Game-Based Intervention to Improve Child Financial Literacy: A Quasi-Experimental Study

Abstract

Purpose: This study assesses the effectiveness of a semester-long, game-based financial education program aimed at improving financial literacy among children in rural China. Method: A quasi-experimental design was used with data collected at baseline, posttreatment, and one-semester follow-up. Random sampling was conducted across four provinces implementing the program. The final sample included 470 fourth-grade students in the treatment group (19 schools) and 422 fourth-grade students in the control group (17 schools). Results: The program significantly improved students’ financial literacy, with effects sustained over one semester. Notable improvements were observed in the understanding of interest, inflation, and the purpose of insurance. However, the impact was not consistent across all six content areas. Discussion: Game-based financial education can effectively enhance children's financial literacy. To achieve broader and more sustained behavioral outcomes, integrating financial social work practices—such as financial coaching and family engagement—may be essential.

Keywords

financial education financial literacy children financial social work quasi-experiment

A robust foundation in financial literacy is critical to achieving a range of life objectives, including educational attainment, retirement planning, debt management, and personal financial control (Organization for Economic Co-operation and Development, 2014). Core competencies in financial literacy encompass calculating, budgeting, long-term financial planning, debt regulating, and expenditure tracking. Deficits in these areas are associated with a heightened risk of adverse financial behaviors, such as excessive borrowing and inadequate preparation for future needs, which may result in serious consequences, including poor credit ratings, insolvency, and home foreclosure (Hastings et al., 2013). Accordingly, advancing financial literacy constitutes a vital public policy and educational priority (Peng et al., 2022).

In contemporary society, children and adolescents are growing up in an environment marked by increasingly complex financial systems and decision-making demands. The significance of child financial literacy cannot be overstated in its correlation with subsequent financial well-being. Nevertheless, an examination of empirical studies reveals a pervasive deficiency in financial literacy among youth on a global scale (Garg & Singh, 2018). Given the developmental differences between adults and youth—particularly in terms of experience with financial responsibilities and exposure to real-world economic challenges—strategies designed for adults cannot be directly applied to younger populations (McCormick, 2009). As a result, efforts to establish a solid financial foundation for children and adolescents often focus on school-based interventions aimed at enhancing their financial literacy (Amagir et al., 2018).

The implementation of school-based interventions is widely supported, largely due to the structured nature of the school environment, which offers a practical platform for delivering financial education to children who typically have limited exposure to financial activities and decision-making compared to adults (Kaiser & Menkhoff, 2020; McCormick, 2009). Given that learning patterns and behavioral foundations are often formed early in life, many scholars advocate for initiating financial education during childhood (Batty et al., 2015). However, the effectiveness of such interventions remains a subject of debate in the literature. While numerous studies report positive effects on financial knowledge and behavior (e.g., Bruhn et al., 2016; Fernandes et al., 2014; Walstad et al., 2010), others have found limited or no significant impact (Mandell & Klein, 2009; Peng et al., 2007).

Amid the rapid development of financial markets and digital payment systems in China, the importance of financial education for children has gained increasing recognition from the Chinese government. In 2015, the State Council issued the Guiding Opinions on Strengthening the Protection of Financial Consumers’ Rights and Interests, which explicitly directed the Ministry of Education to integrate financial literacy education into the national education system to improve the financial competence of the population (The State Council of China, 2015). Although a nationwide mandate for school-based financial education has not yet been implemented, a variety of initiatives have since been launched. However, research on the financial literacy levels of Chinese children—particularly those in suburban and rural areas—and on the effectiveness of such programs remains limited. This study addresses that gap by documenting a school-based intervention led by Shanghai Better Education Development Center (SBEDC), China, offering valuable data on both the financial literacy of suburban and rural children and the impact of the intervention via an experimental-design study.

Literature Review

Child Financial Literacy

The concept of financial literacy has been widely studied, particularly in adult populations, with growing attention to how it develops in children. Since Bernheim and Garrett (1996) introduced the term, defining and measuring financial literacy has become a central concern in the field. Huston (2010) conceptualized financial literacy as comprising four key domains—money basics, borrowing, investing, and protecting resources—arguing that it is an essential component of human capital. Lusardi and Mitchell (2014) further framed financial literacy as an individual capability, commonly measured through three core constructs: numeracy, understanding of inflation, and risk diversification. Building on this foundation, the International Network on Financial Education (INFE) of the Organization for Economic Co-operation and Development (OECD) (2022) proposed a multidimensional definition encompassing awareness, knowledge, skills, attitudes, and behaviors necessary for effective financial decision-making. Although definitions and measurement approaches vary, there is a broad consensus that competencies related to money management, inflation, and risk mitigation are foundational.

The literature on children's financial literacy often builds upon this adult framework, adapting its concepts and measures to age-appropriate levels. For example, Batty et al. (2015) developed a measurement tool for elementary school students as part of a classroom-based financial education program derived from the Council for Economic Education's Financial Fitness for Life curriculum. This tool evaluates children's understanding of numeracy and basic financial concepts, such as saving, interest, budgeting, and cost. Fernandes et al. (2014) focused on high school students, assessing their financial literacy through measures covering inflation, interest rates, risk diversification, and financial product selection based on risk-return tradeoffs. These adapted frameworks reflect an emerging consensus on the importance of introducing core financial concepts early in the developmental process.

A growing body of empirical research provides evidence supporting the effectiveness of school-based financial education programs in improving children's financial knowledge and behavior. Batty et al. (2015) conducted an experimental evaluation of a financial education program for fourth- and fifth-grade students, finding significant and lasting gains in financial knowledge, with effects persisting one year after the intervention. Similarly, Kalwij et al. (2019) employed a controlled field experimental design to examine the impact of a financial education program on Dutch primary school students. Their study revealed substantial improvements in both financial literacy scores and saving behavior among fifth- and sixth-grade participants, suggesting that early exposure to financial education can influence not only knowledge but also financial habits.

Further reinforcing these findings, Dare et al. (2020) evaluated the effectiveness of a national financial education initiative in the Netherlands through a quasi-experimental design. They found that fifth-grade students who participated in the program demonstrated notable improvements in both financial knowledge and practical financial skills. These results contribute to a growing international consensus on the value of early financial education within formal schooling contexts.

Synthesizing the broader evidence base, Kaiser and Menkhoff (2020) conducted a meta-analysis of 37 experimental and quasi-experimental studies assessing the impact of financial education on children and youth. Their findings indicated a sizable and statistically significant positive effect of such education programs on financial knowledge outcomes. While the effect on behavior was more modest, it nonetheless demonstrated the potential for structured financial education to shape both understanding and decision-making at a young age.

Collectively, these studies suggest that school-based financial education is a critical intervention for fostering financial literacy in children. Through well-designed curricula and age-appropriate instruction, children not only gain essential knowledge but also begin to develop positive financial behaviors that can support long-term economic well-being.

Child Financial Literacy and Educational Context in China

In the context of China's rapid economic development, children generally have become increasingly engaged in financial activities from an early age. Some receive pocket money as early as age four, and the majority begin to receive it regularly upon entering elementary school (McNeal & Yeh, 1997). With pocket money, children undertake a variety of financial behaviors, including budgeting, spending, product selection, and saving. A large-scale study based on data from ten provinces reported that by 2010, nearly half of Chinese children and adolescents had accumulated savings exceeding 1,000 CNY—a threefold increase compared to 1999 (Sun, 2011).

Early engagement in financial activities highlights the importance of child financial literacy in China; however, empirical investigation in this area remains limited. Notably, a substantial disparity in financial literacy may exist between rural children and their urban counterparts. Financial literacy is primarily developed through two mechanisms: direct interaction with available financial products and financial socialization, education, and guidance (Sherraden, 2013). Evidence indicates that rural children derive lower benefits from both channels relative to urban children. Residence in rural areas is a negative predictor of financial literacy (He & Ahunov, 2022; Jin & Yuan, 2019), likely reflecting reduced opportunities for rural children to receive high-quality financial socialization and guidance from adults within their communities. Furthermore, the limited availability of financial products in rural settings (Chen & Jin, 2017; Song et al., 2020) constrains children's exposure to the range of financial instruments more readily accessible to their urban peers.

Financial education programs were first introduced in some schools in 2001, predominantly in economically advanced regions such as Beijing, Shanghai, and Guangdong (Gao, 2014). However, financial education has yet to be institutionalized as a national requirement in China. Consequently, most programs remain localized, often initiated by municipal governments, schools, or financial institutions in more developed urban coastal areas. For example, the Guangzhou Branch of the People's Bank of China, in partnership with local financial and educational authorities, launched the “Southern Guangdong Finance—Spring Rain Nurtures Growth” initiative in 2014. This program has since reached more than 1,600 primary and secondary schools across the province, serving over 500,000 students (Yu, 2017). Similarly, the Shanghai Stock Exchange introduced the “Youth Financial Literacy N + 1” initiative in 2018, which has included over 100 educational visits to the Exchange for youth participants (Yang, 2023). By May 2023, financial education had been incorporated into the curriculum of all 360 elementary schools in Nantong, Jiangsu Province—a collaborative effort involving the Nantong Branch of the People's Bank of China, local financial institutions, and the Nantong Bureau of Education (Zhang et al., 2023). However, few financial education programs target rural children. Moreover, such initiatives seldom accompanied by rigorous evaluations of their effectiveness. Notable exceptions have provided evidence of the positive impact of school-based financial education on children in China. Zhu et al. (2021) employed a randomized experimental design to demonstrate that financial education significantly improved financial literacy, although the study was limited to ninth-grade students in Hong Kong secondary schools.

The Game-Based Intervention and the Present Study

While existing studies in other countries have demonstrated the effectiveness of school-based financial education in improving children's overall financial knowledge, few have explored the financial literacy of children in China—particularly those from less developed regions—and the effectiveness of related educational interventions.

This study evaluates a game-based financial education program for children in suburban and rural areas of China. The program was developed and implemented by SBEDC, one of the country's largest social work organizations dedicated to promoting financial literacy among children and youth. By 2024, SBEDC's services had reached more than 1,300 elementary and secondary schools as well as colleges across 30 provinces in China (SBEDC, 2024).

The intervention evaluated in this study is a game-based financial education program targeting elementary school students in China, particularly those in Grades 3 to 6 (typically aged 9–12). It is delivered through a series of game-based workshops facilitated by local schoolteachers. The core component is a board game that simulates managing a chicken farm, where students make financial decisions such as buying or selling chickens, saving or borrowing money, and purchasing insurance. Each workshop begins with a specific financial task that students must accomplish through gameplay. Facilitators are trained to (a) identify teachable moments during the game to provide guidance or pose probing questions, and (b) conduct postgame reviews followed by short lectures on financial concepts illustrated in the game. To ensure consistency, teachers received standardized teaching materials—including the board game and instructional slides—and underwent training provided by SBEDC prior to implementation. According to SBEDC's implementation guide (n.d.), the program is designed to be completed within one academic semester.

The change model underpinning the intervention reflects the aforementioned key mechanisms, specifically direct engagement with financial products and processes of financial socialization, education, and guidance (Sherraden, 2013). The board game functions as a simulated financial environment that operationalizes experiential interaction with financial products, while facilitators serve as agents of financial coaches who mediate learning through guided reflection, instruction, and feedback. Through the interplay of these mechanisms, the intervention is theorized to foster the development of several core financial literacy competencies, including numerical skills, risk–return association, risk diversification, and comprehension of insurance mechanisms.

Using a quasi-experimental design, the evaluation study presents descriptive statistics on children's financial literacy and assesses the program's effectiveness. Furthermore, it examines how specific components of financial literacy are influenced by the intervention, considering demographic and socioeconomic factors.

Method

Data

The data for this study were obtained from the evaluation of the game-based financial education program. A quasi-experimental design was employed for the evaluation. Nineteen schools were randomly sampled from four program-covered provinces in China by the time of evaluation: Guangdong (southeastern coast), Guizhou (mountainous southwest), Sichuan (southwest), and Gansu (north-central). Among the 12 schools with more than one fourth-grade class, two classes were randomly selected and assigned to either the treatment or control group. Fourth-grade students, aged 10–11, were selected based on prior research indicating that children at this age possess sufficient cognitive maturity to engage in basic financial decision-making and to complete questionnaire-based assessments (Batty et al., 2015). In the remaining seven schools, which had only one fourth-grade class, the class was assigned to the treatment group, and a fourth-grade class from a nearby school was recruited to serve as the control group. In total, 24 schools participated in the study: 12 schools contributed both treatment and control groups, seven schools contributed only treatment groups, and five schools contributed only control groups.

Data collection was conducted in three waves: Wave 1 at baseline, immediately prior to the intervention; Wave 2 immediately following the intervention; and Wave 3 at a one-semester follow-up. SBEDC conducted all data collection activities, including student demographic information and financial literacy assessments. All data were de-identified prior to being shared with the research team. The final sample includes 892 students from 24 schools, with 470 in the treatment group and 422 in the control group. See Figure 1 for the flow of participants through each stage of the evaluation.

Measures

Financial literacy was assessed using six items developed from the content of the intervention game, ensuring strong alignment between the evaluation and the learning objectives of the program. Each item is dichotomously scored (1 = correct, 0 = incorrect), with the total score representing a summative index ranging from 0 to 6. The six items measure distinct components of financial literacy: basic calculation, understanding of bank interest, inflation, risk diversification, risk-return association, and the purpose of insurance.

The specific questions are as follows:

Basic calculation: “If you buy a toy for $6 with a $10 bill, how much change should you receive?”

Interest: “If you save $500 in a bank, how much will you have after one year? (more than, equal to, or less than $500)”

Inflation: “Which is worth more: $500 now or $500 a few years ago (i.e., which can buy more)?”

Risk Diversification: “To reduce the risk of losing money, which is better: investing everything in one place or investing in different places?”

Risk–Return Association: “Do you agree that a business that enables people to earn money can also lead to losses?”

The purpose of insurance: “Do you agree that insurance can help buffer unexpected expenses, such as hospital bills?”

The items are content-wise consistent with those developed by OECD (2022) to measure the same components of financial literacy, and the OECD measure has been adopted in several recent studies in China (e.g., Qian et al., 2024). The six items demonstrated acceptable reliability (Cronbach's alpha = .76). Factor analysis indicated a single factor with an eigenvalue > 1, supporting the unidimensional structure of the child financial literacy construct. Standardized factor loadings were 0.96, 0.70, 0.98, 0.96, 0.70, and 0.60 for basic calculation, interest, inflation, risk diversification, risk–return association, and insurance, respectively.

Child demographic variables include child gender (girls = 1, boys = 0), ethnicity (minority = 1, majority [Han ethnicity] = 0), residential area (rural = 1, suburban = 0), and parental highest educational level, coded into three categories: “do not know,” “elementary school and below,” and “middle school and above.” These variables are included to control for potential confounding influences in the analysis of program outcomes.

Thus, the study included the following hypotheses:

Hypothesis 1: Participants in the treatment groups will display statistically greater improvements on financial literacy posttreatment, compared to the control group.

Hypothesis 2: Participants in the treatment groups will display statistically greater improvements on basic calculation skills posttreatment, compared to the control group.

Hypothesis 3: Participants in the treatment groups will display statistically greater improvements on understanding interest posttreatment, compared to the control group.

Hypothesis 4: Participants in the treatment groups will display statistically greater improvements on understanding inflation posttreatment, compared to the control group.

Hypothesis 5: Participants in the treatment groups will display statistically greater improvements on understanding risk diversification posttreatment, compared to the control group.

Hypothesis 6: Participants in the treatment groups will display statistically greater improvements on understanding risk-return association posttreatment, compared to the control group.

Hypothesis 7: Participants in the treatment groups will display statistically greater improvements on understanding the purpose of insurance posttreatment, compared to the control group.

Results

Sample Characteristics

Descriptive results in Table 1 indicate no significant differences in gender distribution, residency status, or parental highest educational attainment between intervention participants and nonparticipants. The only statistically significant difference is a higher proportion of ethnic minority children in the treatment group compared to the control group, χ²(1) = 11.01, p < .001.

Table 1.

Sample Characteristics.

	Sample
	Treatment (n = 470)	Control (n = 422)
Girls, %	45.11	50.95
Ethnic minority***, %	35.11	24.88
Parental highest education, %
Do not know	41.70	37.91
Elementary school and below	37.66	35.07
Middle school and above	20.64	27.01
Rural, %	81.49	78.91

*p < .05. **p < .01. ***p < .001.

Table 2 presents descriptive statistics on financial literacy across three waves for both treatment and control groups. Across all waves, children in the treatment group consistently outperformed those in the control group in overall financial literacy scores; however, the difference reached statistical significance only in Wave 3, t(890) = –2.03, p < .05. The two groups showed no significant differences in basic calculation, understanding of interest, risk–return association, or risk diversification at any wave. In contrast, the treatment group consistently demonstrated significantly higher levels of understanding of inflation and the purpose of insurance throughout the evaluation period.

Table 2.

Children's Financial Literacy.

Financial literacy	Wave 1		Wave 2		Wave 3
Financial literacy	T	C	T	C	T	C
Calculation, %	95.32	96.45	95.11	96.45	94.04	94.79
Interest, %	51.70	50.71	53.40	50.71	51.91	49.29
Inflation, %	41.28	31.52	37.87	26.54	37.66	28.91
Risk diversification, %	67.65	70.62	68.09	68.72	72.77	68.96
Risk-return association, %	72.34	72.51	72.98	73.46	70.00	71.80
Insurance, %	79.15	68.96	77.23	71.33	76.81	69.91
OFL (0–6)	4.07	3.91	4.05	3.87	4.03	3.84

Note. T = treatment; C = control; OFL = overall financial literacy.

Hypotheses Testing

Hypothesis 1 proposed that participants in the treatment groups would demonstrate significantly greater improvements in financial literacy posttreatment compared to those in the control group. To test this, mixed-effects models were employed, specifying a random intercept at the school level to account for clustering. This approach allowed us to assess the association between the intervention and financial literacy outcomes while considering the hierarchical structure of the data. To address potential unobserved confounders and baseline differences, each model included the baseline value of overall financial literacy as a covariate, thereby reducing estimation bias by adjusting for pretreatment variation in the outcome of interest.

Table 3 shows that the intervention had a statistically significant positive effect on financial literacy at both posttreatment and the one-semester follow-up, indicating a sustained impact over time. These results support Hypothesis 1. Being a member of a racial minority group was significantly associated with lower financial literacy scores at Wave 2; however, this association was no longer significant at Wave 3. Children whose parents’ highest level of education was unknown consistently scored lower than those whose parents had completed only elementary school. In contrast, children whose parents had attained a middle school education or higher scored significantly higher than the reference group at Wave 3. Baseline financial literacy scores were a significant predictor of outcomes at both postintervention time points. No significant effects were observed for gender or rural residency.

Table 3.

Effect of the Intervention on Children's Overall Financial Literacy.

	OFL (W2)				OFL (W3)
	B	SE	95% CI		B	SE	95% CI
Intervention	0.36***	0.11	0.152	0.564	0.37*	0.17	0.045	0.699
Girls (yes)	0.10	0.08	−0.065	0.263	0.05	0.10	−0.149	0.242
EM (yes)	−0.36*	0.17	−0.693	−0.118	−0.12	0.15	−0.410	0.171
Parental highest education (elementary school and below as the reference group)
Do not know	−0.38***	0.12	−0.614	−0.155	−0.39***	0.09	−0.572	−0.215
MSA	0.13	0.09	−0.045	0.309	0.28*	0.11	0.062	0.502
Rural (yes)	−0.12	0.19	−0.428	0.247	0.05	0.20	−0.348	0.439
OFL (W1)	0.12**	0.05	0.028	0.210	0.12**	0.05	0.025	0.209

Note. OFL = overall financial literacy; EM = ethnic minority; MSA = middle school and above; W1 = baseline; W2 = posttreatment assessment; W3 = one-semester follow-up assessment; B = unstandardized coefficient; SE = standard error; CI = confidence interval.

*p < .05. **p < .01. ***p < .001.

Hypotheses 2–7 stated that participants in the treatment groups would show significantly greater improvements in basic calculation skills, understanding of interest, inflation, risk diversification, risk–return association, and the purpose of insurance, respectively, at posttreatment compared to the control group. Mixed-effects logistic regression models were used to estimate the odds of correctly answering each financial literacy item. Models were fitted separately for outcomes at Waves 2 and 3, with baseline values of the corresponding outcome variables included as covariates to control for pre-intervention differences and potential confounders.

Tables 4 to 9 report results from mixed-effects logistic models estimating the odds of students correctly answering items across six financial literacy domains: basic calculation skills, understanding of interest, inflation, risk diversification, risk–return association, and the purpose of insurance. The intervention significantly improved students’ understanding of interest, inflation, and the purpose of insurance at both posttreatment and one-semester follow-up (Waves 2 and 3), supporting Hypotheses 3, 4, and 7. In contrast, its effects on basic calculation skills, risk diversification, and risk–return association were not consistently significant, leaving Hypotheses 2, 5, and 6 unsupported. Prior knowledge at baseline strongly predicted performance at either Wave 2 or Wave 3 across all domains except basic calculation skills.

Table 4.

Effect of the Intervention on Children's Skills of Basic Calculation.

	Cal (W2)				Cal (W3)
	OR	SE	95% CI		OR	SE	95% CI
Intervention	0.66	0.24	0.326	1.333	0.83	0.25	0.452	1.505
Girls (yes)	1.42	0.49	0.719	2.792	1.43	0.43	0.794	2.589
EM (yes)	0.66	0.30	0.272	1.607	0.70	0.27	0.325	1.496
Parental highest education (elementary school and below as the reference group)
Do not know	1.07	0.43	0.485	2.365	1.37	0.48	0.688	2.710
MSA	1.34	0.66	0.505	3.537	1.42	0.60	0.615	3.264
Rural (yes)	4.66**	2.37	1.718	12.625	2.87*	1.34	1.145	7.175
Cal (W1)	2.12	1.38	0.593	7.596	0.89	0.68	0.201	3.948

Note. Cal = calculation; EM = ethnic minority; MSA = middle school and above; W1 = baseline; W2 = posttreatment assessment; W3 = one-semester follow-up assessment; OR = odds ratio; SE = standard error; CI = confidence interval.

*p < .05. **p < .01. ***p < .001.

Table 5.

Effect of the Intervention on Children's Understanding of Interest.

	Interest (W2)				Interest (W3)
	OR	SE	95% CI		OR	SE	95% CI
Intervention	1.46*	0.24	1.063	2.008	1.41*	0.23	1.016	1.945
Girls (yes)	1.05	0.16	0.790	1.408	0.98	0.15	0.734	1.322
EM (yes)	0.50*	0.14	0.288	0.870	0.88	0.28	0.472	1.632
Parental highest education (elementary school and below as the reference group)
Do not know	0.57**	0.10	0.398	0.807	0.58**	0.11	0.408	0.836
MSA	1.02	0.21	0.686	1.525	1.34	0.28	0.895	2.019
Rural (yes)	0.89	0.40	0.372	2.149	1.31	0.69	0.470	3.665
Interest (W1)	1.26	0.19	0.935	1.706	1.53**	0.24	1.131	2.077

Note. EM = ethnic minority; MSA = middle school and above; W1 = baseline; W2 = posttreatment assessment; W3 = one-semester follow-up assessment; OR = odds ratio; SE = standard error; CI = confidence interval.

*p < .05. **p < .01. ***p < .001.

Table 6.

Effect of the Intervention on Children's Understanding of Inflation.

	INF (W2)				INF (W3)
	OR	SE	95% CI		OR	SE	95% CI
Intervention	2.43***	0.47	1.668	3.550	2.05***	0.38	1.434	2.936
Girls (yes)	1.28	0.21	0.934	1.762	1.18	0.19	0.861	1.612
EM (yes)	0.75	0.24	0.396	1.417	0.79	0.25	0.417	1.480
Parental highest education (elementary school and below as the reference group)
Do not know	0.79	0.16	0.531	1.171	0.57**	0.12	0.388	0.852
MSA	0.94	0.20	0.612	1.434	1.51	0.32	0.998	2.292
Rural (yes)	0.96	0.54	0.321	2.870	0.76	0.41	0.263	2.199
INF (W1)	1.91***	0.32	1.380	2.656	1.29	0.22	0.925	1.786

Note. INF = inflation; EM = ethnic minority; MSA = middle school and above; W1 = baseline; W2 = posttreatment assessment; W3 = one-semester follow-up assessment; OR = odds ratio; SE = standard error; CI = confidence interval.

*p < .05. **p < .01. ***p < .001.

Table 7.

Effect of the Intervention on Children's Understanding of Risk Diversification.

	RD (W2)				RD (W3)
	OR	SE	95% CI		OR	SE	95% CI
Intervention	1.02	0.15	0.758	1.374	1.38	0.23	0.995	1.921
Girls (yes)	1.18	0.18	0.879	1.575	1.23	0.19	0.904	1.673
EM (yes)	0.89	0.17	0.622	1.286	0.71	0.19	0.418	1.191
Parental highest education (elementary school and below as the reference group)
Do not know	0.82	0.15	0.574	1.158	0.67*	0.13	0.458	0.974
MSA	1.29	0.27	0.850	1.953	1.00	0.22	0.641	1.549
Rural (yes)	0.96	0.22	0.614	1.503	1.26	0.49	0.594	2.692
RD (W1)	2.15***	0.34	1.576	2.920	1.52*	0.25	1.095	2.104

Note. RD = risk diversification; EM = ethnic minority; MSA = middle school and above; W1 = baseline; W2 = posttreatment assessment; W3 = one-semester follow-up assessment; OR = odds ratio; SE = standard error; CI = confidence interval.

*p < .05. **p < .01. ***p < .001.

Table 8.

Effect of the Intervention on Children's Understanding of Risk–Return Association.

	RRA (W2)				RRA (W3)
	OR	SE	95% CI		OR	SE	95% CI
Intervention	1.23	0.22	0.866	1.735	1.08	0.19	0.768	1.515
Girls (yes)	1.09	0.18	0.793	1.505	1.06	0.17	0.776	1.457
EM (yes)	0.58*	0.15	0.348	0.979	0.76	0.21	0.438	1.301
Parental highest education (elementary school and below as the reference group)
Do not know	0.57**	0.11	0.396	0.834	0.74	0.14	0.511	1.069
MSA	1.70*	0.42	1.043	2.755	1.85*	0.45	1.154	2.970
Rural (yes)	0.73	0.28	0.341	1.566	1.01	0.43	0.443	2.312
RRA (W1)	1.09	0.20	0.771	1.554	1.93***	0.33	1.376	2.695

Note. RRA = risk-return association; EM = ethnic minority; MSA = middle school and above; W1 = baseline; W2 = posttreatment assessment; W3 = one-semester follow-up assessment; OR = odds ratio; SE = standard error; CI = confidence interval.

*p < .05. **p < .01. ***p < .001.

Table 9.

Effect of the Intervention on Children's Understanding of the Purpose of Insurance.

	POI (W2)				POI (W3)
	OR	SE	95% CI		OR	SE	95% CI
Intervention	1.62*	0.29	1.133	2.309	1.57*	0.28	1.108	2.230
Girls (yes)	0.84	0.14	0.604	1.157	0.71*	0.12	0.517	0.979
EM (yes)	0.83	0.27	0.447	1.558	1.49	0.40	0.878	2.523
Parental highest education (elementary school and below as the reference group)
Do not know	0.52***	0.10	0.351	0.772	0.65*	0.13	0.440	0.945
MSA	1.02	0.25	0.631	1.635	1.28	0.30	0.806	2.034
Rural (yes)	0.76	0.38	0.289	1.999	0.76	0.29	0.363	1.595
POI (W1)	1.09	0.20	0.756	1.565	1.79***	0.32	1.265	2.531

Note. POI = purpose of insurance; EM = ethnic minority; MSA = middle school and above; W1 = baseline; W2 = posttreatment assessment; W3 = one-semester follow-up assessment; OR = odds ratio; SE = standard error; CI = confidence interval.

*p < .05. **p < .01. ***p < .001.

Demographic characteristics showed varying influences on outcomes. As shown in Table 4, students in rural schools had significantly higher odds of correctly answering calculation items. Ethnic minority students were initially less likely than their Han peers to understand interest and risk–return association at Wave 2, but these differences disappeared by Wave 3 (Tables 5 and 8). At Wave 3, girls were 29% less likely than boys to answer the insurance item correctly. Children who did not know their parents’ educational attainment consistently underperformed—except in basic calculation skills—relative to peers whose parents had completed elementary school or less (Tables 5 to 9). Finally, Table 8 indicates that children with more highly educated parents demonstrated a stronger understanding of risk–return association.

Discussion and Applications to Practice

The two items on interest and inflation used in the financial literacy assessment are identical to two of the three questions developed by Lusardi and Mitchell (2014), which have been widely adopted in the financial literacy literature. This consistency enables meaningful comparisons between the present sample and those in previous studies. According to data from the 2013 wave of the China Household Financial Survey (CHFS), a nationally representative survey of Chinese adults, 14.90% and 15.64% of respondents correctly answered the interest and inflation questions, respectively (Yin et al., 2014). In contrast, the 2014 wave of the Chinese Survey of Consumer Finance, which sampled urban residents, reported correct response rates of ∼50% and 60% for the same questions (Chu et al., 2017). Similarly, Zhu et al. (2017) found accuracy rates of 69.6% for the interest question and 76.1% for the inflation question among a sample of 1,130 urban residents. In the current study, baseline (Wave 1) results showed that 51.70% of the treatment group answered the interest question correctly, while 41.28% of the treatment group answered the inflation question correctly. These findings suggest that the financial literacy level of the target population falls between that of urban and rural Chinese adults. Considering that the sample comprises fourth-grade students attending schools in suburban or rural areas of China—and that their performance on other dimensions, such as calculation, risk diversification, risk–return relationships, and insurance, was relatively strong—their overall financial literacy appears to be high for their age and context. However, it may still be lower than that of their urban counterparts.

The results of the mixed-effects models suggest that the game-based financial education program was effective in promoting overall financial literacy among children, although the effects varied across the six assessed dimensions. Interest and insurance were the two topics most deeply integrated into the chicken-farm board game. In the game, players were required frequently to make decisions such as whether to keep the “cash” earned from selling chickens or deposit some of it in a bank to earn interest, and whether to purchase insurance to protect their chickens from losses due to disease or predators. Consequently, the program had a significant and sustained impact on these two areas. In contrast, inflation was not directly embedded in the gameplay but was introduced during the postgame lecture as part of the instructional review. Compared to interest and insurance, inflation is a more abstract and advanced financial concept and is less tangible in children's everyday financial experiences. However, the educational content effectively supplemented this gap and resulted in an even stronger impact on the topic, as indicated by a larger odds ratio.

The lack of significant associations between the intervention and the dimensions of basic calculation, risk diversification, and risk–return association may be attributable to several different factors. In the case of basic calculation, although frequently required during the game, this skill is already thoroughly developed through the regular mathematics curriculum in Chinese elementary education (Zhou et al., 2023). As such, the program may not have provided additional benefits in this area. Regarding risk diversification and risk–return association, these concepts were not explicitly emphasized in the game. Moreover, both concepts can be encountered in children's everyday financial experiences, suggesting that financial socialization—particularly through parents—may play a more influential role than formal education programs (Grohmann et al., 2015; Jin & Chen, 2020). Supporting this, parental education level emerged as a significant predictor in all models except the one for calculation. Not knowing a parent's highest education level by children may reflect a problematic parent–child relationship and was associated with lower odds of correctly answering items in all dimensions except calculation. Conversely, having at least one parent with a middle school education or higher was positively associated with understanding the concept of risk–return association and the total score of financial literacy. The level of financial literacy at baseline is also a strong predictor of financial literacy at subsequent time points, suggesting the influence of additional factors beyond the intervention. Baseline financial literacy may reflect broader elements of financial socialization, the overall quality of financial education, and the financial environment of the community (Grohmann et al., 2015).

Overall, the findings of this study demonstrate a positive impact of the game-based financial education on children's financial literacy in China. This is consistent with existing evidence (Batty et al., 2015; Kaiser & Menkhoff, 2020), reinforcing the potential of interactive, experiential approaches to promote financial literacy. The study also reveals that children can acquire financial literacy from other sources, including formal school curricula and financial socialization.

Given that financial well-being is the ultimate goal of such interventions, it is important to recognize the mediating role of financial behavior in the relationship between financial literacy and financial well-being (Johnson & Sherraden, 2007; Sherraden, 2013). However, prior research indicates that while financial education can effectively improve financial literacy, it does not consistently lead to improved financial behaviors (Fernandes et al., 2014; Kaiser & Menkhoff, 2020; Mandell & Klein, 2009).

This gap underscores the critical role of financial social work, which aims to promote financial well-being through multi-level strategies: micro-level (e.g., financial education and asset building), meso-level (e.g., access to financial services), and macro-level (e.g., financial policies) interventions (Sherraden et al., 2022). With this holistic framework, financial social work not only supports the development of financial literacy but also addresses structural barriers to sound financial behavior. By doing so, it facilitates the translation of financial literacy into practice and contributes to the long-term goal of enhanced financial well-being. In promoting children's financial literacy, financial social workers may offer distinct advantages due to their established approaches to working with children and families—such as improving access to financial products, providing financial coaching, and delivering financial education (Sherraden et al., 2016). The findings of the study exemplify the effectiveness of the social work agency in promoting child financial literacy. However, the participation of financial social workers in the field is still limited, which requires researchers and practitioners’ collaborative work on developing, promoting, and evaluating the practice of financial social workers.

Several limitations of this study should be acknowledged. First, the financial literacy assessment was primarily developed based on the content of the intervention. Although informed by a relevant measurement toolkit (e.g., Lusardi & Mitchell, 2014), it may lack the robustness needed for cross-population comparisons. Second, although participants in the treatment group were randomly selected from among program participants, the sample was limited to four provinces (i.e., Guangdong, Guizhou, Sichuan, and Gansu) and is not intended to be representative of all suburban and rural children in China. Third, the quasi-experimental design employed in the study may introduce selection bias, which can weaken the strength of causal inferences.

In sum, this study evaluated a game-based financial education program for elementary students in suburban and rural China using a quasi-experimental design. The findings demonstrate that the intervention significantly enhanced children's financial literacy, with sustained effects particularly in the areas of interest, inflation, and the purpose of insurance. The results further suggest that children may also develop financial literacy through other sources, including the standard school curriculum and parent–child financial socialization.

However, enhancing financial literacy alone may not be sufficient to drive better financial behavior. To bridge this gap, the integration of financial social work is essential. Financial social workers, with their strengths in child and family engagement, are well-positioned to support children's financial development through holistic, multi-level interventions. Despite the potential, their involvement in this field remains limited, highlighting the need for a stronger role for financial social work in promoting children's financial well-being.

Footnotes

Acknowledgments

We thank Shanghai Better Education Development Center, China, for supporting the study.

ORCID iDs

Minchao Jin

Jun-Hong Chen

Ethical Approval and Informed Consent Statements

The data contained no private or sensitive information. It was initially collected by the practice agency and then fully de-identified before being transferred to the researchers for further analysis. Therefore, this study was exempt from IRB review.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

The data that support the findings of this study are available from Shanghai Better Development Center, China, but restrictions apply to their use.

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