Beyond the Bell: After-School Programs and Educational Equity in Chinese Primary and Secondary Schools

Abstract

In 2021, China introduced the “double reduction” policy, imposing strict regulations on shadow education and mandating the widespread implementation of after-school programs (ASPs). Against this backdrop, this study examines the role of ASPs in China’s compulsory education system from an equity perspective. By integrating school resources and family background, the study establishes a theoretical framework for understanding the factors influencing educational equity. Building upon this framework, it compares ASPs with shadow education and constructs a conceptual roadmap illustrating the impact mechanisms of ASPs on educational equity. To empirically test this framework, the study employs a Structural Equation Modeling (SEM) approach, analyzing questionnaire data from 1,458 primary and secondary school students in Shenzhen, China. The findings reveal that ASPs partially mediate the relationship between family cultural capital and students’ educational outcomes. Additionally, school resources play a significant role in enhancing student participation in ASPs. Notably, the educational outcomes of students engaged in ASPs are more strongly influenced by school-related factors. Compared to shadow education, school-organized and publicly funded ASPs have demonstrated greater effectiveness in promoting social equity. This study provides empirical evidence supporting the role of ASPs in replacing shadow education as a means to enhance educational equity. By verifying their effectiveness and specific impact pathways, the research offers valuable insights into the development of ASPs in China. Furthermore, it presents practical recommendations for global policymakers and educators committed to fostering educational equity.

Full text

Original Research
SAGE Open
April-June 2025: 1–23
ÓThe Author(s) 2025
DOI: 10.1177/21582440251336078
journals.sagepub.com/home/sgo
Beyond the Bell: After-School Programs
and Educational Equity in Chinese
Primary and Secondary Schools
Ping Wang
1
,FeiyeWang
1
, Yongbin Peng
1
, and Zhiyuan Li
1
Abstract
In 2021, China introduced the ‘‘double reduction’’ policy, imposing strict regulations on shadow education and mandating the
widespread implementation of after-school programs (ASPs). Against this backdrop, this study examines the role of ASPs in
China’s compulsory education system from an equity perspective. By integrating school resources and family background, the
study establishes a theoretical framework for understanding the factors influencing educational equity. Building upon this
framework, it compares ASPs with shadow education and constructs a conceptual roadmap illustrating the impact mechan-
isms of ASPs on educational equity. To empirically test this framework, the study employs a Structural Equation Modeling
(SEM) approach, analyzing questionnaire data from 1,458 primary and secondary school students in Shenzhen, China. The
findings reveal that ASPs partially mediate the relationship between family cultural capital and students’ educational outcomes.
Additionally, school resources play a significant role in enhancing student participation in ASPs. Notably, the educational out-
comes of students engaged in ASPs are more strongly influenced by school-related factors. Compared to shadow education,
school-organized and publicly funded ASPs have demonstrated greater effectiveness in promoting social equity. This study
provides empirical evidence supporting the role of ASPs in replacing shadow education as a means to enhance educational
equity. By verifying their effectiveness and specific impact pathways, the research offers valuable insights into the development
of ASPs in China. Furthermore, it presents practical recommendations for global policymakers and educators committed to
fostering educational equity.
Keywords
after-school programs, educational equity, shadow education, family background, school resources
Introduction
Education is a crucial driver of intergenerational mobility
and a primary mechanism for the reproduction of social
class (Belsky et al., 2018). To enhance educational compe-
titiveness, an increasing number of families are extending
their investments beyond traditional classroom learning
to include out-of-school tutoring, commonly known in
academic discourse as ‘‘shadow education’’ (Marimuthu
et al., 1991). Shadow education is closely linked to social
class, family capital, and educational outcomes. Privileged
social groups often utilize shadow education to maintain
and reinforce social inequality, ultimately undermining
educational equity (Hajar & Karakus, 2022; Xue, 2018).
The prevalence of shadow education has become a
significant policy concern in East Asia, particularly in
South Korea, where approximately 74.5% of K-12
students participated in shadow education in 2019
(Korean Statistical Information Service [KOSIS], 2020).
According to data from the Organization for Economic
Cooperation and Development (OECD), South Korea
allocates the highest proportion of GDP to shadow edu-
cation among Asian OECD member countries (OECD,
2020). However, excessive investment in private educa-
tion can deepen educational inequality (Jung, 2022) and
reduce financial returns (J. S. Han & Lee, 2020). The
pursuit of high-paying jobs often leads to over-
1
East China Normal University, Shanghai, China
Corresponding Author:
Feiye Wang, Faculty of Education, East China Normal University, No. 3663
North Zhongshan Road, Shanghai 200062, China.
Email: fywang@ses.ecnu.edu.cn
Creative Commons CC BY: This article is distributed under the terms of the Creative Commons Attribution 4.0 License
(https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of
the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages
(https://us.sagepub.com/en-us/nam/open-access-at-sage).

education, where individuals acquire more education
than is economically justified by job market premiums.
Additionally, as wage inequality widens, competition for
education intensifies, further amplifying disparities
rooted in family background (Chung & Lee, 2017).
In recent years, shadow education in China’s compul-
sory education system has undergone significant capitali-
zation and expansion. By 2019, more than 20 Chinese
education and training companies were publicly listed on
stock markets in mainland China, Hong Kong, and the
United States (Fiscal First-Quarter, 2019). As a result,
shadow education has transformed into a large-scale
industry, providing educational services to millions of
students and becoming a crucial component of the educa-
tion sector (Feng, 2021). This rapid growth has sparked
considerable concern and debate among scholars.
Xue (2015) applied a logistic regression model to ana-
lyze students’ participation in extracurricular tutoring
during the compulsory education stage, highlighting
shadow education’s role in reinforcing urban-rural and
intergenerational class disparities while undermining gov-
ernment efforts to implement equitable education poli-
cies. Similarly, Fang and Huang (2020), using data from
the China Education Tracking Survey and a generalized
quantile regression framework, demonstrated how the
escalating ‘‘arms race’’ in off-campus training expendi-
tures exacerbates inequalities in educational outcomes.
Building on Bourdieu’s concept of capital, Zhang et al.
(2021) employed a Tobit regression model to investigate
the relationship between family capital, participation in
off-campus training, and associated expenses. Their find-
ings reveal that family capital plays a decisive role in
accessing off-campus training resources, thereby creating
new disparities in educational opportunities.
To promote educational equity, reduce the academic
burden on primary and secondary school students, and
alleviate financial pressures on families, the General
Office of the Central Committee of the Communist Party
of China and the General Office of the State Council
issued the Opinions on Further Reducing the Homework
Burden and Off-Campus Training Burden of Students in
Compulsory Education in 2021, commonly known as the
‘‘double reduction’’ policy. Under this policy, primary
and secondary schools in China are required to offer
after-school programs (ASPs) either free of charge or at
a cost-recovery rate, adhering to non-profit principles.
At the same time, the government has implemented strin-
gent regulations on shadow education, prohibiting off-
campus training institutions from providing subject-
based tutoring during national holidays, weekends, and
school vacations (The Xinhua News Agency, 2021).
The ‘‘double reduction’’ policy aims to reinforce the
primary role of school-based education, enhance the
governance of off-campus training institutions, and
support the holistic development and well-being of stu-
dents. Following its implementation, major domestic
education and training companies, such as New Oriental
and TAL, faced significant financial challenges, includ-
ing cash flow constraints and the need for extensive busi-
ness restructuring to adapt to the evolving educational
landscape (S. Yu et al., 2022). Meanwhile, ASPs have
seen widespread adoption, with approximately 91.9% of
students participating in these programs (Lin, 2022).
Given this shift, it can be argued that ASPs have, to
some extent, replaced traditional shadow education
practices.
Given this context, this study seeks to address two
key questions: (1) Can after-school programs (ASPs)
mitigate the educational inequalities caused by shadow
education and promote educational equity? (2) If so,
what specific pathways and mechanisms drive this
impact? To answer these questions, this study utilizes
survey data collected in 2022 from primary and second-
ary schools in Shenzhen, China. By examining the influ-
ence of school resources and family background on
social reproduction, it investigates the value of ASP
initiatives and empirically assesses their role in advancing
educational equity.
Theoretical Foundations
This section first examines the mechanisms influencing
educational equity and establishes the fundamental theo-
retical framework of the study. It then integrates ASPs
into this framework to develop the final theoretical
foundation.
The Impact Mechanism of Educational Equity
This subsection explores the intricate relationships
among family background, school resources, educational
outcomes, and educational equity. First, it analyzes the
connection between educational outcomes and educa-
tional equity. Next, it examines how family background
shapes access to education and contributes to disparities
in equity. This is followed by an investigation into the
role of school resources in mitigating or exacerbating
these inequalities. Finally, these elements are synthesized
to construct the study’s foundational theoretical
framework.
The Relationship Between Educational Outcomes and
Educational Equity. ‘‘Educational outcomes’’ and ‘‘educa-
tional equity’’ are closely related yet distinct concepts in
the field of education. Their relationship raises a critical
question: Is the evaluation and distribution of education
fair and accessible to all members of society?
2SAGE Open

The Organization for Economic Co-operation and
Development (OECD) explored this relationship in its
2018 report on equity in education, emphasizing that all
schools and education systems should offer equal learn-
ing opportunities to all students (OECD, 2018).
According to this perspective, students from diverse
socioeconomic backgrounds, genders, and family or
immigration statuses should achieve comparable educa-
tional outcomes in key cognitive domains such as read-
ing, mathematics, and science, as well as exhibit similar
levels of social and emotional well-being (OECD, 2018).
In essence, educational equity is achieved when educa-
tional outcomes become more equalized. Conversely,
when disparities in achievement persist or widen, educa-
tional equity is compromised.
The Influence of Family Background on Educational Outcomes
and Equity. The British Plowden Report (Blackstone,
1967) argued that family background is a more signifi-
cant predictor of differences in students’ academic per-
formance than the school itself. The ‘‘status acquisition
model,’’ introduced by Blau and Duncan (1967), empha-
sizes the critical role of family capital in shaping students’
educational outcomes. Subsequent research explored dis-
parities in educational outcomes among students from
various social strata.
Building on this foundation, Boudon (1976) intro-
duced the concept of the ‘‘Primary Effect,’’ which high-
lights the role of resource acquisition in shaping students’
educational trajectories. Raftery and Hout (1993) pro-
posed the Maximally Maintained Inequality (MMI) the-
ory, while Lucas (2001) developed the Effectively
Maintained Inequality (EMI) theory. Both theories
recognize that students from privileged social classes are
granted preferential access to higher-quality educational
opportunities, with resources tailored to their specific
interests and needs. In contrast, students from disadvan-
taged backgrounds are left with fewer educational
opportunities.
The key distinction between the MMI and EMI the-
ories lies in their predictions regarding the impact of
compulsory education. The MMI theory suggests that
the gap between social classes narrows as compulsory
education becomes more widespread. On the other hand,
the EMI theory posits that the post-compulsory educa-
tion era intensifies competition focused on the quality of
education, thereby exacerbating class-based disparities.
These theories further highlight the structural inequal-
ities in the provision of educational resources across dif-
ferent social classes.
In summary, research on educational inequality has
shifted focus from institutional changes and individual
roles to the significant influence of family background.
The connection between family background and
educational outcomes has become a central theme in the
study of educational inequality (Husen, 1975). A growing
body of empirical research (An & Western, 2019;
Bourdieu & Passeron, 1977; Forster & van de Werfhorst,
2020) supports the view that families with higher social,
cultural, economic, and political capital provide their
children with superior educational opportunities.
Children’s academic achievements are closely linked to
their family’s socioeconomic status, which in turn shapes
their learning behaviors and creates distinct educational
environments (The National Center for Education
Statistics, 2018). This influence extends to academic per-
formance in areas such as reading and science (Hung
et al., 2020; Nganga et al., 2019), with significant long-
term implications. As a result, family background contri-
butes to both the quantity and quality of education, hin-
dering the achievement of educational equity.
The Impact of School Resources on Educational Outcomes and
Equity. Dewey (1983) highlighted the crucial role of
schools in providing equal opportunities to students
through effective teaching practices. Similarly, Coleman
(1996) emphasized that schools play a key role in foster-
ing an environment of equality and peer competition.
The educational production function, as proposed by
Greenwald et al. (1996), illustrates how various school
investments—such as adequate resources and reasonable
expenditures—contribute to enhancing student achieve-
ment. Specifically, schools benefit from material
resources like funding and infrastructure (Karl &
Eckland, 1977), human capital such as qualified teachers
(Aaronson et al., 2007), and the influence of peers
(Russell & Gregory, 2005). These factors collectively
shape students’ educational outcomes.
The concept of educational equity has evolved over
time. It has shifted from a focus on equal educational
opportunities to a focus on equal opportunities for edu-
cational outcomes. Equality in academic achievement
does not mean that all students attain the same academic
level. Instead, it means that every student is given the
opportunity to realize their full potential, which is sup-
ported by equitable input elements such as teachers,
facilities, and other educational resources. This ensures a
fair educational process and provides opportunities for
comprehensive personal development (John, 1998). As a
result, active interventions by schools can help address
inequalities in educational opportunities that arise from
broader societal factors.
Empirical research consistently demonstrates positive
associations between various school attributes—such as
academic activities, teacher-student ratios (Oyshi et al.,
2021), and factors like the learning environment and
teaching methods (Chakraborty & Jayaraman, 2019;
Wang et al., 2023)—and student performance in subjects
Wang et al. 3

like mathematics, reading, and science. Schools equipped
with sufficient teachers, facilities, curriculum resources,
and a supportive environment contribute to improved
student learning outcomes, helping to reduce educational
disparities among students from different socioeconomic
backgrounds (Iba
´n
˜ez et al., 2020). Therefore, school
resources play a crucial role in equalizing both the quan-
tity and quality of education, ultimately promoting edu-
cational equity.
Figure 1 illustrates the basic theoretical framework
upon which this research is based. Both school resource
investments and family background can enhance stu-
dents’ academic achievement (+). However, the educa-
tional resources and opportunities provided by schools
are public and equitable, leading to a reduction in aca-
demic achievement gaps and promoting educational
equity (+). In contrast, family background can create dis-
parities in educational resources and opportunities, lead-
ing to an unequal distribution of high-quality resources
and widening achievement gaps, thereby posing a signifi-
cant challenge to educational equity (2).
The Impact Mechanism of ASPs on Educational Equity
Given that After-School Programs (ASPs), introduced
under China’s ‘‘double reduction’’ policy, are closely
linked to shadow education, it is essential to analyze the
role of shadow education in order to understand how
ASPs can serve as a fair alternative.
The Role of Shadow Education in the Impact Mechanism of
Educational Equity. Extracurricular tutoring, commonly
referred to as shadow education, has long posed a chal-
lenge to public education systems across various coun-
tries. In general, wealthier families invest more resources
in shadow education, and the socioeconomic factors
within these families—such as parents’ occupations and
education levels—are closely linked to their children’s
participation in these programs (Bray, 1999). As a result,
shadow education amplifies the impact of family capital
on educational outcomes, potentially acting as a new
intermediary in the intergenerational transmission of
family capital (Xue, 2015).
In public perception, whether regarding formal school
education or non-school education such as family and
social education, investments in education are seen as
yielding future value and long-term returns. Previous
research has predominantly focused on the influence of
family background on the equity of formal school educa-
tion (Bray & Kwok, 2003). However, non-school educa-
tion, particularly shadow education, has emerged as a
key competitive tool for privileged families seeking to
gain an advantage in the educational race (Jansen et al.,
2023). Furthermore, students’ access to shadow educa-
tion and its effects directly influences the fairness of edu-
cational opportunities and, in turn, educational outcomes
(Zhang et al., 2021).
According to the Effectively Maintained Inequality
(EMI) theory (Lucas, 2001), as compulsory education
becomes more widespread, the focus of educational com-
petition among families from different social strata has
shifted from formal school education to shadow educa-
tion. Within this realm, family background plays a cru-
cial role in reinforcing class distinctions, enhancing the
educational acquisition and competitive advantages of
children from privileged backgrounds through interge-
nerational transmission, while creating barriers for those
from disadvantaged backgrounds (Tsiplakides, 2018).
This results in disparities in future educational and
employment opportunities based on varying levels of
family capital. Social stratification (Xue, 2018) refers to
the process by which socioeconomic advantages within
families are converted into future socioeconomic
Figure 1. The impact mechanism of educational equity.
4SAGE Open

advantages for their children. This not only intensifies
academic competition and drains substantial family and
societal resources but also undermines government poli-
cies aimed at promoting educational equity, thereby
exacerbating social inequalities.
In summary, Figure 2 presents the logical framework
illustrating the impact of shadow education on social
equity.
The Role of Shadow Education in the Impact Mechanism of
Educational Equity. Both in-school ASPs and out-of-school
shadow education operate outside the confines of the
official school curriculum, offering supplementary educa-
tional services that complement formal education.
However, there are key differences between the two.
Shadow education is profit-driven and typically provided
by private individuals or businesses (The European
Foundation for the Improvement of Living and Working
Conditions, 2020). It exists outside the public education
system and is sustained by tuition fees paid by families.
In this context, family capital plays a central role in
determining access to these services.
In contrast, ASPs are considered ‘‘quasi-public goods’’
and are funded by government investments in education,
thereby remaining part of the formal school system
(Framework, 2000). ASPs contribute to the development
and well-being of students by providing important
opportunities outside regular school hours (Cureton,
2023). To address the challenges posed by shadow
education, many national governments, such as South
Korea, have adopted ASPs as a key strategy (C. J. Lee
et al., 2010).
In China, the implementation of ASPs involves three
primary components: accessibility for all primary and
secondary school students, alignment with the practical
needs of both parents and students, and promotion of
the overall healthy growth of students (You & Zhou,
2020). These programs have several distinctive features:
they are integrated into the school system, offer a variety
of service content, provide flexible scheduling, and
adhere to inclusive principles while maintaining low ser-
vice fees (You & Zhou, 2020). Consequently, it can be
argued that school-led ASPs have, to some extent,
replaced shadow education by preserving the positive
aspects of school-based educational supplementation,
while reducing the resource-based exclusivity that often
benefits students from privileged backgrounds. Based on
these principles, a theoretical framework has been devel-
oped, as shown in Figure 3.
Research Hypotheses
Family Background: Family Cultural Capital
Over the past 40 years, extensive research has been con-
ducted on the relationship between family cultural capital
and children’s educational development. DiMaggio
(1982), drawing from Weber’s concepts of status groups
and status culture, as well as Bourdieu’s theory of
Figure 2. The role of shadow education on the impact mechanism of educational equity.
Wang et al. 5

cultural capital, found that family cultural capital signifi-
cantly influences students’ academic performance in high
school. In a comprehensive analysis, Xiao (2016) used
data from a survey on the living conditions of Shanghai
citizens, conducted between May and October 2008. This
study revealed that family cultural capital directly affects
educational access, even when controlling for other fam-
ily background factors. A meta-analysis by Tan et al.
(2019), which included 105 studies published between
2000 and 2017, further confirmed that family cultural
capital, particularly variables such as parents’ education
levels and educational expectations, positively impacts
students’ academic achievement. Notably, the relation-
ship between these cultural capital variables and aca-
demic outcomes differs across various educational stages.
Additionally, J. Wang and Wu (2023), analyzing multile-
vel datasets, PISA 2018 data, and country indices from
32 OECD nations, found a strong positive correlation
between cultural capital and academic success.
Building on these findings, we propose the first
research hypothesis:
H1: Family cultural capital significantly and positively
impacts educational outcomes.
In research examining the influence of family cultural
capital on extracurricular tutoring, several scholars have
identified a significant positive effect on both the number
of students participating in extracurricular activities and
the associated costs (Zhang et al., 2021). School-based
ASPs can be seen as a substitute for out-of-school
shadow education. Participation in ASPs helps reduce
the financial burden of extracurricular tutoring on
families (Wan & Weerasena, 2017). This suggests that, to
some extent, families have redirected their investments
toward ASPs. A study by Zhang et al. (2021), using sur-
vey data from 32 counties across six provinces in eastern,
central, and western China, found that primary school
students from families with stronger educational back-
grounds and higher expectations were more likely to par-
ticipate in ASPs. Similarly, junior high school students
from families with higher educational aspirations were
more likely to enroll in these programs. Notably, stu-
dents from different family backgrounds demonstrate
varying performance levels (Philp & Gill, 2020; Yao
et al., 2023). ASPs tend to help students from privileged
families prepare for college and future job prospects,
while for students from disadvantaged backgrounds,
ASPs may serve primarily as childcare or extended
school education. Based on the findings discussed, it can
be inferred that students with higher family cultural capi-
tal are more motivated to participate in ASPs and are
more likely to invest in them. Therefore, we propose the
second research hypothesis:
H2: Family cultural capital significantly and positively
impacts participation in ASPs.
School Resources: School Input Into Construction
Unlike shadow education, participation in ASPs is not
solely influenced by family background. The resources
invested by schools can also play a significant role in
determining the quality of ASPs. High-quality ASPs are
essential for attracting student participation (Y. Yu &
Pan, 2022). Scholars have identified several indicators
Figure 3. The role of ASPs on the impact mechanism of educational equity.
6SAGE Open

for assessing the quality of ASPs, including structural
elements such as the content offered, funding sources,
safety measures, facility quality, and staff qualifications
(Frazier et al., 2019). Process-related factors, such as the
level of support for teacher-student interactions, are also
crucial (Kuperminc et al., 2019). These factors collec-
tively shape students’ experiences with ASPs, and schools
are primarily responsible for providing these elements
during program implementation. The guiding principles
adopted by primary and secondary schools significantly
influence the effectiveness of ASPs (W. C. Zhang, 2021).
When referring to teachers involved in ASPs, this typi-
cally means on-campus educators. In addition to the
advantages of time and space, on-campus teachers bene-
fit from managerial advantages, as they are familiar with
the students at their school (You & Zhou, 2020).
The research mentioned highlights the strong connec-
tion between students’ willingness to participate in ASPs
and the quality of school resources dedicated to these
programs. Therefore, we propose the third research
hypothesis:
H3: School input into construction significantly and
positively impacts participation in ASPs.
Participation in ASPs
After-school education has garnered significant attention
from experts, scholars, and professional organizations,
including the Afterschool Alliance, the National Institute
on Out-of-School Time, and the National Center for
Quality Afterschool. Research and evaluations of service
project implementations have demonstrated that ASPs
can positively impact students’ cognitive abilities, social-
emotional skills, academic performance, and overall phys-
ical and mental well-being. This impact is particularly evi-
dent among children from low-income families, those
facing academic challenges, at-risk students, and immi-
grant children, supporting their comprehensive develop-
ment (J. Lee et al., 2020). High-quality ASPs have been
shown to not only enhance students’ academic perfor-
mance but also help maintain existing academic standards
(L.Lietal.,2022;Vandelletal.,2020).Additionally,com-
pleting homework with higher quality and cultivating
good study habits contribute to the development of stron-
ger teacher-student relationships. Non-academic activities
that align with students’ interests also provide opportuni-
ties for social networking, fostering positive peer relation-
ships (Allen et al., 2019). Moreover, extracurricular
activities have been found to boost students’ self-confi-
dence, self-esteem, positive attitudes toward school, and
prosocial behavior (Lester et al., 2020).
Based on this review, the researcher proposes that par-
ticipation in ASPs has a significant impact on students’
educational outcomes. Therefore, the fourth research
hypothesis is as follows:
H4: Participation in ASPs significantly and positively
impacts educational outcomes.
The Conceptual Roadmap of ASPs
Xue and Li (2016) utilized the Structural Equation
Model (SEM) to analyze the mediating effect of shadow
education on the learning processes of primary and sec-
ondary school students, as influenced by family capital.
Their study aimed to uncover the mechanisms of social
reproduction within shadow education, examine its
impact on social mobility, and highlight the challenges
shadow education faces in providing equitable and con-
sistent influence on compulsory education. Building on
their concept map of the role of shadow education and
integrating insights from existing research, this study
presents a conceptual roadmap that outlines the role
path of ASPs, as illustrated in Figure 4.
Research Design
This study employed a self-report questionnaire survey.
To ensure the rigor of this approach, we meticulously
managed several key aspects of the research process,
including: (1) justifying the selection of analysis methods,
(2) ensuring the age appropriateness of the participant
sample, (3) confirming the reliability of data collection
procedures, (4) maintaining the scientific integrity of
data processing, (5) ensuring the balance of the data
sample, and (6) verifying the reliability of the variable
measurements.
Research Methodology
This study adopts a quantitative research approach, spe-
cifically structural equation modeling (SEM), to address
Figure 4. The conceptual roadmap of after-school programs.
Wang et al. 7

the research questions. Quantitative research enables the
objective measurement and analysis of variables, provid-
ing clear, numerical data that quantifies the impact of
ASPs on educational outcomes and equity. This
approach not only enhances the clarity of evidence but
also strengthens the generalizability of the findings (Polit
& Beck, 2010). By using a large sample size and standar-
dized data collection methods, the results of this study
can be more easily applied to other similar contexts
within China or in countries with comparable educa-
tional systems.
Quantitative methods, particularly SEM, are valuable
tools for testing and validating theories. SEM allows for
the examination of relationships between observed and
latent variables, helping to identify both direct and indi-
rect effects (Mueller & Hancock, 2018). This capability is
essential for understanding the nuanced ways in which
ASPs influence educational equity. Given that this study
seeks to validate the theoretical framework and concep-
tual roadmap of ASPs, SEM is an ideal choice.
Study Sample
To enhance the applicability and reliability of the
research results, this study aims to provide persuasive
and instructive conclusions that can serve as valuable
references for schools and educational institutions. The
research design includes a diverse range of schools in
Shenzhen, representing various educational settings: a
private primary school, a public primary school, an
international primary school, a private junior high
school, a public junior high school, and an international
junior high school.
All of these schools are part of the same educational
group, which helps control for factors such as manage-
ment systems and teaching philosophies that might influ-
ence the research outcomes. This approach enhances the
internal validity of the study and supports the reliability
of its conclusions. Since the study’s primary focus is on
examining the impact of school input, family cultural
capital, and participation in after-school programs on
educational outcomes, differences in school types are not
the central concern. These differences will be explored in
more detail in future studies, given the space limitations
in this one.
The study excludes students from grades 1 to 3 of pri-
mary school for two main reasons. First, students in
grades 4 to 9 are generally considered to have the cogni-
tive ability to independently comprehend and complete
the survey questionnaire. Second, international stan-
dards, such as the OECD SSES 2023 China survey data,
suggest that students surveyed should be at least 10 years
old (J. Zhang et al., 2024), which corresponds to the age
of fourth-grade students. Thus, the sample selection in
this study aligns with these international guidelines.
Data Acquisition
This study gathered sample data and conducted an
empirical analysis through a questionnaire survey
(Questionnaire for After-School Programs in Primary
and Secondary Schools; see Appendix A for specific
scales). The questionnaire was designed to be non-inva-
sive, ensuring no physical or psychological interventions
that could cause harm to participants. In compliance
with Chinese laws, regulations, and institutional require-
ments, this study did not require approval from an ethics
committee.
To maintain participant anonymity, no identifiable
information was recorded in the survey responses, elimi-
nating the possibility of tracing data back to individual
participants. All data were securely stored, with access
restricted to the research team to minimize the risk of
data breaches. Furthermore, prior to administration, the
questionnaire underwent a comprehensive review and
proofreading process conducted by the principals of the
participating schools. This review ensured that the sur-
vey was age-appropriate, culturally sensitive, and free
from potentially distressing content. Explicit permission
was obtained from the school principals, securing institu-
tional support for the study.
The survey was conducted using the online platform
‘‘Questionnaire Star.’’ To address potential technical lim-
itations, students completed the questionnaire in their
school’s computer laboratory, ensuring that all partici-
pants had equal access to the survey. Informed consent
was obtained through a written form at the beginning of
the questionnaire. The form included explicit permission
from the school principal to ensure institutional backing
for the research. Participants were informed of their right
to skip any questions they did not wish to answer or to
withdraw from the study at any time without facing any
negative consequences. By completing the survey, parti-
cipants indicated their consent, thus confirming that
informed consent was obtained from all research
participants.
This study focuses on primary and secondary schools
in Shenzhen, where each institution offers a free 2-hr
ASPs funded by either the government or the school.
These ASPs encompass various courses, including self-
learning, school-based courses, and social practice.
Shenzhen was chosen for its relevance in studying the
effectiveness of ASPs in reducing social reproduction,
given the Chinese government’s strict regulations on
shadow education. As a rapidly developing city,
Shenzhen offers a representative context for examining
8SAGE Open

policies related to ASPs and their impact on educational
equity.
The data collection methods used in this study—self-
reporting, anonymity, confidentiality, and voluntary
participation—ensured that participants were not
exposed to harm. In addition, this study utilized
Structural Equation Modeling (SEM) as a quantitative
research method, and the questionnaire data were ana-
lyzed using statistical measures, such as means. The sta-
tistical results did not allow for the identification or
inference of individual participants’ identities, further
minimizing any potential risks. Ethically, this study
offers several benefits to student participants. First, par-
ticipating in the study allows students to increase their
self-awareness and gain a deeper understanding of edu-
cational equity and personal development. Additionally,
the study provides valuable data and insights to schools
and families, aiding the improvement of extracurricular
programs and supporting the long-term development of
students.
Data Processing
Online questionnaires present several challenges, includ-
ing a lack of supervision, technical issues, respondent
distractions, and difficulties in understanding and inter-
preting questions. These factors introduce greater risks
to the research compared to offline questionnaires
(Kongsved et al., 2007). To mitigate these challenges and
ensure data quality, this study employs the following cri-
teria: (1) Response Time: A minimum response time of
2 s is required for each question. Responses falling below
this threshold are considered indicative of inattention
and are categorized as low-quality data, which are subse-
quently excluded. (2) Consistency of Answers: Responses
to key sections of the questionnaire are reviewed for con-
sistency. Responses that are excessively similar or
demonstrate insufficient engagement are removed from
the dataset.
In total, 1,719 questionnaires were initially collected.
Following data cleaning, 1,458 valid responses were
retained, resulting in a questionnaire validity rate of
84.82%.
Data Description
A descriptive analysis was conducted on the 1,458 valid
samples, and the results are presented in Table 1. The
analysis reveals notable diversity in terms of gender,
grade, and school type among the respondents.
Additionally, the even distribution of the sample size fur-
ther supports the representativeness of the data collected
in this survey.
Variable Measurement
The self-report questionnaire employed in this study was
developed based on existing literature and research, par-
ticularly drawing from effectiveness evaluation tools for
ASPs and standardized questionnaires used in educa-
tional equity studies. To ensure the relevance and appro-
priateness of the questions, we sought feedback from
education experts, who conducted a preliminary review.
Based on their suggestions, we made revisions and
adjustments to enhance the clarity and accuracy of some
of the questions.
The Preliminary Investigation. Prior to the official imple-
mentation of the questionnaire, a small-scale pre-survey
was conducted at each participating school using the
Questionnaire Star online platform. The pre-survey col-
lected 142 valid responses, with 54.23% from primary
school students and 45.77% from junior high school stu-
dents, ensuring a balanced data distribution.
Based on the feedback gathered during the pre-survey,
several revisions were made to improve the clarity and
conciseness of the questionnaire. This included rewording
Table 1. Descriptive Analysis of Sample Data.
Item Category
Stage of study
Elementary school (Grades 4–6) Junior high school (Grades 7–9)
Frequency % of Total Frequency % of Total
Gender Male 328 53.07 363 43.21
Female 290 46.93 477 56.79
Total 618 42.39 840 57.61
School type Public 182 29.17 252 30.22
Private 216 34.61 300 35.97
International 226 36.22 282 33.81
Total 624 42.80 834 57.20
Wang et al. 9

unclear questions for better understanding and removing
redundant items to shorten the survey.
Statistical analysis indicated satisfactory internal
consistency, with a Cronbach’s avalue of .810 and a
KMO value of 0.765, both of which point to high
reliability and validity. The reliability and validity of
each measurement variable were also assessed, yielding
the following results: Family cultural capital
(KMO = 0.712, Cronbach’s a= .655); School input
into construction (KMO = 0.728, Cronbach’s a=.751);
Participation in ASPs (KMO = 0.832, Cronbach’s
a= .897); Educational outcomes (KMO = 0.918,
Cronbach’s a= .951). These revisions and evaluations
confirmed that the questionnaire was both reliable and
valid, providing a solid foundation for the formal data
collection phase.
The Official Survey. The statistical analysis of the formal
survey demonstrated excellent internal consistency, with
a Cronbach’s avalue of .953 and a KMO value of 0.887.
These results indicate that the questionnaire possesses
high reliability and validity.
Family Cultural Capital. The Family Cultural Capital
Scale used in this study (see Appendix A Table A1) is
adapted from Qiu and Xiao’s (2011)‘‘Parent Cultural
Capital Scale’’ and ‘‘Children’s Cultural Capital Scale.’’
It consists of 13 items, categorized into three compo-
nents: investment in cultural education (6 items), parents’
cultural background (3 items), and children’s embodied
cultural capital (4 items).
Factor analysis was conducted using SPSS 26.0,
employing the principal axis factoring method with opti-
mal oblique rotation (kappa = 4). The KMO value was
0.767, and Bartlett’s test of sphericity was significant.
The scale exhibited acceptable internal consistency, with
a Cronbach’s alpha coefficient of .678. Confirmatory
factor analysis, performed using AMOS 24.0, confirmed
good validity (x
2
/df = 5.921, RMSEA = 0.058,
CFI = 0.846, SRMR = 0.0507).
School Resources: School Input Into Construction. Based on
the concepts and values of ASP course construction out-
lined in the ‘‘Double Reduction’’ policy (Q. X. Yang &
Wu, 2021; B. Zhang & Cheng, 2021) and the ‘‘After-School
Programs Questionnaire for Primary and Secondary
Schools’’ developed by Wang et al. (2023), this study devel-
oped the ‘‘School Input into Construction Scale’’ (see
Appendix A Table A2). This scale measures students’ per-
ceptions of their school’s efforts in developing ASPs and
serves as the primary dependent variable in this study.
Reliability and validity were assessed using both
Exploratory Factor Analysis (EFA) and Confirmatory
Factor Analysis (CFA). EFA, conducted with SPSS 26.0
and the principal axis factoring method with optimal
oblique rotation (kappa = 4), resulted in a KMO value
of 0.844, with Bartlett’s test of sphericity showing signifi-
cant results. The scale demonstrated strong reliability,
with a Cronbach’s aof .915. CFA, performed with
AMOS 24.0, confirmed good validity (x
2
/df = 7.25,
RMSEA = 0.065, CFI = 0.997, SRMR = 0.0086).
Participation in ASPs. Student participation in ASPs
serves as the mediating variable in this study. Given the
widespread promotion of ASPs and the experimental
approach of parents, nearly all students engage in ASPs,
making direct measurement of participation impractical.
Therefore, perceived satisfaction with ASP participation is
used as a proxy for engagement. The ‘‘ASPs Participation
Scale’’ (see Appendix A Table A3) was developed based
on the conceptual framework of ASP course construction
within the ‘‘Double Reduction’’ initiative (Q. X. Yang &
Wu, 2021; B. Zhang & Cheng, 2021).
SPSS 26.0 was used for statistical analysis, employing
the principal axis decomposition method with optimal
oblique rotation (kappa = 4). The KMO value was
0.855, and Bartlett’s test of sphericity was significant.
The scale demonstrated strong reliability, with a
Cronbach’s avalue of .937. Confirmatory factor analy-
sis, using AMOS 24.0, affirmed the scale’s good validity
(x
2
/df = 11.535, RMSEA = 0.085, CFI = 0.996,
SRMR = 0.0083).
Educational Outcomes. The Educational Outcomes
Scale evaluates student development resulting from par-
ticipation in ASPs. Following Epstein’s framework,
which includes learning progress, behavioral changes,
and improvements in the learning environment (Epstein
et al., 2018), this study adapted the educational out-
comes scale from Diao’s (2021)‘‘Family Investment in
Off-Campus Education and Behaviour Effect Scale.’’
The scale (Appendix A Table A4) includes categories
such as academic development (7 items), interests and
talents (6 items), parent-child relationship (3 items), and
family burden (6 items).
SPSS 26.0 was used for factor analysis with the princi-
pal axis factoring method and optimal oblique rotation
(kappa = 4). The KMO value was 0.973, and Bartlett’s
test of sphericity was significant. The scale exhibited
strong internal consistency, with a Cronbach’s acoeffi-
cient of 0.977. Confirmatory factor analysis, conducted
with AMOS 24.0, confirmed good validity (x
2
/df = 8.672,
RMSEA = 0.073, CFI = 0.961, SRMR = 0.0284).
10 SAGE Open

Results
Descriptive Statistics and Correlation Analysis
Table 2 presents the descriptive statistics and correlation
analysis for the key variables in this study. This includes
the mean, standard deviation, and correlation coeffi-
cients. Notably, family cultural capital, participation in
ASPs, school input into construction, and educational
outcomes all show positive correlations. These results
are consistent with the study’s expectations and provide
initial support for the proposed research hypotheses.
Measurement Model
A confirmatory factor analysis (CFA) was conducted to
evaluate the fitness, validity, and reliability of the mod-
el’s constructs. The CFA was performed using AMOS
24.0 software. The results showed a good model fit
(x
2
= 3879.827, df = 847, x
2
/df = 4.581, TLI = 0.941,
CFI = 0.945, RMSEA = 0.050), indicating that the
model variables align well with their respective
constructs.
Common Method Variance
Common method bias (CMB) refers to the potential
influence of the data collection instrument on responses,
rather than the actual constructs being measured. Given
that this study’s data were collected through an online
survey, Batista-Foguet et al. (2014) highlighted the possi-
bility of CMB. In structural equation modeling (SEM)
analysis, an accurate model is developed to explain the
observed data. If CMB is present but not accounted for,
it can impact the model’s explanatory power, as the SEM
may mistakenly interpret the common method variance
as the true relationship between variables (Podsakoff
et al., 2003).
In SEM analysis, the measurement model is estab-
lished first, followed by the structural model. The mea-
surement model assesses the relationship between
observed variables and their underlying constructs, while
the structural model evaluates the relationships between
these constructs. Since CMB involves controlling for bias
between observed variables, it is typically addressed after
the measurement model has been established.
This study uses Harman’s single-factor test to evalu-
ate the presence of common method bias (Podsakoff &
Organ, 1986). Exploratory factor analysis was conducted
on all measurement items related to the variables in the
model, employing principal component analysis without
rotation. The first factor explained 41.625% of the var-
iance, which is below the 50% threshold, indicating that
CMB is not a significant issue (Malhotra et al., 2006).
To further assess CMB, confirmatory factor analysis
was performed. The resulting model fit indices were less
than ideal (x
2
/df = 25.61, RMSEA = 0.13, CFI = 0.616,
SRMR = 0.0983, TLI = 0.597, NFI = 0.607). However,
these findings suggest that common method bias is not a
severe issue in the dataset for this study (Zou, 2020).
Question 1: the Impact of ASPs on Educational Equity
Based on the theoretical framework illustrating the
impact of ASPs on educational equity, this article estab-
lishes a structural equation model with school input into
construction and family cultural capital as independent
variables, participation in ASPs as an intermediary vari-
able, and educational outcomes as the dependent
variable.
The model fit indices are as follows: x
2
/df = 4.581,
RMSEA = 0.050, CFI = 0.945, SRMR = 0.0578, and
PNFI = 0.875. According to the criteria used to assess
the goodness of fit for SEM models (Wu, 2013), these
results indicate a strong fit to the data (see Table 3 for
detailed information). The model is in line with theoreti-
cal assumptions and shows a path relationship that aligns
with the empirically measured data.
The construction of the structural model and its
underlying assumptions are deemed ideal, confirming
that the proposed model—outlining the influences of
family and school on educational outcomes—is sup-
ported by solid theoretical foundations. Overall, the
empirical evidence strongly supports the hypothesized
conceptual model illustrating the relationship between
ASPs and educational equity.
Table 2. Mean, Standard Deviation and Correlation Coefficients.
Variable Mean Std.
School input into
construction
Participation
in ASPs
Educational
outcomes
Family culture
capital
School input into construction 4..843 1.057 1.000
Participation in ASPs 4.740 1.176 0.906*** 1.000
Educational outcomes 4.352 1.148 0.537*** 0.622*** 1.000
Family cultural capital 3.124 0.579 0.090*0.109** 0.234*** 1.000
*p\.05. **p\.01. ***p\.001.
Wang et al. 11

Table 4 presents the standardized regression path
coefficients derived from the model. All path coefficients
in the model pass the significance level tests. According
to the joint significance test, school input into construc-
tion significantly and positively predicts participation in
ASPs (b= .917, p\.001). Furthermore, participation in
ASPs significantly and positively predicts educational
outcomes (b= .499, p\.001). This suggests that school
input into construction may indirectly influence educa-
tional outcomes through its impact on ASPs participa-
tion. Thus, participation in ASPs can act as a mediating
factor in the relationship between school input into con-
struction and educational outcomes.
The direct path from family cultural capital to educa-
tional outcomes is also significant (b= .215, p= .004, p
\.01). Additionally, family cultural capital significantly
and positively predicts participation in ASPs (b= .069,
p= .041, p\.05), and participation in ASPs signifi-
cantly and positively influences educational outcomes
(b= .499, p\.001). These results suggest that participa-
tion in ASPs may partially mediate the relationship
between family cultural capital and educational
outcomes.
In summary, the conceptual model developed in this
study, grounded in the theoretical framework, success-
fully passed both the path test and the model fit test. This
confirms that the educational equity framework estab-
lished here is applicable to ASPs learning in primary and
secondary schools. Furthermore, the findings highlight
that both home and school environments during ASPs
learning play a significant role in promoting the equitable
development of education (Figure 5).
Question 2: The Specific Impact Mechanism of ASPs
on Educational Equity
This study uses the Bootstrap method to test and analyze
the mediation effect of the school and family environ-
ments on educational outcomes within the SEM model.
The results of this test provide a detailed assessment of
the specific impact mechanism through which ASPs
influence educational equity. While the path analysis
highlighted the impact of school input and family cul-
tural capital on educational outcomes, as well as the
mediating role of participation, applying the Bootstrap
method offers additional statistical evidence to
strengthen these findings.
The Bootstrap method calculates the standard error
and confidence interval of the mediation effect, allowing
for a more precise evaluation of its significance. It also
enhances the credibility of the research, as it does not
require assumptions of normality or large sample sizes.
This method is more efficient than traditional mediation
techniques, such as stepwise regression or the Sobel test,
ensuring greater accuracy and scientific rigor.
Additionally, by generating a large number of samples
through repeated sampling, the Bootstrap method can
more reliably estimate the distribution of parameters,
thus improving the robustness of the results.
In this study, 800 individuals were repeatedly sampled
at a 90% confidence interval. The analysis results, shown
in Table 5, indicate a significant mediation effect.
Specifically, the point estimate for the total family effect
is 0.192, with a bias-corrected confidence interval of
(0.132, 0.264). The exclusion of 0 from this interval
Table 3. The Adaptation Results of the SEM Model.
Statistical testing
Absolute fitness indices Value-added adaptation indices Parsimonious fitness indices
x
2
/df RMSEA GFI NFI IFI CFI PNFI PCFI PGFI
Adaptation standard 2–5 \0.08 .0.8 .0.9 .0.9 .0.9 .0.5 .0.5 .0.5
Parameter 4.581 0.050 0.886 0.931 0.945 0.945 0.875 0.888 0.795
Note. Other parameters: n= 1,458; p\.001; SRMR = 0.0578; TLI = 0.941.
Table 4. The Path Test of the SEM Model.
Hypothesis Path
Standardized
estimate
Standard
error Critical ratio pValue Result
H1 Family cultural capital !Educational outcomes 0.168 0.089 5.029 *** Supported
H2 Family cultural capital !Participation in ASPs 0.040 0.059 2.077 *Supported
H3 School input into construction !Participation in ASPs 0.904 0.022 40.221 ** Supported
H4 Participation in ASPs !Educational Outcomes 0.607 0.025 20.955 *** Supported
*p\.05. **p\.01. ***p\.001.
12 SAGE Open

confirms the significance of the mediation effect.
Similarly, the point estimate for the total school effect is
0.549, with a bias-corrected confidence interval of (0.511,
0.591), also indicating a significant mediation effect.
Moreover, the point estimate for the total effect of the
model is 0.740, with a bias-corrected confidence interval
of (0.674, 0.810). Once again, the exclusion of 0 from this
interval suggests a significant mediation effect.
In summary, both family cultural capital and school
investments in ASPs significantly influence students’ edu-
cational outcomes through the mediating effect of ASPs
participation. The findings show that family cultural cap-
ital contributes 25.94% of the total effect, with 3.24% of
this attributed to the indirect path of ‘‘family cultural
capital !participation in ASPs !educational out-
comes.’’ In contrast, school resources account for a larger
portion, contributing 74.06% of the total effect, with this
effect flowing through the indirect path of ‘‘school input
into construction !participation in ASPs !educational
outcomes.’’
Discussion
This study is rooted in the context of educational equity
and explores the theoretical framework concerning the
influence of school resources and family background on
equity. Building on this foundation, we develop a con-
ceptual model and roadmap that highlight the impact of
ASPs on educational equity. Within this cohesive
research framework, we examine the complex interaction
between family cultural capital and school input to better
understand how these factors contribute to students’
educational outcomes. Through empirical analysis, we
carefully investigate the mediating role of ASPs, unco-
vering the intricate network of influences linking ASPs
to educational equity. The study presents several key
findings, outlined as follows:
The Impact of Familial Cultural Capital on Educational
Outcomes via ASPs
The study reveals that participation in ASPs partially
mediates the relationship between family cultural capital
and educational outcomes. Specifically, ‘‘family cultural
capital’’ not only has a direct effect on ‘‘educational out-
comes’’ but also indirectly influences them through
‘‘ASPs participation.’’ The direct influence can be attrib-
uted to the multifaceted role of family cultural capital in
individual learning processes, including providing sup-
port (Tan et al., 2019), fostering academic attitudes
(Cheng & Kaplowitz, 2016), and creating a conducive
learning environment (Liang et al., 2022; Tramonte &
Willms, 2010), which aligns with prior research findings.
The indirect effect arises from ASPs offering students
a complementary learning platform that includes addi-
tional study time (Budd et al., 2020), fostering an inclu-
sive, safe, and respectful environment (M. V. B. Yu
et al., 2021), providing structured interaction opportuni-
ties (Leos-Urbel, 2015), and facilitating rich extracurricu-
lar activities (Huang, 2022). These factors collectively
enhance students’ educational attainment. However,
despite the government’s support covering major operat-
ing costs and implementing free or cost-based non-profit
policies for ASPs, participation in arts and science-based
ASPs often requires the purchase of musical instruments,
art supplies, science materials, and other resources. As a
result, families with higher cultural capital are more
Table 5. The Bootstrap Test of the Mediation Effect.
Path (Std) Std estimate Standard error
Bias-corrected confidence interval (90%)
pValue Effect ratio
Lower Upper
The family direct effect 0.168 0.036 0.107 0.226 ** 22.70%
The family indirect effect 0.024 0.015 0.001 0.048 3.24%
The total family effect 0.192 0.039 0.132 0.264 ** 25.94%
The total school effect 0.549 0.024 0.511 0.591 *** 74.06%
The total effect 0.740 0.041 0.674 0.810 **
p\0.1. **p\.01. ***p\.001.
Figure 5. The SEM model of participation in ASPs.
Wang et al. 13

likely to invest in such cultural education (Zhang et al.,
2021), thus promoting improved educational outcomes
for students involved in ASPs.
The Role of School Input Into Construction on
Educational Outcomes Through ASPs
The empirical results of this study suggest that a school’s
investment in ASPs can indirectly influence students’
educational outcomes through their participation in these
programs. First, school-led ASPs in China are often
more seamlessly integrated with formal school education
(Gao & Qu, 2023), provide teachers with enhanced pro-
fessional development opportunities (W. D. Yang &
Tang, 2023), and promote closer home-school coopera-
tion (S. Yang, 2023). These factors collectively address
students’ developmental needs and contribute to their
overall educational improvement.
Second, schools play a pivotal role in administering
ASPs (Zou, 2020), with teachers acting as the primary
implementers who directly affect the quality of these ser-
vices (Ni, 2021). Schools can enhance the quality of
ASPs by improving the professional skills of participat-
ing teachers and fostering their enthusiasm for their
work. These efforts lead to increased student satisfaction
with ASP participation, which, in turn, boosts student
engagement. Additionally, since ASP participation is
voluntary (The Xinhua News Agency, 2021), students,
particularly underage teenagers, often participate in
alignment with their parents’ preferences. By refining the
ASP implementation environment and establishing an
effective home-school communication system, schools
can enhance parents’ confidence in the programs they
offer, ultimately improving student participation.
The Beneficial Impact of ASPs on Educational Equity
Through Educational Outcomes
The conceptual model developed in this study, grounded
in the theoretical framework, successfully passed both
the path and model fitness tests. This indicates that the
educational equity framework proposed here is applica-
ble to After-School Programs (ASPs) in primary and sec-
ondary schools. Moreover, the model demonstrates that
both family and school environments during ASPs play
a significant role in fostering educational equity.
This study also reveals that, in the context of ASP
implementation, the impact of school investment in infra-
structure on students’ educational outcomes is approxi-
mately three times greater than that of family cultural
capital. Therefore, students’ academic achievements after
participating in ASPs are not solely dependent on family
cultural capital but are heavily influenced by the school’s
investment in ASP infrastructure. This finding aligns
with the perspective of Fu and Zhong (2024), who argue
that the quality of after-school services provided by
schools is crucial in enabling students to achieve diverse
developmental outcomes.
When analyzed within the final theoretical framework
established in this study, it becomes evident that school
factors predominantly influence the formation of educa-
tional outcomes in ASPs for primary and secondary
school students. As a result, ASPs serve to enhance the
equitable distribution of school resources, potentially
advancing educational equity. This supports existing
research that suggests school-led after-school programs
effectively guide and utilize students’ after-school time
and space. These programs play a crucial role in safe-
guarding children’s right to education and promoting
educational equity and social justice (L. Han & Zhou,
2024; Ma & Zeng, 2018).
The Transformative Impact of ASPs Replacing Shadow
Education on Educational Equity
Through an analysis from both the family and school
perspectives, this study reveals the transformative role of
ASPs in replacing shadow education. Specifically, ASPs
can largely substitute shadow education by increasing
participation while simultaneously enhancing the educa-
tional functions of schools to achieve greater educational
equity.
Families with higher cultural capital tend to show
greater enthusiasm for and willingness to engage in
shadow education (W. Zhang, 2020). However, with the
implementation of the ‘‘double reduction’’ policy, the
prevalence of shadow education has significantly
decreased (Ministry of Education of the People’s
Republic of China, 2023), while the reach of ASPs has
expanded (China Educational Daily, 2022). As a result,
affluent families are increasingly turning to ASPs as an
alternative to traditional shadow education.
Moreover, school-organized ASPs align with the three
dimensions of fair educational development: fair educa-
tional starting points, fair educational processes, and fair
educational outcomes (Huse
´n, 1972). They embody the
difference principle and compensation principle of edu-
cational equity (Rawls, 1999). ASPs foster equitable edu-
cational opportunities by offering affordable and
inclusive learning experiences for all students (Roemer &
Trannoy, 2016). This ensures a fair starting point in edu-
cation, consistent with the compensation principle of
educational equity. At the same time, all students,
regardless of their family background, receive the same
teacher-led content and access to resources in ASPs,
ensuring an equitable educational process. Finally, the
diverse curriculum offered by ASPs allows students with
varying backgrounds, abilities, talents, and challenges to
14 SAGE Open

select courses that meet their specific needs, thereby
guaranteeing fair educational outcomes and adhering to
the difference principle of educational equality.
Conclusions and Implications
This study compares After-School Programs (ASPs) with
shadow education and constructs a theoretical frame-
work to understand the mechanisms by which ASPs
influence educational equity. Using questionnaire data
from primary and secondary school students in
Shenzhen, a structural equation model (SEM) was devel-
oped for empirical testing. The results demonstrate that
both familial cultural capital and school investments in
infrastructure can impact educational outcomes through
participation in ASPs. Furthermore, the study highlights
the positive effects of ASPs on educational equity, partic-
ularly in terms of improving educational outcomes, and
explores the transformative role of ASPs in replacing
shadow education to foster greater equity.
This pioneering study adopts an equity-focused per-
spective to examine the value and implementation path-
ways of ASPs, offering new insights into the mechanisms
that can promote educational equity. It addresses the
pervasive challenge, seen in many countries, where fam-
ily background hinders educational equity. While previ-
ous research has explored this issue through the lens of
shadow education, many studies have found that shadow
education amplifies family capital, thus exacerbating
educational inequities and limiting social mobility (Jung,
2022; Tsiplakides, 2018). In contrast, other scholars have
emphasized the benefits of ASPs, highlighting their
potential to support students’ overall development and
educational growth (Jenson et al., 2018; J. Lee et al.,
2020). With the backing of China’s ‘‘double reduction
policy,’’ a natural experiment examining the relationship
between shadow education and ASPs is unfolding within
Chinese society. This study builds on these evolving
dynamics, combining findings from earlier research to
construct a theoretical framework that explores how
ASPs can contribute to promoting educational equity.
Empirical data are used in this study to assess the fea-
sibility of After-School Programs (ASPs) in promoting
educational equity. In many countries, grappling with
the negative effects of after-school private tutoring—
such as financial burdens, the erosion of public schools,
and widening educational opportunity gaps—ASPs have
been introduced as a potential solution (S. H. Bae &
Jeon, 2013). However, empirical studies from countries
like South Korea have shown limited impacts of ASPs
on students’ overall school life, academic performance,
and extracurricular tutoring expenses (Park et al., 2012).
This disparity in findings may stem from differences in
national policies, such as guidelines for ASP fees and the
regulation of shadow education, which may hinder the
expected benefits of ASPs in promoting educational
equity. Although many theoretical articles in China have
explored the potential role of ASPs in promoting equity
(T. Han & Su, 2022), there is a lack of empirical research
to support these claims. This study addresses this gap by
employing Structural Equation Modeling (SEM) to trace
the path through which ASPs contribute to educational
equity. The empirical results suggest that, although ASPs
are influenced by school resources and family back-
ground, the impact of school education is more signifi-
cant. As a result, ASPs, to some extent, replace shadow
education and help promote educational equity.
The findings from this study provide valuable gui-
dance for future research on the effectiveness of ASPs
and other educational interventions aimed at promoting
equity. In light of China’s strict ‘‘double reduction’’ pol-
icy on shadow education, ASPs appear to be stepping in
to replace traditional shadow education. This shift chal-
lenges the previously established pattern where family
background perpetuated educational inequities through
shadow education, thus contributing to class-based edu-
cational gaps (Wang et al., 2023). For ASPs to effectively
reduce social reproduction, it is essential that the Chinese
government continues its strict control over shadow edu-
cation and ensures that ASPs are charged at non-profit
rates, including fees for necessary equipment in subjects
like sports, science, and art. Therefore, the government
should prioritize the inclusive implementation of ASPs
while rigorously regulating shadow education. The
insights from this study can assist policymakers and edu-
cators in developing and implementing educational inter-
ventions that promote equity and reduce disparities in
educational access and outcomes.
Limitations and Future Directors
Firstly, it is important to acknowledge that the results of
this study are based solely on self-report questionnaires
completed by students. This introduces a potential bias
due to self-reporting tendencies, which may affect the
establishment of causal relationships. To enhance the
validity of future studies, it would be beneficial to inte-
grate qualitative methods, such as on-site observations
and interviews, alongside quantitative data to construct a
more comprehensive and robust measurement approach.
Secondly, although the sample in this study includes
primary and secondary students from various types of
schools, the primary focus was on analyzing the impact
of ASPs on educational outcomes and the mechanisms
influencing these outcomes. As a result, no specific com-
parative analysis was conducted based on academic
stages or school types. However, it is important to note
that the school stage and type may influence the
Wang et al. 15

adaptability of ASPs, as well as students’ study habits
and outcomes. Future research should explore these
potential differences more thoroughly.
Regarding future research prospects, this study sug-
gests several promising directions. One area worth inves-
tigating is whether an alienation effect exists between
schools in terms of the equity impact of ASPs. While this
study treated the group of students participating in ASPs
as a whole to explore their collective educational impact,
it remains unclear whether ASPs might inadvertently
exacerbate disparities between schools, even while pro-
moting equity within individual schools.
Additionally, further research could focus on the spe-
cific levels of impact of ASP implementation. Beyond a
broad consideration of students’ educational outcomes,
there is room for more nuanced exploration of topics
such as demographic outcomes, academic achievements,
and sociopolitical impacts.
Acknowledgments
We express deep appreciation for the K-12 school principals,
teachers, and students who have kindly participated in the
study, as well as the research staff members responsible for
coordinating research activities.
ORCID iDs
Ping Wang https://orcid.org/0000-0001-6354-2235
Feiye Wang https://orcid.org/0000-0002-2953-2241
Ethical Considerations
In accordance with Chinese laws, regulations, and institutional
requirements, this study did not require approval from an ethics
committee, as it does not involve animal or human clinical trials
and is not considered unethical. Prior to conducting the study,
we obtained permission from the school principal, and the ques-
tionnaire underwent a thorough review by the local K-12 school
principal. Additionally, all participants provided informed con-
sent before participating in the study. Measures were implemen-
ted to ensure the anonymity, confidentiality, and voluntary
participation of all individuals involved. Therefore, the involve-
ment of the school and the completion of the survey confirm
that this study adheres to ethical standards.
Funding
The author(s) received no financial support for the research,
authorship, and/or publication of this article.
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with
respect to the research, authorship, and/or publication of this
article.
Data Availability Statement
Data sharing not applicable to this article as no datasets were
generated or analyzed during the current study.
References
Aaronson, D., Barrow, L., & Sander, W. (2007). Teachers and
student achievement in the Chicago public high schools.
Journal of Labor Economics,25(1), 95–135. https://doi.org/
10.1086/508733
Allen, P. J., Chang, R., Gorrall, B. K., Waggenspack, L.,
Fukuda, E., Little, T. D., & Noam, G. G. (2019). From
quality to outcomes: A national study of afterschool STEM
programming. International Journal of Stem Education,6(1),
1–21. https://doi.org/10.1186/s40594-019-0191-2
An, W., & Western, B. (2019). Social capital in the creation of
cultural capital: Family structure, neighborhood cohesion
and extracurricular participation. Social Science Research,
81, 192–208. https://doi.org/10.1016/j.ssresearch.2019.03.015
Bae, S. H., & Jeon, S. B. (2013). Research on afterschool pro-
grams in Korea: Trends and outcomes. International Journal
for Research on Extended Education,1(1), 11–12.
Batista-Foguet, J. M., Revilla, M., Saris, W. E., Boyatzis, R.,
& Serlavo
´s, R. (2014). Reassessing the effect of survey char-
acteristics on common method bias in emotional and social
intelligence competencies assessment. Structural Equation
Modeling A Multidisciplinary Journal,21, 596–607. https://
doi.org/10.1080/10705511.2014.934767
Belsky, D. W., Domingue, B. W., Wedow, R., Arseneault, L.,
Boardman, J. D., Caspi, A., Conley, D., Fletcher, J. M.,
Freese, J., Herd, P., Moffitt, T. E., Poulton, R., Sicinski, K.,
Wertz, J., & Harris, K. M. (2018). Genetic analysis of social-
class mobility in five longitudinal studies. Proceedings of the
National Academy of Sciences,115(31), E7275–E7284.
https://doi.org/10.1073/pnas.1817958115
Blackstone, T. (1967). The Plowden Report. British Journal of
Sociology,18(3), 291–302.
Blau, P. M., & Duncan, O. D. (1967). The American occupa-
tional structure. American Journal of Sociology,33(2),
296–297. https://doi.org/10.1086/228904
Boudon, R. (1976). Education, opportunity, and social inequal-
ity: Changing prospects in western society. American Politi-
cal Science Review,70(2), 589–590. https://doi.org/10.2307/
1959667
Bourdieu, P., & Passeron, J. C. (1977). Reproduction in educa-
tion, society and culture. Sage Publications.
Bray, M. (1999). The shadow education system: Private tutoring
and its implications for planners. Fundamentals of Educa-
tional Planning Series, 61 UNESCO.
Bray, M., & Kwok, P. (2003). Demand for private supplemen-
tary tutoring: Conceptual considerations and socioeconomic
patterns in Hong Kong. Economics of Education Review,
22(6), 611–620. https://doi.org/10.1016/S0272-
7757(03)00032-3
Budd, E. L., Nixon, C. T., Hymel, A. M., & Tanner-Smith, E.
E. (2020). The impact of afterschool program attendance on
16 SAGE Open

academic outcomes of middle school students. Journal of
Community Psychology,48(8), 2439–2456. https://doi.org/
10.1002/jcop.22416
Chakraborty, T., & Jayaraman, R. (2019). School feeding and
learning achievement: Evidence from India’s midday meal
program. Journal of Development Economics,139, 249–265.
https://doi.org/10.1016/j.jdeveco.2018.10.011
Cheng, S. T., & Kaplowitz, S. A. (2016). Family economic sta-
tus, cultural capital, and academic achievement: The case of
Taiwan. International Journal of Educational Development,
49, 271–278.
China Educational Daily. (2022, January 8). How to solidly pro-
mote after-school services in primary and secondary
schools?https://theory.gmw.cn/2022-01/08/content_
35434927.htm
Chung, K., & Lee, D. (2017). Inefficient competition in
shadow-education investment. Journal of Economic Behavior
& Organization,139, 152–165. https://doi.org/10.1016/j.jebo.
2017.05.007
Coleman, J. S. (1996). Equal schools or equal students? Public
Interest,4, 71–72.
Cureton, A. (2023). ‘‘After the school day, what’s next?’’:
Exploring refugee youths’ engagement in after-school pro-
grams. Journal of Adolescent Research,38(6), 1114–1141.
https://doi.org/10.1177/07435584221144952
Dewey, J. (1983). The middle works of John Dewey, 1899-1924
(vol.13) (Ed. J.A. Boydston), Southern Illinois University
Press.
Diao, R. (2021). Research on the motivation, behavior and effect
of primary school students’ family out of school education
investment. Nanchang University.
DiMaggio, P. (1982). Cultural capital and school success: The
impact of status culture participation on the grades of US
high school students. American Sociological Review,47(2),
189–201.
Epstein, J. L., Sanders, M. G., Sheldon, S. B., Simon, B. S.,
Salinas, K. C., Jansorn, N. R., & Williams, K. J. (2018).
School, family, and community partnerships: Your handbook
for action. Corwin Press.
Fang, C., & Huang, B. (2020). Matthew effect or equity effect:
Heterogeneity test of family education expenditure and
inequality of educational outcome. Education and Economy,
36(4), 58–67.
Feng, S. (2021). The evolution of shadow education in China:
From emergence to capitalisation. Hungarian Educational
Research Journal,11(2), 89–100. https://doi.org/10.1556/063.
2020.00032
Fiscal First-Quarter. (2019). Regulatory upgrading promotes
industry clearance, and the capitalization path of education
enterprises is becoming increasingly clear. https://www.yicai.
com/news/100096623.html
Forster, A. G., & van de Werfhorst, H. G. (2020). Navigating
institutions: Parents’ knowledge of the educational system
and students’ success in education. European Sociological
Review,36, 48–64. https://doi.org/10.1093/esr/jcz049
Framework, D. (2000). Dakar framework for action—Education
for all: Meeting our collective commitments. Paper presented
in World Education Forum. https://unesdoc.unesco.org/
images%20/0012/001211/121147e.pdf.
Frazier, S. L., Chou, T., Ouellette, R. R., Helseth, S. A.,
Kashem, E. R., & Cromer, K. D. (2019). Workforce sup-
port for urban after-school programs: Turning obstacles
into opportunities. American Journal of Community Psychol-
ogy,63(3–4), 430–443. https://doi.org/10.1002/ajcp.12328
Fu, R., & Zhong, Y. (2024). Construction of a school-based
curriculum system for after-school services of ‘‘five-pronged
education’’ in rural primary schools. Teaching and Manage-
ment,36(02), 21–24.
Gao, J. B., & Qu, T. T. (2023). Informal- curriculum attribute
and implementation of after-school service. Curriculum,
Teaching Material and Method,3, 63–70. https://doi.org/10.
19877/j.cnki.kcjcjf.2023.03.009
Greenwald, R., Hedges, L. V., & Laine, R. D. (1996). The effect
of school resources on student achievement. Review of Edu-
cational Research,66(3), 361–396. https://doi.org/10.3102/
00346543066003361
Hajar, A., & Karakus, M. (2022). A bibliometric mapping of
shadow education research: Achievements, limitations, and
the future. Asia Pacific Education Review,23(2), 341–359.
https://doi.org/10.1007/s12564-022-09759-4
Han, J. S., & Lee, J. W. (2020). Demographic change, human
capital, and economic growth in Korea. Japan and the World
Economy,53, 100984. https://doi.org/10.1016/j.japwor.2019.
100984
Han, L., & Zhou, H. (2024). The evolutionary characteristics,
current dilemmas, and approach choices of after-school ser-
vice policies in my country. Teaching and Management,
36(03), 19–22.
Han, T., & Su, D. (2022). The connotation, value and direction
of improving school education quality under the ‘‘double
reduction’’ policy. China Educational Technology,5, 42–48.
Huang, X. (2022). American after-school service evaluation sys-
tem and its enlightenment to Chinese after-school services
under the ‘‘double reduction’’ policy. Transactions on Com-
parative Education,4(3), 22–29. https://doi.org/10.23977/
trance.2022.040304
Hung, M., Smith, W. A., Voss, M. W., Franklin, J. D., Gu, Y.,
& Bounsanga, J. (2020). Exploring student achievement
gaps in school districts across the United States. Education
and Urban Society,52, 175–193. https://doi.org/10.1177/
0013124519833442
Huse
´n, T. (1972). Social background and educational career:
Research perspectives on equality of educational opportunity.
John Wiley & Sons.
Husen, T. (1975). Social influences on educational attainment. In
research perspectives on educational equality (p. 186). Organi-
sation for Economic Cooperation and Development.
Iba
´n
˜ez, M. B., Uriarte Portillo, A., Zatarain Cabada, R., &
Barro
´n, M. L. (2020). Impact of augmented reality technol-
ogy on academic achievement and motivation of students
from public and private Mexican schools. A case study in a
middle-school geometry course. Computers & Education,
145, 103734. https://doi.org/10.1016/j.compedu.2019.103734
Jansen, D., Elffers, L., & Jak, S. (2023). A cross-national
exploration of shadow education use by high and low SES
families. International Studies in Sociology of Education,
32(3), 653–674. https://doi.org/10.1080/09620214.2021.
1880332
Wang et al. 17

Jenson, J. M., Veeh, C., Anyon, Y., St. Mary, J., Calhoun, M.,
Tejada, J., & Lechuga-Pen
˜a, S. (2018). Effects of an after-
school program on the academic outcomes of children and
youth residing in public housing neighborhoods: A quasi-
experimental study. Children and Youth Services Review,88,
211–217. https://doi.org/10.1016/j.childyouth.2018.03.01
John, A. A. (1998). Lyndon Johnson and the great society.Ivan
R. Dee Inc.
Jung, J. (2022). Education and social stratification in South
Korea. Social Science Japan Journal,25(1), 173–176. https://
doi.org/10.1093/ssjj/jyab040
Karl, L. A., & Eckland, B. K. (1977). High school context and
college selectivity: Institutional constraints in educational
stratification. Social Forces,56(1), 166–188. https://doi.org/
10.2307/2577419
Kongsved, S. M., Basnov, M., Holm-Christensen, K., & Hjol-
lund, N. H. (2007). Response rate and completeness of ques-
tionnaires: A randomized study of Internet versus paper-
and-pencil versions. Journal of Medical Internet Research,
9(3), e25.
Korean Statistical Information Service (KOSIS). (2020).
Shadow education participation rate by school level [in Kor-
ean]. https://kosis.kr/statHtml/statHtml.do?orgId=101&
tblId=DT_1PE301&vw_cd=MT_ZTITLE&list_id=
O153&seqNo=&lang_mode=ko&language=kor&obj_
var_id=&itm_id=&conn_path=MT_ZTITLE
Kuperminc, G. P., Seitz, S., Joseph, H., Khatib, N., Wilson, C.,
Collins, K., & Guessous, O. (2019). Enhancing program
quality in a national sample of after-school settings: The role
of youth-staff interactions and staff/organizational function-
ing. American Journal of Community Psychology,63(3–4),
391–404. https://doi.org/10.1002/ajcp.12329
Lee, C. J., Lee, H., & Jang, H. M. (2010). The history of policy
responses to shadow education in South Korea: Implica-
tions for the next cycle of policy responses. Asia Pacific Edu-
cation Review,11, 97–108. https://doi.org/10.1007/s12564-
009-9064-6
Lee,J.,Zhang,T.,Chu,T.L.A.,Gu,X.,&Zhu,P.(2020).Effects
of a fundamental motor skill-based afterschool program on
children’s physical and cognitive health outcomes. International
Journal of Environmental Research and Public Health,17(3),
Article 733. https://doi.org/10.3390/ijerph17030733
Leos-Urbel, J. (2015). What works after school? The relation-
ship between after-school program quality, program atten-
dance, and academic outcomes. Youth & Society,47(5),
684–706.
Lester, A. M., Chow, J. C., & Melton, T. N. (2020). Quality is
critical for meaningful synthesis of afterschool program
effects: A systematic review and meta-analysis. Journal of
Youth and Adolescence,49(2), 369–382. https://doi.org/10.
1007/s10964-019-01188-8
Liang, Q., Niu, W., Cheng, L., & Qin, K. (2022). Creativity out-
side school: The influence of family background, perceived
parenting, and after-school activity on creativity. Journal of
Creative Behavior,56(1), 138–157. https://doi.org/10.1002/
jocb.521
Li, L., Yang, Y., & Zhou, L. (2022). Can after-school tutoring
improve the academic performance of students from low-
income families? Trial evidence from economically backward
areas in China. Asia Pacific Education Review.23(1), 1–13.
https://doi.org/10.1007/s12564-022-09803-3
Lin, L. (2022). The impact of double reduction policy on K12 edu-
cation and training enterprises: Case studies of new oriental
and tomorrow advancing life [Conference session]. 2022 2nd
International Conference on Enterprise Management and
Economic Development (ICEMED 2022) (pp. 1281–1286).
Atlantis Press. https://doi.org/10.2991/AEBMR.K.220603.
208
Lucas, S. (2001). Effectively maintained inequality: Education
transitions track mobility, and social background effects.
American Journal of Sociology,106(6), 1642–1690. https://
doi.org/10.1086/321300
Lu, X. (2002). A report on social stratification in contemporary
China. Social Sciences Academic Press.
Malhotra, N. K., Kim, S. S., & Patil, A. (2006). Common
method variance in IS research: A comparison of alternative
approaches and a reanalysis of past research. Management
Science,52(12), 1865–1883. https://doi.org/10.1287/mnsc.
1060.0597
Marimuthu,T.,Singh,J.S.,Ahmad,K.,Kuan,L.H.,&Osman,
S. (1991). Extra school instruction, social equity and educational
quality. International Development Research Centre.
Ma, Y., & Zeng, Q. (2018). The narrowing of the functions of
after-school services in schools and their institutional break-
through. Contemporary Educational Science,12(11), 60–64.
Ministry of Education of the People’s Republic of China.
(2023). Interim measures for administrative penalties for off-
campus training. http://www.moe.gov.cn/srcsite/A02/s5911/
moe_621/202309/t20230912_1079788.html
Mueller, R. O., & Hancock, G. R. (2018). Structural equation
modeling. In G. R. Hancock & R. O. Mueller (Eds.), The
reviewer’s guide to quantitative methods in the social sciences
(pp. 445–456). Routledge.
Nganga, L., Kambutu, J., & Han, K. T. (2019). Caring schools
and educators: A solution to disparities in academic perfor-
mance: Learners of color speak. Sage Open, 9, 1–9. https://
doi.org/10.1177/2158244019841923
Ni, M. (2021). How to implement the ‘‘double reduction’’" pol-
icy. Shanghai Education Research,9, 1–9. https://doi.org/10.
16194/j.cnki.31-1059/g4.2021.09.001
OECD. (2018). Equity in education and social mobility.OECDiLi-
brary. https://read.oecd-ilibrary.org/education/equity-in-edu-
cation/overview-and-policy-implications_9789264073234-4-en
OECD. (2020). Private spending on education (indicator).
https://data.oecd.org/eduresource/private-spending-on-edu-
cation.htm
Oyshi, F. J., Suhi, S. S., Sultana, A., Jahan, N., & Hossain, M.
T. (2021). The academic achievement of secondary students
in Bangladesh: Assessing the role of socioeconomic status,
school attributes, and academic activities. Education
Research International,2021, 5360672. https://doi.org/10.
1155/2021/5360672
Park, H. J., Byun, J., & Jo, S. (2012). Do after-school programs
matter? A longitudinal study on the effectiveness of partici-
pating in after-school programs in Korea. KEDI Journal of
Educational Policy,9(1), 1–21.
Philp, K. D., & Gill, M. G. (2020). Reframing after-school pro-
grams as developing youth interest, identity, and social
18 SAGE Open

capital. Policy Insights from the Behavioral and Brain
Sciences,7(1), 19–26. https://doi.org/10.1177/2372732
219892647
Podsakoff, P. M., MacKenzie, S. B., Lee, J. Y., & Podsakoff,
N. P. (2003). Common method biases in behavioral research:
A critical review of the literature and recommended reme-
dies. Journal of Applied Psychology,88, 879–903. https://doi.
org/10.1037/0021-9010.88.5.879
Podsakoff, P. M., & Organ, D. W. (1986). Self-reports in orga-
nizational research: Problems and prospects. Journal of
Management,12(4), 531–544. https://doi.org/10.1177/
014920638601200408
Polit, D. F., & Beck, C. T. (2010). Generalization in quantita-
tive and qualitative research: Myths and strategies. Interna-
tional Journal of Nursing Studies,47(11), 1451–1458. https://
doi.org/10.1016/j.ijnurstu.2010.06.004
Qiu, L., & Xiao, R. (2011). Cultural capital and status attain-
ment: An empirical study based in Shanghai. Social Sciences
in China,12(06), 121–135.
Raftery, A. E., & Hout, M. (1993). Maximally maintained
inequality: Expansion, reform, and opportunity in Irish edu-
cation, 1921-75. Sociology of Education,66(1), 41–62.
https://doi.org/10.2307/2112784
Rawls, J. (1999). A theory of justice. Harvard University Press.
Roemer, J. E., & Trannoy, A. (2016). Equality of opportunity:
Theory and measurement. Journal of Economic Literature,
54(4), 1288–1332. https://doi.org/10.1257/jel.20151206
Russell, W. R., & Gregory, J. P. (2005). Does segregation still
matter? The impact of student composition on academic
achievement in high school. Teachers College Record,107,
999–2045. https://doi.org/10.1111/J.1467-9620.2005.00583.X
Tan, C. Y., Peng, B., & Lyu, M. (2019). What types of cultural
capital benefit students’ academic achievement at different
educational stages? Interrogating the meta-analytic evidence.
Educational Research and Reviews,28, 100289. https://doi.
org/10.1016/j.edurev.2019.100289
The European Foundation for the Improvement of Living and
Working Conditions. (2020). Out-of-school care: Provision
and public policy. Publications Office of the European
Union.
The National Center for Education Statistics. (2018). The condi-
tion of education 2015. http://nces.ed.gov/programs/coe/ata-
glance.asp
The Xinhua News Agency. (2021). The general offices of the
Communist Party of China Central Committee and the State
Council ‘‘ease the burden of excessive homework and off-
campus tutoring for students undergoing compulsory educa-
tion.’’http://www.gov.cn/zhengce/2021-07/24/content_
5627132.htm
Tramonte, L., & Willms, J. D. (2010). Cultural capital and its
effects on education outcomes. Economics of Education
Review,29(2), 200–213. https://doi.org/10.1016/j.econe-
durev.2009.09.001
Tsiplakides, I. (2018). Shadow education and social class
inequalities in secondary education in Greece: The case of
teaching English as a foreign language. International Journal
of Sociology of Education,7(1), 71–93. https://doi.org/10.
17583/rise.2018.2987
Vandell, D. L., Lee, K. T. H., Whitaker, A. A., & Pierce, K.
M. (2020). Cumulative and differential effects of early child
care and middle childhood out-of-School time on adolescent
functioning. Child Development,91(1), 129–144. https://doi.
org/10.1111/cdev.13136
Wan, C. D., & Weerasena, B. (2017). Shadow education in
Malaysia: Identifying the determinants of spending and
amount of time attending private supplementary tutoring of
upper secondary school students. Journal of International
Comparative Education,6(2), 91–103. https://doi.org/10.
14425/jice.2017.6.2.91
Wang, J., & Wu, Y. (2023). Income inequality, cultural capital, and
high school students’ academic achievement in OECD countries:
A moderated mediation analysis. British Journal of Sociology,
74(2), 148–172. https://doi.org/10.1111/1468-4446.12997
Wang, Z., Tang, S., & Luo, F. (2023). A comparative study of
Texas-Mexico border vs. Non-border students’ achievement
on high-stakes state test: A propensity score matching
method. Frontiers in Education,8, 1–10. https://doi.org/10.
3389/FEDUC.2023.1010009
Wu, M. L. (2013). Structural equation modeling——Tips for
practical application. University Press.
Xiao, R. (2016). Family background, cultural capital and educa-
tion attainment. Education Research Monthly,12(2), 12–20.
Xue, H. P. (2015). From school education to shadow education:
Education competition and social reproduction. Peking Uni-
versity Education Review,13(3), 47–69. https://doi.org/10.
19355/j.cnki.1671-9468.2015.03.005
Xue, H. P. (2018). Family capital and educational attainment:
Analysis on the mediating effect of shadow education. Edu-
cation and Economy,4, 69–78.
Xue, H. P., & Li, J. (2016). Family capital shadow education
and social reproduction. Economics of Education Review,
1(4), 60–81. https://doi.org/10.19512/j.cnki.issn2096-2088.
2016.04.004
Yang, Q. X., & Wu, Z. H. (2021). The policy blocking point
and dredging strategy of after-school service in compulsory
education schools. Research in Educational Development,41,
42–49. https://doi.org/10.14121/j.cnki.1008-3855.2021.z2.008
Yang, S. (2023). Typical practices and problem analysis of my
country’s local governments’ implementation of ‘‘double
reduction’’—based on four batches of typical cases selected
by the Ministry of Education. Journal of Shanghai Educa-
tional Research,6, 42–47. https://doi.org/10.16194/j.cnki.31-
1059/g4.2023.06.004
Yang, W. D., & Tang, X. (2023). On the public welfare nature
of after-school services. Journal of Educational Science of
Hunan Normal University, 22, 1–11.
Yao, J., Yao, J., Li, P., Xu, Y., & Wei, L. (2023). Effects of
after-school programs on student cognitive and non-
cognitive abilities: A meta-analysis based on 37 experimen-
tal and quasi-experimental studies. Science Insights Educa-
tion Frontiers,17(1), 2627–2649. https://doi.org/10.15354/
sief.23.re228
You, S., & Zhou, X. J. (2020). On connotation, value and goal
of after-school service for primary and secondary school stu-
dents under background of flexible school leaving. Teaching
and Administration,9, 31–35.
Wang et al. 19

Yu, M. V. B., Liu, Y., Soto-Lara, S., Puente, K., Carranza, P.,
Pantano, A., & Simpkins, S. D. (2021). Culturally responsive
practices: Insights from a high-quality math afterschool pro-
gram serving underprivileged Latinx youth. American Jour-
nal of Community Psychology,68(3–4), 323–339. https://doi.
org/10.1002/ajcp.12518
Yu, S., Zheng, J., Xu, Z., & Zhang, T. (2022). The transforma-
tion of parents’ perception of education involution under
the background of ‘‘double reduction’’ policy: The mediat-
ing role of education anxiety and perception of education
equity. Frontiers in Psychology,13, 800039. https://doi.org/
10.3389/fpsyg.2022.800039
Yu, Y., & Pan, Y. D. (2022). The research on operation mode
and guarantee mechanism of after school program in United
States. Studies in Foreign Education,49(10), 60–73.
Zhang, B., & Cheng, T. J. (2021). An expedient execution: The
action logic of school after-class service. Research in Educa-
tional Development,41, 50–58. https://doi.org/10.14121/j.
cnki.1008-3855.2021.z2.009
Zhang, H. P., Zhang, Q. G., & Yin, X. (2021). On family capi-
tal, shadow education and the equity of educational oppor-
tunities. Education Research Monthly,2, 3–11. https://doi.
org/10.16477/j.cnki.issn1674-2311.2021.02.001
Zhang, J., Zheng, J., Cui, H., & Zhang, L. (2024). How school
education contributes to the social and emotional develop-
ment of students: A study based on cluster analysis. Journal
of East China Normal University (Educational Sciences),
12(5), 72–82.
Zhang, W. (2020). Shadow education in the service of tiger par-
enting: Strategies used by middle-class families in China.
European Journal of Education,55(3), 388–404.
Zhang, W. C. (2021). Idea tendency and improvement direction
of for implementation of school after-class service. Teaching
and Administration,20, 7–10.
Zou, M. (2020). Discussion on the attributes and related rights
and responsibilities of after-school services in primary and
secondary schools. Journal of the Chinese Society of Educa-
tion,3, 32–36.
20 SAGE Open

Table A1. Family Cultural Capital.
Higher-order
latent variables
Primary latent
variables
Indicator
coding Survey questions
measurement
Items
Family cultural
capital
Investment in cultural
education
ICE1 How many books do you have at home?
(Typically, a one-meter-long bookshelf can hold
approximately 40 books. Please do not include
magazines, newspapers, or textbooks in your
count.)
6-point (1–6). ffi0–10, ffl11–25, 26–100, Ð101–200,
ð201–500, Þmore than 500
ICE2 How many musical instruments do you have at
home?
5-point (1–5). ffi0, ffl1, 2, Ð3, ð4 and more
ICE3 How often do you visit bookstores, book fairs,
or libraries (including school libraries)?
5-point (1–5). ffinever or almost never, fflonce or twice
a year,once or twice a month, Ðonce or twice a week,
ðevery day or almost every day
ICE4 How often do you visit museums related to art,
science, or history?
5-point (1–5). ffinever or almost never,ffl1–2 times a
year, 1–2 times ever y 6 months, Ð1–2 times per
quarter,ðevery month or almost every monthICE5 How often do your parents participate in school
activities (e.g., volunteering at sports events,
coordinating social practice activities, etc.)?
ICE6 How often do you travel abroad for study-
related purposes?
Parents’ cultural
background
PCB1 What is your mother’s highest level of
education?
7-point (1–7). ffijunior high school and below,
fflsecondary vocational education, general high school,
Ðvocational training after high school graduation,
ðjunior college,Þundergraduate, a
˜I
ˆmaster’s degree and
above
PCB2 What is your mother’s occupation? 5-point (1–5). Parents’ occupation, classified into 10
categories as per Lu’s (2002) social class report, and then
coded twice in reverse as ffiupper-class, fflupper-middle
class, middle-middle class,Ðlower-middle class, ð
lower-class.
PCB3 What is your father’s occupation?
Children’s embodied
cbr78-21ultural capital
CECP1 On average, how many times per year do you
participate in academic, cultural, scientific,
sports, or art competitions and receive awards
at the school level or higher?
5-point (1–5). ffi0 times, ffl1 time, 2 times, Ð3
times, ð4 times and above.
CECP2 Which of the following levels of education do
you expect to complete?
8-point (1–8). ffijunior high school, fflsecondary
vocational education,regular high school, Ðvocational
training after high school graduation,ðjunior college,
Þundergraduate, a
˜I
ˆmaster’s degree,a
˜I
¨doctoral degree
CECP3 How would you describe your overall academic
performance in school? (Primarily based on mid-
term, final, and regular assessments.)
4-point (1–4). ffiunqualified, fflqualified,good,
Ðexcellent
CECP4 Do you frequently read non-fiction books (e.g.,
informational, documentary) for personal
interest?
5-point (1–5). ffinever or almost never, fflseveral times
a year,about once a month, Ðseveral times a month,
ðseveral times a week
Appendix A
Wang et al. 21

Table A2. School Input into Construction.
Latent variables
Indicator
coding Survey questions
Measurement
items
School input into
construction
SIC1 The school has assigned highly professional teachers to the
ASPs project.
6-point Likert (1–7).
ffiStrongly disagree, fflBasically
disagree, Somewhat disagree,
ÐSomewhat disagree,
ðBasically disagree, ÞStrongly
disagree
SIC2 The school has assigned teachers with a strong work ethic
to the ASPs project.
SIC3 The school has provided a well-developed educational
environment for the ASPs project.
SIC4 The school has established a robust safety and
accountability system for the ASPs project.
Table A3. Participation in ASPs.
Latent variables
Indicator
coding Survey questions Measurement items
Participation in ASPs PASPs1 You are satisfied with the subject-based educational
content provided in the school’s ASPs.
6-point Likert (1–7).
ffiStrongly disagree, fflBasically
disagree, Somewhat disagree,
ÐSomewhat disagree,
ðBasically disagree, ÞStrongly
disagree
PASPs2 You are satisfied with the quality of courses offered in the
school’s ASPs.
PASPs3 You are satisfied with the scheduling and time management
of the school’s ASPs.
PASPs4 You are satisfied with the safety measures implemented in
the school’s ASPs.
Table A4. Educational Outcomes.
Higher latent
variables
Primary latent
variables
Indicator
coding Survey questions Measurement items
Educational
outcomes
Academic
development
AD1 After participating in the school’s ASPs, your study habits
have significantly improved.
6-point Likert (1–7).
ffiStrongly disagree,
fflBasically disagree,
Somewhat disagree,
ÐSomewhat disagree,
ðBasically disagree,
ÞStrongly disagree
AD2 After participating in the ASPs, your problem-solving skills
have significantly improved.
AD3 After participating in the school’s ASPs, you are more
willing to explore problems in depth.
AD4 After participating in the school’s ASPs, you have gained a
better mastery of basic knowledge.
AD5 After participating in the school’s ASPs, your study
methods have significantly improved.
AD6 After participating in the school’s ASPs, you demonstrate
greater self-discipline.
AD7 After participating in the school’s ASPs, your self-
confidence has significantly improved.
Interests and
hobbies
IH1 After participating in the school’s ASPs, you can better
focus on your hobbies.
IH2 After participating in the school’s ASPs, you can further
develop your personal strengths.
IH3 After participating in the school’s ASPs, you have
developed a broad interest in various subjects.
IH4 After participating in the school’s ASPs, you can better
concentrate on your favorite activities.
IH5 After participating in the school’s ASPs, you can further
(continued)
22 SAGE Open

Table A4. (continued)
Higher latent
variables
Primary latent
variables
Indicator
coding Survey questions Measurement items
cultivate your personal hobbies.
IH6 After participating in the school’s ASPs, you actively
engage in extracurricular interest classes.
Parent-child
relationship
PCR1 After participating in the school’s ASPs, you can develop
more harmonious relationships with your family.
PCR2 After participating in the school’s ASPs, you can improve
communication with your parents.
PCR3 After participating in the school’s ASPs, you are more
willing to share your life experiences with your family.
Family burden FB1 After participating in the ASPs, you have a reduced need
for academic tutoring.
FB2 After participating in the ASPs, your family experiences
fewer difficulties in picking you up from school.
FB3 After participating in the ASPs, your family’s financial
burden related to education decreases.
FB4 After participating in the ASPs, you experience less
criticism from your parents.
FB5 After participating in the ASPs, your family’s expenses for
extracurricular activities are reduced.
FB6 After participating in the ASPs, your safety and well-being
are better ensured.
Wang et al. 23