Skip to main content
Download PDF

Exploring the influence of cognitive factors among Chinese parents on the sustainability of children’s digital education

BMC Psychology volume 13, Article number: 298 (2025) Cite this article

Abstract

Background

The proliferation of mobile internet requires children’s educational software to be evaluated rigorously and implemented effectively to ensure quality and sustainable development. Understanding the determinants of parents’ decisions to sustain the use of such tools is critical with respect to efforts to optimize software design, develop frameworks for relevant policies, and improve digital education strategies.

Research methods

A theoretical model that integrates the expectation confirmation model (ECM) with the technology acceptance model (TAM) was developed to predict parents’ continuance intentions. Data collected from 276 Chinese parents were analysed via structural equation modelling (SEM) with the goal of validating the proposed hypotheses.

Findings

Perceived playability, usefulness, social influence, and satisfaction significantly predict continuance intention. Expectation confirmation positively influences playability, ease of use, and satisfaction while reducing perceived risk, although it does not affect continuance decisions directly.

Conclusion

Chinese parents prioritize educational efficacy and interactivity in terms of the apps used by their children; thus, developers should establish a balance between pedagogical value and engagement. Social influence serves as a pivotal driver of adoption, thus highlighting the need for reliable information dissemination. Although perceived risk has only a minimal impact in this context, proactive measures to safeguard content quality and privacy remain imperative.

Peer Review reports

Introduction

The ubiquity of digital screens has profoundly reshaped childhood experiences, and electronic device usage ranks among the top three out-of-school activities for Chinese children [1]. While young learners are the primary users of educational applications, their parents’ perceptions and decisions critically mediate the relationship between adoption and sustained usage. Previous studies on this topic have identified various drivers of parents’ choices, including test anxiety, time costs, and social trust [2, 3]. Additionally, concerns regarding privacy risks and service quality (e.g., in terms of content updates or interactivity) further complicate decision-making in this context [4, 5]. This study addresses these complexities by constructing a theoretical framework that can facilitate an investigation of the cognitive factors that influence Chinese parents’ continuance intentions; this approach is in line with market demands and educational realities associated with China’s “double reduction” policy.

This integrated model synthesizes various variables drawn from the TAM, ECM, and UTAUT, thus extending their scope of application to encompass parental decision-making. The feasibility of the integration model is underpinned by substantial empirical evidence from prior studies. Notably, across various contexts such as mobile payment [6, 7], online learning [8, 9], and digital application systems [10, 11], the concurrent integration of various theoretical frameworks (e.g., UTAUT, ECM, etc.) has been shown to significantly enhance the explanatory power in understanding user behaviour. In the study of this paper, perceived usefulness and ease of use (TAM) capture pragmatic evaluations [12, 13], whereas social influence (UTAUT) reflects collectivist cultural dynamics [13]. Expectation confirmation (ECM) elucidates postadoption assessments, and the variables of perceived playfulness [14] /risk [15] contextualize the dual objectives of engagement and safety [4, 16]. Preinterviews were conducted, thus validating the relevance of these constructs and highlighting parents’ alignment with utility-driven and socially influenced logic.

Literature review and hypothesis development

Perceived usefulness

Perceived usefulness directly affects users’ willingness to continue using a given system and has a positive indirect effect on their willingness to continue using such a system via their satisfaction. Previous research has confirmed that perceived usefulness positively affects users’ satisfaction and willingness to use mobile networks [17] and educational technology [5]. Recent research has emphasized the multifaceted nature of perceived benefits pertaining to digital educational tools, including in terms of the functional, affective and social dimensions; functional benefits, such as improved academic performance, i.e., perceived usefulness, are particularly salient for parents during the process of evaluating educational apps [18]. These findings are consistent with the TAM framework, according to which perceived usefulness represents a key predictor of users’ satisfaction and continuance intentions [12, 19]. In addition, the cumulative effects of multiple benefits (e.g., educational value and entertainment) can increase parents’ satisfaction and continuance intentions regarding such apps [18]. Therefore, we propose the following hypotheses:

  • Hypothesis 1: Perceived usefulness is positively related to satisfaction with children's educational apps among Chinese parents.

  • Hypothesis 2: Perceived usefulness is positively related to continuance intentions towards children's educational apps among Chinese parents.

Perceived playfulness

The notion of perceived playfulness, which was initially conceptualized in the field of developmental psychology to describe children's capacity to derive intrinsic satisfaction from behavioural interactions [14], has been empirically demonstrated to enhance emotional engagement and task performance. Empirical evidence has suggested that effective perceptions of playful elements are significantly correlated with increased positive affect, improved task execution, and sustained intrinsic motivation [20]. While this construct remains underutilized in conventional technology acceptance model (TAM) frameworks, its pedagogical relevance in educational technology has received increasing recognition, particularly regarding its associations with user experience optimization, learning motivation enhancement, and technology continuance behaviours.

The pedagogical efficacy of gameplay mechanics has been further corroborated by contemporary research on digital engagement paradigms. When gamified interactive features are strategically implemented in educational applications, they have been shown to stimulate intrinsic motivation cycles among young learners [21, 22]. This motivational reinforcement subsequently influences parents’ perceptions of technological playfulness, thus leading to the emergence of a behavioural feedback mechanism that is consistent with Barnett's (1991) foundational theories concerning the development of motivation via playful interaction.

In the context of Chinese educational technology, it has been postulated that perceived playfulness may have measurable effects on the determinants of technology adoption among parents. However, the magnitudes of the impacts of this factor on satisfaction metrics and continuance intention requires careful contextualization in light of the potential moderating effects of cultural educational paradigms and assessment-driven pedagogical pressures in this context [23]. Notably, the prioritization of playfulness features in contexts involving competing educational objectives, particularly standardized testing preparation, remains an underexplored dimension that thus requires empirical validation. Therefore, the following hypotheses are proposed:

  • Hypothesis 3: Perceived playfulness is positively correlated with satisfaction with children’s educational apps among Chinese parents.

  • Hypothesis 4: Perceived playfulness is positively correlated with continuance intention towards children’s educational apps among Chinese parents.

Perceived ease of use

Perceived of use, which was originally conceptualized in terms of the degree of effort reduction associated with system interaction [12], exhibits substantial positive correlations with both perceived utility and behavioural adoption intentions. Empirical investigations have further established tripartite interdependencies among perceived usefulness, interface intuitiveness, and technology continuance behaviours across diverse digital environments [19, 24, 25].

In contexts involving educational technology, interface intuitiveness operates as both a primary determinant of user satisfaction and an enabler of hedonic engagement and functional utility perceptions [21]. This relationship has been substantiated by analyses of mobile learning platforms, in which context system interactivity—a core dimension of usability—has been empirically linked to enhanced engagement metrics and sustained usage patterns [21]. From parents’ perspective, children's autonomous navigation capabilities within educational interfaces may reduce the cognitive load associated with skill acquisition, thereby increasing caregivers’ levels of satisfaction and technology retention tendencies. Therefore, the following hypotheses are proposed:

  • Hypothesis 5: Perceived ease of use is positively correlated with satisfaction with children’s educational apps among Chinese parents.

  • Hypothesis 6: Perceived ease of use is positively correlated with continuance intentions towards children’s educational apps among Chinese parents.

  • Hypothesis 7: Perceived ease of use is positively correlated with the perceived playfulness of children’s educational apps among Chinese parents.

  • Hypothesis 8: Perceived ease of use is positively correlated with the perceived usefulness of children’s educational apps among Chinese parents.

Perceived risk

Perceived risk, which has been conceptualized as an individual’s subjective assessment of decision-related uncertainty and potential adverse consequences [15], has been widely recognized as a critical determinant of technology adoption. Increased risk perceptions negatively influence behavioural intentions by amplifying decision-making hesitancy [26, 27]. Although contextual factors—such as perceived benefits—have traditionally viewed as barriers to adoption, they may actually attenuate its impact [28]. In educational contexts, parents’ prioritization of academic gains (e.g., skill enhancement) often supersedes their concerns regarding screen exposure or data privacy [18], a phenomenon that is further moderated by social validation and expectation confirmation [29]. Despite the empirical emphasis on the protection of children from various risks in digital learning environments, preinterview data revealed that parents emphasized risk mitigation strategies in this context. Consequently, this study operationalizes perceived risk in terms of three dimensions, i.e., performance risk (alignment with learning expectations), safety risk (privacy and security), and health risk (developmental impacts), thereby capturing its multifaceted role in the parental decision-making process. Therefore, the following hypothesis is proposed:

  • Hypothesis 9: Perceived risk is negatively correlated with continuance intention towards children’s educational apps among Chinese parents.

Social influence

According to the unified theory of acceptance and use of technology (UTAUT), social influence is defined as the degree to which individuals’ decisions regarding technology adoption are shaped by their social networks [13]. This construct becomes increasingly significant in collectivist cultural contexts, such as China, where parental choices regarding educational applications are strongly mediated by communal norms and trusted referent groups [30]. Research on platforms such as WeChat has revealed that network heterogeneity and social capital significantly shape parents’ reliance on recommendations from trusted authorities, including educators and social media influencers [30]. Furthermore, emotional attachment, which can be cultivated through sustained social interactions, has been reported to reinforce continuance intention, thus highlighting the interactions between relational dynamics and technology persistence [29]. In line with these findings, it is hypothesized that social influence has positive effects on both parental satisfaction and sustained usage intentions. Therefore, the following hypotheses are proposed:

  • Hypothesis 10: Social influence is positively correlated with satisfaction with children’s educational apps among Chinese parents.

  • Hypothesis 11: Social influence is positively correlated with continuance intention towards children’s educational apps among Chinese parents.

Confirmation

Confirmation indicates the degree of congruence between users' initial expectations and postadoption experiences in the context of information systems [19]. In the context of educational applications, this construct has been reported to reinforce perceived playability and usability by substantiating parents’ anticipations regarding pedagogical efficacy and interactive functionalities [29]. Unlike satisfaction, which involves subjective emotional feedback, confirmation is an objective assessment of the extent to which expectations match reality [31]. Empirical evidence obtained from preliminary interviews has revealed that decision-making processes among Chinese parents frequently involve evaluations during trial periods with the goal of verifying the compliance of software with advertised claims, a phenomenon that is in line with the theoretical conceptualization of confirmation. Furthermore, this confirmation mechanism ensures alignment between application performance and parental expectations concerning educational outcomes and security protocols, thereby mitigating perceived operational risks [29]. This phenomenon has been validated in mobile social media research, in which context confirmation has been empirically identified as a significant determinant of user satisfaction and affective commitment [29]. Therefore, the following hypotheses are proposed:

  • Hypothesis 12: Confirmation is positively correlated with satisfaction with children’s educational apps among Chinese parents.

  • Hypothesis 13: Confirmation is positively correlated with the perceived playfulness of children’s educational apps among Chinese parents.

  • Hypothesis 14: Confirmation is positively correlated with the perceived ease of use of children’s educational apps among Chinese parents.

  • Hypothesis 15: Confirmation is negatively correlated with the perceived risk of children’s educational apps among Chinese parents.

Satisfaction and continuance intention

Satisfaction represents a psychological construct. In the context of educational applications, user satisfaction has been empirically demonstrated to be mediated by multifactorial determinants, including perceived utility, playability, usability, social influence, and expectation confirmation [18, 29]. Furthermore, sustained usage intentions are frequently reinforced by affective commitment—a corollary phenomenon that results from increased satisfaction—in line with core propositions of the expectation confirmation model (ECM) [29]. Scholarly investigations that have been conducted on the basis of the ECM paradigm have consistently identified satisfaction as the primary predictor of continuance intentions, a relationship that has been robustly validated in subsequent studies [19]. Therefore, the following hypothesis is proposed:

  • Hypothesis 16: Satisfaction is positively correlated with continuance intention towards children’s educational apps among Chinese parents.

This research proposes the following model on the basis of the preceding theoretical discussions and research hypotheses (see Fig. 1). This theoretical model includes eight constructs and sixteen relevant research hypotheses.

Fig. 1
figure 1

The theoretical model in this study

Full size image

Research methods

Data collection

The questionnaire was distributed via Credamo, a professional platform, and stratified sampling was used to ensure that parents from tier-1 to tier-4 cities with diverse educational backgrounds were covered. If the respondent’s answer to the first screening question—‘Have you ever downloaded and used a children’s educational app for your child?’—was ‘No,’ the survey was terminated. Following the exclusion of 48 invalid responses, 276 valid responses were retained; these responses represented parents between the ages of 20 and 50 years (66.3% female) with children mainly between the ages of 0 of 12 years (see Table 1). All scales were scored in a 5-point Likert format, and ambiguous items were revised on the basis of a pretest (N = 30).

Table 1 Demographic characteristics of respondents
Full size table

Variable measurement

This study encompasses eight key constructs, including perceived usefulness (PU), perceived playfulness (PP), perceived ease of use (PEU), perceived risk (PR), social influence (SI), confirmation (CON), satisfaction (SAT), and continuance intention (CI). All the constructs were derived from established measurement scales, as detailed in Appendix A (Tables A1), which provides information regarding each construct and the corresponding survey items.

The measurement of perceived usefulness was based on the scale developed by Davis [12] and was operationalized on the basis of four items, such as “The use of children’s educational apps will improve your child’s academic performance.” The measurement of perceived playfulness was based on four items that were adapted from the research of Moon and Kim [32], such as “The use of children’s educational apps sparks curiosity in children.” The measurement of perceived ease of use featured items drawn from Venkatesh [33] and Davis [12], including “Children can quickly learn to use children’s educational apps.” The measurement of perceived risk focused on items drawn from Stone [34], such as “Children’s educational apps may not meet my educational needs for my children.”

Social influence was operationalized on the basis of scales developed by Bhattacherjee [19] and Taylor & Todd [35], including items such as “My willingness to download and use it increases when a teacher or education professional recommends it” Confirmation was measured on the basis of items drawn from Bhattacherjee [19] and Lee [36], such as “Most of my expectations regarding the use of a children’s educational app were confirmed.” Satisfaction and continuance intention were operationalized on the basis of scales developed by Bhattacherjee [19] as well as Hsu and Chiu [37] for satisfaction and by Lee [36] and Roca [8] for continuance intention.

The survey items were tailored to the context and respondents of this study. All the constructs were scored using a 5-point Likert scale, in which context "1" indicated "Disagree" and "5" indicated "Absolutely Agree."

Empirical analysis and results of the hypothesis tests

Reliability and validity

SPSS 26.0 software (IBM et al., USA) was used to test the reliability of the measurements used in this research. As indicated in Table 2, the Cronbach’s \(\alpha\) coefficients of perceived usefulness, perceived playfulness, perceived ease of use, perceived risk, social influence, confirmation, satisfaction, and continuance intention ranged from 0.818 to 0.922; these values were well above the recommended acceptable level of 0.70 [38, 39]. Furthermore, the KMO values ranged from 0.720 to 0.858, which were above the recommended acceptable level of 0.70 [39]. Finally, the values revealed by Bartlett’s test of sphericity were all 0.000, i.e., much lower than the recommended acceptable level of 0.01 [40, 41], thus indicating high reliability of the measurements.

Table 2 Results of reliability analysis
Full size table

The validity test used AMOS 24.0 software to conduct a confirmatory factor analysis with the goal of verifying the validity of each construct. As indicated in Table 2, the standardized factor load coefficients of all the variables ranged between 0.704 and 0.894, which exceeded the reference value of 0.05. The combined reliability (CR) values of all the constructs were greater than 0.70 [42], thus indicating that the scales exhibited good convergence. Moreover, the average variance extracted (AVE) values of the variables ranged from 0.530 to 0.797, thus surpassing the relevant threshold of 0.50 [43]. Furthermore, the square roots of the AVE values of the variables were more significant than the Pearson correlation coefficients between any given variable and other variables (see Table 3), thus indicating that each construct exhibited a high level of discriminant validity.

Table 3 Correlation matrix and AVE
Full size table

Model fit

AMOS 24.0 software was used to assess the goodness-of-fit indices of the model. Table 4 presents the statistical indicators used in the model fit test. The CMIN value of this study was 307.402 (lower values are better in this context). The CMIN/DF value was 1.134, which met the relevant criteria of 1.0 and 3.0. The CFI, RFI, IFI, TLI, and NFI values were 0.992, 0.924, 0.992, 0.990, and 0.937, respectively, all of which exceeded the acceptable level of 0.90. In addition, the RMSEA value was 0.022 < 0.05, and the SRMR value was 0.0351 < 0.05 [44], both of which indicated that this model exhibited a good fit and was suitable for further validation analyses of the structural model with the goals of testing the path relationships among potential variables and verifying whether the proposed theoretical assumptions were valid.

Table 4 Main indicators of the model fit test
Full size table

Hypothesis test

The results of the hypothesis tests are presented in Fig. 2 and Table 5. Perceived usefulness had significantly positive effects on satisfaction (\(\beta\) = 0.246, p < 0.001) and continuance intention (\(\beta\) = 0.228, p = 0.002 < 0.05). Perceived playfulness had a significantly positive influence on continuance intention (\(\beta\) = 0.196, p = 0.003 < 0.05), whereas it did not have a significantly positive effect on satisfaction (\(\beta\) = 0.116, p = 0.054 > 0.05). Perceived ease of use had a significantly positive effect on satisfaction (\(\beta\) = 0.31, p < 0.001), whereas it did not have a positive effect on continuance intention (\(\beta\) = −0.021, p = 0.786 > 0.05). Perceived ease of use had significantly positive effects on perceived playfulness (\(\beta\) = 0.2, p = 0.006 < 0.05) and perceived usefulness (\(\beta\) = 0.232, p = 0.002 < 0.05). Perceived risk did not negatively affect continuance intention (\(\beta\) = −0.131, p = 0.064 > 0.05). Social influence had positive effects on satisfaction (\(\beta\) = 0.26, p < 0.001) and continuance intention (\(\beta\) = 0.164, p = 0.019 < 0.05). Confirmation positively affected satisfaction (\(\beta\) = 0.188, p = 0.002 < 0.05), perceived playfulness (\(\beta\) = 0.211, p = 0.002 < 0.05), and perceived ease of use (\(\beta\) = 0.335, p < 0.001) but negatively affected perceived risk (\(\beta\) = −0.308, p < 0.001). Satisfaction significantly affected continuance intention (\(\beta\) = 0.175, p = 0.031 < 0.05). Therefore, the results of this research supported H1, H2, H4, H5, H7, H8, H10, H11, H12, H13, H14, H15 and H16, whereas H3, H6 and H9 were not supported.

Fig. 2
figure 2

Influence between variables in the structural model

Full size image
Table 5 Hypothesis testing results
Full size table

Discussion

The dual factors involved in parental selection: absolute utility and relative playfulness

The study posited six hypotheses (H1, H2, H3, H4, H5, and H6) concerning the positive effects of perceived usefulness, playfulness, and ease of use on satisfaction and continuance intention. However, H3 and H6 were not confirmed. In contrast, H7 and H8, which focused on the positive influence of perceived ease of use on perceived usefulness and playability, respectively, were validated. Specifically, the empirical findings of this research revealed that, among the constructs of perceived usefulness, playfulness, and ease of use, only perceived usefulness directly enhances parents’ satisfaction and continuance intention. This result is in line with both the theoretical framework of the technology acceptance model (TAM) and the insights obtained from preinterviews with parents.

Although perceived ease of use was not observed to have a direct effect on continuance intention, its indirect influence via satisfaction can be inferred, thus confirming H16, which highlighted the positive relationship between satisfaction and continuance intention. Furthermore, perceived ease of use significantly enhances the perceived usefulness and playability of the application. Children’s interaction with educational apps, which is characterized by intuitive operations and comprehensible interactive activities, facilitates their immersion in a gamified learning environment. This immersion, in turn, fosters enjoyment, stimulates learning interest, and improves educational outcomes; these claims have also been supported by Crescenzi-Lanna [16].

In the Chinese educational context, the usefulness of children’s educational apps is particularly significant. The prevalence of an educational philosophy that emphasizes academic, language, and cognitive development, alongside parents’ educational anxiety during the early childhood stage—which has been exacerbated by the “double reduction” policy (e.g., “Education Burden Reduction, Family Education Investment, and Education Equity,” 2023)—has increased the importance of these apps. In the context of digital tools that integrate gamification and online education, playability and usefulness are the most critical determinants of perceived enjoyment and practical value. These constructs represent the most notable influences on parents’ intention to use children’s educational apps.

Integrative judgement regarding subjective and objective outcomes: trust in social factors and confirmation of expectations

The results of this study revealed that social factors have a significant positive influence on parents' satisfaction with and intention to use children's educational apps, thereby validating H10 and H11. These findings are in line with the results of previous research on the impacts of community influence and external factors on individuals' behavioural intentions [13]. A notable characteristic of online education lies in its accessibility and cost-effectiveness, which can enhance parents' willingness to trust information obtained from external sources and to accept the associated risks. Combining the results of the study and extrapolating from the theory of Culturomics [45], it can be found that achieving digital educational efficiency is a multi-level, multi-scale, and complex system involving a variety of micro-to macro-level factors.

Additionally, the study revealed that expectation confirmation significantly positively influences satisfaction, perceived playability, and perceived ease of use, thereby validating H12, H13, and H14. Parents' levels of expectation confirmation indirectly affect their intention to continue using children's educational apps via these factors. These findings are consistent with the empirical results reported by Bhattacherjee [19] as well as with research on the continued use of related MOOCs [2]. Thus, this study highlights the important influence of expectation confirmation on parents' long-term engagement with educational apps.

The parental selection paradox: attention to perceived risks versus actual disregard

Perceived risk was observed to be negatively influenced by expectation confirmation (thus confirming H15), although it did not significantly affect continuance intentions pertaining to children’s educational apps (thus indicating that H9 was not confirmed). Specifically, expectation confirmation was observed to weaken parents’ perceptions of the potential risks associated with the use of educational apps; this finding is consistent with the expectancy confirmation model and perceived risk theory. Notably, despite the theoretical expectation that increased risk perceptions would weaken parents’ usage intentions, the nonsignificant negative effect of perceived risk on continuance intention observed in this context was unexpected. This result is particularly surprising in light of the documented risks associated with children’s screen exposure, particularly in the context of digital education.

Since the advent of digitalization, research has highlighted significant risks to children’s health and development that result from excessive screen exposure. These risks have also been highlighted by the World Health Organization’s (WHO) 2019 guidelines, which emphasize the need to limit screen time for young children. These guidelines recommend that infants under one year of age should avoid screen exposure, whereas children aged 2–4 years should limit their daily screen time to no more than one hour spent in a sedentary manner [46]. In addition to the potential privacy and security concerns that are inherent in digital products [4, 47], prolonged screen time can negatively impact children’s development of motor skills, manual dexterity, and fine motor development [48, 49].

During the preliminary research and interviews conducted for this study, Chinese parents’ concerns regarding their children’s health and well-being were identified. However, despite these concerns, the model validation revealed that risk perceptions did not significantly influence parents’ intention to use children’s educational apps. This finding suggests that, in the context of this study, the benefits of digital education may outweigh the perceived risks for Chinese parents.

Conclusions

Theoretical implications

On the basis of a combination of the technology acceptance model (TAM), the expectation confirmation model (ECM), and social influence theory, this study is the first to present a novel theoretical framework that can be used to explain persistent intentions to use children’s educational software among Chinese parents. This framework addresses the following theoretical gaps in the literature:

  • First, the study highlights the unique role of parents as decision-making agents in children’s digital education. Whereas previous research on this topic has focused predominantly on students or teachers as the primary adopters of educational technology, this study examines the role of parents as "gatekeepers" in their children’s digital learning processes. This finding validates the significant influence of social factors, such as teachers' recommendations and social media opinions, on parents’ decision-making, thereby extending the scope of applicability of the UTAUT framework to encompass family contexts.

  • Second, the study emphasizes the integration of perceived fun with educational utility. Unlike previous studies on this topic, which have often treated "fun" as a secondary attribute in gamified educational products, this research reveals that, among Chinese parents, perceived playfulness not only affects continuance intention directly but also enhances perceived usefulness indirectly by increasing children’s intrinsic motivation to learn. This finding challenges the traditional "utility-first" paradigm in educational technology research and provides empirical support for the design of pedagogical approaches that are rooted in the notion of "teaching through fun."

  • Third, the study highlights the cultural specificity of risk perceptions. While Western studies have predominantly emphasized the inhibitory effects of privacy and health risks on technology adoption, this research reveals that perceived risk has no significant influence on parents’ decision-making. This result reflects the prioritization of educational benefits resulting from "educational anxiety" among Chinese parents as well as the buffering effect of social trust (e.g., authoritative recommendations) on risk perception. This insight adds a cultural dimension to risk-perception theory.

Against the backdrop of previous research on this topic, this study also contributes several methodological advancements:

  • First, whereas traditional TAM/ECM models have focused primarily on technology adoption on the part of individual users, this study introduces the concept of "dual users"—i.e., parents as decision-makers and children as end-users—thereby revealing the complex mechanisms governing relevant interactions in family contexts.

  • Second, this study explores the influence of social network heterogeneity on information dissemination in educational settings. Accordingly, it reveals that information obtained by parents from WeChat parent groups and educational key opinion leaders (KOLs) can significantly reduce their risk sensitivity. This finding provides new empirical evidence regarding how online capital translates into trust in the context of educational decision-making.

  • Third, while previous studies have identified the ability of depression to strengthen the risk perceptions associated with mobile apps, this research suggests that Chinese parents’ strong emphasis on educational outcomes (e.g., academic advancement) may overshadow their risk concerns. This "goal-oriented" model of decision-making contributes a cross-cultural perspective to "risk–benefit" trade-off theory, thereby enriching its theoretical depth.

Policy implications

This study offers actionable recommendations for key stakeholders:

  • First, the findings of this research confirm that perceived playfulness, ease of use, and usefulness are the primary determinants of Chinese parents' satisfaction with and intention to use children's educational apps. Developers of educational technology should thus establish a balance between educational and recreational features, such as by designing a "gamified learning progress feedback system" that can allow parents to intuitively observe learning enhancement (perceived usefulness) and ensure seamless operation for children (perceived ease of use). Additionally, the integration of social sharing features, such as one-click forwarding of learning achievements to the WeChat social platform, can help use parents' social networks to expand the app's influence and enhance the dissemination process.

  • Second, the study reveals that the perceived risk associated with children's educational apps does not significantly impact parents' usage intentions. This finding suggests certain limitations in the market's natural filtering and regulatory mechanisms, which may allow high-risk apps to remain in circulation and thus propagate risks within digital education. Consequently, organizations and institutions concerned with children's development are urged to address this gap by disseminating the findings of relevant research, raising awareness of risks among parents, and strengthening regulatory oversight of children's educational apps. Furthermore, a "white list" of trusted educational software should be established. Third-party organizations, such as educational authorities and paediatric medical associations, should certify the content quality, screen-time management, and data privacy associated with these apps. Such measures could decrease parents' risk-perception thresholds on the basis of authoritative endorsements, thereby enhancing the safety and reliability of digital educational tools.

  • Third, social influence is identified as a crucial influence on Chinese parents' intention to use children's educational apps. Parents are inclined to heed advice and opinions drawn from their personal networks, mass media, and educators; this situation thus offers a unique opportunity to promote the sustainable development of digital education. However, social management systems must also monitor and evaluate the authenticity of publicly available information regarding educational apps, such as app descriptions, user reviews, download counts, and other metrics displayed on platforms. Schools and educators can play a proactive role in this process by regularly distributing curated lists of educational apps and organizing "digital education parent workshops." These initiatives can enable teachers to play a role that extends beyond the process of traditional instruction to include guidance concerning technology usage, thereby strengthening their authoritative social influence, which can shape parents' decisions.

Limitations and directions for future research

This study has several limitations:

  • First, while previous research on digital education for children has focused on pedagogical, psychological, interaction design as well as the dimensions of health and safety, this paper emphasizes the urgency of addressing the needs and psychological profiles of Chinese consumers in the context of complex family upbringing dynamics. However, the implementation of sustainable digital education for children in China remains underexplored; thus, further investigation into how design practices can effectively respond to the multifaceted demands of Chinese parents and children is needed.

  • Second, this study did not feature a separate examination of the intention to use online education or the decision-making rationale of respondents who had not previously used children's educational apps (CEApps). Exploring the psychological profiles and behaviours of such individuals could provide valuable insights for CEApp developers, particularly with regard to their efforts to design products that cater to a broader demographic of parents and children.

  • Thirdly, the mechanisms by which moderating variables affect people's intention to use CEApps were not examined in the study. The factors influencing parents' intention to use educational apps for their children are indirectly related to neural mechanisms, socio-cultural, economic, and geographic contexts, in addition to perceived psychological factors. To put it another way, macro-level cultural norms have a big impact on parents' acceptance of digital education, and family willingness to invest in educational technology is influenced by economic factors. Furthermore, access to digital resources is greatly impacted by geographic differences, such as the digital divide between urban and rural areas. Further investigation into the impact of product pricing, variances in instructional materials, and usage duration and frequency is necessary, as these factors have the potential to moderate or mediate the adoption of CEApps.

  • Finally, this study did not fully account for the role played by children in their parents’ decision-making or the broader implications of this role with respect to CEApp adoption. While parents may act as observers, they are also recipients of input and feedback from their children. The interviews revealed cases in which children directly requested access to CEApps, thus highlighting the need for future research that can examine these intergenerational dynamics and their influence on parents' decision-making processes.

Three key directions for future research are proposed:

  1. 1.

    Cross-cultural comparative studies: Examining how the risk‒benefit assessment frameworks employed by Chinese parents differ from those used by parents from European and American contexts could be helpful. Such a comparative analysis could reveal the moderating effects of cultural values, such as collectivism and individualism, on technology adoption behaviours.

  2. 2.

    Longitudinal tracking studies: On the basis of the ‘stress‒strain’ framework, future researchers should track the effects of CEApp usage on children's noncognitive competencies (e.g., creativity, social skills) longitudinally over extended periods. Such research could address the limitation entailed by the fact that the current study focuses primarily on short-term usage intentions.

  3. 3.

    Technology‒interpersonal interaction integration: Investigation of parent‒child couse of CEApps in the context of a "collaborative learning" framework could shed light on how children's preferences and experiences shape their parents’ decision-making. Additionally, examining how parent‒child interactions can enhance the sustainability of digital education at home on the basis of theories of emotional attachment could provide valuable insights for both designers and policy-makers.

  4. 4.

    Cross-scalar Integration: In order to fully comprehend the complexities involved in digital education, a framework for the integration of data across several scales that incorporates psychological, biological, and socio-cultural dimensions must be developed. The creation of cross-scalar analysis tools appropriate for digital education research will be done using the Culturomics research methodology.

Through a process of theoretical synthesis and cultural contextualization, this study highlights the central role played by parents’ decision-making in children's digital education. It not only adapts technology acceptance theories to address family contexts but also offers actionable insights for global educational technology developers seeking to design culturally sensitive products. On the basis of these findings, future researchers can explore the intricate interactions that occur within the "human-technology-society" system in digital education in further detail, thereby providing a robust foundation for efforts to create inclusive and sustainable digital learning ecosystems for children.

Data availability

The datasets generated and analysed during the current study are not publicly available due [REASON WHY DATA ARE NOT PUBLIC] but are available from the corresponding author on reasonable request.

References

  1. China Children’s Centre. China children’s development report (2019) ——children’s out-of-school living conditions (in chinese). Beijing: Social Sciences Academic Press (China); 2019 p. 49–72.x

  2. Lin WS, Wang CH. Antecedences to continued intentions of adopting e-learning system in blended learning instruction: A contingency framework based on models of information system success and task-technology fit. Comput Educ. 2012;58(1):88–99.

    Google Scholar 

  3. Tao L-Z. Research on Children’s Education APP Guidance Service under the Perspective of Multiple Provision (in Chinese). Library Science Research & Work. 2022;10:49–55.

    Google Scholar 

  4. Allana S, Chawla S. ChildShield: A rating system for assessing privacy and security of internet of toys. Telematics Inform. 2021;56:101477.

    Google Scholar 

  5. Scherer R, Siddiq F, Tondeur J. The technology acceptance model (TAM): A meta-analytic structural equation modeling approach to explaining teachers’ adoption of digital technology in education. Comput Educ. 2019;1(128):13–35.

    Google Scholar 

  6. Oliveira T, Thomas M, Baptista G, Campos F. Mobile payment: Understanding the determinants of customer adoption and intention to recommend the technology. Comput Hum Behav. 2016;61:404–14.

    Google Scholar 

  7. Singh S. An integrated model combining ECM and UTAUT to explain users’ post-adoption behaviour towards mobile payment systems. Australasian Journal of Information Systems. 2020;24. Available from: https://ajis.aaisnet.org/index.php/ajis/article/view/2695.

  8. Roca JC, Chiu CM, Martínez FJ. Understanding e-learning continuance intention: An extension of the Technology Acceptance Model. Int J Hum Comput Stud. 2006;64(8):683–96.

    Google Scholar 

  9. Vasuthevan K, Vaithilingam S, Ng JWJ. Academics’ continuance intention to use learning technologies during COVID-19 and beyond. PLoS ONE. 2024;19(1):e0295746.

    PubMed  PubMed Central  Google Scholar 

  10. Tam C, Santos D, Oliveira T. Exploring the influential factors of continuance intention to use mobile Apps: Extending the expectation confirmation model. Inf Syst Front. 2020;22(1):243–57.

    Google Scholar 

  11. Yousaf A, Mishra A, Gupta A. ‘From technology adoption to consumption’: Effect of pre-adoption expectations from fitness applications on usage satisfaction, continual usage, and health satisfaction. J Retail Consum Serv. 2021;62:102655.

    Google Scholar 

  12. Davis FD. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q. 1989;13(3):319–40.

    Google Scholar 

  13. Venkatesh V, Morris MG, Davis GB, Davis FD. User acceptance of information technology: toward a unified view. MIS Quarterly. 2003;27(3):425.

    Google Scholar 

  14. Barnett L. The playful child: Measurement of a disposition to play. Play & Culture. 1991;1(4):51–74.

    Google Scholar 

  15. Bauer RA. Consumer behavior as risk taking. Marketing classics : a selection of influential articles. 1969;

  16. Crescenzi-Lanna L. Emotions, private speech, involvement and other aspects of young children’s interactions with educational apps. Comput Hum Behav. 2020;111:106430.

    Google Scholar 

  17. Alalwan AA, Baabdullah AM, Rana NP, Tamilmani K, Dwivedi YK. Examining adoption of mobile internet in Saudi Arabia: Extending TAM with perceived enjoyment, innovativeness and trust. Technol Soc. 2018;1(55):100–10.

    Google Scholar 

  18. Pang H, Zhang K. How multidimensional benefits determine cumulative satisfaction and eWOM engagement on mobile social media: Reconciling motivation and expectation disconfirmation perspectives. Telematics Inform. 2024;1(93):102174.

    Google Scholar 

  19. Bhattacherjee A. Understanding information systems continuance: an expectation-confirmation model. MIS Q. 2001;25(3):351–70.

    Google Scholar 

  20. Martocchio JJ, Webster J. Effects of feedback and cognitive playfulness on performance in microcomputer software training. Pers Psychol. 1992;45(3):553–78.

    Google Scholar 

  21. Pang H, Ruan Y. Disentangling composite influences of social connectivity and system interactivity on continuance intention in mobile short video applications: The pivotal moderation of user-perceived benefits. J Retail Consum Serv. 2024;1(80):103923.

    Google Scholar 

  22. Zhai X, Chu X, Chai CS, Jong MSY, Istenic A, Spector M, et al. A Review of Artificial Intelligence (AI) in Education from 2010 to 2020. Complexity. 2021;2021(1):8812542.

    Google Scholar 

  23. He Y, Wijaya TT, Habibi A, Chen H, Gao M. Exploring the relationship between teacher and parent support and students’ noncognitive outcomes via Latent Profile Analysis. Humanit Soc Sci Commun. 2025;12(1):105.

    Google Scholar 

  24. Lin WS. Perceived fit and satisfaction on web learning performance: IS continuance intention and task-technology fit perspectives. Int J Hum Comput Stud. 2012;70(7):498–507.

    Google Scholar 

  25. Thong JYL, Hong SJ, Tam KY. The effects of post-adoption beliefs on the expectation-confirmation model for information technology continuance. Int J Hum Comput Stud. 2006;64(9):799–810.

    Google Scholar 

  26. Finucane ML, Alhakami A, Slovic P, Johnson SM. The affect heuristic in judgments of risks and benefits. J Behav Decis Mak. 2000;13(1):1–17.

    Google Scholar 

  27. Slovic P, Peters E. Risk perception and affect. Curr Dir Psychol Sci. 2006;15(6):322–5.

    Google Scholar 

  28. Pang H. Determining the influence of depressive mood and self-disclosure on problematic mobile app use and declined educational attainment: Insight from stressor-strain-outcome perspective. Educ Inf Technol. 2024;29(4):4635–56.

    Google Scholar 

  29. Pang H, Zhang K. Determining influence of service quality on user identification, belongingness, and satisfaction on mobile social media: Insight from emotional attachment perspective. J Retail Consum Serv. 2024;1(77):103688.

    Google Scholar 

  30. Pang H, Yang T. Network structure matters: unpacking associations among informational wechat use, network heterogeneity, network capital, and civic involvement. SAGE Open. 2024;14(2):21582440241253052.

    Google Scholar 

  31. Yun JJ, Choi B, Kim J. Changes and challenges in museum management after the COVID-19 pandemic. J Open Innov: Technol, Market, Complexity. 2021J 1;7(2):148.

    Google Scholar 

  32. Moon JW, Kim YG. Extending the TAM for a World-Wide-Web context. Information & Management. 2001;38(4):217–30.

    Google Scholar 

  33. Venkatesh V, Davis FD. A theoretical extension of the technology acceptance model: four longitudinal field studies. Manage Sci. 2000;46(2):186–204.

    Google Scholar 

  34. Stone RN, Grønhaug K. Perceived risk: further considerations for the marketing discipline. Eur J Mark. 1993;27(3):39–50.

    Google Scholar 

  35. Taylor S, Todd PA. Understanding information technology usage: a test of competing models. Inf Syst Res. 1995;6(2):144–76.

    Google Scholar 

  36. Lee MC. Explaining and predicting users’ continuance intention toward e-learning: An extension of the expectation–confirmation model. Comput Educ. 2010;54(2):506–16.

    Google Scholar 

  37. Hsu MH, Chiu CM. Predicting electronic service continuance with a decomposed theory of planned behaviour. Behav Inform Technol. 2004;23(5):359–73.

    Google Scholar 

  38. Nunnally J. Psychometric Theory. Encyclopedia of Behavioral Medicine. 2020. Available from: https://www.semanticscholar.org/paper/Psychometric-Theory-Nunnally/853f1d0a0c306ab7fa6feeb953af9d7403ecdbdd.

  39. Wu M-L. Statistical analysis of questionnaires–SPSS operation and application (in chinese). Chongqing: Chongqing University Press; 2010.

    Google Scholar 

  40. Kaiser HF. An index of factorial simplicity. Psychometrika. 1974;39(1):31–6.

    Google Scholar 

  41. Norusis MJ. SPSS for Windows: Base System User’s Guide, Release 5.0. SPSS Incorporated; 1992. 768 p.

  42. Chin WW. The Partial Least Squares Approach to Structural Equation Modeling. In: Modern Methods for Business Research. Psychology Press; 1998.

  43. Fornell C, Larcker DF. Evaluating structural equation models with unobservable variables and measurement error. J Mark Res. 1981;18(1):39–50.

    Google Scholar 

  44. Wu M-L. Structural equation modeling: An advanced AMOS practice (in chinese). Chongqing: Chongqing University Press; 2013.

    Google Scholar 

  45. Luo S, Yuan H, Wang Y, Bond MH. Culturomics: Taking the cross-scale, interdisciplinary science of culture into the next decade. Neurosci Biobehav Rev. 2024;1(167):105942.

    Google Scholar 

  46. Organization WH. Guidelines on physical activity, sedentary behaviour and sleep for children under 5 years of age [Internet]. World Health Organization; 2019. Available from: https://iris.who.int/handle/10665/311664. Cited 2024 May 30.

  47. Pinheiro Amâncio FM, Souza AP, Fantinato M, Peres SM, Hung PCK, Coutinho Do Rêgo LG, et al. Parental perception of children’s privacy in smart toys in countries of different economic levels. Technology in Society. 2023;72:102180.

  48. Daud AZC, Aman NA ah, Chien CW, Judd J. The effects of touch-screen technology usage on hand skills among preschool children: A case-control study. F1000Research. 2020;9(1306). Available from: http://www.scopus.com/inward/record.url?scp=85121327064&partnerID=8YFLogxK. Cited 2024 May 31.

  49. Webster EK, Martin CK, Staiano AE. Fundamental motor skills, screen-time, and physical activity in preschoolers. J Sport Health Sci. 2019;8(2):114–21.

    PubMed  Google Scholar 

Download references

Funding

The research leading to these results received funding from the Wuxi University Research Start-up Fund for Introduced Talents 2024r080 under Grant Agreement No.550224080, and 2024 Jiangsu Higher Education Philosophy and Social Science Research General Project “Research on the Talent Cultivation model Model for Art and Technology Majors Based on New Quality Productive Forces” No.2024SJYB0656.

Author information

Authors and Affiliations

  1. School of Humanities and School of Design, Jiangnan University, Wuxi, China

    Tingyu Zhang

  2. School of Design, Jiangnan University, Wuxi, China

    Qianling Jiang

  3. School of Media and Arts, Wuxi University, Wuxi, China

    Wenjing Zhang

Authors
  1. Tingyu Zhang
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Qianling Jiang
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Wenjing Zhang
    View author publications

    You can also search for this author inPubMed Google Scholar

Contributions

Conceptualization, T.Z., W.Z.; formal analysis, T.Z.; data curation, T.Z.; writing-original draft, T.Z.; writing-review and editing, T.Z., Q.J.; All authors have read and agreed to the published version of the manuscript.

Corresponding author

Correspondence to Tingyu Zhang.

Ethics declarations

Ethics approval and consent to participate

We submitted our research plan to the Medical Ethics Committee, Jiangnan University, Wuxi Medical College of Jiangnan University, No.1800 Lihu Avenue, Binhu District, Wuxi, China, and obtained moral approval and review of the plan’s content (Reference number: JNU202412RB018). At the start of the interview, participants were asked if they have any questions regarding the study, data anonymity, and the confidentiality of their data. They were also asked to confirm that they had read the consent form carefully and signed it to ensure informed consent was obtained. In addition, we obtained verbal confirmation of their consent, ensuring that both written and verbal informed consent were secured from all participants. All the participants willingly took part in the questionnaire survey. We ensure the guidelines outlined in the Declaration of Helsinki are followed. The participants’ anonymity was also safeguarded through anonymization of data. The data are stored in a safe university repository.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, T., Jiang, Q. & Zhang, W. Exploring the influence of cognitive factors among Chinese parents on the sustainability of children’s digital education. BMC Psychol 13, 298 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s40359-025-02614-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s40359-025-02614-2

Keywords

BMC Psychology

ISSN: 2050-7283

Contact us