Antecedents and consequences of organized extracurricular activities among Chinese preschoolers in Hong Kong

Learning and Instruction 65 (2020) 101267

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Antecedents and consequences of organized extracurricular activities among Chinese preschoolers in Hong Kong

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Lixin Rena,b,∗, Xiao Zhangc,∗∗ a

Faculty of Education, East China Normal University (Shanghai, China), Tian Jia Bing 501, 3663 North Zhongshan Road, Shanghai, 200062, China Collaborative Innovation Center for Assessment towards Basic Education Quality, Tian Jia Bing 501, 3663 North Zhongshan Road, Shanghai, 200062, China c Faculty of Education, The University of Hong Kong (Hong Kong, China), Room 629, Meng Wah Complex, The University of Hong Kong, Pokfulam Road, Hong Kong b

ARTICLE INFO

ABSTRACT

Keywords: Extracurricular activities Chinese preschoolers Family socioeconomic status Mathematics skills Reading skills

Organized extracurricular activities (EAs) are an important component of the microsystem that impacts children's lives. Previous literature has primarily focused on school-aged children and youth in Western societies. This study utilized a longitudinal design and examined the antecedents and consequences of extracurricular participation in a sample of 194 Hong Kong Chinese preschoolers. The results showed that higher family socioeconomic status (SES) predicted higher levels of participation in EAs (e.g., attendance intensity and the breadth of participation). Children from higher-SES families were more likely to involve in non-academic-oriented EAs. Participation in EAs was generally associated with the growth trajectories of reading and math skills in children from less advantaged SES backgrounds, but not higher-SES children. In contrast, EA participation was not associated with children's social skills. Findings highlight the importance of examining the relationship between EA participation and children's early development in non-Western societies.

1. Introduction According to the bioecological systems theory of human development, many settings make up the fabric of family and community life, which provides young children with resources and contexts for learning and development (Bronfenbrenner, 1979). Much research has been focused on microsystems such as family and school that directly impact children's development. However, many children today have access to learning opportunities outside both the conventional school and the immediate home environment. In this study, we examined one of these additional contexts—organized extracurricular activities (EAs).1 Over the last two decades, how children spend out-of-school hours has attracted researchers’ interest, because how this time is utilized can provide essential information about the socialization experiences of children that may contain opportunities for positive development (Larson & Varma, 1999). In the study of EAs among school-aged populations, “organized activities” is a blanket term used to describe a broad array of activities that fall outside the regular school curriculum (Bohnert, Fredricks, & Randall, 2010). In contrast to unorganized

activities that are spontaneous and informal (e.g., watching television and free play), organized EAs are “characterized by structure, adultsupervision, and an emphasis on skill-building. … [and] have regular and scheduled meetings” (Mahoney, Larson, Eccles, & Lord, 2005, p. 4). The present study focused on preschoolers in Hong Kong, where organized EAs for this age group are provided, almost without exception, by independent providers outside regular preschool, among which the majority are commercial institutions and some are public entities such as community centers. Organized EAs for preschool children in Hong Kong do not necessarily align with school curriculums, and they are usually aimed at helping children “develop competencies that are beyond the scope of training provided in schools” (Lau & Cheng, 2016, p. 9). Lau and Cheng found that Hong Kong parents enrolled preschool children in diverse EAs, with some more academically oriented and others mostly related to sports, music, and arts. We used the term “organized EAs” in this study, because similar to EAs among schoolaged populations, the EAs we examined were also formal activities that generally had regular schedules, adult supervision, accompany of peers, and well-defined learning goals.

∗ Corresponding author. Faculty of Education, East China Normal University (Shanghai, China), Tian Jia Bing 501, 3663 North Zhongshan Road, Shanghai, 200062, China. ∗∗ Corresponding author. E-mail addresses: [email protected] (L. Ren), [email protected] (X. Zhang). 1 In this article, the term “EAs” is used to refer to organized EAs. We do not spell out “organized EAs” every time when it is used for simplicity. It is clearly noted when unorganized EAs are mentioned.

https://doi.org/10.1016/j.learninstruc.2019.101267 Received 20 July 2018; Received in revised form 22 September 2019; Accepted 24 September 2019 0959-4752/ © 2019 Elsevier Ltd. All rights reserved.

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Research on EAs has been primarily centered on school-aged populations in Western societies. Despite the increasing popularity of EAs in Chinese society, research on EAs is scarce (Chiu & Lau, 2018). In this study, we aimed to examine the antecedents (i.e., child gender, family SES, and prior achievement) and the consequences of EA involvement for the development of mathematics, reading, and social skills in a group of Chinese preschoolers from Hong Kong. Informed by findings on the interplay between EA participation and family SES in relation to school-aged children's development (e.g., Covay & Carbonaro, 2010; Marsh & Kleitman, 2002), we further examined whether family SES moderated the relations between EA participation and child outcomes. Such data are important because they will not only offer insights into EA participation in a non-Western context but also help reveal whether findings discovered among school-aged children and youth on the subject of EAs apply to preschool-aged children. In addition, since EAs in Chinese societies are primarily a market-driven industry (Karsten, 2015), empirical research is needed to support the public's awareness of the impact of EAs and to inform policy makers about the need to regulate the EA industry.

more financial resources are being spent on fewer children, and meanwhile the increasing global competition contributes to rising standards for children's personal achievement (Karsten, 2015). Karsten's ethnographic study suggests that contemporary Hong Kong parents are driven by the belief that “they have to invent a new childhood in a global and competitive city, one that requires a significant investment of time, energy, and money for the development of children's skills” (p. 567), which contributes to the prevalence of EAs in Hong Kong. Hong Kong's school system may also partly contribute to the flourish of EAs among young children. Although children have equal opportunities to enter most primary schools (e.g., government schools and aided schools) through the “Primary One Admission System” where candidates are randomly allocated without an interview, getting into some quality elementary schools (e.g., direct subsidy scheme schools, private independent schools, and international schools) is highly competitive: many children have to attend interviews where they need to demonstrate superior cognitive and noncognitive skills to stand out among the applicants. In Lau and Cheng's (2016) interviews with Hong Kong parents, some parents (9.5%) considered EAs as a way to increase their child's competitiveness in elementary-school admission process. However, it is worth noting that the concern for academic success is not the sole motive for Hong Kong parents to arrange EAs for young children. A recurring theme in Lau and Cheng's study was that parents wished to cultivate a broad range of competencies in their children through EAs, such as language skills, interpersonal competence, and self-confidence. Despite many parents' positive beliefs and attitudes toward EAs, some parents in Hong Kong are also concerned that a hectic schedule of EAs may elicit too much pressure for their children (Karsten, 2015) or inhibit children's intrinsic motivation for learning (Lau & Cheng, 2016). However, little empirical evidence is available about the potential benefits and harms of EAs for young children in China.

1.1. Theoretical framework This study is grounded in Bronfenbrenner's (1979) bioecological systems theory. The theory defines five environmental systems, among which microsystems are the ones that children most closely and frequently interact with. A microsystem refers to “the complex of relations between the developing person and environment in an immediate setting containing that person,” and a setting is defined as “a place with particular physical features in which the participants engage in particular activities in particular roles … for particular periods of time” (Bronfenbrenner, 1977, p. 514). Ample research has revealed how characteristics of various microsystems shape children's prospects, including home, school, and neighborhood (e.g., Bornstein & Bradley, 2003; Burchinal et al., 2008; Coulton & Korbin, 2007). However, little research has attended to the microsystem of EAs among preschool-aged children and how it affects young children's development (Chiu & Lau, 2018; Lau & Cheng, 2016). The current study aimed to enhance our understanding of what role the EA microsystem might play in young children's development. In addition, the bioecological systems theory emphasizes the interplay between microsystems (Bronfenbrenner, 1979), and our examination of the interaction effect of EA participation and family SES on child outcomes represents an effort to uncover how the EA and home microsystems are interrelated in relation to child development: do they compensate for or reinforce the role of each other? If children from less advantaged households are found to reap greater benefits from EA participation, then we may conclude that EA participation compensates for disadvantages within the family microsystem. If children from higher-SES families are benefited more from EAs, it will indicate that participating in EAs intensifies the role of family SES in child development.

1.3. Antecedents of participation in EAs Many factors can contribute to children's EA participation. Existing research has mainly focused on the effects of demographic variables. School-aged children and youth from higher-SES backgrounds were consistently found to have higher levels of EA participation (Dumais, 2006; Fredricks, 2012; Lareau, 2011). EA participation also varies by child gender, although the findings are mixed. Some studies showed higher levels of EA involvement for girls (e.g., Anderson, Funk, Elliott, & Smith, 2003), while others demonstrated opposite findings (e.g., Knifsend & Graham, 2012) or no gender differences (Chen, 2015; Mahoney, Cairns, & Farmer, 2003). In addition, Fredricks (2012) reported that high school boys participated in more activity domains than girls, but girls were found to spend more time in EAs. It seems that the effect of gender on EA participation may depend on how participation is assessed and the age of the children. Nevertheless, in the Chinese context, Chen (2015) and Chiu and Lau (2018) did not find gender differences in preschoolers' breadth of participation or total number of EAs. In addition to demographic factors, we examined whether children's prior achievement in reading and mathematics would influence their EA participation in this study. We found no existing evidence on the link between children's prior achievement and their subsequent EA participation, a gap which will be filled by this study. Lau and Cheng (2016) reported that cultivating children's skills and enhancing their areas of weakness were among the main reasons for Hong Kong parents to enroll preschoolers in EAs. Thus, we speculated that parents might purposefully select EAs to cultivate skills that they considered necessary for their children to improve on or excel in.

1.2. EAs in the Chinese context EAs have become increasingly prevalent among young children in China. According to a survey of parents from 12 cities across mainland China, 65.6% of the children aged 3–6 years participated in EAs (Yi, 2013). Similar trends have been observed in Hong Kong and Taiwan as well (Chen, 2015; Lau & Cheng, 2016). The pervasiveness of EAs may be partially driven by the cultural value on the role of parents in providing “condition” for children's learning from an early age to lay the foundation for their future success (Lau, Li, & Rao, 2011). The current study took place in Hong Kong, a sociocultural context that is quite different from Western societies. Hong Kong is a highly urbanized international city with almost 7.4 million inhabitants. Due to the shrunken family size and the increase of dual-income households, 2

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1.4. EA participation in relation to academic and psychosocial outcomes

focus of the activity itself. For instance, involvement in sports and organized clubs was found to be associated with positive academic and noncognitive skills in children and youth (e.g., Broh, 2002; Covay & Carbonaro, 2010; Denault, Poulin, & Pedersen, 2009; Dumais, 2006). Participation in dance lessons and school music groups were positively related to children's mathematics and reading achievement (Broh, 2002; Dumais, 2006). The idea that participation in one type of EAs can have positive carryover effects on multiple domains of development aligns with Marsh and Kleitman's (2002) developmental model which proposes that EA experiences can further the total development of the individual children. The developmental model views EAs as a particular set of socialization experiences that can benefit both academic and nonacademic outcomes, which has been well supported by existing evidence (see reviews by Bohnert et al., 2010 and Farb & Matjasko, 2012). Research focused on preschoolers' participation in EAs is very limited. We only located two studies that examined the relations between overall EA involvement and development in Chinese preschoolers. Specifically, Chen (2015) found no relation between children's breadth or duration of EA participation and teacher-reported school engagement among a sample of 5-6-year-old children in Taiwan. Chiu and Lau (2018) revealed positive associations between the number of EAs and school readiness among a group of Hong Kong preschoolers. However, both studies used cross-sectional designs, and the researchers measured limited aspects of EA involvement. The mixed findings also suggest a need for further examination of the effect of EAs on young children's development. Although it is important to examine the overall experience of EA participation, we also concur with the idea that different types of EAs may contain distinct developmental affordances and produce varying effects on different developmental domains (Farb & Matjasko, 2012). In the literature, researchers proposed different ways to categorize EAs: some focused on specific activities, while others used broad categories. For instance, Dumais (2006) classified EAs into six specific types, including music lessons, dance lessons, performing arts, art lessons, athletic activities, and organized clubs. She found that children's involvement in dance lessons, athletic activities, and clubs in kindergarten and first grade all contributed to their gains in reading between first and third grade, and only participation in dance lessons predicted gains in math achievement. However, none of the EAs was related to teacherrated child language arts skills. Chambers and Schreiber (2004) classified organized EAs into three broad types based on the context (inschool and out-of-school) and academic orientation (academic and nonacademic) of the activities. They showed that participation in in-school academic EAs was positively related to achievement in all subject areas among adolescent girls, whereas involvement in in-school or out-ofschool non-academic EAs was either unrelated or negatively related to achievement. Other classifications have also been used in existing studies (e.g., sports, academic EAs, and fine arts in Lleras, 2008; sports vs. non-sports in Darling et al., 2005). To summarize, there is no agreedupon categorization of EAs in the literature, and how to classify EAs largely depends on the research question and the context under study. In the current study, we collapsed EAs into two broad categories—academic- and non-academic-oriented EAs—for two reasons. First, unlike Western societies where children are mainly involved in nonacademic EAs (Dumais, 2006; Holloway & Pimlott-Wilson, 2014), academic-oriented EAs are prevalent among young children in Hong Kong (Lau & Cheng, 2016). This phenomenon aligns with existing evidence that East Asian students spend more time in academic learning both in school and out of school than their European and North American counterparts (Larson & Varma, 1999). Cultivating skills that may facilitate future academic success is one of the reasons for Hong Kong parents to enroll their young children in EAs; in contrast, educators in Hong Kong have been advocating for unstructured play and playful learning during early childhood (Lau & Cheng, 2016). In the midst of these conflicting forces, it is of great importance to understand the consequences of involvement in academic-oriented EAs during early

In determining the impact of EAs, an important issue is how to assess EA participation. To date, there is no unified measure on EA involvement. Two approaches have been utilized—assessing the overall levels of participation without differentiating the specific types of EAs and assessing different types of the activities. Both approaches are valuable, as they help answer different research questions, with the former focused on how much participation is beneficial and the later concerning about what activities are beneficial. In terms of overall EA involvement, some scholars advocated for using refined measures to capture its multidimensional nature (Bohnert et al., 2010; Simpkins, Little, & Weiss, 2004). Bohnert et al. (2010) reviewed research on youth EA involvement and proposed four dimensions to consider, namely breadth (i.e., the number of EAs or different activity contexts), intensity (i.e., the frequency or dosage of participation), duration/consistency (i.e., the number of months or years of participation/the stability of participation), and engagement (i.e., affective, cognitive, and behavioral aspects of engagement). The breadth of EAs concerns how focused or diverse the activity participation profile is (Bohnert et al., 2010). Both cross-sectional and longitudinal studies have shown that greater breadth was related to more positive academic (e.g., academic orientation in Denault & Poulin, 2009 and RoseKrasnor, Busseri, Willoughby, & Chalmers, 2006; gains in reading in Dumais, 2006; grades and school belonging in Fredricks & Eccles, 2006a) and psychosocial (e.g., reduced internalizing problems in Aumètre & Poulin, 2018; resilience, positive peer context, and reduced psychological distress in Fredricks & Eccles, 2006a; psychological wellbeing, interpersonal skills, and reduced risk behavior in RoseKrasnor et al., 2006) outcomes. Intensity is defined as the amount of exposure an individual has to EAs over a period of time (Bohnert et al., 2010). Greater attendance intensity has also been linked to development in both academic (e.g., academic orientation in Denault & Poulin, 2009; grades and educational aspiration in Marsh & Kleitman, 2002; mathematics achievement in Schuepbach, 2015) and psychosocial (e.g., social skills and reduced conduct problems in Denault & Déry, 2015; psychological wellbeing, interpersonal skills, and reduced risk behavior in Rose-Krasnor et al., 2006) domains. The duration and engagement dimensions have been less studied compared to breadth and intensity. However, emerging evidence has provided support for the benefits of continuous participation (e.g., Darling, Caldwell, & Smith, 2005; Gardner, Roth, & Brooks-Gunn, 2008) and high engagement (see a review by Bohnert et al., 2010). In explaining the benefits of EA participation for child and youth academic and psychosocial outcomes, Covay and Carbonaro (2010) postulated that EAs could enhance noncognitive skills such as approaches to learning (i.e., learning dispositions and behaviors such as attentiveness, persistence, motivation, and flexibility), which, in turn, would influence children's school achievement. This idea resonates with Stearns and Glennie's (2010) claim that EAs may provide children with opportunities “to develop prosocial peer groups and a sense of belonging, a ‘hook’ into school that may help to keep students enrolled, and increased academic achievement” (p. 296). Organized EAs resemble classroom contexts in many ways. They both have regular schedules and established rules, provide adult supervision and guidance, contain activities designed to promote given skills, and often involve similar-aged peers, which exposes participants to developmentally facilitative experiences that are both cognitively and socially stimulating (Blomfield & Barber, 2011; Covay & Carbonaro, 2010; Fredricks, 2012). The rationale behind treating EA participation as an aggregated construct is not clearly articulated in the literature. However, the findings reviewed above showed that overall EA participation was related to a broad range of academic and psychosocial outcomes, suggesting that involvement in a particular EA may facilitate children's development in various domains beyond the specific skills that are the 3

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childhood. In addition, although using detailed activity-type categories allows for more nuanced analyses, this approach absorbs a large number of degrees of freedom (Chambers & Schreiber, 2004). Collapsing EAs into a few categories is more appropriate in terms of statistical power for studies with a relatively small sample size, like the current study.

is EA participation associated with children's development of mathematics, reading, and social skills? Drawing upon the vast evidence of EA participation in promoting academic and psychosocial development among school-aged children and youth (Bohnert et al., 2010; Simpkins et al., 2004), we hypothesized that the total number, breadth, and intensity of EAs would be positively associated with children's mathematics, reading, and social skills. In addition, as the EAs participated by preschoolers are often play-based and delivered in small groups regardless of the content focus, we hypothesized that participation in both academic- and non-academic-oriented EAs would promote mathematics, reading, and social skills. Finally, do family SES moderate the relations between EA participation and child outcomes? We hypothesized that EA participation would be more beneficial for children from socioeconomically less advantaged households.

1.5. Variable effect of EA participation by family SES Although EA participation has been associated with many positive outcomes, the benefits of EAs may vary by SES backgrounds. As Covay and Carbonaro (2010) posit, for low-SES children, engagement in organized EAs can replace unorganized leisure time and provide extra opportunities for learning. In comparison, EAs may be redundant for high-SES children, as they can already access high-quality home environments that contain rich experiences and interactions fostering both cognitive and noncognitive skills. Marsh and colleague demonstrated that higher involvement in EAs benefited socioeconomically disadvantaged high school students as much as or more than students from higher-SES homes depending on the outcomes at consideration (Marsh, 1992; Marsh & Kleitman, 2002). Consistently, Covay and Carbonaro (2010) and Dumais (2006) found that lower-SES children benefited more from EAs than higher-SES children with respect to their mathematics and reading achievement. In this study, we explored whether the relations between EA involvement and Chinese preschoolers’ mathematics, reading, and social skills varied by family SES. Situated in a broader context of early intervention research, EAs may be considered as a form of intervention that parents voluntarily engage their children in. Studies on the effectiveness of early childhood care and education programs suggest that many programs showed a particular benefit for the cognitive and socialemotional development of socioeconomically disadvantaged children, while nearly no program was disproportionally beneficial for privileged children (Burger, 2010; Zhang & Chan, 2019). Thus, participation in EAs may also be more beneficial for children from less advantaged households.

2. Methods 2.1. Participants A total of 194 Chinese preschoolers (98 boys; mean age at the first measurement occasion = 41.78 ± 3.25 months) and their parents were recruited from four kindergartens in Hong Kong. Because EAs are more prevalent in middle-class than working-class or poor families in Hong Kong (Karsten, 2015), we purposefully selected preschools located in middle-class neighborhoods. Kindergarten programs in Hong Kong include three years of education serving children aged three to six years. The children were all native Cantonese speakers. This study involved four measurement occasions. At the first measurement occasion (T1), children were in the fall semester (November and December) of the first kindergarten academic year. A year later (November and December; T2), the second-wave data were collected. Then, data were collected every six months: May and June in the spring semester of the second kindergarten year (T3), and November and December in the fall semester of the third kindergarten year (T4). About 54.7% of the mothers and 61% of the fathers had a Bachelor's degree or a higher degree. About 77.3% of the families reported a monthly household income of 30,000 Hong Kong dollars (approximately 3835 US dollars) or above, while the over-all median monthly household income was 22,400 Hong Kong dollars at the time of this study (Census & Statistics Department, 2014). Thus, many participating families could be considered as middle- or upper-middle-class. Maternal education strongly correlated with paternal education (r = 0.62, p < .001). We thus used the highest education in the household to represent parental education, in order to use data on education for almost all family structures. Parental education was coded into six categories: 1 = middle school (3.8%), 2 = junior high school (17.2%). 3 = high school to associate degree (11.5%), 4 = Bachelor's degree (39.5%), 5 = Master's degree (24.8%), and 6 = Doctoral degree (3.2%). Monthly household income was also coded into six categories: 1 = below HK$10,000 (2.5%), 2 = HK$10,000−HK$29,999 (2.2%), 3 = HK$30,000−HK$49,999 (25.8%), 4 = HK$50,000−HK$69,999 (23.2%), 5 = HK$70,000−HK$89,999 (14.6%), and 6 = above HK $90,000 (13.6%). A continuous SES variable was created by averaging the standardized scores of parental education and household income.

1.6. The present study In the current study, we examined both overall EA participation and specific types of EAs. Attending to both aspects will shed light on the issue that whether it is merely participating in EAs in general or participation in certain types of EAs that is associated with positive outcomes. For overall EA participation, we assessed three dimensions, including attendance intensity, the number of EAs, and the breadth of participation (i.e., the number of different EA contexts). When examining specific types of EAs, we divided EAs into two major types—academic-oriented and non-academic-orientated. In this study, four waves of data were collected over a span of two years from a group of Chinese preschoolers and their parents in Hong Kong. We assessed three outcomes of interest longitudinally, including children's mathematics, reading, and social skills. We chose these three outcomes, because they constitute important aspects of school readiness and are crucial for children's later achievement (Duncan et al., 2007). Acquiring these school readiness skills has even been regarded as the goal of early childhood education (Zhang, Hu, Ren, Huo, & Wang, 2019). Three research questions were examined. First, how are family SES, child gender, and child prior achievement related to children's EA participation? We hypothesized that children from higher-SES backgrounds would be more likely to attend both academic- and non-academic-oriented EAs, participate in a larger number of EAs, as well as to have greater breadth and intensity of participation. Due to the mixed findings on gender differences in EA participation, we did not propose specific hypotheses regarding gender. To our knowledge, children's prior achievement has not been examined as a predictor of EA participation, and thus, no specific hypothesis was generated. Second, how

2.2. Measures and procedures At T1, parents reported demographic information. At T2, parents reported children's participation in EAs. Mothers rated their child's social skills from T2 to T4. Across all four occasions, individual tests were administered to assess children's mathematics and reading skills. The three assessments described below were selected because they are among the few available tools that can be used across a relatively wide age range and therefore appropriate for longitudinal research. Moreover, all three assessments have good psychometric properties and have been used in previous studies on Hong Kong children. The testing 4

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was conducted in Cantonese by trained testers during school hours in a quiet room. Children received a small token (e.g., pencils, erasers) as a reward for participating.

34.5%), sports (e.g., swimming lessons, gymnastics; 33.3%), math/ science (e.g., the “little scientist” program, mental calculation classes; 16.1%), and others (e.g., boy/girl scouts, attention-training classes; 10.9%) (see Appendix A). The breadth of EAs was operationalized as the number of EA contexts that a child was involved in. Because five types of contexts were coded, the possible range for breadth was 0 (i.e., non-participation) to 5. About 36.4% of the children were involved in one EA context (i.e., breadth = 1); 34.1% participated in two contexts; 13.6% engaged in three contexts; and 4.5% had four contexts. Children who did not participated in any EA received a score of zero for the number, breadth, and intensity of EAs. In examining the effects of different types of EAs, we further grouped EAs into two major categories: academic-oriented EAs included language and math/science, and non-academic-oriented EAs included arts, sports, and others. Two dummy variables were created (0 = no participation; 1 = participation). Children who did not participate in EAs received a score of zero for both “academic-oriented EAs” and “nonacademic-oriented EAs” variables. About 46.98% of the children participated in academic-oriented EAs, and about 81.21% of them participated in non-academic-oriented EAs.

2.2.1. Mathematics abilities Children's mathematics abilities were assessed using a test of arithmetic word problems that the second author developed and modeled after the story problems subtest of Jordan, Kaplan, Ramineni, and Locuniak's (2009) number competency core battery. At T1, children were asked to solve 12 word problems, including six addition problems and six subtraction problems (Cronbach's a = 0.54). For each item, children received one point for the correct answer and zero for incorrect responses. Because several children obtained full scores at T1, we developed two more addition and two more subtraction items to avoid ceiling performance from T2 to T4. The Cronbach's as were 0.79, 0.85, and 0.84 for T2, T3, and T4, respectively. The raw sum scores of correct items were used. The test has been used in Hong Kong preschoolers (Zhang & Lin, 2017) and has shown satisfactory convergent and discriminant validity. Specifically, performance in this test had significant convergent correlations with performance in nonverbal arithmetic (r = 0.539, p < .001) and that in written arithmetic (r = 0.565, p < .001). The convergent correlations were larger than the discriminant correlations that the test performance had with morphological (r = 0.084, p = .476) and visual-orthographic (r = 0.084, p = .475) skills.

2.3. Analytic plan Analyses were conducted using Mplus 7.2. The first research question focused on how family SES, child gender, and child prior mathematics and reading skills were associated with children's later participation in EAs. We used information collected at T1 to predict children's EA participation at T2. We ran a multivariate multiple regression analysis in which the attendance intensity, the number of EAs, and the breadth of participation were predicted by child age, gender, family SES, T1 mathematics skills, and T1 reading skills. We then conducted a multivariate logistic regression analysis to examine whether the aforementioned factors predicted children's participation in academicand non-academic-oriented EAs at T2. The second research question concerned the effects of EA participation on children's mathematics, reading, and social skills from T2 to T4. The use of a longitudinal design allowed us to examine the effects of EAs on both children's levels of and their rates of growth in these skills. We first used unconditional growth curve modeling to estimate the level and growth parameters of the growth trajectories of the three child outcomes from T2 to T4. Linear growth models were estimated for each outcome first, and spline models were utilized to capture nonlinear growth patterns if linear growth models resulted in poor model fit (Fan & Konold, 2009). In growth curve models, two latent factors were created: intercept and slope. An intercept represents the level of an outcome at a certain measurement occasion, and a slope reflects the rate of growth in the outcome. In all the models, we centered zero at T3, so that the intercept referred to children's levels of a certain outcome at T3. We used this approach to set up the models, in order to examine how children's participation in EAs at T2 predicted their levels of mathematics, reading, and social skills at the subsequent measurement occasion (i.e., T3). In the unconditional models, we also constrained the residual variances to be equal for model parsimony if model fit was not compromised. Once unconditional models were established, we then used conditional growth models to examine the effects of attendance intensity, the number of EAs, and the breadth of participation on children's levels of and rates of growth in mathematics, reading, and social skills. Because the three aspects of EAs were significantly correlated (rs = 0.36–0.72, ps < .001), we examined one aspect at a time to avoid collinearity. We controlled for child age, child gender, and family SES, as well as children’ mathematics or reading scores at T1, in order to better delineate the effects of EA participation. Similarly, we used conditional growth models to estimate the effects of participating in academic-oriented and non-academic-oriented EAs on children's levels of and rates of growth in all outcomes, controlling for the same set of covariates. Finally, we

2.2.2. Chinese word reading The Chinese word reading task was developed and successfully used in Hong Kong preschoolers (McBride-Chang & Ho, 2000; Zhang, 2018). It includes 61 items, among which 27 are single-character words and 34 are double-character words. The tester asked the child to read out aloud the words one by one on the list. The testing was terminated when children failed to read 10 consecutive words. The Cronbach's as were 0.97, 0.98, 0.97, and 0.96 for T1 to T4, respectively. 2.2.3. Social skills Mothers reported their children's social skills using the Social Skills subscale from the Social Skills Improvement System-Rating Scales (Gresham & Elliott, 2008). The subscale (46 items) measures multiple aspects of social skills, including communication, cooperation, assertiveness, responsibility, empathy, engagement, and self-control. Mothers rated the frequency with which their child exhibited each behavior using a 4-point Likert scale (1 = never and 4 = almost always). In this study, mothers completed the questionnaire from T2 to T4. Child social skills were not assessed at T1. The Cronbach's as were 0.94, 0.94, and 0.93 for T2 to T4, respectively. In previous research with Hong Kong children (Cheung, Siu, & Brown, 2017), the Chinese version of this subscale showed strong psychometric properties, including good Cronbach's α (0.94) and high sensitivity and specificity in differentiating children with developmental disabilities from typically developing children. 2.2.4. Extracurricular activities At T2, parents were asked to report their child's participation in organized out-of-school classes or programs over the fall semester of the second kindergarten year. Parents reported the number of hours that their child participated in EAs every week, which was used an index of attendance intensity (range = 0–8 h). Parents also reported the number of EAs (range = 0 to 5): about 9.60% of the children did not participate in any EA; 15.25% had one EA; 27.68% had two EAs; 23.16% had three EAs; 15.25% had four EAs; and 9.04% had five or more EAs. Parents were also asked to describe the contents of EAs using an open-ended question, based on which we coded the contexts of EAs. We referred to the coded categories used by Fredricks and Eccles (2006a, 2006b) and Chen (2015). EAs were coded into five types: arts (e.g., music, dancing, performing arts; 70.1%), language (e.g., English/Chinese lessons; 5

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Table 1 The Multivariate Regression Model and the Multivariate Logistic Regression Model Testing the Effects of SES, Child Gender, and Prior Mathematics and Reading Skills on Children's EA Participation (standardized coefficients with standard errors in parentheses). Variable Child Age Child Gender Family SE T1 Mathematics Skills T1 Reading Skills

Multivariate Regression Model

Multivariate Logistic Regression Model

Attendance Intensity

Number of EAs

Breadth of EAs

Academic-oriented

Non-academic-oriented

-.01 (.07) .05 (.07) .31*** (.07) .07 (.07) .06 (.06)

.01 (.07) .01 (.07) .25*** (.08) .07 (.07) .19** (.07)

.02 (.07) .19** (.07) .20* (.08) .19* (.08) .03 (.06)

-.004 (.09) .10 (.09) .06 (.09) .08 (.11) .10 (.10)

.08 (.11) .12 (.11) .26* (.11) .22 (.16) .06 (.15)

Note. Child gender was dummy coded (0 = girl, 1 = boy). Academic- and non-academic-oriented EAs were both dummy coded (0 = no participation, 1 = participation). *p < .05. **p < .01. ***p < .001.

tested conditional growth models to examine whether family SES moderated the effects of EA participation on child outcomes by adding the interaction terms between all dimensions of EA participation and family SES to the previous set of models.

final model achieved an acceptable model fit (see Appendix F for all model fit information). On average, children obtained a score of 5.56 in the mathematics assessment at T3, and they grew by 2.29 (p < .001) points every six months from T2 to T4. Children differed in their levels of T3 mathematics skills, as well as in their rates of growth, as indicated by the significant intercept variance (σ2 = 7.23, p < .001) and slope variance (σ2 = 1.63, p = .003). The linear growth pattern also fit well for social skills. Children obtained an average score of 2.76 on social skills at T3, and their social skills grew by 0.05 (p < .001) every six months. Children differed in their T3 social skills (σ2 = 0.08, p < .001) and their rates of growth in social skills (σ2 = 0.01, p = .02). However, the linear growth curve model did not fit well for reading skills. Thus, a spline model was tested to capture the potential nonlinear growth pattern (Fan & Konold, 2009). The loadings of T2 and T3 reading skills on “slope” were fixed to be −1 and 0, respectively, while the loading of T4 reading skills was freely estimated. The residual variances were constrained to be equal to have enough parameters to estimate model fit. The model achieved an acceptable fit. The loading of T4 reading skills on “slope” was 0.82, indicating that there was less growth from T3 to T4 compared to the growth between T2 and T3. In this model, “slope” represented the average rate of growth in reading skills from T2 to T3, which showed significant variance (σ2 = 20.93, p < .001). Children achieved a reading score of 33.01 on average at T3 and their reading skills increased by 11.39 (p < .001) points between T2 and T3 on average. Children's levels of reading skills at T3 also showed significant individual variability (σ2 = 189.89, p < .001).

3. Results Appendix B presents the descriptive statistics of the study variables. Appendix C presents a series of independent t-tests examining differences in mathematics, reading, and social skills between EA participating children and non-participating children. Some significant differences emerged in terms of children's mathematics and reading skills, but not social skills. Appendix D presents the correlations between EA participation and child outcomes. EA participation was associated with children's mathematics and reading skills at some measurement occasions, but not with children's social skills. Appendix E presents the correlations among children's mathematics, reading, and social skills across all measurement occasions. 3.1. Antecedents of child participation in EAs As shown in Table 1, family SES positively predicted all three dimensions of overall EA participation. Children from higher-SES families were more likely to spend more hours in EAs per week, participate in a larger number of EAs, and engage in more diverse EA contexts at T2. Boys had greater breadth of participation than girls, but boys and girls did not differ on attendance intensity or the number of EAs. We conducted additional analyses to compare across gender. Chi-square tests showed that boys were more likely to engage in sports than girls, χ2 = 9.82, p = .002, but they did not differ in participation in the other four types of EAs. One-way ANOVA showed that girls participated in more different kinds of art activities than boys, F(1) = 4.17, p = .04. Interestingly, children with better mathematics skills at T1 tended to engage in greater breadth of EAs. Children with better reading skills at T1 also engaged in a larger number of EAs. In addition, children's age, gender, and prior reading and mathematics skills were not related to their likelihood of participation in academic- or non-academic-oriented EAs. However, children from higher-SES families were more likely to participate in non-academic-oriented EAs compared to children from less advantaged SES backgrounds.2

3.3. EA participation in relation to child mathematics, reading, and social skills We examined EA participation in relation to children's outcomes using conditional growth models. All the following reported models achieved acceptable model fit (see Appendix F). Several covariates were controlled for, including T1 scores of the examined outcome (except for social skills as they were not assessed at T1), child age, gender, and family SES. As shown in Table 2, higher attendance intensity, participating in a larger number of EAs, and engaging in greater breadth of EAs all contributed to children's reading skills at T3. More importantly, higher attendance intensity also predicted more rapid growth in children's reading skills. However, participation in EAs did not contribute to children's mathematics or social skills. The models examining the effects of participation in academic-oriented and non-academic-oriented EAs on child outcomes showed that participating in academic-oriented EAs predicted better reading skills at T3 (Table 2). However, participation in academic-oriented and nonacademic-oriented EAs did not uniquely contribute to children's levels of or rates of growth in mathematics and social skills, nor did they predict children's rates of growth in reading skills.

3.2. Levels of and growth in child mathematics, reading, and social skills We first tested an unconditional linear growth curve model for mathematics skills. We fixed the loadings of T2, T3, and T4 mathematics skills on the “slope” variable as −1, 0, and 1, respectively. The 2 As described in the Participants section, the study sample was primarily composed of middle-class families. Thus, we avoided using the term “low-SES” or “lower-SES” when describing the current findings. We chose to use the term “less advantaged” instead.

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Table 2 Conditional Growth Models Testing the Effects of EA Participation on Child Outcomes (standardized coefficients with standard errors in parentheses). Variable

Intensity Model: T1 Math/Read Child Age Child Gender Family SES Intensity Number of EAs Model: T1 Math/Read Child Age Child Gender Family SES Number of EAs Breadth Model: T1 Math/Read Child Age Child Gender Family SES Breadth Academic Orientation Model: T1 Math/Read Child Age Child Gender Family SES Academic-oriented EAs Non-academic-oriented EAs

Mathematics Skills

Reading Skills

Social Skills

Intercept

Slope

Intercept

Slope

Intercept

Slope

.26* (.11) .25*** (.07) .07 (.07) .10 (.08) .03 (.08)

-.03 (.14) .11 (.14) .15 (.11) -.24 (.13) .18 (.13)

.59*** (.04) .19*** (.06) -.006 (.06) .02 (.07) .16* (.07)

-.64*** (.06) .03 (.08) -.07 (.07) .16 (.09) .20* (.09)

– -.04 (.08) -.13 (.07) .12 (.09) -.05 (.09)

– -.10 (.14) .25 (.14) .07 (.16) .13 (.15)

.25* (.11) .25*** (.07) .08 (.07) .09 (.07) .08 (.08)

-.03 (.14) .11 (.14) .17 (.11) -.24 (.13) .19 (.13)

.56*** (.04) .18*** (.06) .002 (.06) .02 (.07) .16** (.06)

-.65*** (.06) .03 (.09) -.06 (.08) .19* (.09) .12 (.09)

– -.04 (.08) -.14 (.07) .12 (.09) -.02 (.09)

– -.11 (.14) .25 (.14) .06 (.16) .16 (.15)

.25* (.11) .25*** (.07) .06 (.07) .09 (.07) .09 (.07)

-.02 (.13) .11 (.14) .16 (.11) -.19 (.12) .06 (.13)

.57*** (.04) .17** (.06) -.03 (.06) .03 (.06) .18** (.06)

-.63*** (.06) .03 (.08) -.06 (.08) .22** (.09) .02 (.09)

– -.05 (.08) -.14 (.08) .10 (.09) .03 (.08)

– -.11 (.14) .24 (.14) .08 (.16) .11 (.16)

.32*** (.10) .25** (.08) .10 (.08) .12 (.08) .04 (.08) .02 (.08)

-.16 (.16) .24 (.21) .11 (.16) -.24 (.17) -.04 (.16) -.01 (.16)

.58*** (.06) .18** (.06) -.02 (.06) .04 (.07) .15* (.06) .07 (.07)

-.67*** (.08) .10 (.09) -.10 (.08) .26** (.09) .06 (.08) -.16 (.09)

– -.05 (.08) -.13 (.08) .12 (.09) .02 (.09) .02 (.09)

– -.10 (.15) .18 (.16) .10 (.18) -.06 (.17) .06 (.18)

Note. Child gender was dummy coded (0 = girl, 1 = boy). Academic-oriented EAs and Non-academic-oriented EAs were dummy coded (0 = no participation, 1 = participation). *p < .05. **p < .01. ***p < .001. Zero was centered at T3 in the models, and therefore the intercept referred to children's levels of a certain outcome at T3.

but not among their more advantaged counterparts (B = −0.16, p = .31). Engaging in more diverse EA contexts was beneficial for less advantaged children's reading skills at T3 (B = 4.20, p < .001), but not for more advantaged children (B = 1.38, p = .21) (see Fig. 1b). Finally, we examined the interplay between family SES and children's participation in academic-oriented and non-academic-oriented EAs in relation to children's development. Only one significant interaction effect emerged. Specifically, family SES moderated the effect of children's participation in non-academic-oriented EAs on their T3 reading skills. Simple slope analyses revealed that children from less advantaged families who participated in non-academic-oriented EAs had better reading skills than their non-participating counterparts (B = 5.43, p = .03). In contrast, participation in non-academic-oriented EAs was not related to T3 reading skills in children from more advantaged SES backgrounds (B = −2.98, p = .41) (see Fig. 1b). In addition, the interaction effect of family SES and participation in academic-oriented EAs on children's slope of mathematics skills approached significance (β = −0.61, p = .07). Simple slope analyses showed that participation in academic-oriented EAs was positively associated with the rates of growth in mathematics skills among less advantaged children (B = 0.67, p = .04), whereas the relation between participation in academic-oriented EAs and mathematics growth was negative for children from more advantaged families (B = −0.79, p = .03).

3.4. Moderating role of family SES in the relations between EA participation and child outcomes Table 3 presents the results for the interaction effects between family SES and EA participation on child outcomes. Family SES significantly interacted with attendance intensity in predicting the slope of mathematics skills, as well the intercept of reading skills. We conducted simple slope analyses to better characterize the interactions. In the analyses, the relations between attendance intensity and the slope or intercept of child outcomes were observed at two levels of family SES: 1 SD above the mean (more advantaged families) and 1 SD below the mean (less advantaged families), controlling for other predictors in the models. All significant interactions were plotted in Fig. 1. As shown in Fig. 1, attendance intensity had a positive effect on the slope of mathematics skills among less advantaged children (B = 0.32, p = .01), but not among more advantaged children (B = −0.05, p = .64). Thus, more intensive participation in EAs contributed to more rapid growth in children's mathematics skills, but only for those from relatively less advantaged SES backgrounds (see Fig. 1a). Additionally, higher attendance intensity predicted better reading skills at T3, but only for children from less advantaged families (B = 2.76, p < .001), not for those from more advantaged households (B = 0.09, p = .91) (see Fig. 1b). The number of EAs had very similar patterns of effects on child outcomes to attendance intensity. Simple slope analyses indicated that, larger numbers of EAs predicted more rapid growth in mathematics skills among less advantaged children (B = 0.34, p = .01), but not among more advantaged children (B = −0.04, p = .76). Participating in more EAs was positively related to T3 reading skills among children from less advantaged households (B = 3.40, p < .001), but not among those from more advantaged families (B = −0.05, p = .95) (see Fig. 1a). Similarly, we found significant SES*Breadth interactions with respect to the slope of mathematics skills and the intercept of reading skills. According to the simple slope analyses, participating in more diverse EA contexts was associated with more rapid growth in mathematics skills among less advantaged children (B = 0.37, p = .02),

4. Discussion EAs constitute an important microsystem in which many children's development takes place. However, the role of EAs during early childhood has been overlooked, particularly among children from nonWestern societies. In the present study, we examined both the antecedents and consequences of EA participation among preschoolers in Hong Kong. The findings showed the importance of child gender, child prior achievement, and family SES for parents' choice of EAs, as well as the positive effects of EAs on children's mathematics and reading 7

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Table 3 Conditional Growth Models Testing the Interaction Effects between Family SES and EA Participation on Child Outcomes (standardized coefficients with standard errors in parentheses). Variable

Intensity Model: T1 Math/Read Child Age Child Gender Family SES Intensity SES*Intensity Number of EAs Model: T1 Math/Read Child Age Child Gender Family SES Number of EAs SES*Number of EAs Breadth Model: T1 Math/Read Child Age Child Gender Family SES Breadth SES*Breadth Academic Orientation Model: T1 Math/Read Child Age Child Gender Family SES Academic-oriented EAs Non-academic-oriented EAs Academic-oriented EAs*SES Non-academic-oriented EAs*SES

Mathematics Skills

Reading Skills

Social Skills

Intercept

Slope

Intercept

Slope

Intercept

Slope

.27* (.12) .25*** (.07) .07 (.07) .08 (.08) .04 (.08) -.09 (.08)

-.004 (.12) .09 (.14) .15 (.10) -.32* (.13) .22 (.13) -.26* (.13)

.59*** (.04) .18*** (.06) -.003 (.06) -.02 (.06) .18** (.07) -.15** (.06)

-.64*** (.06) .03 (.08) -.07 (.07) .17 (.09) .20* (.09) .02 (.10)

– -.05 (.08) -.13 (.08) .11 (.10) -.04 (.09) -.06 (.10)

– -.10 (.15) .24 (.14) .08 (.17) .12 (.15) .05 (.16)

.26* (.12) .25*** (.07) .07 (.07) .06 (.08) .09 (.08) -.09 (.08)

-.02 (.12) .10 (.14) .16 (.11) -.32* (.13) .20 (.12) -.27* (.14)

.58*** (.04) .19*** (.06) -.01 (.05) -.03 (.06) .17** (.06) -.19*** (.06)

-.64*** (.06) .03 (.08) -.06 (.08) .18* (.09) .13 (.09) -.05 (.10)

– -.04 (.08) -.14 (.07) .11 (.09) -.02 (.09) -.05 (.10)

– -.11 (.14) .25 (.14) .06 (.17) .16 (.15) .01 (.16)

.26* (.11) .25*** (.07) .06 (.07) .08 (.08) .10 (.07) -.06 (.07)

.02 (.12) .10 (.14) .14 (.11) -.25* (.12) .10 (.12) -.28* (.14)

.58*** (.04) .17** (.06) -.03 (.06) .01 (.06) .20*** (.06) -.11* (.05)

-.63*** (.06) .03 (.08) -.07 (.08) .21* (.08) .03 (.08) -.08 (.08)

– -.05 (.08) -.14 (.08) .09 (.09) .04 (.08) -.06 (.09)

– -.11 (.14) .23 (.14) .06 (.16) .13 (.17) -.07 (.17)

.34*** (.10) .25** (.08) .10 (.08) .34** (.11) .05 (.08) .02 (.08) -.15 (.11) -.14 (.12)

-.10 (.15) .21 (.20) .12 (.16) .10 (.30) .08 (.18) .02 (.30) -.04 (.16) -.61 (.34)

.59*** (.06) .19*** (.06) -.04 (.06) .31* (.12) .17** (.06) -.06 (.08) .04 (.07) -.26* (.12)

-.65*** (.08) .11 (.08) -.10 (.08) .46** (.17) .07 (.08) -.16 (.09) -.17 (.11) -.10 (.16)

– -.06 (.08) -.12 (.08) .02 (.18) .01 (.09) .07 (.09) -.16 (.12) .23 (.16)

– -.09 (.16) .17 (.16) .18 (.36) -.04 (.17) .01 (.19) .18 (.23) -.23 (.32)

Note. Child gender was dummy coded (0 = girl, 1 = boy). Academic-oriented EAs and Non-academic-oriented EAs were dummy coded (0 = no participation, 1 = participation). *p < .05. **p < .01. ***p < .001. Zero was centered at T3 in the models, and therefore the intercept referred to children's levels of a certain outcome at T3.

Fig. 1. The moderation role of family SES in the effects of EA participation on children's rates of growth in mathematics skills (a) and their T3 reading skills (b). Note. Solid lines represent the less advantaged group (1 SD below the mean of family SES) and dashed lines represent the more advantaged group (1 SD above the mean of family SES). Diamond marker represents EA intensity, square marker represents the number of EAs, triangle marker represents EA breadth, and circle marker represents participation in non-academic-oriented EAs.

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development, particularly among those from relatively less advantaged families.

EA microsystem as well as the kind of experiences in this microsystem they have access to.

4.1. Antecedents of EA participation

4.2. Impact of EA participation on child outcomes

Family SES was positively associated with children's attendance intensity, the number of EAs, and the breadth of participation in the current study, which corroborates existing evidence among school-aged children and youth (e.g., Dumais, 2006; Fredricks, 2012). Firstly, higher-SES parents may endorse scheduled activities more than parents of less advantaged backgrounds. In her ethnographic study, Lareau (2011) argued that middle-class parents expected to foster talents and a wide range of skills in their children through EAs. In addition, the robust relations between SES and EA participation may be partly due to the associated cost of EAs, particularly considering the fact that EAs in Hong Kong are mostly provided by commercial institutions. Family SES was positively correlated with the amount of money parents invested in EAs in this study (r = 0.24, p = .003). Chin and Phillips (2004) found that although working-class parents valued EAs, they often faced income and time constraints that prevented their children's involvement in EAs. Higher-SES parents possess more financial resources to invest in EAs. Also, many upper- and middle-class families in Hong Kong have domestic helpers who can help transport children to EAs (Karsten, 2015). In terms of the type of EAs, higher-SES parents more often enrolled their children in non-academic-oriented EAs (i.e., arts, sports, and others). In a study of American children, Dumais (2006) found that organized sports, art activities, and clubs had large enrollment discrepancies between lower- and higher-SES children, with higher-SES children having higher participation rates. Thus, higher-SES parents in this study might also value sports, arts, and other non-academic-focused activities more than their less advantaged counterparts, and wish to balance their child's life through enrolling children in these activities. However, family SES did not matter in children's participation in academic-oriented EAs. Academic achievement is highly valued in Chinese culture (Lau et al., 2011), and it may be true for all walks of society. We found that child gender was related to some aspects of children's EA participation, but not others. Boys and girls did not differ in the number of EAs that they participated in, which is consistent with Chiu and Lau's (2018) finding. However, in contrast to what Chen (2015) reported, we found significant gender differences in the breadth of participation. Additional analyses showed that boys were more likely to participate in sports, while girls participated in more kinds of art activities. These differences may reflect parents' gender socialization efforts. Passmore and French (2001) found that males were more likely to be involved in sports, while females were more likely to participate in art and performing art activities. Parents' choice of EAs might reflect their gender-stereotyped beliefs and wishes to cultivate masculinity in boys through sports (Leaper & Friedman, 2007) and qizhi (refined disposition, elegance) in girls through immersion in art activities (Su, 2008). We also found that children with better mathematics skills at T1 tended to have a greater breadth of participation and that those with better reading skills at T1 were likely to engage in a larger number of EAs. In China, children's abilities in math and reading are considered as an indicator of their intelligence or general ability by parents (Furnham, Rakow, & Mak, 2002). It is likely that parents purposefully enroll higher-achieving children in more EAs to make good use of children's intelligence and foster talents. Alternatively, children who participated in more EAs at T2 might also have participated in more outside enrichment activities before T1, which led to better mathematics and reading skills at T1. Qualitative research is needed to examine parents' rationales behind their choice of EAs, in order to better understand the relations between children's prior achievement and their EA participation. Our findings indicate that children's personal characteristics do play a role in their overall amount of exposure to the

We assessed several dimensions of EA participation to thoroughly examine the impact of EAs, including the number of EAs, the breadth of participation, attendance intensity, and the type of EAs. These dimensions captured different features of the activities that children were engaged in the EA microsystem. As the results revealed, the associations between EA participation and child outcomes varied across different dimensions of EAs, suggesting the value of attending to multiple facets of EAs to gain a more comprehensive understanding of how children's experiences in the EA microsystem might influence their development. The number of EAs and the breadth of participation predicted children's reading skills half a year later, even after controlling for children's initial reading skills and multiple demographic variables. Both dimensions reflect the range of experiences that children have in the EA microsystem. Thus, exposing children to a wide range of EAs may benefit the process of reading development. In addition, more intensive participation was related to better reading skills half a year later as well as more rapid growth in reading skills. The findings corroborate existing evidence on the relations between overall EA participation and academic achievement among school-aged children and youth (e.g., Dumais, 2006; Fredricks, 2012; Fredricks & Eccles, 2006a, 2006b). Several tentative explanations are proposed. First, organized EAs often resemble classroom contexts in many ways, and more opportunities to engage in structured learning might promote children's reading skills (Covay & Carbonaro, 2010; Fredricks, 2012). We used a Chinese word reading task to assess children's reading skills in this study. Children might have more exposure to Chinese print in EAs. Second, Chiu and Lau (2018) proposed that young children tended to focus on having fun and trying out new things in EAs. As many EAs in Hong Kong are offered in small groups, children with higher EA involvement might have more opportunities to interact with adults and peers and develop good oral language abilities that could facilitate their reading skills (Zhang, Hu, Ren, & Fan, 2018). Third, Dumais (2006) argued that parents who enrolled their children in EAs might also tend to involve in other aspects, such as reading with them at home. Thus, children with higher EA involvement might also have access to more learning activities at home that can promote reading skills. All these explanations are our speculations. Closer examinations of children's experiences in EAs that consider aspects, such as the content and quality of EAs and parents' involvement, are needed to understand the processes through which EAs may affect children's reading development. In addition, participation in academic-oriented EAs uniquely contributed to children's reading skills at T3, controlling for the effect of participation in non-academic-oriented EAs. EAs focused on language and math/science were coded as academic-oriented EAs. These activities are likely to involve learning materials that contain prints of Chinese characters, exposing children to ample opportunities to acquire reading skills. In contrast, participation in non-academic-oriented EAs, such as arts and sports, was not related to children's mathematics or reading skills. This finding was inconsistent with Dumais' (2006) finding that participation in sports, dance lessons, and clubs was related to elementary school children's gains in reading and involvement in dance lessons was associated with gains in mathematics. Non-academicoriented EAs provide young children with little exposure to academic content and thus may not lead to their immediate gains in academic skills during the preschool years. However, our finding does not necessarily indicate that participation in non-academic-oriented EAs is not beneficial for children's academic development in the long run. The benefits of involvement in non-academic-oriented EAs may not surface until children reach formal education when the learning of mathematics and reading becomes a major focus of schooling. Children may gain important noncognitive skills, such as regulation of attention and 9

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perseverance, through participating in non-academic-oriented EAs that will promote academic learning in the long run (Covay & Carbonaro, 2010; Deasy, 2002). However, it is worth noting that the effect sizes for the effects of EAs on child outcomes were relatively small. After controlling for the effects of children's initial reading scores and several demographic variables, children's T3 reading scores only increased by 0.11, 0.17, and 0.08 standard deviation for one unit increase in the number of EAs, breadth, and intensity, respectively. The T3 reading scores of children who participated in academic-oriented EAs were higher than those of nonparticipating children by 0.28 standard deviation. Thus, higher levels of EA involvement were related to better reading, but EAs in and of themselves were not a major factor in explaining individual variations in reading. Although overall EA participation was not related to children's levels of or rates of growth in mathematics skills, overall involvement in EAs was positively associated with the growth rate in mathematics among relatively less advantaged children. Family SES also moderated the relations between overall EA participation and children's reading skills at T3. These findings add to previous studies which showed that EA involvement was more beneficial for children and youth from lowerSES families in the United States (e.g., Covay & Carbonaro, 2010; Dumais, 2006; Marsh, 1992; Marsh & Kleitman, 2002), indicating the importance of bringing the family microsystem into the picture when examining the effect of EAs on child outcomes. Children from higherSES backgrounds may already have access to high-quality home learning environments (e.g., books, toys, and home learning activities), and EAs may be somewhat redundant for them. In contrast, organized EAs can provide children from relatively less privileged homes with learning opportunities to compensate for their family disadvantages. However, it is also plausible that children from less advantaged SES backgrounds attended preschools of lower quality. If this is the case, then the interplay between family SES and overall EA involvement in relation to children's mathematics skills might indicate that EA participation helped compensate for the lack of quality in preschool education among less advantaged children. Unfortunately, only four preschools participated in the study, and we did not measure the quality of the preschools. Nevertheless, future research needs to recruit children from more diverse backgrounds, and detailed data on school quality and home environments need to be collected, in order to disentangle whether EA participation compensates for low-quality home or preschool learning environment. Participation in non-academic-oriented EAs was particularly beneficial for T3 reading skills in less advantaged children. The non-academic-oriented EAs in this study were mainly art-related and athletic activities. Both activities have been linked to children’s academic development (Deasy, 2002; Sibley & Etnier, 2003). They may enhance academic learning through promoting noncognitive skills, such as creativity (Deasy, 2003) and executive functioning (Diamond & Lee, 2011). Less advantaged children may receive a boost in developing reading skills through non-academic-oriented EAs, while children from more advantaged homes might have already gained access to literacy activities at home. The findings are consistent with previous research showing that some early interventions were particularly beneficial for disadvantaged children (Burger, 2010; Zhang & Chan, in press). Similar to early education programs that aim to serve disadvantaged families (e.g., Early Head Start and Head Start programs), EAs often provide children with opportunities to engage in learning along with peers under the guidance of adults. The interaction effect of family SES and participation in non-academic-oriented EAs on children’s growth in mathematics skills approached significance. Interestingly, involvement in non-academic-oriented EAs benefited less advantaged children, but it actually posed risks for more advantaged children’s mathematical development. For children from higher-SES homes, participating in nonacademic-oriented EAs might have reduced their time spent within the home context that was likely to be rich in math learning opportunities.

However, EA participation was not associated with children's social skills, despite that EAs are also thought of as opportunities for children to socialize with similar-aged peers in addition to skill-building (Lau & Cheng, 2016). Most studies linking EA participation to social-emotional outcomes were focused on school-based EAs among adolescents (e.g., Fredricks & Eccles, 2006a, 2006b; Kort-Butler & Hagewen, 2011; Mahoney et al., 2003). School-based EAs afford adolescents with opportunities to form positive relationships with adults and peers outside of their own classrooms, which helps prevent negative social outcomes (Mahoney et al., 2003). Unexpectedly, we did not find similar effects of EAs on younger children's social skills in this study. Guidance from adults may be required to help children initiate and maintain positive social interactions at such a young age. Because EAs often have a designated goal for skill building, adults in EAs may focus more on developing specific skills in children than on facilitating child-adult and peer interactions. In addition, some of the EAs may be carried out in very small groups or through one-on-one lessons (e.g., playing musical instruments). Therefore, children may not always have access to many peers to practice interpersonal skills. Future research needs to assess specific characteristics of EAs (e.g., format of instruction and group size) to better understand the relations between EAs and young children's social skills. 4.3. Strengths, Limitations, and future directions The present study focused on an overlooked microsystem in which preschool-aged children participate in particular activities. Because many Chinese preschoolers regularly, consistently, and sometimes even intensively participate in EAs, EAs have become an important immediate setting for children's development. The current findings not only provided insights in how EAs might be related to young children's development but also furthered our understanding of how EAs interacted with the family microsystem in relation to child outcomes, extending the application of the bioecological systems theory in developmental research. The current study also has several strengths in its methodology, including the use of a longitudinal design and assessing multiple aspects of EAs. In addition, the current study focused on Chinese preschool-aged children in Hong Kong, a rarely studied cultural group and age range in the field of EAs. Our findings have significant contributions to the existing literature that is largely based on studies of school-aged children and youth in Western societies. However, this study also has some limitations. First, the sample size was relatively small, particularly considering the large number of models tested. Larger samples are preferred in future research to increase statistical power, as well as to allow researchers to use detailed activity-type categories to reveal nuanced relationships between participation in specific activities and developmental outcomes. Relatedly, our sample was mainly consisted of middle-class families, which constrains the generalizability of the current findings. Although it was encouraging to discover the moderating role of SES among such a constrained sample, more diverse samples are needed to better understand the role of SES in children's EA involvement. Second, we only assessed limited aspects of child outcomes. For instance, we only focused on story problem solving for mathematics and word reading accuracy for reading. The role of EA participation may vary across different domains of children's mathematics and reading skills, as some of the skills rely more on formal instruction, while others can be acquired through informal interactions (Huntsinger, Jose, Liaw, & Ching, 1997). In addition to reading and mathematics skills, other potential outcomes, such as executive functioning and approaches to learning, should also be included in future studies. Furthermore, child social skills were reported only by mothers. Children's social behaviors can vary considerably in different contexts (Renk & Phares, 2004). Indeed, the use of multiple informants of social behaviors is strongly recommended (Achenbach, McConaughy, & Howell, 1987; Renk & Phares, 2004; Zhang & Nurmi, 2012). This study 10

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popularity of EAs during early childhood. Hong Kong represents a unique context where EAs are very prevalent. Parents enroll young children in EAs, in hopes of providing their children with extra opportunities that are beyond the scope of family and preschool education, in order to cultivate diverse cognitive and noncognitive competencies in children (Karsten, 2015; Lau & Cheng, 2016). Although EA participation was positively linked to children's reading and mathematics skills, the effects were relatively small and only a very few effects pertained to children's growth rate in early academic skills in this study. In addition, EA participation was not related to children's social skills reported by mothers, although providing children with opportunities for social interaction is one of reasons that Hong Kong parents enroll their children in EAs (Lau & Cheng, 2016). The current findings raise questions about the effectiveness of EA involvement in fostering young children's development. Instigated by both global environment and cultural values on achievement, how this reconfiguration of childhood affects young children's wellbeing deserves a critical look. As many EAs are provided by private entities, government regulations are required to oversee the education market. Considering that increasing EA involvement among preschool-aged children is becoming a trend not just in Hong Kong, but also other parts of Asia (Chen, 2015; Na & Moon, 2003; Yi, 2013), the current study calls for cautionary attitudes toward EAs in early childhood. Our finding of the moderating role of family SES in the associations between EA involvement and child outcomes suggests that, the early onset of socioeconomic gaps in academic achievement may be partially attributed to young children's unequal access to EAs. In Hong Kong, EAs for preschool-aged children have been industrialized and often demand high investment in time and money on part of the parents. The income and time constraint may be significant barriers for less advantaged children to participate in EAs. The Hong Kong government has dramatically increased expenditure on early childhood education and worked hard to equalize the early childhood education system over the last decade (Wong & Rao, 2015). However, the EA market may counteract the government's efforts. Based on the findings of the current study, more resources need to be allocated to less advantaged families. For instance, the government may provide funding and support for preschools or public entities to deliver low-cost after-school EAs to less advantaged children, as these children can benefit more from EAs. Delivering EAs at preschools can also help parents save the time and cost in transporting children to the activities. In conclusion, EAs can be a potential form of early intervention to reduce the achievement gap between children from different SES backgrounds, if low-SES children are provided with equal access to EAs.

could have been strengthened if fathers' reports, preschool teachers' evaluations, and/or individual assessments of children's social skills were included. Third, we only assessed children's EA participation in the first year of kindergarten. In future studies, children's EA participation can be measured longitudinally to evaluate how children's trajectories of participation are related to their developmental outcomes throughout preschool years. Relatedly, other aspects of EA participation such as the form of EAs (e.g., class size, format of instruction), the duration of EA participation, children's enjoyment of EAs, the quality of EA experiences, the targeted level of proficiency of EAs, and parents' involvement in EAs should also be included in future studies. Furthermore, in this study, about 81% of the children participated in non-academic-oriented EAs, suggesting that parents' rationales for enrolling their children in EAs were more than just academic concerns. Parents' motivation for arranging EAs for young children should be examined in future research, which can shed light on the broader cultural context. In addition, in some EAs, parents attend along with their children and participate in activities together. In this case, parents' quality of participation, such as their effectiveness in guiding children's attention and keeping children engaged, matters for how well children can absorb the developmental “nutrients” of EAs. Parents' direct participation may also affect their attitudes to EAs, which can further influence their motivation and involvement in EAs as well as children's developmental processes as a result. Although our study provided initial evidence for the effects of EAs on young children's development, our understanding of the EA microsystem is still limited. Future research needs to assess these various aspects of EAs to better capture the complex features of the EA microsystem. Moreover, comprehensive examinations of how different aspects of EAs as well as the interplay between these aspects are related to child development will deepen our knowledge about how children's development unfolds in this complex microsystem. Fourth, there have been conjectures on the underlying mechanisms through which EAs affect child outcomes (e.g., parental involvement and social networks) (Dumais, 2006), which requires empirical research to confirm. Finally, this study only examined the interplay between family SES and EAs. Other family factors, such as parental involvement and parenting practices, were not included as controls of family influence on child development or potential moderators of the relations between EA participation and child outcomes. Moreover, children's experiences in other contexts, such as school and unorganized activities (e.g., family shared leisure activities and visiting libraries), were not assessed. As children's development is influenced by all these microsystems and the interactions among them (Bronfenbrenner, 1979), future studies need to include the multiple contexts and examine how home, school, neighborhood, and EA microsystems interrelate with one another in relation to child development.

Funding This study was supported by an ECS grant from the Research Grants Council of Hong Kong [No. 28404114 & No. 17603817] to Xiao Zhang.

4.4. Conclusions and practical implications The current findings extend the literature of EAs on school-aged children in Western societies, and highlight the relation between EAs and preschool-aged children's development. Examining the role of EAs in today's society is particularly meaningful due to the increasing

Declaration of competing interest All authors declare that they have no conflict of interest.

Appendix G. Supplementary data Supplementary data to this article can be found online at https://doi.org/10.1016/j.learninstruc.2019.101267.

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Appendix A Categories of Different Types of Extracurricular Activities Activity Type

Description & Examples

Percentage

Arts

All types of art activities (performing arts included), such as learning musical instruments, phonics, chorus, dancing, drawing, painting, clay, crafting, and drama (theater). There were only a couple of children that participated in science programs, and thus were combined with math programs. This category includes math, science, Lego, and other activities with math or science content involved. English and Chinese lessons. Athletic activities, such as swimming, ping pong, skating, gymnastics, rope jumping, fencing, tennis, and taekwondo. Other activities other than the above four categories, including church activities, organized clubs (boy/girl scouts), attention/social skills/multiple intelligence training, etc.

70.1%

Math/science Language Sports Others

16.1% 34.5% 33.3% 10.9%

Note. Although many of the athletic activities were individual sports (e.g., swimming, tennis), they were often delivered in small group settings.

Appendix B Descriptive Statistics of the Study Variables

Age (T2) SES Weekly Cost of EAs Intensity (hours/week) of EAs Number of EAs Breadth of EAs Mathematics Skills (T1) Mathematics Skills (T2) Mathematics Skills (T3) Mathematics Skills (T4) Reading Skills (T1) Reading Skills (T2) Reading Skills (T3) Reading Skills (T4) Social Skills (T2) Social Skills (T3) Social Skills (T4)

# of Items

Mean

SD

Range

Possible Max Score

– – – – – – 12 16 16 16 61 61 61 61 46 46 46

54.04 .01 489.64 2.80 2.46 1.65 1.41 3.27 5.49 7.88 4.93 21.64 32.93 42.22 2.70 2.76 2.79

3.53 .89 445.79 1.68 1.41 1.00 1.54 2.90 3.69 3.57 9.91 16.75 14.90 12.86 .33 .33 .31

38–61 −2.09–1.82 0–2800 0–8 0–5 0–4 0–12 0–16 0–16 0–16 0–50 0–60 0–61 5–61 1.80–3.57 1.87–3.67 1.96–3.61

– – – – 5 5 12 16 16 16 61 61 61 61 4 4 4

Note. N = 194.

Appendix C Independent t-tests Comparing Differences in Mathematics, Reading, and Social Skills between Children with and without Participation in EAs, in Academic-Oriented EAs, and in Non-Academic-Oriented EAs Participation in EAs

Mathematics Skills (T1) Mathematics Skills (T2) Mathematics Skills (T3) Mathematics Skills (T4) Reading Skills (T1) Reading Skills (T2) Reading Skills (T3) Reading Skills (T4) Social Skills (T2) Social Skills (T3) Social Skills (T4)

Participation in Academic-oriented EAs

Participation in Non-academic-oriented EAs

Yes M (SD)

No M (SD)

t-value

Yes M (SD)

No M (SD)

t-value

Yes M (SD)

No M (SD)

t-value

1.44 (1.53) 3.34 (2.98) 5.51 (3.66) 7.91 (3.47) 5.41 (10.63) 22.96 (16.67) 34.30 (14.66) 43.28 (12.38) 2.70 (.32) 2.77 (.32) 2.79 (.31)

1.00 (1.28) 2.26 (1.88) 4.63 (3.15) 6.88 (3.71) 2.11 (5.20) 14.32 (17.20) 25.68 (16.49) 35.65 (17.99) 2.68 (.41) 2.67 (.39) 2.70 (.36)

1.17 2.18* 1.00 1.15 1.33 2.13* 2.39* 1.71 .22 1.20 1.08

1.60 (1.84) 3.40 (3.38) 5.78 (3.80) 7.95 (3.71) 6.01 (9.33) 25.59 (16.84) 37.34 (14.55) 45.88 (12.02) 2.70 (.34) 2.74 (.31) 2.80 (.30)

1.24 (1.16) 3.04 (2.46) 4.93 (3.33) 7.60 (3.27) 3.79 (9.84) 18.72 (16.06) 29.84 (14.58) 39.37 (13.35) 2.70 (.33) 2.77 (.34) 2.76 (.32)

1.56 .78 1.55 .65 1.51 2.75** 3.36*** 3.31*** .11 .43 .87

1.49 (1.56) 3.40 (2.94) 5.45 (3.65) 7.97 (3.39) 5.26 (10.24) 23.09 (16.54) 34.29 (14.72) 43.31 (12.40) 2.69 (.32) 2.77 (.32) 2.80 (.31)

.97 (1.16) 2.31 (2.57) 4.69 (3.12) 6.77 (3.72) 2.61 (5.97) 15.94 (16.49) 28.03 (15.37) 37.70 (15.56) 2.72 (.38) 2.69 (.35) 2.73 (.32)

1.74 1.93 1.10 1.74 1.39 2.21* 2.15* 2.14* .39 1.16 1.01

Note. N = 194. *p < .05. **p < .01. ***p < .001.

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Appendix D Correlations between extracurricular participation and child mathematics, reading, and social skills.

Mathematics Skills (T1) Mathematics Skills (T2) Mathematics Skills (T3) Mathematics Skills (T4) Reading Skills (T1) Reading Skills (T2) Reading Skills (T3) Reading Skills (T4) Social Skills (T2) Social Skills (T3) Social Skills (T4)

T2 Age

Child Gender

Family SES

EA Intensity

Number of EAs

EA Breadth

Arts

Sports

Math/ Science

Language

Other EAs

Academic-oriented EAs

Non-academic-oriented EAs

.25***

.08

.21**

.15

.16*

.25***

.05

.16*

.26***

.09

.09

.12

.14

.25***

.01

.22**

.03

.11

.16*

-.05

.15

.07

.05

.03

.07

.16*

.32***

.16*

.20**

.10

.17*

.20**

-.10

.20*

.20*

.04

.07

.12

.09

.24**

.09

.09

.10

.15*

.14

.03

.02

.18*

.01

.02

.06

.15

.08

.03

.14

.07

.24**

.14

-.04

.13

.02

.14

-.05

.11

.10

.20*

.04

.12

.10

.26***

.24**

.02

.04

.18*

.16*

-.05

.21**

.17*

.23**

.00

.13

.18*

.33***

.27***

.05

.05

.21**

.18*

-.04

.25***

.17*

.24**

.01

.24**

.28***

.36***

.30***

.05

.11

.18*

.20*

.04

.25***

.18*

.00 .00 -.06

-.13 -.15* .03

.07 .07 .15

-.04 .02 .09

.001 .05 .12

-.03 .06 .12

.00 .11 .08

.07 .10 .08

-.08 -.10 -.07

.00 -.03 .13

-.15 -.06 -.07

-.01 -.04 .06

-.06 .07 .06

Note. N = 194. Child gender was dummy coded (0 = girl, 1 = boy). Arts, Sports, Math/Science, Language, Other EAs, Academic-oriented EAs, and Non-academicoriented EAs were all dummy coded (0 = no participation, 1 = participation). *p < .05. **p < .01. ***p < .001.

Appendix E Correlations among child mathematics, reading, and social skills across all time points.

1. Mathematics Skills (T1) 2. Mathematics Skills (T2) 3. Mathematics Skills (T3) 4. Mathematics Skills (T4) 5. Reading Skills (T1) 6. Reading Skills (T2) 7. Reading Skills (T3) 8. Reading Skills (T4) 9. Social Skills (T2) 10. Social Skills (T3) 11. Social Skills (T4)

1

2

3

4

5

6

7

8

9

10

– .31*** .30*** .23** .18* .18* .15* .15** -.12 -.04 .02

– .57*** .54*** .32*** .42*** .39*** .32*** -.01 .02 -.03

– .63*** .35*** .47*** .44*** .44*** .01 -.04 -.05

– .24*** .46*** .43*** .42*** -.13 -.16* -.10

– .66*** .58*** .48*** -.06 -.10 .002

– .90*** .79*** -.16* -.17* -.08

– .88*** -.14 -.15* -.09

– -.16* -.14 -.06

– .75*** .61***

– .64***

Note. N = 194. *p < .05. **p < .01. ***p < .001.

Appendix F Model Fit Information for the Unconditional and Conditional Growth Curve Models Model Unconditional growth curve models (T2-T4) Mathematics skills (Linear) Social skills (Linear) Reading skills (Linear) Reading skills (Spline model) Intensity models in Table 2 Mathematics skills Reading skills Social skills Number of EAs models in Table 2 Mathematics skills Reading skills Social skills Breadth models in Table 2 Mathematics skills Reading skills Social skills Academic orientation models in Table 2 Mathematics skills Reading skills Social skills

χ2 (p-value)

df

CFI

RMSEA (90% CI)

SRMR

.099 (.952) 4.693 (.196) 11.593 (.009) 5.878 (.053)

2 3 3 2

1.000 .991 .970 .986

0 (0–0) .055 (0~.144) .122 (.053~.199) .100 (0~.198)

.005 .114 .030 .051

13.016 (.292) 13.414 (.267) 9.343 (.500)

11 11 10

.990 .996 1.000

.031 (0~.085) .034 (0~.086) 0 (0~.075)

.038 .032 .065

12.146 (.353) 12.258 (.345) 7.972 (.632)

11 11 10

.995 .998 1.000

.023 (0~.081) .024 (0~.081) 0 (0~.066)

.035 .028 .062

17.208 (.102) 17.682 (.089) 14.398 (.156)

11 11 10

.971 .990 .981

.054 (0~.101) .056 (0~.102) .048 (0~.099)

.046 .042 .070

23.463 (.005) 9.948 (.269) 7.039 (.532)

9 8 8

.924 .996 1.000

.104 (.053~.156) .040 (0~.108) 0 (0~.087)

.061 .017 .035

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16.277 (.235) 17.397 (.182) 10.539 (.569)

13 13 12

.985 .994 1.000

.036 (0~.084) .042 (0~.088) 0 (0~.066)

.036 .029 .058

13.575 (.404) 13.863 (.384) 12.052 (.442)

13 13 12

.997 .999 1.000

.015 (0~.074) .019 (0~.075) .005 (0~.074)

.033 .027 .057

18.245 (.148) 23.524 (.036) 16.655 (.163)

13 13 12

.977 .984 .979

.046 (0~.091) .065 (.016~.106) .045 (0~.092)

.042 .039 .063

23.879 (.013) 15.737 (.107) 12.637 (.245)

11 10 10

.936 .990 .986

.088 (.039~.137) .061 (0~.117) .041 (0~.101)

.048 .014 .031

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