A Study on the Influencing Factors of Non-Cognitive Abilities of Junior High School Students Based on Hierarchical Linear Models

A Study on the Influencing Factors of Non-Cognitive Abilities of Junior High School Students Based on Hierarchical Linear Models | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article A Study on the Influencing Factors of Non-Cognitive Abilities of Junior High School Students Based on Hierarchical Linear Models Yingying WANG, Xinbi ZHANG, Xiaoke ZHONG This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6379829/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Non-cognitive abilities are essential for adolescent development, yet research examining their multilevel determinants remains limited. While prior studies have identified individual or school-level factors independently, few have investigated how these levels interact to shape non-cognitive development during the critical junior high school period. Methods: Using data from 7,894 students in the China Education Panel Survey (CEPS), this study employed Hierarchical Linear Modeling (HLM) to simultaneously examine individual and school-level predictors. The analysis focused on three dimensions of non-cognitive abilities (resilience, cooperation, and emotional stability) while testing cross-level interactions between student characteristics and school environment factors. Results: Individual-level analysis revealed significant effects of gender (β=-0.043), appearance (β=0.160), exercise time (β=0.002), family background (β=0.061), and parental involvement (β=0.101). School-level factors showed school type (β=-0.071) and locations (β=-0.034) significantly predicted outcomes. Notably, school location moderated the effects of migration status (β=-0.076) and appearance (β=0.037), while school ranking enhanced exercise benefits (β=0.001). Conclusion: This study demonstrates the complex interplay between individual and school factors in shaping non-cognitive abilities. The findings suggest that educational interventions should adopt a multilevel approach, addressing both student characteristics and school environment improvements, particularly in resource allocation for rural schools and physical activity programs. These results provide both theoretical insights for developmental psychology and practical guidance for educational policy-making. HLM Junior high school students Non-cognitive abilities China Education Panel Survey Influencing factors Figures Figure 1 Figure 2 Introduction Non-cognitive abilities refer to stable patterns of thoughts, feelings, and behaviors that individuals display in various situations[1]. These abilities encompass performance, interpersonal skills, and emotional regulation[2], significantly influence academic achievement, career acquisition, and labor market status[3]. However, non-cognitive abilities exhibit educational instabilities [4], and the junior high school years are a critical period for the development of non-cognitive abilities. During this stage, non-cognitive abilities are shaped not only by individual and family factors but also by school education [5]. Therefore, exploring the multifaceted influences on junior high school students' non-cognitive abilities is crucial for their long-term education and personal development. Non-cognitive abilities are distinct from cognitive abilities, such as mathematical operation, linguistic understanding, and logical thinking. Instead, they encompass personality traits, social-emotional skills, and behavioral characteristics [6]. Early interventions targeting these abilities have been shown to improve educational achievement and socio-economic benefits in adulthood [7]. Parents, as key participants in their children’s early education, play a pivotal role in cultivating positive behavioral habits, self-control, resilience, and self-efficacy [8]. All of which contribute to the development of non-cognitive abilities. Additionally, parental socioeconomic status and educational attainment influence the quality of a child’s environment, including access to educational resources [9]. Which in turn affects future productivity and economic income [10]. Gender differences in non-cognitive abilities have also been observed, with studies indicating that girls tend to exhibit stronger non-cognitive abilities than boys at the same ages [11]. Furthermore, physical exercise plays a significant role in enhancing non-cognitive abilities by promoting sociability, openness, independence, and constructive social skills among junior high school students. School-level factors, such as school type, class size, and teacher experience, also contribute to the development of socio-emotional competence [10,12]. However, existing studies on the factors influencing non-cognitive abilities primarily focus on individual, family, or school-levels in isolation. There is limited research on the direct effects of multilevel factors and their interaction on non-cognitive abilities. First, most studies have examined the impact of single factors on junior high school students' noncognitive abilities, with few exploring how factors at different levels interact or jointly influence these abilities. Second, due to the limitation of data, some studies used small or unrepresentative samples, leading to potential biases in their findings. This study utilizes data from the China Education Panel Survey (CEPS) (2014-2015) and employs a Hierarchical Linear Model (HLM) to examine the impact of individual and school-level factors on junior high school students' non-cognitive abilities. It also aims to elucidate the interaction mechanisms between these factors, providing a multidimensional perspective on their influence. By applying HLM, this study seeks to deepen the understanding of how multilevel factors shape non-cognitive abilities and their interplay, contributing to a more comprehensive framework for future research. Materials And Methods Data Sources The data for this study were obtained from CEPS (2014-2015), the first large-scale, nationally representative tracking survey program for junior high school students in China. The program adopts the probabilities proportional to the sampling (PPS) sampling method, covering 28 counties (districts) and 112 schools. The 2014-2015 dataset primarily focuses on follow-up data from seventh-grade students who participated in the baseline survey. A total of 9,449 students were successfully interviewed, and after addressing missing values and outliers in the core variables based on research requirements, 7,894 valid samples were retained for analysis. Variable Selection and Definition In this study, the development of junior high school students' non-cognitive abilities serves as the dependent variable. Drawing on Zhou Jinan’s (2021) framework for measuring non-cognitive abilities in Chinese primary and secondary schools, and aligning with the survey items in CEPS, three key indicators of "resilience", "cooperation" and "emotional stabilities" were selected for measurement. the descriptions of these variables and the corresponding question items in CEPS are detailed in Table 1. Table 1 Definition of Non-cognitive Abilities Variable Indicator Variable Description Corresponding question items in CEPS Options Resilience People's persistence and enthusiasm for long-term goals, the quality of pursuing goals and beliefs in the face of adversity [13] even if I am a little unwell or have another reason to stay home, I still try to go to school. I try my best to do my homework even if I don't like it. Even if it takes me a long time to finish my homework, I still try my best to do it。. I can keep up with my hobbies. Totally disagree = 1 Not at all agree = 2 Quite agree = 3 Completely agree = 4 Cooperation The psychological desire to learn and contribute with others [14] most of the students in my class are friendly to me. the classroom culture in my class is good I often participate in activities organized by the school or class I feel close to people in this school Completely disagree = 1 Quite disagree = 2 Comparatively agree = 3 Totally agree = 4 Emotional Stabilities An individual's control and regulation of his or her own emotions, negative emotions include characteristics such as anxiety, depression, frustration, and vulnerabilities[15] In the past seven days, have you felt depressed. In the past seven days, have you felt so depressed that you could not concentrate on anything. In the past seven days, did you feel unhappy. In the past seven days, have you felt that life is not interesting. Within the past seven days, have you felt so demotivated that you couldn't concentrate on things Within the past seven days, have you felt sad and upset. In the past seven days, have you felt nervous. in the past seven days, did you worry too much. in the past seven days, did you have a premonition that something bad was going to happen. Never = 5 Rarely = 4 Sometimes = 3 Often = 2 Always = 1 In this study, factor influencing the development of junior high school students' non-cognitive abilities were categorized into two levels: individual and school (Table 2). At the individual-level, factors were further divided into personal and family influence. Personal influences included gender[11], appearance[16], immigrant status[17], boarding status[18], and hours of exercise [19]. Family influences primarily encompassed family background [20,21]and parental involvement [22,23,24,25]. At the School-level, three indicators were selected: school type, school location, and school ranking. The selected variables were transformed and filtered based on the variable definitions in the CEPS (2014-2015) questionnaire. Descriptive statistics were applied to analyze the data, and the results are detailed in Table 3. Table 2 Definition of Explanatory Variables Variable type Variable name Corresponding question item in CEPS Variable description Individual-level Gender What is your gender? Female = 0, Male = 1 appearance How do you think you have an appearance? (very ugly, rather ugly) = 1, average = 2, (rather beautiful, very beautiful) = 3 Migration Where is your home now? This county = 0, out of county = 1 Boarding Do you board at school Monday through Thursday nights? No=0, Yes=1 Hours of exercise How long do you usually exercise: () days per week, () minutes per day. Excluding extreme values where exercise per day exceeds 360 minutes, duration = ln (days per week * exercise per day)/7 Family background Economic How do you think your family's financial situation is now? Very difficult=1, more difficult=2, moderate=3, richer=4, very rich=5 Cultural Does your family have a lot of books? Few = 1, less = 2, average = 3, more = 4, many = 5 Educational Father's education level? Mother's education level? No at all = 0, Elementary school = 6, Junior high school=9, Vocational high school/general high school = 12, University college=15, Undergraduate college = 16, Graduate school and above = 19 Social class What kind of work does your father do now? What kind of work does your mother do now? Government = 12, Institution = 11, Scientist = 10, Doctor = 9, Accountant = 8, General Employee = 7, Service Worker = 6, Laborer = 5, Farming, Livestock, and Fishing = 4, Laborer = 3, Self-employed = 2, Unemployed = 1 Parental involvement Parent-child relationship How is your relationship with your dad? How is your relationship with your mom? Not close = 1, normal = 2, very close = 3 Educational Expectations What are your parents' educational expectations for you? Indifferent = 0, Below college = 1, College = 2, Undergraduate = 3, Graduate = 4, Ph.D. = 5 Future Confidence Do your parents have confidence in your future? Not at all = 1, Not too confident = 2, More confident = 3, Very confident = 4 School-level School type The type of school your school belongs to? Public school = 1, (privately-run, ordinary private school) = 2, privately-run school for working children = 3 School location What is the type of area where the school is located? Central urban area = 1, (Marginal urban area, urban-rural interface) = 2, (Outside urban area, town, rural area) = 3 School ranking In terms of school performance, where does your junior high school currently rank in the county (district)? Worst = 1, Lower middle = 2, Middle = 3, Upper middle = 4, Best = 5 Table 3 Descriptive Statistical Analysis of All Variables Variable Type Variable Name Sample size Mean Standardize Min Max Explained Variables Non-cognitive abilities Resilience 7894 3.22 0.68 1 4 Cooperation 7894 3.07 0.67 1 4 Emotional Stabilities 7894 3.83 0.83 1 5 Explanatory Variables Individual-level Gender 7894 0.50 0.50 0 1 appearance 7894 2.05 0.46 1 3 Migration 7894 0.03 0.178 0 1 Boarding 7894 0.30 0.46 0 1 Hours of exercise 7894 22.47 23.03 0.14 300 Family background 7894 2.97 1.23 0.75 8.5 Economic 7894 2.95 0.60 1 5 Cultural 7894 3.11 1.15 1 5 Educational 7894 2.38 4.10 0 19 Social class 7894 3.42 0.86 1 5 Parental involvement 7894 2.90 0.95 0.33 4.67 Parent-child relationship 7894 2.80 1.29 0 5 Educational Expectations 7894 2.80 1.29 0 5 Future Confidence 7894 3.10 0.69 1 4 Explanatory Variables School-level School type 110 1.14 0.50 1 3 School location 110 1.91 0.90 1 3 School ranking 110 3.86 0.89 1 5 Model construction HLM, proposed by Roudebush [26], is an extension of traditional linear regression model designed to analyze non-independent data with a multilevel nested structure. HLM has been widely applied in fields such as teacher job satisfaction[27], student academic achievement[28], early childhood education[29], and teaching quality [30], enabling researchers to examine influences at both individual and group levels simultaneously. In this study, HLM is employed to account for the nested structure of students within schools. At the individual-level, factors such as gender, appearance, Hours of exercise, family background, and parental involvement significantly influence junior high school students' noncognitive abilities. However, students are nested within schools, and school-level factors (e.g., school type, location, and ranking) may also impact these abilities. Specifically, the development of non-cognitive abilities is shaped not only by individual-level factors but also by the school context, with potential interactions between the two levels (Figure 1). For instance, school-level variables may moderate the effects of individual-level factors, thereby influencing non-cognitive development. Based on the above analysis, it is essential to examine the factors influencing the development of junior high school students’ non-cognitive abilities at both the individual and school-levels. To achieve this, a HLM was constructed, and the data were processed using SPSS26.0. The overall model fit was evaluated using the maximum likelihood value. The mechanisms and interactions of these influencing factors were explored by analyzing four models: Model 1 (null model), Model 2, Model 3 and Model 4. Among them, the non-cognitive abilities development of junior high school students was used as an explanatory variable, while individual-level and school-level factors were used as explanatory variables, and the HLM formula was as follows: Model 1 (null model) Hierarchical Model: L1: Non-cognitive U ij = b 0j + l ij L2: b 0j = g 00 + m 0j Mixed Model: Non-cognitive U ij = g 00 + m 0j + l ij L1 represents the individual-level, L2 represents the school-level, i is the student number, j is the school number, Non-cognitive U ij is the explanatory variable, it is the non-cognitive abilities of i student in the j school; b 0j is the mean of the j school; l ij is the random error at the individual-level, g 00 is the overall mean at the level of all schools, m 0j is the random error at the School-level. Model 2 Hierarchical Model: L1: Non-cognitive U ij = b 0j + b nj c n + l ij L2: b 0j = g 00 + m 0j b nj = g n0 + m nj ( n = 1,2,3,4……,7894) Mixed Model: Non-cognitive U ij = g 00 + m 0j + g n0 c n + m nj c n + l ij c n is the n explanatory variable in the first level, b nj is the slope of the n explanatory variable in the first level, g n0 is the mean of b nj , and m nj is the random error of b nj . Other symbols are as above. Model 3 Hierarchical Model: L1: Non-cognitive U ij = b 0j + b nj c n + l ij L2: b 0j = g 00 + g 0m d m + m 0j b nj = g n0 + m nj ( m = 1,2,3,4……,110) Mixed Model: Non-cognitive U ij = g 00 + g 0m d m + m 0j + g n0 c n + m nj c n + l ij g n0 is the slope of the regression for the m explanatory variable at the school level, d m is the m explanatory variable at the school level, and the other symbols are as above. Model 4 Hierarchical Model: L1: Non-cognitive U ij = b 0j + b nj c n + l ij L2: b 0j = g 00 + g 0m d m + m 0j b nj = g n0 + g nm d m + m nj Mixed Model: Non-cognitive U ij = g 00 + g 0m d m + m 0j + g n0 c n + g nm d m c n + m nj c n + l ij g nm is the slope of the m explanatory variable in the school level that explains the slopes of the explanatory variables in the individual level, reflecting the presence of interactions between the strata, and the other symbols are as above. To analyze the factors influencing the development of junior high school students' non-cognitive abilities using HLM, the applicability of the model must first be validated. Model 1, the null model, specifies the proportion of variance in non-cognitive abilities attributable to school-level factors, assessing the feasibility of applying an HLM. This model includes only the random effect of the school level, with no explanatory variables. Model 2 examines the effects of individual-level variables on non-cognitive abilities, incorporating only individual-level explanatory variables, in this model, the regression coefficients and intercepts of the individual-level equations could be varied randomly across School-levels. Model 3 tests the direct effect of School-level variables on non-cognitive abilities, and contains only school-level explanatory variables. Model 4, the full model, includes both individual and school-level variables. It verifies the direct effect of school-level factors while allowing individual-level variables to vary randomly across schools. Additionally, it explores the interaction between individual- and school-level factors in influencing junior high school students' non-cognitive abilities. Results The null model analysis results (Table 4) reveal a between-group variance of 0.024 (P<0.001), indicating significant difference in the development of non-cognitive abilities among junior high school students at the School-level. The Intragroup Correlation Coefficient (ICC) is calculated to be 9.5%, indicating that 9.5% of the variance in non-cognitive abilities is attributable to differences between schools. Based on the criteria that an ICC value greater than 5.9% justifies the use of HLM (Cohen, 1988), this study confirms the appropriateness of employing a HLM approach. Table 4 Results of Data Analysis for the Null Model Random effect Variance Standard error Degree of freedom P-value Log likelihood (ML) Non-cognitive abilities（m 0 ） 0.024 0.004 108 0.000 11097.013 Individual-level（R） 0.232 0.004 Model 2, a random coefficient regression model, examines the direct effects of individual-level variables on the development of junior high school students’ non-cognitive abilities. The results (Table 5) indicate significant effects (P<0.001) of gender, appearance, hours of exercise, family background, and parental involvement. Gender has a negative effect, with each unit increase associated with a 0.043-unit decrease in non-cognitive abilities. In contrast, appearance, hours of exercise, family background, and parental involvement show significant positive effects. No significant differences were found for migrant and boarding (P>0.1). Model 3, an intercept model, analyzes the direct effect of school-level variables. School type significantly affects non-cognitive abilities (P<0.05), with each unit increase associated with a 0.071-unit decrease. School location also has a significant negative effect (P<0.1), while school ranking shows no direct effect. Model 4 incorporates both individual- and school-level variables (Table 5), revealing the moderating effects of school-level variables on individual-level factors. Significant interactions include school location and migrant children, showing a significant negative effect (P<0.05); school location and appearance, as well as school ranking and hours of exercise, showing significant positive effects (P<0.05). Table 5 Results of the HLM Analysis of the Factors Influencing the Development of Non-cognitive Abilities of Junior High School Student Variables Model 2 Model 3 Model 4 Individual-level Gender -0.043 *** （0.011） 0.015（0.070） appearance 0.160 *** （0.012） 0.027（0.080） Migration -0.043（0.030） 0.345 * （0.180） Boarding -0.021（0.014） -0.188（0.137） Hours of exercise 0.002 *** （0.000） -0.003 * （0.002） Family background 0.061 *** （0.006） 0.051（0.052） Parental involvement 0.101 *** （0.006） 0.089 ** （0.038） School-level School type -0.071 ** （0.030） -0.016（0.081） School location -0.034 * （0.017） -0.090 ** （0.044） School ranking 0.014（0.018） -0.073（0.047） Interaction School location & Migration -0.076 ** （0.038） School location & appearance 0.037 ** （0.015） School ranking & Hours of exercise 0.001 *** （0.000） Constant 2.564 **** （0.031） 3.458 *** （0.089） 2.993 *** （0.239） Log-likelihood value 10316.866 10860.360 10059.700 ICC 0.070 0.079 0.067 AIC 10336.866 10872.360 10127.700 BIC 10406.605 10914.078 10364.098 Note: (1) *** , ** , and * are at the 1%, 5%, and 10% levels, respectively; (2) Numbers in parentheses are standard errors of regression coefficients; The development of junior high school students’ non-cognitive abilities is influence by factors at both the individual and school levels, as well as their interactions, exhibiting distinct hierarchical characteristics (Figure 2). At the individual level, gender, appearance, hours of exercise, family background, and parental involvement directly affect non-cognitive abilities. At the school level, school type and location also exert significant influences. In addition, the school-level variable indirectly affects non-cognitive abilities by moderating the individual-level factors. The effect of individual-level factors on noncognitive abilities increases with the improvement of school location; The impact of hours of exercise on non-cognitive abilities is enhanced with high school ranking; School location negatively moderates the effect of migrant status on non-cognitive abilities. Discussion Based on CEPS (2014-2015), this study constructs an HLM to examine the factors influencing junior high school students' non-cognitive abilities. It reveals the mechanism through which individual- and school-level factors directly impact these abilities, as well as their interactions, thereby advancing research in this field. The study reveals gender differences in non-cognitive abilities among junior high school students, with girls demonstrating superior abilities compared to boys, consistent with Barnett et al.'s finding[11]. This disparity may stem from several factors. First, girls are often socialized to be well-behaved, understanding, and obedient, leading to higher parental expectations and more frequent communication, which fosters self-efficacy and prosocial behaviors [8]. Second, societal gender expectations encourage girls to comply with rules and seek approval, further enhancing their non-cognitive abilities(Christopher et al., 2013). Regarding appearance, students who perceive themselves as more attractive exhibit better-developed non-cognitive abilities, aligning with prior research[31]. Attractive appearance confers advantages in social interactions, emotional experiences, and adaptability. In addition, the study finds that increased hours of exercise positively impact non-cognitive abilities, consistent with Wilson’s results [32]. This effect may arise from: (1) Expanded social networks and improved interpersonal skills through exercise[33]; (2) Reduced anxiety and depression, enhanced self-efficacy, and increased future confidence[34]; (3) Positive emotional experiences and a greater willingness to embrace challenges fostered by family and peer involvement in exercise[35]. This study also found the influence of family economic, cultural, and social capital on junior high school students’ non-cognitive abilities. Families with high economic capital can provide more educational opportunities and create a conducive learning environment[36]. The cultural capital investment enhances students' "soft power," positively impacting qualities such as openness, resilience, adaptability, and emotional stability. Additionally, high-quality parental communication and companionship foster non-cognitive abilities like self-esteem, cooperation, and interpersonal skills[37], providing children with security and confidence to explore the world. Contrary to previous findings by Liu [38] and Curto[39], this study found that migration and boarding status do not significantly affect non-cognitive abilities. This discrepancy may arise from differences in research subjects, as earlier studies primarily focused on elementary school students, who are more dependent on family support, in contrast, junior high school students exhibit greater independence. Additionally, cultural and educational differences may play a role. Compared to the Western emphasis on individuality, Chinese education prioritize cooperation and group living, and boarding schools often provide substantial peer and teacher support, mitigating potential negative effects on non-cognitive abilities. At the School-level, both school type and location significantly influence the non-cognitive abilities of junior high school students. Firstly, public schools, characterized by abundant education resources, high operational costs, and substantial investments, meet parental expectations for quality education[20]. These institutions, equipped with advanced facilities, diverse curricula, and rich experience teachers, subtly enhance students’ non-cognitive abilities. Secondly, schools located near central urban areas, often with long operational histories, well-established institutional norms, and rigorous cultivation standards, exert a profound impact through their word-of-mouth, environmental, and role model effects[40]. These factors shape students’ learning attitudes and future development expectations, fostering continuous self-improvement and influencing their non-cognitive abilities development. Lastly, the non-cognitive abilities of junior high school students are closely linked to teachers’ teaching experience. Experienced teachers, particularly those in public schools where recruitment criteria emphasize both academic qualifications and teaching experience, effectively enhance students’ non-cognitive abilities, especially in areas such as extraversion and neuroticism[41], thereby promoting socio-emotional development. This study further identifies a moderating effect of school-level variables on the relationship between individual-level factors and the non-cognitive abilities of junior high school students. Specifically, the impact of migration on students' non-cognitive abilities varies by school location. Schools farther from urban centers tend to exhibit lower levels of non-cognitive development among students, likely due to unequal distribution of educational resources, limited transportation accessibility, and geographic isolation[42]. These constraints restrict students' access to resources, thereby hindering their non-cognitive skill development. Additionally, the influence of an appearance on non-cognitive abilities is moderated by school location. Schools in central urban areas, characterized by rigorous discipline, high academic expectations, and a focus on knowledge and personality development, place less emphasis on external image[31]. In contrast, students in remote areas often prioritize appearance to gain social recognition and avoid negative evaluations, diverting time and energy from other developmental activities[31]. Moreover, the effect of physical activity time on non-cognitive abilities is positively correlated with school ranking. Higher-ranked schools prioritize students' physical health and holistic development by providing advanced exercise facilities, fostering a supportive exercise environment, and encouraging sports-related interactions[43]. This promotes extroverted personalities, enhances trust, and cultivates pro-social behaviors, thereby strengthening non-cognitive abilities. Limit This study offers a novel perspective and theoretical framework for examining the factors influencing junior high school students' non-cognitive abilities using HLM. However, several limitations should be acknowledged. First, while non-cognitive abilities are shaped by a multitude of factors, the study's selected indicators are limited. Future research could incorporate a broader range of measurement indices to explore this issue from multiple dimensions, thereby enhancing the precision and explanatory power of the model. Second, the study relies on data from the CEPS conducted in 2014–2015. Utilizing more recent data in future studies would provide a more accurate understanding of the current factors affecting students' non-cognitive abilities. Finally, while the HLM model was employed to analyze the effects of individual-level and school-level variables, as well as their interaction mechanisms, future research could expand the framework by incorporating additional layers of variables, such as family-level factors. This would enable a more comprehensive exploration of the interactions among individual, school, and family variables, further advancing the depth of the study. Conclusion The study revealed the following key findings: (1) junior high school students' non-cognitive abilities are directly and interacted influenced by factors at both the individual and School-levels; (2) at the individual level, gender, appearance, hours of exercise, family background, and parental involvement, as well as at the School-level the type of school and school location can directly influence junior high school students' non-cognitive abilities to varying degrees; (3) the school location and migration, school location and appearance, school ranking and hours of exercise interacted with each other to influence the development of junior high school students' non-cognitive abilities. Declarations Ethics statement The data collection was approved by the ethics committee of Renmin university of China, and each participant was informed of the purpose of this research. This manuscript does not apply to clinical trial numbers. All participants had given their informed consent. Their parents or legal guardians had also given informed consent. And this study complies with the Helsinki Declaration. Consent for publication Not applicable. Availability of data and materials The original contributions presented in the study are included in the article material, further inquiries can be directed to the corresponding author. Conflict of Interest Statement The authors declare no competing interests. Funding The project is not supported by the funding. Author’s contributions WYY Contributed to the study design and manuscript draft. ZXB was data analysis. ZXK gave critical feedback. All authors have read and approved the manuscript. Acknowledgments We thank the China Education Panel Survey (CEPS) for data access and colleagues at the Capital University of Physical Education and Sports for their feedback. All errors remain our own. 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The contribution of cultural capital to students’ mathematics achievement in medium and high socioeconomic gradient economies. British Educational Research Journal. 2015;41:1050–67. Corry Y, Iskandar Agung, Novrian, Satria Perdana, Simon Silisabon. A Study of Factors Influencing the Development of Student Talent. International Journal of Education and Practice. 2020;8:441–56. Datu JAD, Yuen M. Students’ connectedness is linked to higher gratitude and self-efficacy outcomes. Children and Youth Services Review. 2020 116:105210. D’Urso G, Symonds J, Pace U. Positive Youth Development and Being Bullied in Early Adolescence: A Sociocultural Analysis of National Cohort Data. The Journal of Early Adolescence. 2021;41:577–606. Wang S, Zheng L. Parenting style and the non-cognitive development of high school student: evidence from rural China. Front Psychol. 2024 15:1393445. Raudenbush SW, Chan WS. 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Studies in Educational Evaluation. 2024;83:101419. Xie Y, Fan Y, He J. Perceived appearance, body shape and adolescent academic achievement: Evidence from Chinese middle school. Br Educ Res J. 2023;49:1338–56. Wilson KE, Dishman RK. Personality and physical activity: A systematic review and meta-analysis. Personality and Individual Differences. 2015;72:230–42. Stubbs B, Koyanagi A, Hallgren M, Firth J, Richards J, Schuch F, et al. Physical activity and anxiety: A perspective from the World Health Survey. Journal of Affective Disorders. 2017;208:545–52. Knapen J, Vancampfort D, Moriën Y, Marchal Y. Exercise therapy improves both mental and physical health in patients with major depression. Disability and Rehabilitation. 2015;37:1490–5. Canetti L, Bachar E, Galili-Weisstub E, Atara Kaplan D-N, Shalev AY. EconStor: The height premium in earnings: the role of physical capacity and cognitive and non-cognitive skills. Rpslyn Heights. 1997;32:381–94. Khaled Sarsour, Margerat Sheridan, Douglas Jutte, Amani Nuru-jeter, Stephen Hinshaw, W. Thomas Boyce. Family Socioeconomic Status and Child Executive Functions: The Roles of Language, Home Environment, and Single Parenthood. Journal of the International Neuropsychological Society. 2011;17:120–32. Li L, Liu H, Kang Y, Shi Y, Zhao Z. The influence of parental involvement on students’ non-cognitive abilities in rural ethnic regions of northwest China. Studies in Educational Evaluation. 2024;81:101344. Liu M, Villa KM. Solution or isolation: Is boarding school a good solution for left-behind children in rural China? China Economic Review. 2020;61:101456. Curto VE, Jr RGF. The Potential of Urban Boarding Schools for the Poor: Evidence from SEED. Journal of Labor Economics. 2014; Fasasi RA. Effects of ethnoscience instruction, school location, and parental educational status on learners’ attitude towards science. Int J Sci Educ. 2017;39:548–64. Chen B, Zhao C. Teachers’ administrative positions and students’ non-cognitive abilities in China: evidence from a quasi-natural experiment. Appl Econ. 2024;56:6091–108 Moreno-Monroy AI, Lovelace R, Ramos FR. Public transport and school location impacts on educational inequalities: Insights from Sao Paulo. J Transp Geogr. 2018;67:110–8. Derek W, Craig, Timothy J., Walker, Shreela V., Sharma, et al. Examining associations between school-level determinants and the implementation of physical activity opportunities-Web of Science Core Collection. Translational Behavioral Medicine. 2024;89–97. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6379829","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":463493535,"identity":"12598379-6969-4ab6-b3c6-f2fd82665f93","order_by":0,"name":"Yingying WANG","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAzElEQVRIiWNgGAWjYBAC+/sH0n9IVPyX42dvIFbPDYYHEhZnmI0lew4QrYXxgURlG3PihhkJROpgnN2cYHDjDBvjBsnHG28w1NhEE9TCLHMsIXFGBQ+zuXRasQXDsbTcBkJa2BhyEg5LnJFgs5ydYybB2HCYsBYehvyPzX/bDHgMbp4hUouEREIyg2RbgoTBDR4itRjwHEhjkDhzwECyB+iXBGL8YsDeANRScaC+n/3wxhsfamwIa0HRLpFAinKIFlJ1jIJRMApGwcgAAEqLQVxS73BqAAAAAElFTkSuQmCC","orcid":"","institution":"","correspondingAuthor":true,"prefix":"","firstName":"Yingying","middleName":"","lastName":"WANG","suffix":""},{"id":463493537,"identity":"724d76fb-6868-49b0-81d9-360e57ada9e8","order_by":1,"name":"Xinbi ZHANG","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Xinbi","middleName":"","lastName":"ZHANG","suffix":""},{"id":463493539,"identity":"d122130f-15ad-4445-8852-20dbea84f99b","order_by":2,"name":"Xiaoke ZHONG","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Xiaoke","middleName":"","lastName":"ZHONG","suffix":""}],"badges":[],"createdAt":"2025-04-05 05:08:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6379829/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6379829/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":83657378,"identity":"28428058-8264-4836-a751-c49a84e15f07","added_by":"auto","created_at":"2025-05-30 08:57:23","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":156211,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eHLM Framework for Non-cognitive Abilities of Junior High School Students\u003c/em\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6379829/v1/021c5ba5caa5b7bbbe1dea8b.png"},{"id":83657377,"identity":"42a4c97b-f454-4711-9c38-6a3964a4189f","added_by":"auto","created_at":"2025-05-30 08:57:23","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":32915,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eMultilevel Influences on the Development of Non-cognitive Abilities in Junior High School Students\u003c/em\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6379829/v1/53aa52e0b37055cfc021da8f.png"},{"id":98943299,"identity":"d62f589e-4df2-4a02-a63e-87537fc3fd1a","added_by":"auto","created_at":"2025-12-24 11:39:54","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":889081,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6379829/v1/223e1543-c341-4b28-a12c-1bddd0592ca6.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"A Study on the Influencing Factors of Non-Cognitive Abilities of Junior High School Students Based on Hierarchical Linear Models","fulltext":[{"header":"Introduction","content":"\u003cp\u003eNon-cognitive abilities refer to stable patterns of thoughts, feelings, and behaviors that individuals display in various situations[1]. These abilities encompass performance, interpersonal skills, and emotional regulation[2], significantly influence academic achievement, career acquisition, and labor market status[3]. However, non-cognitive abilities exhibit educational instabilities [4], and the junior high school years are a critical period for the development of non-cognitive abilities. During this stage, non-cognitive abilities are shaped not only by individual and family factors but also by school education [5]. Therefore, exploring the multifaceted influences on junior high school students\u0026apos; non-cognitive abilities is crucial for their long-term education and personal development.\u003c/p\u003e\n\u003cp\u003eNon-cognitive abilities are distinct from cognitive abilities, such as mathematical operation, linguistic understanding, and logical thinking. Instead, they encompass personality traits, social-emotional skills, and behavioral characteristics [6]. Early interventions targeting these abilities have been shown to improve educational achievement and socio-economic benefits in adulthood [7]. Parents, as key participants in their children\u0026rsquo;s early education, play a pivotal role in cultivating positive behavioral habits, self-control, resilience, and self-efficacy [8]. All of which contribute to the development of non-cognitive abilities. Additionally, parental socioeconomic status and educational attainment influence the quality of a child\u0026rsquo;s environment, including access to educational resources [9]. Which in turn affects future productivity and economic income [10].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eGender differences in non-cognitive abilities have also been observed, with studies indicating that girls tend to exhibit stronger non-cognitive abilities than boys at the same ages [11]. Furthermore, physical exercise plays a significant role in enhancing non-cognitive abilities by promoting sociability, openness, independence, and constructive social skills among junior high school students. School-level factors, such as school type, class size, and teacher experience, also contribute to the development of socio-emotional competence [10,12].\u003c/p\u003e\n\u003cp\u003eHowever, existing studies on the factors influencing non-cognitive abilities primarily focus on individual, family, or school-levels in isolation. There is limited research on the direct effects of multilevel factors and their interaction on non-cognitive abilities. First, most studies have examined the impact of single factors on junior high school students\u0026apos; noncognitive abilities, with few exploring how factors at different levels interact or jointly influence these abilities. Second, due to the limitation of data, some studies used small or unrepresentative samples, leading to potential biases in their findings.\u003c/p\u003e\n\u003cp\u003eThis study utilizes data from the China Education Panel Survey (CEPS) (2014-2015) and employs a Hierarchical Linear Model (HLM) to examine the impact of individual and school-level factors on junior high school students\u0026apos; non-cognitive abilities. It also aims to elucidate the interaction mechanisms between these factors, providing a multidimensional perspective on their influence. By applying HLM, this study seeks to deepen the understanding of how multilevel factors shape non-cognitive abilities and their interplay, contributing to a more comprehensive framework for future research.\u003c/p\u003e"},{"header":"Materials And Methods","content":"\u003cp\u003e\u003cstrong\u003eData Sources\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data for this study were obtained from CEPS (2014-2015), the first large-scale, nationally representative tracking survey program for junior high school students in China. The program adopts the probabilities proportional to the sampling (PPS) sampling method, covering 28 counties (districts) and 112 schools. The 2014-2015 dataset primarily focuses on follow-up data from seventh-grade students who participated in the baseline survey. A total of 9,449 students were successfully interviewed, and after addressing missing values and outliers in the core variables based on research requirements, 7,894 valid samples were retained for analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eVariable Selection and Definition\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn this study, the development of junior high school students\u0026apos; non-cognitive abilities serves as the dependent variable. Drawing on Zhou Jinan\u0026rsquo;s (2021) framework for measuring non-cognitive abilities in Chinese primary and secondary schools, and aligning with the survey items in CEPS, three key indicators of \u0026quot;resilience\u0026quot;, \u0026quot;cooperation\u0026quot; and \u0026quot;emotional stabilities\u0026quot; were selected for measurement. the descriptions of these variables and the corresponding question items in CEPS are detailed in Table 1.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eTable\u0026nbsp;\u003c/em\u003e\u003cem\u003e1\u003c/em\u003e\u003cem\u003e\u0026nbsp;Definition of Non-cognitive Abilities Variable\u003c/em\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003eIndicator\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003eVariable Description\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 250px;\"\u003e\n \u003cp\u003eCorresponding question items in CEPS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003eOptions\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003eResilience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003ePeople\u0026apos;s persistence and enthusiasm for long-term goals, the quality of pursuing goals and beliefs in the face of adversity [13]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 250px;\"\u003e\n \u003col\u003e\n \u003cli\u003eeven if I am a little unwell or have another reason to stay home, I still try to go to school.\u003c/li\u003e\n \u003cli\u003eI try my best to do my homework even if I don\u0026apos;t like it.\u003c/li\u003e\n \u003cli\u003eEven if it takes me a long time to finish my homework, I still try my best to do it。.\u003c/li\u003e\n \u003cli\u003eI can keep up with my hobbies.\u003c/li\u003e\n \u003c/ol\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eTotally disagree = 1\u003c/p\u003e\n \u003cp\u003eNot at all agree = 2\u003c/p\u003e\n \u003cp\u003eQuite agree = 3\u003c/p\u003e\n \u003cp\u003eCompletely agree = 4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003eCooperation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003eThe psychological desire to learn and contribute with others [14]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 250px;\"\u003e\n \u003col\u003e\n \u003cli\u003emost of the students in my class are friendly to me.\u003c/li\u003e\n \u003cli\u003ethe classroom culture in my class is good\u003c/li\u003e\n \u003cli\u003eI often participate in activities organized by the school or class\u003c/li\u003e\n \u003cli\u003eI feel close to people in this school\u003c/li\u003e\n \u003c/ol\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003eCompletely disagree = 1\u003c/p\u003e\n \u003cp\u003eQuite disagree = 2\u003c/p\u003e\n \u003cp\u003eComparatively agree = 3\u003c/p\u003e\n \u003cp\u003eTotally agree = 4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003eEmotional Stabilities\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003eAn individual\u0026apos;s control and regulation of his or her own emotions, negative emotions include characteristics such as anxiety, depression, frustration, and vulnerabilities[15]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 250px;\"\u003e\n \u003col\u003e\n \u003cli\u003eIn the past seven days, have you felt depressed.\u003c/li\u003e\n \u003cli\u003eIn the past seven days, have you felt so depressed that you could not concentrate on anything.\u003c/li\u003e\n \u003cli\u003eIn the past seven days, did you feel unhappy.\u003c/li\u003e\n \u003cli\u003eIn the past seven days, have you felt that life is not interesting.\u003c/li\u003e\n \u003cli\u003eWithin the past seven days, have you felt so demotivated that you couldn\u0026apos;t concentrate on things\u003c/li\u003e\n \u003cli\u003eWithin the past seven days, have you felt sad and upset.\u003c/li\u003e\n \u003cli\u003eIn the past seven days, have you felt nervous.\u003c/li\u003e\n \u003cli\u003ein the past seven days, did you worry too much.\u003c/li\u003e\n \u003cli\u003ein the past seven days, did you have a premonition that something bad was going to happen.\u003c/li\u003e\n \u003c/ol\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eNever = 5\u003c/p\u003e\n \u003cp\u003eRarely = 4\u003c/p\u003e\n \u003cp\u003eSometimes = 3\u003c/p\u003e\n \u003cp\u003eOften = 2\u003c/p\u003e\n \u003cp\u003eAlways = 1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eIn this study, factor influencing the development of junior high school students\u0026apos; non-cognitive abilities were categorized into two levels: individual and school (Table 2). At the individual-level, factors were further divided into personal and family influence. Personal influences included gender[11], appearance[16], immigrant status[17], boarding status[18], and hours of exercise [19]. Family influences primarily encompassed family background [20,21]and parental involvement [22,23,24,25].\u0026nbsp;At the School-level, three indicators were selected: school type, school location, and school ranking. The selected variables were transformed and filtered based on the variable definitions in the CEPS (2014-2015) questionnaire. Descriptive statistics were applied to analyze the data, and the results are detailed in Table 3.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eTable 2 Definition of Explanatory Variables\u003c/em\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"558\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003eVariable type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eVariable name\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 171px;\"\u003e\n \u003cp\u003eCorresponding question item in CEPS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003eVariable description\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"12\" valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003eIndividual-level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 162px;\"\u003e\n \u003cp\u003eWhat is your gender?\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 179px;\"\u003e\n \u003cp\u003eFemale = 0, Male = 1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eappearance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 162px;\"\u003e\n \u003cp\u003eHow do you think you have an appearance?\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 179px;\"\u003e\n \u003cp\u003e(very ugly, rather ugly) = 1, average = 2, (rather beautiful, very beautiful) = 3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eMigration\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 162px;\"\u003e\n \u003cp\u003eWhere is your home now?\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 179px;\"\u003e\n \u003cp\u003eThis county = 0, out of county = 1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eBoarding\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 162px;\"\u003e\n \u003cp\u003eDo you board at school Monday through Thursday nights?\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 179px;\"\u003e\n \u003cp\u003eNo=0, Yes=1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eHours of exercise\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 162px;\"\u003e\n \u003cp\u003eHow long do you usually exercise: () days per week, () minutes per day.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 179px;\"\u003e\n \u003cp\u003eExcluding extreme values where exercise per day exceeds 360 minutes, duration = ln (days per week * exercise per day)/7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003eFamily background\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eEconomic\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 162px;\"\u003e\n \u003cp\u003eHow do you think your family\u0026apos;s financial situation is now?\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 179px;\"\u003e\n \u003cp\u003eVery difficult=1, more difficult=2, moderate=3, richer=4, very rich=5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eCultural\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 162px;\"\u003e\n \u003cp\u003eDoes your family have a lot of books?\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 179px;\"\u003e\n \u003cp\u003eFew = 1, less = 2, average = 3, more = 4, many = 5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eEducational\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 162px;\"\u003e\n \u003cp\u003eFather\u0026apos;s education level?\u003c/p\u003e\n \u003cp\u003eMother\u0026apos;s education level?\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 179px;\"\u003e\n \u003cp\u003eNo at all = 0, Elementary school = 6, Junior high school=9, Vocational high school/general high school = 12, University college=15, Undergraduate college = 16, Graduate school and above = 19\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eSocial class\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 162px;\"\u003e\n \u003cp\u003eWhat kind of work does your father do now?\u003c/p\u003e\n \u003cp\u003eWhat kind of work does your mother do now?\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 179px;\"\u003e\n \u003cp\u003eGovernment = 12, Institution = 11, Scientist = 10, Doctor = 9, Accountant = 8, General Employee = 7, Service Worker = 6, Laborer = 5, Farming, Livestock, and Fishing = 4, Laborer = 3, Self-employed = 2, Unemployed = 1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003eParental involvement\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eParent-child relationship\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 162px;\"\u003e\n \u003cp\u003eHow is your relationship with your dad?\u003c/p\u003e\n \u003cp\u003eHow is your relationship with your mom?\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 179px;\"\u003e\n \u003cp\u003eNot close = 1, normal = 2, very close = 3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eEducational Expectations\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 162px;\"\u003e\n \u003cp\u003eWhat are your parents\u0026apos; educational expectations for you?\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 179px;\"\u003e\n \u003cp\u003eIndifferent = 0, Below college = 1, College = 2, Undergraduate = 3, Graduate = 4, Ph.D. = 5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eFuture Confidence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 162px;\"\u003e\n \u003cp\u003eDo your parents have confidence in your future?\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 179px;\"\u003e\n \u003cp\u003eNot at all = 1, Not too confident = 2, More confident = 3, Very confident = 4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003eSchool-level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eSchool type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 162px;\"\u003e\n \u003cp\u003eThe type of school your school belongs to?\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 179px;\"\u003e\n \u003cp\u003ePublic school = 1, (privately-run, ordinary private school) = 2, privately-run school for working children = 3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eSchool location\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 162px;\"\u003e\n \u003cp\u003eWhat is the type of area where the school is located?\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 179px;\"\u003e\n \u003cp\u003eCentral urban area = 1, (Marginal urban area, urban-rural interface) = 2, (Outside urban area, town, rural area) = 3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eSchool ranking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 162px;\"\u003e\n \u003cp\u003eIn terms of school performance, where does your junior high school currently rank in the county (district)?\u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 179px;\"\u003e\n \u003cp\u003eWorst = 1, Lower middle = 2, Middle = 3, Upper middle = 4, Best = 5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eTable 3 Descriptive Statistical Analysis of All Variables\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003eVariable Type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003eVariable Name\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eSample size\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eStandardize\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003eMin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003eMax\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 198px;\"\u003e\n \u003cp\u003eExplained Variables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 346px;\"\u003e\n \u003cp\u003eNon-cognitive abilities\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003eResilience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e7894\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e3.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003eCooperation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e7894\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e3.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003eEmotional Stabilities\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e7894\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e3.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 198px;\"\u003e\n \u003cp\u003eExplanatory Variables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 346px;\"\u003e\n \u003cp\u003eIndividual-level\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 198px;\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e7894\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 198px;\"\u003e\n \u003cp\u003eappearance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e7894\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e2.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 198px;\"\u003e\n \u003cp\u003eMigration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e7894\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.178\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 198px;\"\u003e\n \u003cp\u003eBoarding\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e7894\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 198px;\"\u003e\n \u003cp\u003eHours of exercise\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e7894\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e22.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e23.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e300\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 198px;\"\u003e\n \u003cp\u003eFamily background\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e7894\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e2.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e1.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e8.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003eEconomic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e7894\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e2.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003eCultural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e7894\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e3.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e1.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003eEducational\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e7894\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e2.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e4.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSocial class\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e7894\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 198px;\"\u003e\n \u003cp\u003eParental involvement\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e7894\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e2.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e4.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003eParent-child relationship\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e7894\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e2.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e1.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003eEducational Expectations\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e7894\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e2.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e1.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003eFuture Confidence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e7894\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e3.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 198px;\"\u003e\n \u003cp\u003eExplanatory Variables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 346px;\"\u003e\n \u003cp\u003eSchool-level\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003eSchool type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e110\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e1.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003eSchool location\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e110\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e1.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003eSchool ranking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e110\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e3.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eModel construction\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHLM, proposed by Roudebush [26], is an extension of traditional linear regression model designed to analyze non-independent data with a multilevel nested structure. HLM has been widely applied in fields such as teacher job satisfaction[27], student academic achievement[28], early childhood education[29], and teaching quality [30], enabling researchers to examine influences at both individual and group levels simultaneously. In this study, HLM is employed to account for the nested structure of students within schools. At the individual-level, factors such as gender, appearance, Hours of exercise, family background, and parental involvement significantly influence junior high school students\u0026apos; noncognitive abilities. However, students are nested within schools, and school-level factors (e.g., school type, location, and ranking) may also impact these abilities. Specifically, the development of non-cognitive abilities is shaped not only by individual-level factors but also by the school context, with potential interactions between the two levels (Figure 1). For instance, school-level variables may moderate the effects of individual-level factors, thereby influencing non-cognitive development.\u003c/p\u003e\n\u003cp\u003eBased on the above analysis, it is essential to examine the factors influencing the development of junior high school students\u0026rsquo; non-cognitive abilities at both the individual and school-levels. To achieve this, a HLM was constructed, and the data were processed using SPSS26.0. The overall model fit was evaluated using the maximum likelihood value. The mechanisms and interactions of these influencing factors were explored by analyzing four models: Model 1 (null model), Model 2, Model 3 and Model 4. Among them, the non-cognitive abilities development of junior high school students was used as an explanatory variable, while individual-level and school-level factors were used as explanatory variables, and the HLM formula was as follows:\u003c/p\u003e\n\u003cp\u003eModel 1 (null model)\u003c/p\u003e\n\u003cp\u003eHierarchical Model:\u003cem\u003e\u0026nbsp;L1: Non-cognitive\u0026nbsp;\u003c/em\u003eU\u003cem\u003e\u003csub\u003eij\u0026nbsp;\u003c/sub\u003e\u003c/em\u003e=\u0026nbsp;b\u003cem\u003e\u003csub\u003e0j\u003c/sub\u003e\u003c/em\u003e +\u0026nbsp;l\u003cem\u003e\u003csub\u003eij\u003c/sub\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eL2:\u003c/em\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;b\u003cem\u003e\u003csub\u003e0j\u003c/sub\u003e\u003c/em\u003e =\u0026nbsp;g\u003cem\u003e\u003csub\u003e00\u003c/sub\u003e\u003c/em\u003e +\u0026nbsp;m\u003cem\u003e\u003csub\u003e0j\u003c/sub\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eMixed Model:\u0026nbsp;\u003cem\u003eNon-cognitive\u0026nbsp;\u003c/em\u003eU\u003cem\u003e\u003csub\u003eij\u0026nbsp;\u003c/sub\u003e\u003c/em\u003e=\u0026nbsp;g\u003cem\u003e\u003csub\u003e00\u003c/sub\u003e\u003c/em\u003e +\u0026nbsp;m\u003cem\u003e\u003csub\u003e0j\u003c/sub\u003e\u003c/em\u003e +\u0026nbsp;l\u003cem\u003e\u003csub\u003eij\u003c/sub\u003e\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eL1\u0026nbsp;\u003c/em\u003erepresents the individual-level,\u003cem\u003e\u0026nbsp;L2\u0026nbsp;\u003c/em\u003erepresents the school-level, \u003cem\u003ei\u0026nbsp;\u003c/em\u003eis the student number, \u003cem\u003ej\u003c/em\u003e is the school number, \u003cem\u003eNon-cognitive\u0026nbsp;\u003c/em\u003eU\u003cem\u003e\u003csub\u003eij\u003c/sub\u003e\u003c/em\u003e is the explanatory variable, it is the non-cognitive abilities of \u003cem\u003ei\u0026nbsp;\u003c/em\u003estudent in the\u003cem\u003e\u0026nbsp;j\u0026nbsp;\u003c/em\u003eschool;\u0026nbsp;b\u003cem\u003e\u003csub\u003e0j\u003c/sub\u003e\u003c/em\u003e is the mean of the \u003cem\u003ej\u003c/em\u003e school; l\u003cem\u003e\u003csub\u003eij\u003c/sub\u003e\u003c/em\u003e is the random error at the individual-level,\u0026nbsp;g\u003cem\u003e\u003csub\u003e00\u0026nbsp;\u003c/sub\u003e\u003c/em\u003eis the overall mean at the level of all schools,\u0026nbsp;m\u003cem\u003e\u003csub\u003e0j\u003c/sub\u003e\u003c/em\u003e is the random error at the School-level.\u003c/p\u003e\n\u003cp\u003eModel 2\u003c/p\u003e\n\u003cp\u003eHierarchical Model: \u003cem\u003eL1:\u003c/em\u003e \u003cem\u003eNon-cognitive\u0026nbsp;\u003c/em\u003eU\u003cem\u003e\u003csub\u003eij\u0026nbsp;\u003c/sub\u003e\u003c/em\u003e=\u0026nbsp;b\u003cem\u003e\u003csub\u003e0j\u003c/sub\u003e\u003c/em\u003e +\u0026nbsp;b\u003cem\u003e\u003csub\u003enj\u003c/sub\u003e\u003c/em\u003ec\u003cem\u003e\u003csub\u003en\u003c/sub\u003e\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e+\u0026nbsp;l\u003cem\u003e\u003csub\u003eij\u003c/sub\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eL2:\u0026nbsp;\u003c/em\u003eb\u003cem\u003e\u003csub\u003e0j\u0026nbsp;\u003c/sub\u003e\u003c/em\u003e=\u0026nbsp;g\u003cem\u003e\u003csub\u003e00\u003c/sub\u003e\u003c/em\u003e +\u0026nbsp;m\u003cem\u003e\u003csub\u003e0j\u003c/sub\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eb\u003cem\u003e\u003csub\u003enj\u0026nbsp;\u003c/sub\u003e\u003c/em\u003e=\u0026nbsp;g\u003cem\u003e\u003csub\u003en0\u0026nbsp;\u003c/sub\u003e\u003c/em\u003e+\u0026nbsp;m\u003cem\u003e\u003csub\u003enj\u003c/sub\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e(\u003cem\u003en\u0026nbsp;\u003c/em\u003e= 1,2,3,4\u0026hellip;\u0026hellip;,7894)\u003c/p\u003e\n\u003cp\u003eMixed Model:\u0026nbsp;\u003cem\u003eNon-cognitive\u003c/em\u003eU\u003cem\u003e\u003csub\u003eij\u0026nbsp;\u003c/sub\u003e\u003c/em\u003e=\u0026nbsp;g\u003cem\u003e\u003csub\u003e00\u003c/sub\u003e\u003c/em\u003e +\u0026nbsp;m\u003cem\u003e\u003csub\u003e0j\u003c/sub\u003e\u003c/em\u003e +\u0026nbsp;g\u003cem\u003e\u003csub\u003en0\u003c/sub\u003e\u003c/em\u003ec\u003cem\u003e\u003csub\u003en\u003c/sub\u003e\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e+\u0026nbsp;m\u003cem\u003e\u003csub\u003enj\u003c/sub\u003e\u003c/em\u003ec\u003cem\u003e\u003csub\u003en\u0026nbsp;\u003c/sub\u003e\u003c/em\u003e+\u0026nbsp;l\u003cem\u003e\u003csub\u003eij\u003c/sub\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003ec\u003cem\u003e\u003csub\u003en\u003c/sub\u003e\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003eis the\u003cem\u003e\u0026nbsp;n\u0026nbsp;\u003c/em\u003eexplanatory variable in the first level,\u0026nbsp;b\u003cem\u003e\u003csub\u003enj\u003c/sub\u003e\u003c/em\u003e is the slope of the \u003cem\u003en\u003c/em\u003e explanatory variable in the first level,\u0026nbsp;g\u003cem\u003e\u003csub\u003en0\u0026nbsp;\u003c/sub\u003e\u003c/em\u003eis the mean of\u0026nbsp;b\u003cem\u003e\u003csub\u003enj\u003c/sub\u003e\u003c/em\u003e, and\u0026nbsp;m\u003cem\u003e\u003csub\u003enj\u003c/sub\u003e\u003c/em\u003e is the random error of\u0026nbsp;b\u003cem\u003e\u003csub\u003enj\u003c/sub\u003e\u003c/em\u003e. Other symbols are as above.\u003c/p\u003e\n\u003cp\u003eModel 3\u003c/p\u003e\n\u003cp\u003eHierarchical Model: \u003cem\u003eL1:\u003c/em\u003e \u003cem\u003eNon-cognitive\u0026nbsp;\u003c/em\u003eU\u003cem\u003e\u003csub\u003eij\u0026nbsp;\u003c/sub\u003e\u003c/em\u003e=\u0026nbsp;b\u003cem\u003e\u003csub\u003e0j\u003c/sub\u003e\u003c/em\u003e +\u0026nbsp;b\u003cem\u003e\u003csub\u003enj\u003c/sub\u003e\u003c/em\u003ec\u003cem\u003e\u003csub\u003en\u003c/sub\u003e\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e+\u0026nbsp;l\u003cem\u003e\u003csub\u003eij\u003c/sub\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eL2:\u0026nbsp;\u003c/em\u003eb\u003cem\u003e\u003csub\u003e0j\u0026nbsp;\u003c/sub\u003e\u003c/em\u003e=\u0026nbsp;g\u003cem\u003e\u003csub\u003e00\u003c/sub\u003e\u003c/em\u003e +\u0026nbsp;g\u003cem\u003e\u003csub\u003e0m\u003c/sub\u003e\u003c/em\u003ed\u003cem\u003e\u003csub\u003em\u003c/sub\u003e\u003c/em\u003e +\u0026nbsp;m\u003cem\u003e\u003csub\u003e0j\u003c/sub\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eb\u003cem\u003e\u003csub\u003enj\u0026nbsp;\u003c/sub\u003e\u003c/em\u003e=\u0026nbsp;g\u003cem\u003e\u003csub\u003en0\u0026nbsp;\u003c/sub\u003e\u003c/em\u003e+\u0026nbsp;m\u003cem\u003e\u003csub\u003enj\u003c/sub\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e(\u003cem\u003em\u0026nbsp;\u003c/em\u003e= 1,2,3,4\u0026hellip;\u0026hellip;,110)\u003c/p\u003e\n\u003cp\u003eMixed Model:\u0026nbsp;\u003cem\u003eNon-cognitive\u0026nbsp;\u003c/em\u003eU\u003cem\u003e\u003csub\u003eij\u0026nbsp;\u003c/sub\u003e\u003c/em\u003e=\u0026nbsp;g\u003cem\u003e\u003csub\u003e00\u003c/sub\u003e\u003c/em\u003e +\u0026nbsp;g\u003cem\u003e\u003csub\u003e0m\u003c/sub\u003e\u003c/em\u003ed\u003cem\u003e\u003csub\u003em\u003c/sub\u003e\u003c/em\u003e +\u0026nbsp;m\u003cem\u003e\u003csub\u003e0j\u003c/sub\u003e\u003c/em\u003e +\u0026nbsp;g\u003cem\u003e\u003csub\u003en0\u003c/sub\u003e\u003c/em\u003ec\u003cem\u003e\u003csub\u003en\u003c/sub\u003e\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e+\u0026nbsp;m\u003cem\u003e\u003csub\u003enj\u003c/sub\u003e\u003c/em\u003ec\u003cem\u003e\u003csub\u003en\u003c/sub\u003e\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e+\u0026nbsp;l\u003cem\u003e\u003csub\u003eij\u003c/sub\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eg\u003cem\u003e\u003csub\u003en0\u0026nbsp;\u003c/sub\u003e\u003c/em\u003eis the slope of the regression for the \u003cem\u003em\u003c/em\u003e explanatory variable at the school level,\u0026nbsp;d\u003cem\u003e\u003csub\u003em\u003c/sub\u003e\u003c/em\u003e is the\u003cem\u003e\u0026nbsp;m\u003c/em\u003e explanatory variable at the school level, and the other symbols are as above.\u003c/p\u003e\n\u003cp\u003eModel 4\u003c/p\u003e\n\u003cp\u003eHierarchical Model: \u003cem\u003eL1:\u003c/em\u003e \u003cem\u003eNon-cognitive\u0026nbsp;\u003c/em\u003eU\u003cem\u003e\u003csub\u003eij\u0026nbsp;\u003c/sub\u003e\u003c/em\u003e=\u0026nbsp;b\u003cem\u003e\u003csub\u003e0j\u003c/sub\u003e\u003c/em\u003e +\u0026nbsp;b\u003cem\u003e\u003csub\u003enj\u003c/sub\u003e\u003c/em\u003ec\u003cem\u003e\u003csub\u003en\u003c/sub\u003e\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e+\u0026nbsp;l\u003cem\u003e\u003csub\u003eij\u003c/sub\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eL2:\u0026nbsp;\u003c/em\u003eb\u003cem\u003e\u003csub\u003e0j\u0026nbsp;\u003c/sub\u003e\u003c/em\u003e=\u0026nbsp;g\u003cem\u003e\u003csub\u003e00\u003c/sub\u003e\u003c/em\u003e +\u0026nbsp;g\u003cem\u003e\u003csub\u003e0m\u003c/sub\u003e\u003c/em\u003ed\u003cem\u003e\u003csub\u003em\u003c/sub\u003e\u003c/em\u003e +\u0026nbsp;m\u003cem\u003e\u003csub\u003e0j\u003c/sub\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eb\u003cem\u003e\u003csub\u003enj\u0026nbsp;\u003c/sub\u003e\u003c/em\u003e=\u0026nbsp;g\u003cem\u003e\u003csub\u003en0\u0026nbsp;\u003c/sub\u003e\u003c/em\u003e+\u0026nbsp;g\u003cem\u003e\u003csub\u003enm\u003c/sub\u003e\u003c/em\u003ed\u003cem\u003e\u003csub\u003em\u003c/sub\u003e\u003c/em\u003e +\u0026nbsp;m\u003cem\u003e\u003csub\u003enj\u003c/sub\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eMixed Model:\u0026nbsp;\u003cem\u003eNon-cognitive\u0026nbsp;\u003c/em\u003eU\u003cem\u003e\u003csub\u003eij\u0026nbsp;\u003c/sub\u003e\u003c/em\u003e=\u0026nbsp;g\u003cem\u003e\u003csub\u003e00\u003c/sub\u003e\u003c/em\u003e +\u0026nbsp;g\u003cem\u003e\u003csub\u003e0m\u003c/sub\u003e\u003c/em\u003ed\u003cem\u003e\u003csub\u003em\u003c/sub\u003e\u003c/em\u003e +\u0026nbsp;m\u003cem\u003e\u003csub\u003e0j\u003c/sub\u003e\u003c/em\u003e +\u0026nbsp;g\u003cem\u003e\u003csub\u003en0\u003c/sub\u003e\u003c/em\u003ec\u003cem\u003e\u003csub\u003en\u003c/sub\u003e\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e+\u0026nbsp;g\u003cem\u003e\u003csub\u003enm\u003c/sub\u003e\u003c/em\u003ed\u003cem\u003e\u003csub\u003em\u003c/sub\u003e\u003c/em\u003ec\u003cem\u003e\u003csub\u003en\u003c/sub\u003e\u003c/em\u003e +\u0026nbsp;m\u003cem\u003e\u003csub\u003enj\u003c/sub\u003e\u003c/em\u003ec\u003cem\u003e\u003csub\u003en\u003c/sub\u003e\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e+\u0026nbsp;l\u003cem\u003e\u003csub\u003eij\u003c/sub\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eg\u003cem\u003e\u003csub\u003enm\u003c/sub\u003e\u003c/em\u003e is the slope of the \u003cem\u003em\u003c/em\u003e explanatory variable in the school level that explains the slopes of the explanatory variables in the individual level, reflecting the presence of interactions between the strata, and the other symbols are as above.\u003c/p\u003e\n\u003cp\u003eTo analyze the factors influencing the development of junior high school students\u0026apos; non-cognitive abilities using HLM, the applicability of the model must first be validated. Model 1, the null model, specifies the proportion of variance in non-cognitive abilities attributable to school-level factors, assessing the feasibility of applying an HLM. This model includes only the random effect of the school level, with no explanatory variables.\u003c/p\u003e\n\u003cp\u003eModel 2 examines the effects of individual-level variables on non-cognitive abilities, incorporating only individual-level explanatory variables, in this model, the regression coefficients and intercepts of the individual-level equations could be varied randomly across School-levels.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eModel 3 tests the direct effect of School-level variables on non-cognitive abilities, and contains only school-level explanatory variables.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eModel 4, the full model, includes both individual and school-level variables. It verifies the direct effect of school-level factors while allowing individual-level variables to vary randomly across schools.\u003c/p\u003e\n\u003cp\u003eAdditionally, it explores the interaction between individual- and school-level factors in influencing junior high school students\u0026apos; non-cognitive abilities.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThe null model analysis results (Table 4) reveal a between-group variance of 0.024 (P\u0026lt;0.001), indicating significant difference in the development of non-cognitive abilities among junior high school students at the School-level. The Intragroup Correlation Coefficient (ICC) is calculated to be 9.5%, indicating that 9.5% of the variance in non-cognitive abilities is attributable to differences between schools. Based on the criteria that an ICC value greater than 5.9% justifies the use of HLM (Cohen, 1988), this study confirms the appropriateness of employing a HLM approach.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eTable 4 Results of Data Analysis for the Null Model\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eRandom effect\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003eVariance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eStandard error\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eDegree of freedom\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003eLog likelihood (ML)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eNon-cognitive abilities（m\u003csub\u003e0\u003c/sub\u003e）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e108\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e11097.013\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eIndividual-level（R）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e0.232\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eModel 2, a random coefficient regression model, examines the direct effects of individual-level variables on the development of junior high school students\u0026rsquo; non-cognitive abilities. The results (Table 5) indicate significant effects (P\u0026lt;0.001) of gender, appearance, hours of exercise, family background, and parental involvement. Gender has a negative effect, with each unit increase associated with a 0.043-unit decrease in non-cognitive abilities. In contrast, appearance, hours of exercise, family background, and parental involvement show significant positive effects. No significant differences were found for migrant and boarding (P\u0026gt;0.1).\u003c/p\u003e\n\u003cp\u003eModel 3, an intercept model, analyzes the direct effect of school-level variables. School type significantly affects non-cognitive abilities (P\u0026lt;0.05), with each unit increase associated with a 0.071-unit decrease. School location also has a significant negative effect (P\u0026lt;0.1), while school ranking shows no direct effect.\u003c/p\u003e\n\u003cp\u003eModel 4 incorporates both individual- and school-level variables (Table 5), revealing the moderating effects of school-level variables on individual-level factors. Significant interactions include school location and migrant children, showing a significant negative effect (P\u0026lt;0.05); school location and appearance, as well as school ranking and hours of exercise, showing significant positive effects (P\u0026lt;0.05).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eTable 5 Results of the HLM Analysis of the Factors Influencing the Development of Non-cognitive Abilities of Junior High School Student\u003c/em\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eModel 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eModel 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eModel 4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"7\" valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003eIndividual-level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 141px;\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e-0.043\u003csup\u003e***\u003c/sup\u003e（0.011）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e0.015（0.070）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 141px;\"\u003e\n \u003cp\u003eappearance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e0.160\u003csup\u003e***\u003c/sup\u003e（0.012）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e0.027（0.080）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 141px;\"\u003e\n \u003cp\u003eMigration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e-0.043（0.030）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e0.345\u003csup\u003e*\u003c/sup\u003e（0.180）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 141px;\"\u003e\n \u003cp\u003eBoarding\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e-0.021（0.014）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e-0.188（0.137）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 141px;\"\u003e\n \u003cp\u003eHours of exercise\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e0.002\u003csup\u003e***\u003c/sup\u003e（0.000）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e-0.003\u003csup\u003e*\u003c/sup\u003e（0.002）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 141px;\"\u003e\n \u003cp\u003eFamily background\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e0.061\u003csup\u003e***\u003c/sup\u003e（0.006）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e0.051（0.052）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 141px;\"\u003e\n \u003cp\u003eParental involvement\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e0.101\u003csup\u003e***\u003c/sup\u003e（0.006）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e0.089\u003csup\u003e**\u003c/sup\u003e（0.038）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003eSchool-level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 141px;\"\u003e\n \u003cp\u003eSchool type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e-0.071\u003csup\u003e**\u003c/sup\u003e（0.030）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e-0.016（0.081）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 141px;\"\u003e\n \u003cp\u003eSchool location\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e-0.034\u003csup\u003e*\u003c/sup\u003e（0.017）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e-0.090\u003csup\u003e**\u003c/sup\u003e（0.044）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 141px;\"\u003e\n \u003cp\u003eSchool ranking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e0.014（0.018）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e-0.073（0.047）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003eInteraction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 141px;\"\u003e\n \u003cp\u003eSchool location \u0026amp; Migration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e-0.076\u003csup\u003e**\u003c/sup\u003e（0.038）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 141px;\"\u003e\n \u003cp\u003eSchool location \u0026amp; appearance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e0.037\u003csup\u003e**\u003c/sup\u003e（0.015）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 141px;\"\u003e\n \u003cp\u003eSchool ranking \u0026amp; Hours of exercise\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e0.001\u003csup\u003e***\u003c/sup\u003e（0.000）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 141px;\"\u003e\n \u003cp\u003eConstant\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e2.564\u003csup\u003e****\u003c/sup\u003e（0.031）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e3.458\u003csup\u003e***\u003c/sup\u003e（0.089）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e2.993\u003csup\u003e***\u003c/sup\u003e（0.239）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 141px;\"\u003e\n \u003cp\u003eLog-likelihood value\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e10316.866\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e10860.360\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e10059.700\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 141px;\"\u003e\n \u003cp\u003eICC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e0.070\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e0.079\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e0.067\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 141px;\"\u003e\n \u003cp\u003eAIC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e10336.866\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e10872.360\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e10127.700\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 141px;\"\u003e\n \u003cp\u003eBIC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e10406.605\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e10914.078\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e10364.098\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote: (1) \u003csup\u003e***\u003c/sup\u003e, \u003csup\u003e**\u003c/sup\u003e, and \u003csup\u003e*\u003c/sup\u003e are at the 1%, 5%, and 10% levels, respectively; (2) Numbers in parentheses are standard errors of regression coefficients;\u003c/p\u003e\n\u003cp\u003eThe development of junior high school students\u0026rsquo; non-cognitive abilities is influence by factors at both the individual and school levels, as well as their interactions, exhibiting distinct hierarchical characteristics (Figure 2). At the individual level, gender, appearance, hours of exercise, family background, and parental involvement directly affect non-cognitive abilities. At the school level, school type and location also exert significant influences. In addition, the school-level variable indirectly affects non-cognitive abilities by moderating the individual-level factors. The effect of individual-level factors on noncognitive abilities increases with the improvement of school location; The impact of hours of exercise on non-cognitive abilities is enhanced with high school ranking; School location negatively moderates the effect of migrant status on non-cognitive abilities.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eBased on CEPS (2014-2015), this study constructs an HLM to examine the factors influencing junior high school students\u0026apos; non-cognitive abilities. It reveals the mechanism through which individual- and school-level factors directly impact these abilities, as well as their interactions, thereby advancing research in this field.\u003c/p\u003e\n\u003cp\u003eThe study reveals gender differences in non-cognitive abilities among junior high school students, with girls demonstrating superior abilities compared to boys, consistent with Barnett et al.\u0026apos;s finding[11]. This disparity may stem from several factors. First, girls are often socialized to be well-behaved, understanding, and obedient, leading to higher parental expectations and more frequent communication, which fosters self-efficacy and prosocial behaviors [8]. Second, societal gender expectations encourage girls to comply with rules and seek approval, further enhancing their non-cognitive abilities(Christopher et al., 2013).\u003c/p\u003e\n\u003cp\u003eRegarding appearance, students who perceive themselves as more attractive exhibit better-developed non-cognitive abilities, aligning with prior research[31]. Attractive appearance confers advantages in social interactions, emotional experiences, and adaptability. In addition, the study finds that increased hours of exercise positively impact non-cognitive abilities, consistent with Wilson\u0026rsquo;s results [32]. This effect may arise from: (1) Expanded social networks and improved interpersonal skills through exercise[33]; (2) Reduced anxiety and depression, enhanced self-efficacy, and increased future confidence[34]; (3) Positive emotional experiences and a greater willingness to embrace challenges fostered by family and peer involvement in exercise[35].\u003c/p\u003e\n\u003cp\u003eThis study also found the influence of family economic, cultural, and social capital on junior high school students\u0026rsquo; non-cognitive abilities. Families with high economic capital can provide more educational opportunities and create a conducive learning environment[36]. The cultural capital investment enhances students\u0026apos; \u0026quot;soft power,\u0026quot; positively impacting qualities such as openness, resilience, adaptability, and emotional stability. Additionally, high-quality parental communication and companionship foster non-cognitive abilities like self-esteem, cooperation, and interpersonal skills[37], providing children with security and confidence to explore the world.\u003c/p\u003e\n\u003cp\u003eContrary to previous findings by Liu [38] and Curto[39], this study found that migration and boarding status do not significantly affect non-cognitive abilities. This discrepancy may arise from differences in research subjects, as earlier studies primarily focused on elementary school students, who are more dependent on family support, in contrast, junior high school students exhibit greater independence. Additionally, cultural and educational differences may play a role. Compared to the Western emphasis on individuality, Chinese education prioritize cooperation and group living, and boarding schools often provide substantial peer and teacher support, mitigating potential negative effects on non-cognitive abilities.\u003c/p\u003e\n\u003cp\u003eAt the School-level, both school type and location significantly influence the non-cognitive abilities of junior high school students. Firstly, public schools, characterized by abundant education resources, high operational costs, and substantial investments, meet parental expectations for quality education[20]. These institutions, equipped with advanced facilities, diverse curricula, and rich experience teachers, subtly enhance students\u0026rsquo; non-cognitive abilities. Secondly, schools located near central urban areas, often with long operational histories, well-established institutional norms, and rigorous cultivation standards, exert a profound impact through their word-of-mouth, environmental, and role model effects[40]. These factors shape students\u0026rsquo; learning attitudes and future development expectations, fostering continuous self-improvement and influencing their non-cognitive abilities development. Lastly, the non-cognitive abilities of junior high school students are closely linked to teachers\u0026rsquo; teaching experience. Experienced teachers, particularly those in public schools where recruitment criteria emphasize both academic qualifications and teaching experience, effectively enhance students\u0026rsquo; non-cognitive abilities, especially in areas such as extraversion and neuroticism[41], thereby promoting socio-emotional development.\u003c/p\u003e\n\u003cp\u003eThis study further identifies a moderating effect of school-level variables on the relationship between individual-level factors and the non-cognitive abilities of junior high school students. Specifically, the impact of migration on students\u0026apos; non-cognitive abilities varies by school location. Schools farther from urban centers tend to exhibit lower levels of non-cognitive development among students, likely due to unequal distribution of educational resources, limited transportation accessibility, and geographic isolation[42]. These constraints restrict students\u0026apos; access to resources, thereby hindering their non-cognitive skill development. Additionally, the influence of an appearance on non-cognitive abilities is moderated by school location. Schools in central urban areas, characterized by rigorous discipline, high academic expectations, and a focus on knowledge and personality development, place less emphasis on external image[31]. In contrast, students in remote areas often prioritize appearance to gain social recognition and avoid negative evaluations, diverting time and energy from other developmental activities[31]. Moreover, the effect of physical activity time on non-cognitive abilities is positively correlated with school ranking. Higher-ranked schools prioritize students\u0026apos; physical health and holistic development by providing advanced exercise facilities, fostering a supportive exercise environment, and encouraging sports-related interactions[43]. This promotes extroverted personalities, enhances trust, and cultivates pro-social behaviors, thereby strengthening non-cognitive abilities.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLimit\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study offers a novel perspective and theoretical framework for examining the factors influencing junior high school students\u0026apos; non-cognitive abilities using HLM. However, several limitations should be acknowledged. First, while non-cognitive abilities are shaped by a multitude of factors, the study\u0026apos;s selected indicators are limited. Future research could incorporate a broader range of measurement indices to explore this issue from multiple dimensions, thereby enhancing the precision and explanatory power of the model. Second, the study relies on data from the CEPS conducted in 2014\u0026ndash;2015. Utilizing more recent data in future studies would provide a more accurate understanding of the current factors affecting students\u0026apos; non-cognitive abilities. Finally, while the HLM model was employed to analyze the effects of individual-level and school-level variables, as well as their interaction mechanisms, future research could expand the framework by incorporating additional layers of variables, such as family-level factors. This would enable a more comprehensive exploration of the interactions among individual, school, and family variables, further advancing the depth of the study.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe study revealed the following key findings: (1) junior high school students\u0026apos; non-cognitive abilities are directly and interacted influenced by factors at both the individual and School-levels; (2) at the individual level, gender, appearance, hours of exercise, family background, and parental involvement, as well as at the School-level the type of school and school location can directly influence junior high school students\u0026apos; non-cognitive abilities to varying degrees; \u0026nbsp;(3) the school location and migration, school location and appearance, school ranking and hours of exercise interacted with each other to influence the development of junior high school students\u0026apos; non-cognitive abilities.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data collection was approved by the ethics committee of Renmin university of China, and each participant was informed of the purpose of this research. This manuscript does not apply to clinical trial numbers.\u0026nbsp;All participants had given their informed consent. Their parents or legal guardians had also given informed consent.\u0026nbsp;And this study complies with the Helsinki Declaration.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe original contributions presented in the study are included in the article material, further inquiries can be directed to the corresponding author.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eThe authors declare no competing interests.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe project is not supported by the funding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor\u0026rsquo;s contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWYY Contributed to the study design and manuscript draft. ZXB was data analysis. ZXK gave critical feedback. All authors have read and approved the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank the China Education Panel Survey (CEPS) for data access and colleagues at the Capital University of Physical Education and Sports for their feedback. All errors remain our own.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData source\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis institute is an open questionnaire, questionnaire url is: http://ceps.ruc.edu.cn/xmwd/dcwj.htm. Data of the site at: http://www.cnsda.org/index.php?r=projects/view\u0026amp;id=61662993, \u0026nbsp;if the data you have any questions please contact email: [email protected]\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eRoberts BW, Kuncel NR, Shiner R, Caspi A, Goldberg LR. 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Teaching quality and student achievement inequalities in low- and middle-income countries: A hierarchical linear model analysis. Studies in Educational Evaluation. 2024;83:101419. \u003c/li\u003e\n\u003cli\u003eXie Y, Fan Y, He J. Perceived appearance, body shape and adolescent academic achievement: Evidence from Chinese middle school. Br Educ Res J. 2023;49:1338\u0026ndash;56.\u003c/li\u003e\n\u003cli\u003eWilson KE, Dishman RK. Personality and physical activity: A systematic review and meta-analysis. Personality and Individual Differences. 2015;72:230\u0026ndash;42. \u003c/li\u003e\n\u003cli\u003eStubbs B, Koyanagi A, Hallgren M, Firth J, Richards J, Schuch F, et al. Physical activity and anxiety: A perspective from the World Health Survey. Journal of Affective Disorders. 2017;208:545\u0026ndash;52.\u003c/li\u003e\n\u003cli\u003eKnapen J, Vancampfort D, Mori\u0026euml;n Y, Marchal Y. Exercise therapy improves both mental and physical health in patients with major depression. 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Solution or isolation: Is boarding school a good solution for left-behind children in rural China? China Economic Review. 2020;61:101456. \u003c/li\u003e\n\u003cli\u003eCurto VE, Jr RGF. The Potential of Urban Boarding Schools for the Poor: Evidence from SEED. Journal of Labor Economics. 2014; \u003c/li\u003e\n\u003cli\u003eFasasi RA. Effects of ethnoscience instruction, school location, and parental educational status on learners\u0026rsquo; attitude towards science. Int J Sci Educ. 2017;39:548\u0026ndash;64. \u003c/li\u003e\n\u003cli\u003eChen B, Zhao C. Teachers\u0026rsquo; administrative positions and students\u0026rsquo; non-cognitive abilities in China: evidence from a quasi-natural experiment. Appl Econ. 2024;56:6091\u0026ndash;108\u003c/li\u003e\n\u003cli\u003eMoreno-Monroy AI, Lovelace R, Ramos FR. Public transport and school location impacts on educational inequalities: Insights from Sao Paulo. J Transp Geogr. 2018;67:110\u0026ndash;8. \u003c/li\u003e\n\u003cli\u003eDerek W, Craig, Timothy J., Walker, Shreela V., Sharma, et al. Examining associations between school-level determinants and the implementation of physical activity opportunities-Web of Science Core Collection. Translational Behavioral Medicine. 2024;89\u0026ndash;97.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"HLM, Junior high school students, Non-cognitive abilities, China Education Panel Survey, Influencing factors","lastPublishedDoi":"10.21203/rs.3.rs-6379829/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6379829/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Non-cognitive abilities are essential for adolescent development, yet research examining their multilevel determinants remains limited. While prior studies have identified individual or school-level factors independently, few have investigated how these levels interact to shape non-cognitive development during the critical junior high school period.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003e\u0026nbsp;Using data from 7,894 students in the China Education Panel Survey (CEPS), this study employed Hierarchical Linear Modeling (HLM) to simultaneously examine individual and school-level predictors. The analysis focused on three dimensions of non-cognitive abilities (resilience, cooperation, and emotional stability) while testing cross-level interactions between student characteristics and school environment factors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e Individual-level analysis revealed significant effects of gender (β=-0.043), appearance (β=0.160), exercise time (β=0.002), family background (β=0.061), and parental involvement (β=0.101). School-level factors showed school type (β=-0.071) and locations (β=-0.034) significantly predicted outcomes. Notably, school location moderated the effects of migration status (β=-0.076) and appearance (β=0.037), while school ranking enhanced exercise benefits (β=0.001).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eThis study demonstrates the complex interplay between individual and school factors in shaping non-cognitive abilities. The findings suggest that educational interventions should adopt a multilevel approach, addressing both student characteristics and school environment improvements, particularly in resource allocation for rural schools and physical activity programs. These results provide both theoretical insights for developmental psychology and practical guidance for educational policy-making.\u003c/p\u003e","manuscriptTitle":"A Study on the Influencing Factors of Non-Cognitive Abilities of Junior High School Students Based on Hierarchical Linear Models","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-30 08:57:18","doi":"10.21203/rs.3.rs-6379829/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"23d057bf-78de-4922-a148-b2cc9917e456","owner":[],"postedDate":"May 30th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-12-24T11:39:34+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-30 08:57:18","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6379829","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6379829","identity":"rs-6379829","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}