaut, J. W. (1978). Interpersonal relations: A theory of interdependence. New York: Wiley. Kline, R. B. (1998). Principles of practice of structural equation modeling. New York: Guilford Press. Lyle, J. (2002). Sports coaching concepts: A framework for coaches behaviour. Oxon: Routledge. Olympiou, A., Jowett, S., & Duda, J. L. (in press). The interface of the coach-created motivational climate and the coach-athlete relationship. The Sport Psychologist. Pierce, G. R., Sarason, I. G., Sarason, B. R., Solky-Butzel, J. A., & Nagle, L. C. (1997). Assessing the quality of personal relationships. Journal of Social and Personal Relationships, 14, Pierce, G. R., Sarason, I. G., & Sarason, B. R. (1991). General and relationship-based perceptions of social support: Are two constructs better than one? Journal of Personality and Social Psychology, 61, Sarason, B. R., Pierce, G. R., Sarason, I. G., & Bannerman, A. (1993). Investigating the antecedents of perceived social support: Parents views of and behavior toward their children. Journal of Personality and Social Psychology, 65, West, S. G., Finch, J. F., & Curran, P. J. (1995). Structural equation models with non-normal variables: Problems with remedies. In R.H. Hoyle (Ed.), Structural equation modeling: Concepts, issues, and applications (pp ). Thousand Oaks, CA: Sage.
18 CRITERION VALIDITY OF THE CART-Q 51 APPENDIX A 11-Item CART-Q (Direct and Meta-Perspectives) Item Note: Upper diagonal values represent correlations for the CART-Q items of the direct perspective, and lower diagonal values represent correlations for the CART-Q items of the meta-perspective. CART-Q = Coach-Athlete Relationship Questionnaire (1 4 items Closeness; 5 7 items Commitment; 9 11 items Complementarity). 18-Item QRI Item Note: Upper diagonal values represent correlations for the QRI items from Study 1 and lower diagonal values represent correlations for the QRI items from Study 2. QRI = Quality Relationship Inventory (1 6 items Depth; 7 12 items Support; Conflict).
Climate Surveys: Useful Tools to Help Colleges and Universities in Their Efforts to Reduce and Prevent Sexual Assault Why are we releasing information about climate surveys? Sexual assault is a significant
International Journal of Sports Science & Coaching Volume 4 Number 1 2009 93 It s Not What They Do, It s How They Do It: Athlete Experiences of Great Coaching Andrea J. Becker Department of Kinesiology,
Academy of Management Learning & Education, 2008, Vol. 7, No. 2, 209 221.... Experimental Analysis of a Web-Based Training Intervention to Develop Positive Psychological Capital FRED LUTHANS University
The Revised Two Factor Study Process Questionnaire: R-SPQ-2F John Biggs 1, David Kember 2 & Doris Y.P. Leung 2 1 University of Hong Kong 2 Hong Kong Polytechnic University Biggs, J.B., Kember, D., & Leung,
RATING SCALES FOR COLLECTIVE INTELLIGENCE IN INNOVATION COMMUNITIES: WHY QUICK AND EASY DECISION MAKING DOES NOT GET IT RIGHT Completed Research Paper Christoph Riedl Technische Universität München Boltzmannstr.
Journal of Applied Psychology Copyright 2008 by the American Psychological Association 2008, Vol. 93, No. 1, 84 94 0021-9010/08/$12.00 DOI: 10.1037/0021-9010.93.1.84 Me or We? The Role of Personality and
Journal of Educational Administration 39,4 308 Received December 1999 Accepted March 2000 Journal of Educational Administration, Vol. 39 No. 4, 2001, pp. 308-331. # MCBUniversity Press, 0957-8234 The current
Emotion 2011 American Psychological Association 2011, Vol. 11, No. 2, 391 402 1528-3542/11/$12.00 DOI: 10.1037/a0022575 Becoming Happier Takes Both a Will and a Proper Way: An Experimental Longitudinal
Child Development, January/February 2002, Volume 73, Number 1, Pages 287 301 Are Effective Teachers Like Good Parents? Teaching Styles and Student Adjustment in Early Adolescence Kathryn R. Wentzel This
Research report January 2010 CREATING AN ENGAGED WORKFORCE CREATING AN ENGAGED WORKFORCE FINDINGS FROM THE KINGSTON EMPLOYEE ENGAGEMENT CONSORTIUM PROJECT This report has been written by: Kerstin Alfes,
Sample Review by Micro Editor I enjoyed reading this paper, which has a number of noteworthy strengths. Understanding the boundary conditions for the psychological and behavioral effects of transformational
Computers & Education 47 (2006) 222 244 www.elsevier.com/locate/compedu The influence of system characteristics on e-learning use q Keenan A. Pituch a, *, Yao-kuei Lee b a Department of Educational Psychology,
The Emerald Research Register for this journal is available at http://www.emeraldinsight.com/researchregister The current issue and full text archive of this journal is available at http://www.emeraldinsight.com/0268-3946.htm
Support Materials Contents This resource guide has been developed to support the work of school leaders, teachers and educators who work in and with schools across Australia. guide is designed to enable
December 2009 Evaluation of Provision and Support for Disabled Students in Higher Education Report to HEFCE and HEFCW by the Centre for Disability Studies and School of Sociology and Social Policy at the
Journal of Applied Psychology Copyright 1998 by the American Psychological Association, nc. 1998, Vol. 83, No. 6, 835-852 0021-9010/98/$3.00 Enhancing Role Breadth Self-Efficacy: The Roles of Job Enrichment
CD Enclosed Second Edition A First Course in Structural Equation Modeling TENKO RAYKOV GEORGE A. MARCOULDES A First Course in Structural Equation Modeling Second Edition A First Course in Structural Equation
The RBC Foundation After-School Programs Evaluation Factor-Inwentash Faculty of Social Work University of Toronto Final Report March 2013 Faye Mishna Jenn Root Rida Abboud Joanne Daciuk Katie MacDonald
SOCIAL SUPPORT QUESTIONNAIRE Reference: Sarason, I.G., Levine, H.M., Basham, R.B., et al. (1983). Assessing social support: The Social Support Questionnaire. Journal of Personality and Social Psychology,
1 Chapter 1 PRINCIPAL COMPONENT ANALYSIS Introduction: The Basics of Principal Component Analysis........................... 2 A Variable Reduction Procedure.......................................... 2
What makes great teaching? Review of the underpinning research Robert Coe, Cesare Aloisi, Steve Higgins and Lee Elliot Major October 2014 Executive Summary A framework for professional learning This review
Chapter 3 Study Design and Methodology 3.1. Introduction This study conducted exploratory and descriptive research on the creation of a specific information technology standard to gain an understanding
DOI 10.1007/s10734-007-9065-5 Is that paper really due today? : differences in first-generation and traditional college students understandings of faculty expectations Peter J. Collier Æ David L. Morgan
Jl. of Technology and Teacher Education (2006) 14(1), 173-207 Implementing Computer Technologies: Teachers Perceptions and Practices LORI WOZNEY, VIVEK VENKATESH, AND PHILIP C. ABRAMI Centre for the Study