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DOI: 10.1039/D5RP00074B (Paper) Chem. Educ. Res. Pract., 2025, 26, 734-747

Examining the influences of peer and teacher support on chemistry learning satisfaction: an analysis of a serial mediation model

Qian Huangfu *a, Hanxi Wang a and Liping Zhu b
aSouthwest University, Chongqing, 400715, China. E-mail: chemqian16@swu.edu.cn
bSchool of Education, Central China Normal University, Wuhan, 430079, China

Received 4th March 2025 , Accepted 1st April 2025

First published on 16th April 2025

Abstract

Given students' perceptions of the chemistry curriculum as abstract and content-heavy, a lack of passion and motivation, as well as a low level of learning satisfaction in chemistry, have become commonplace issues for students. Therefore, increasing students' chemistry learning satisfaction has drawn plenty of interest and attention. Yet, few studies currently exist that explain how to increase students' satisfaction with their chemistry learning from both personal (growth mindset and grit) and environmental angles (teacher and peer support). Thus, this research intends to investigate how these variables connect to students' chemistry learning satisfaction. A total of 1430 tenth graders were involved in the survey. The direct and indirect connections between these variables were evaluated adopting structural equation modeling (SEM). The findings demonstrated that (1) teacher and peer support, grit in chemistry, and growth mindsets in chemistry all held a significant positive effect on students' chemistry learning satisfaction; (2) both (a) growth mindsets in chemistry and (b) grit in chemistry acted as significant mediators between the associations of teacher and peer support with chemistry learning satisfaction; and (3) (a) growth mindsets in chemistry and (b) grit in chemistry held a chain mediating impact on the associations of teacher and peer support with chemistry learning satisfaction. This may help inform chemistry educational practices to develop effective teaching and learning strategies.

Introduction

Chemistry is recognized as a required introductory subject in science, technology, engineering, and mathematics (STEM) discipline fields (Gonzalez and Paoloni, 2015), which have been shown to be crucial to the societal issues, competitiveness of contemporary societies, and future sustainable development (Stuckey et al., 2013; Guo et al., 2022). Given its critical role in laying the groundwork for their lifetime development and study, it is essential to promote students' chemistry learning.

Nevertheless, chemistry is often identified as a challenging and demanding subject for the high school students, who usually struggle in it and exhibit signs of disinterest, decreased study zeal, and decreased involvement (George and Kaplan, 1998; Salta et al., 2012; Ferrell and Barbera, 2015). Thus, developing chemistry learning satisfaction is crucial for chemistry education, especially for raising chemistry literacy and inspiring students to learn the subject (European Commission, 2015; Hu et al., 2022). Learning satisfaction is the reflection of how learners view their learning experience, including the enjoyment, fulfillment, and sense of accomplishment they feel in learning (Aldhahi et al., 2022), which is recognized as the widely vital indicator of the caliber and efficacy of instruction (Diep et al., 2017). In addition, learning satisfaction was found to be highly connected with students' learning motivation and school engagement (Sneyers and Witte, 2017; Alqurashi, 2019) and also crucial for comprehending how students view their learning experiences (Alqurashi, 2019) and improving the overall level of education (Kuo et al., 2014).

According to previous research, factors influencing students' learning satisfaction can be investigated from both personal and environmental angles. The social constructivist paradigm noted that learning is a fundamentally social process where the production of knowledge and understanding depends on interpersonal interactions (Vygotsky, 1978; Wong and Chapman, 2023). Consistent with this theory, relevant studies have discovered that students' perceived teacher and peer support, which are crucial social elements, had significant influencing roles in their academic success and satisfaction (Lee et al., 2011; Cheng and Chau, 2016). In addition to such social factors, previous research and theories have demonstrated that grit and growth mindsets, as essential intrapersonal elements, can promote positive emotions in learning activities (Sun and Mu, 2023; Yao et al., 2024), which had a potential and important influence on increasing learning satisfaction. However, research on the impacts of intrapersonal elements, including growth mindset and grit, on learning satisfaction is scarce. Furthermore, several research studies have provided evidence that peer and teacher support, grit, and growth mindset are positively related in pairs. Haimovitz and Dweck (2017) indicated that growth mindsets can be influenced by perceived social support. Evidence has suggested that grit held significant correlations with peer and teacher support (Orson et al., 2020; Sadoughi and Hejazi, 2023). Fan et al. (2024) discovered the significant predictive power of growth mindset over grit. But so far, there is no research using a comprehensive model to test all of the associations. Therefore, this study proposed a chain-mediating model and aims to provide a detailed exploration regarding the effects and mechanism of teacher and peer support on chemistry learning satisfaction by investigating the mediation influence of (a) growth mindset in chemistry and (b) grit in chemistry in these associations. This may offer valuable insights to enhance chemistry learning effectiveness, maximize the chemistry learning experience, as well as foster chemistry learning satisfaction.

Teacher support, peer support and chemistry learning satisfaction

Learning satisfaction refers to the sum of the emotions and attitudes obtained from summing up all the positive outcomes a student anticipates from interacting with the educational system (Wu et al., 2010). In this research, chemistry learning satisfaction is viewed as the overall level of fulfillment perceived by the students when the chemistry learning outcomes meet their expectations (Diep et al., 2017). Students are able to like or follow chemistry courses, actively and joyfully participate in studying chemistry subjects, and persevere in completing chemistry-related tasks. All these scenarios are specific manifestations of high chemistry learning satisfaction.

Support for student learning has been acknowledged as critical for affecting students' learning satisfaction (Lee et al., 2011). Existing studies have revealed that learners’ experiences of social support, particularly peer and teacher support, serve as essential factors for inspiring their motivation and achieving learning goals (Engels et al., 2016; Wong and Chapman, 2023). Teacher support is known as the behavior of teachers to convey concern, respect, and personal support for their students, as well as to offer guidance and recommendations for their development (Sadoughi and Hejazi, 2023). Such behavior and guidance (Kuo et al., 2014; Cheng and Chau, 2016) can contribute to building students' feelings of belongingness and increase their liking of school in order to foster students’ learning satisfaction. In addition to teacher support, peer support, described as students helping one another with academic or non-academic problems, such as tutoring, facilitation, and encouragement (Lee et al., 2011), also satisfies students' need for relatedness and then facilitates their feeling satisfied in school. Research suggests that learners who experienced assistance and encouragement from peers are able to relieve their heavy study pressure (Sun et al., 2013) and improve learning efficiency, ultimately helping to promote their learning satisfaction (Cheng and Chau, 2016).

Growth mindset in chemistry as a potential mediator

Mindset refers to students' perceptions of how malleable their ability is, which possesses the power to affect people's thoughts, feelings, and behaviors in learning environments (Sadoughi and Hejazi, 2023). In Dweck's social-cognitive model (Dweck, 1999), people possess two primary categories of implicit beliefs (Dweck, 1986), namely, fixed and growth mindsets (or entity and incremental theory). Specifically, students who view their intellectual abilities as fixed and immutable are characterized as holding fixed mindsets, while those who regard their basic abilities as flexible, mutable, and able to be developed with effort are characterized as possessing growth mindsets (Limeri et al., 2020). According to recent research, students tend to have distinct perspectives on different subjects, and discipline-specific mindsets are more accurate indicators of students' performance in those subjects (Scott and Ghinea, 2014; Gunderson et al., 2017; Santos et al., 2022). Therefore, it can be speculated that compared to general incremental theory, chemistry-specific incremental beliefs are more significant for the advancement and intended outcomes in the chemistry field. Accordingly, this research mainly focuses on the growth mindset in chemistry, which describes the conviction that individuals could improve their chemistry learning skills and abilities by working harder and showing more resilience to obstacles and failures during the learning process (Santos et al., 2022).

As the self-determination theory noted, contextual elements like perceived social support can affect students’ growth mindset by activating their autonomy and triggering their organismic processes of integration and growth (Deci and Ryan, 2000). Since school serves as the primary setting for students' daily lives and education, healthy relationships with peers and teachers can satisfy their basic psychological needs, including intimacy and autonomous development. And these satisfactions of autonomous development give students a feeling of control and make them believe that their abilities are flexible. Therefore, it makes sense that peer and teacher support would favorably link to students' growth mindsets. Besides, it has been revealed that students are inclined to develop growth mindsets when they perceive sufficient support from their peers and teachers (King, 2020; Yu et al., 2022). Therefore, peer and teacher support are positively correlated with growth mindsets.

Regarding the associations between growth mindsets and chemistry learning satisfaction, it can be rooted in the mindset theory, which revealed that those who hold growth mindsets are inclined to consider that their abilities can constantly increase (Dweck, 2006). They exhibit a strong feeling of self-efficacy regarding learning and believe that they hold the competence needed to overcome difficult tasks and setbacks (Zhao et al., 2024). Thus, compared with learning outcomes, students who possess growth mindsets concentrated more on improving their skills (e.g., chemical laboratory skills, scientific thinking, and analytical ability) during the learning process and tend to developmentally evaluate themselves and their knowledge, which is conducive to high degrees of learning satisfaction. Consequently, it seems reasonable that growth mindsets can positively impact learning satisfaction. However, scant empirical support has so far been offered in previous studies. The investigation of Yao et al. (2024) indicated that students who possess growth mindsets are inclined to be optimistic during the learning process and to study with joy, passion, and willingness. Zarrinabadi et al. (2022) stated that growth mindsets can promote an individual's capacity to adjust oneself in response to various situations to cultivate positive learning emotions, which are highly correlated with student satisfaction. Therefore, we can speculate that the growth mindset in chemistry will possess a crucial mediating function in the associations of teacher and peer support with chemistry learning satisfaction.

Grit in chemistry as a potential mediator

According to Duckworth et al. (2007), grit can be defined as a higher-order construct containing two constituent components: passion and perseverance. Specifically, perseverance is recognized as the tendency to put out effort despite facing obstacles and setbacks, whereas passion refers to the inclination to maintain interest in the goals (Credé et al., 2017). These two components are often studied in combination, which has been revealed to have an essential impact in educational settings (Cheng et al., 2024). Although grit was originally conceptualized as a domain-general construct (Duckworth et al., 2007), some recent research (Cormier et al., 2019; Mosewich et al., 2021; Gao et al., 2024) has indicated that it is beneficial to conceptualize and measure grit as a domain-specific construct in various achievement domains and offered evidence to favor the adoption of the domain-specific grit in an academic setting. Besides, learning chemistry is a challenging and drawn-out process during which students generally encounter a variety of learning difficulties and challenges, such as misconceptions of basic chemical concepts (Tümay, 2016), poor cognitive structures in organic chemistry (Hrin et al., 2018), and insufficient comprehension of chemical kinetics concepts and facts (Gegios et al., 2017), which requires students to maintain a great deal of enthusiasm and exert increasing effort to gain achievement. Thus, a high degree of grit is crucial for students in chemistry studies. Yet, the grit in the context of chemistry and its influencing factors has received less attention (Carbonneau et al., 2020; Sadoughi and Hejazi, 2023). Thus, the current study mainly focuses on the grit in chemistry.

Notably, grit is regarded as a malleable trait that might be cultivated by supportive environmental factors (Duckworth, 2016), which has been revealed in prior research. According to Sadoughi and Hejazi (2023), teachers who are supportive and care about students can create a supportive learning climate that increases adolescents’ sense of belonging so as to inspire them to show greater persistence and enthusiasm toward goals (Roorda et al., 2011). Besides, Orson et al. (2020) noted that peers can provide effective, timely, and empathetic assistance, which helps students to manage negative emotions and thus reframe confidence in their underlying ability to persevere (Datu, 2017). Based on the above analyses, it can be speculated that grit in chemistry would be positively predicted by teacher and peer support.

As to the connection between grit in chemistry and learning satisfaction, Hill and Jackson's (2016) invest-and-accrue model may provide some insight. According to this model, people with grit tend to invest in behaviors that are helpful for achieving their goals, which can lead to greater academic and professional accomplishments (Altintas and Canbulat, 2024; Cheng et al., 2024), making gritty people feel more satisfied with their behavior and experiences. In short, grit can increase students' willingness to invest in learning activities that foster feelings of identity and achievement while learning, resulting in a high level of student satisfaction with learning. Nevertheless, scant empirical studies have examined how grit relates to emotional academic outcomes such as learning satisfaction. Based on this, the current study postulated that grit in chemistry would mediate the correlations of peer and teacher support with chemistry learning satisfaction.

The serial mediating effect of (a) growth mindset in chemistry and (b) grit in chemistry

Regarding how grit and growth mindsets have links under the context of chemistry learning, it can be deduced from Dweck's social-cognitive model of achievement motivation, which noted that students' perceptions about the stability or malleability of intelligence guide their goal setting, responses to obstacles, and coping mechanisms (Dweck, 1986; Dweck and Leggett, 1988). Consequently, it is reasonable to assume that those that possessed a growth mindset generally tended to display higher grit, as evidenced by earlier studies. Limeri et al. (2020) showed that students who view intellect as malleable tend to engage in challenging assignments and persevere despite difficulties by exerting more effort. In analogy, research by Fan et al. (2024) discovered that students adopting growth mindsets tend to interpret challenging experiences as chances, display a lower level of anxiety, and increase perseverance when encountered with challenges and obstacles. In other words, people are more inclined to set and maintain high-level and long-term goals and show high degrees of grit when they are convinced that their basic ability can be enhanced via their efforts. Therefore, we can anticipate that the higher the growth mindset in chemistry that students possess, the higher the possibility that they exhibited grit in chemistry.

The present study

According to existing research, learning satisfaction is significantly predicted by peer and teacher support. Little research has fully investigated the connection among the conceptions, especially in specific subject domains. Therefore, this research intends to explore the relationships between peer and teacher support and chemistry learning satisfaction. Additionally, students' growth mindsets might be influenced by teacher and peer support, and the growth mindsets are beneficial for improving students' learning satisfaction. Thus, we postulate that the influences of peer and teacher support on chemistry learning satisfaction are mediated by growth mindsets in chemistry. Meanwhile, teacher and peer support can also have an impact on students' grit, and the grit can positively predict the level of students’ learning satisfaction. We thus assume that grit in chemistry functioned as a mediator between the impacts of peer and teacher support on chemistry learning satisfaction.

Finally, since both (a) growth mindset in chemistry and (b) grit in chemistry can mediate the impacts of peer and teacher support on learning satisfaction, and growth mindset can positively predict grit, we assume that growth mindsets in chemistry and grit in chemistry play chain mediating effects in the associations of teacher and peer support with chemistry learning satisfaction.

Based on this, a serial mediation model is constructed in this research (Fig. 1), and the following hypotheses are proposed:


image file: d5rp00074b-f1.tif
Fig. 1 The hypothesized chain mediation model.

Hypothesis 1: Teacher support holds a positive impact on chemistry learning satisfaction.

Hypothesis 2: Peer support holds a positive effect on chemistry learning satisfaction.

Hypothesis 3: Growth mindset in chemistry can mediate the correlation between teacher support and chemistry learning satisfaction.

Hypothesis 4: Growth mindset in chemistry can mediate the correlation between peer support and chemistry learning satisfaction.

Hypothesis 5: Grit in chemistry can mediate the correlation between teacher support and chemistry learning satisfaction.

Hypothesis 6: Grit in chemistry can mediate the correlation between peer support and chemistry learning satisfaction.

Hypothesis 7: Growth mindset in chemistry and grit in chemistry can serially mediate the correlations between teacher support and chemistry learning satisfaction.

Hypothesis 8: Growth mindset in chemistry and grit in chemistry can serially mediate the correlations between peer support and chemistry learning satisfaction.

Method

Participants

Utilizing the stratified sampling method, this research was carried out among 10th graders. First, 12 high schools located in the Chinese central inland region and eastern coastline region were chosen based on gathering data viability and the geographical location. Next, depending on students' academic performance, students in Grade 10 at each school were separated into three levels (low, medium, and high). We then made a random selection of roughly 40 students from each level. 1430 high school students in total were chosen as the sample for this research, in which 691 students (48.32%) were female, while 739 students (51.68%) were male. The participants ranged in age from 15 to 17, with an average age of 16.15 years. The Chinese 10th graders were chosen for the following points: on the one hand, they already have a basic comprehension of the chemistry subject because they have studied it systematically for at least two years. On the other hand, they need to make a decision about whether or not to continue studying chemistry, and this decision will be somewhat influenced by their chemistry learning satisfaction (the study's dependent variable).

Survey administration

The research was performed by adopting an electronic questionnaire. The data collection was conducted in 12 different schools, spending two weeks. Consent was provided by the students' parents and the Academic Ethics Committee of Southwest University in China for this research before the data gathering. Besides, each participant was given notification of the investigation's purpose and the data's application, and the confidentiality of participants’ personal information was guaranteed to be strictly maintained. Every student who participated was voluntary and was given a small gift in appreciation.

Survey instruments

The scales that have been extensively utilized in prior research and have exhibited high validity and reliability were selected as this study's measurement instruments. Besides, we modified these scales to fit the context of the Chinese high school chemistry curriculum. Due to the fact that the original scales were in English, which is not the participants’ native language, each English question was translated into Chinese with the purpose of guaranteeing easy understanding for students. First of all, each item was independently translated by two researchers who were proficient in English and native speakers of Chinese. They then conferred to decide on the final version. Finally, five 10th graders were invited to read the questionnaire and give feedback. Based on their comments, we adjusted the expressions of some items to ensure the students' understanding of the questions aligned precisely with the questionnaire's wording.
Teacher support. With the purpose of gauging the students’ perceptions of teacher support, four scale items were utilized, which were modified from the teacher support dimension of the Child and Adolescent Social Support Scale (CASSS; Malecki and Elliott, 1999). Example items were “My teacher will listen to my thoughts and feelings” and “My teacher will help me solve the problems in my study and life by providing information resources.” These items were graded by adopting a scale of 1 (strongly disagree) to 5 (strongly agree), with higher numbers showing more favorable degrees of teacher support.
Peer support. Learners’ perceptions of peer support were gauged employing five scale items that were adapted from the peer support dimension of the Child and Adolescent Social Support Scale (CASSS; Malecki and Elliott, 1999). Sample items include “When I am in trouble or nervous, my peers will make me feel relieved” and “When I perform well, I will receive praises from my peers.” These items were graded by adopting a scale of 1 (strongly disagree) to 5 (strongly agree), with higher numbers showing more favorable degrees of teacher support.
Growth mindset in chemistry. Five scale items were adopted from the Growth Mindset Questionnaire (Dweck, 1999) to gauge the extent of growth mindset in chemistry. The study's scale was modified to fit the context of the Chinese chemistry curriculum. Sample items include: “I can’t do well in the chemistry subject even though I work hard” and “I can change my chemistry intelligence level significantly.” A scale of 1 (strongly disagree) to 5 (strongly agree) was adopted to rate each item. After reverse-scoring fixed mindset items, the mean score was computed to form a growth mindset in chemistry, with higher ratings representing larger degrees of growth mindset in chemistry.
Grit in chemistry. Eight scale items were utilized to gauge grit, which were adapted from the Grit Scale developed by Duckworth et al. (2007). In order to be more accurate and predictive of the chemistry subject being studied, we tailored it to the chemistry course context. This scale consists of two factors: passion (4 items; “During chemistry learning, every few months I will get interested in new goals”) and perseverance (4 items; “Setbacks in chemistry learning don't discourage me”). These items were judged by utilizing a scale of 1 (strongly disagree) to 5 (strongly agree). The overall mean score of grit was acquired by reverse-scoring the four passion items, with higher numbers representing greater degrees of grit.
Chemistry learning satisfaction. The 4-item chemistry learning satisfaction questionnaire was modified from the Perceived Student Satisfaction Scale designed by Arbaugh (2000), which has shown excellent validity and reliability in previous studies (Arbaugh, 2000; Cheng and Chau, 2016). Some items' wording of this scale was modified to be more predictive of the chemistry subject being studied. Two such items were, “I was very satisfied with high school chemistry learning,” and “I feel that high school chemistry learning served my needs well.” A scale of 1 (strongly disagree) to 5 (strongly agree) was adopted to rate each item, with higher numbers reflecting greater degrees of chemistry learning satisfaction.

Data analysis procedures and tools

In the current research, SPSS 27.0 and AMOS 26.0 were implemented to carry out the data analyses. The following were the specific procedures for analysis:

Inspection of measuring tools

Firstly, by using SPSS 27.0, we performed preliminary analysis, including calculating skewness, kurtosis, means, and standard deviations for each variable as well as evaluating the subscales' descriptive and distributional properties. Given that the measuring instruments utilized for present research were translated and modified from well-established scales, the confirmatory factor analysis (CFA) was implemented in AMOS 26.0 to validate each scale of this study. The model fit was assessed using a series of indices, including the Tucker-Lewis index (TLI), comparative fit index (CFI), standardized root mean square residual (SRMR), and root mean square error of approximation (RMSEA). Table 1 shows the suggested values for the CFA fitting index (Hu and Bentler, 1999; Marsh et al., 2004; Lee et al., 2008; Opperman et al., 2013). Specifically, a one-factor CFA was performed to verified the teacher support, growth mindset in chemistry, peer support, and chemistry learning satisfaction scales in this study, considering that these scales all had only one factor. For the grit in chemistry scale, given that it consists of two factors, passion and perseverance, CFA of the two-factor model was carried out in this research to confirm its structural validity for it. Following confirmation of the two-factor model's strong structural validity, a one-factor CFA for two factors of the grit in chemistry scale was carried out, respectively. The unidimensionality criteria were satisfied by the one-factor model's fit test findings, suggesting that each component of the grit in chemistry scale has a unidimensional structure. This establishes the basis for the reliability test that follows (Green and Yang, 2015; Guo et al., 2022).
Table 1 Goodness-of-fit and reliability indicators of the measurement tools
Variable χ 2/df CFI TLI RMSEA SRMR ω
Teacher support 3.144 0.999 0.996 0.039 0.007 0.888
Peer support 2.616 0.998 0.997 0.034 0.008 0.914
Growth mindset in chemistry 2.774 0.999 0.996 0.035 0.008 0.863
Grit in chemistry 4.133 0.990 0.985 0.047 0.023 0.892
Perseverance 2.073 1.000 0.993 0.027 0.005 0.861
Passion 2.511 0.999 0.997 0.033 0.005 0.867
Chemistry learning satisfaction 3.181 0.998 0.995 0.039 0.009 0.861
Acceptable value <5 >0.9 >0.9 <0.08 <0.08 >0.7

Besides, since the omega coefficient has been proven to have a reduced likelihood of overestimating or underestimating reliability compared to Cronbach's alpha, we implemented the omega coefficient using SPSS 27.0 for checking all modified scales' internal consistency (Dunn et al., 2013). The value of the omega coefficient is between 0 and 1. Scale items consistently reflect the goal construct when the omega coefficient has values close to 1 (McDonald, 1999). According to Green and Yang (2015), the omega coefficient above 0.7 on each scale is considered acceptable.

Validation of model hypotheses

With the intention of ensuring that there is no common method bias, it is necessary to perform a Harman single factor test before assessing the model of this study (Podsakoff et al., 2003). Following CFA, the reliability and convergent validity of the survey instrument implemented in this research were evaluated via the composite reliability (CR) and average variance extracted (AVE) methods, respectively. If scores are greater than 0.4 for AVE and more than 0.6 for CR, the constructed validity was considered dependable (Fornell and Larcker, 1981; Hamid et al., 2017). We implemented the structural equation model (SEM) adopting AMOS 26.0 to explore the direct and mediating effects in this research's model. In a simple mediation model, there are partially mediated relationships and fully mediated relationships. A partially mediated relationship has both direct and indirect effects that are significant, while in a fully mediated relationship, the direct effect is nonsignificant and the indirect effect is significant (Gonzalez and Paoloni, 2015). Previous research has demonstrated that the bias-corrected nonparametric percentile bootstrap method is one of the most effective approaches for mediation analysis yields, which possesses more accurate confidence intervals than the Sobel method and has a greater test power (Taylor et al., 2008). Thus, the bias-corrected percentile bootstrap method was employed to sample the formal data 2000 times with a 95% confidence interval (CI 95%) to test the significance of the mediation effects (Guo et al., 2022). The effects were significant (p ≤ 0.05) if zero is not included in their CI 95% (Hayes, 2015). The χ2/df, RMSEA, SRMR, GFI, AGFI, TLI, and CFI were employed to assess the fit of the entire model of this research. Scores for χ2/df lower than 5, SRMR and RMSEA below 0.08, AGFI greater than 0.8, and GFI, TLI, and CFI more than 0.9 were identified as indicators of a well-fitting model (Hu and Bentler, 1999; Marsh et al., 2004; Lee et al., 2008; Opperman et al., 2013).

Suitability for measurement instruments

Teacher support. For assessing the structural validity of the teacher support scale, we conducted a CFA analysis on the four items employed to gauge teacher support. The results suggested a well-fitting model. Thus, all items were maintained. Table 6 shows that each item's factor loading was larger than 0.40, and Table 1 shows that the model fit indices satisfied the required standards, suggesting the scale's strong structural validity. Moreover, the teacher support scale's omega coefficient was 0.888, which demonstrated the scale's high degree of reliability.
Peer support. A CFA analysis was implemented for the five items of the peer support scale in order to assess the scale's structural validity. The findings revealed that the model fits the data well. Hence, all items were maintained. All items exhibited factor loadings greater than 0.40 (Table 6), and the model fit indices fulfilled the established criteria (Table 1). Moreover, the peer support scale's omega coefficient was 0.914, which demonstrated the scale's high degree of reliability.
Growth mindset in chemistry. A CFA analysis was carried out for the items of growth mindset in chemistry to evaluate the scale's structural validity. One item's factor loading was discovered to be below 0.4 in the first round of CFA. Thus, it was eliminated. Then, we implemented the second round of CFA on the four items that remained, which obtained a well-fitting model. The scale's high structural validity was demonstrated by the fact that all of the items in the second round of CFA had factor loadings greater than 0.40 (Table 6) and that the model fit indices satisfied the required standards (Table 1). Internal consistency was evaluated using omega reliability analysis after the validity of the scale's factor structure was confirmed. According to the analysis, the growth mindset in the chemistry scale had an omega coefficient of 0.863, which revealed that the scale holds good reliability and high internal consistency.
Grit in chemistry. For assessing the structural validity of the grit in chemistry scale, we employed a two-factor model and implemented the confirmatory factor analysis on the eight items. The findings revealed that the model fits the data well. Hence, all items were retained. Table 4 shows that the factor loadings of all items were greater than 0.40, and Table 1 shows that the model fit indices fulfilled the established standards. Then, single-factor CFA tests were performed for perseverance and passion, respectively, in order to confirm each factor's unidimensionality. All of the items in these single-factor CFAs showed factor loadings greater than 0.40 (Table 5), and each factor's model fit results satisfied acceptable criteria (Table 1). These findings suggested that each factor possessed a unidimensional structure, laying the groundwork for further reliability testing. The scale's overall omega coefficient was 0.892, which demonstrated the overall scale's high degree of reliability. And its two dimensions' omega coefficients were 0.861 and 0.867, verifying that each dimension's items revealed a good level of internal consistency.
Chemistry learning satisfaction. We adopted CFA to evaluate the scale of chemistry learning satisfaction. All items were retained, and the results demonstrated a good fit of this model. According to Table 6, all items in this scale exhibited factor loadings greater than 0.4. Besides, Table 1 shows that the model fit indices satisfied the required standards, revealing the scale's strong structural validity. Internal consistency was evaluated using omega reliability analysis after the validity of the scale's factor structure was confirmed. According to the analysis, the chemistry learning satisfaction scale had an omega coefficient of 0.863, which revealed the scale's good reliability and a good level of high internal consistency.

Results

Preliminary analyses

Following the advice of Podsakoff et al. (2003), the Harman single factor test was implemented, and the outcomes demonstrated that there was no common method bias in our measurement tools. To be specific, the first factor's explained variance was 36.659% [<40%], and the initial eigenvalues of six factors were greater than one. At the same time, the total variance interpretation rate is 72.482%, which has reached the standard of 60%, indicating that the six factors of reservation are appropriate (Wu, 2010).

Each research variable's standard deviations, means, skewness, and kurtosis are shown in Table 2. The data were demonstrated to be normally distributed by the skewness and kurtosis of the variables, which varied from −0.366 to −0.032 and −0.629 to −0.132, respectively (Kline, 2005). Also, the results of the Pearson's product-moment bivariate correlations are represented in Table 2, revealing that both within and between structures held significant correlations. Specifically, teacher and peer support were discovered to positively and significantly associate with growth mindset in chemistry (teacher support: r = 0.437, p < 0.01; peer support: r = 0.411, p < 0.01), grit (teacher support: r = 0.383, p < 0.01; peer support: r = 0.394, p < 0.01), and chemistry learning satisfaction (teacher support: r = 0.440, p < 0.01; peer support: r = 0.428, p < 0.01). Both grit (r = 0.506, p < 0.01) and chemistry learning satisfaction (r = 0.499, p < 0.01) were significantly and favorably predicted by growth mindset in chemistry. Grit held a positive and significant predictive ability on chemistry learning satisfaction (r = 0.451, p < 0.01). Furthermore, both components of grit in chemistry held significant positive correlations with teacher support (perseverance: r = 0.339, p < 0.01; passion: r = 0.353, p < 0.01), peer support (perseverance: r = 0.379, p < 0.01; passion: r = 0.334, p < 0.01), growth mindset in chemistry (perseverance: r = 0.449, p < 0.01; passion: r = 0.466, p < 0.01), and chemistry learning satisfaction (perseverance: r = 0.407, p < 0.01; passion: r = 0.408, p < 0.01).

Table 2 Descriptive statistics and correlations between the variables
Variables Mean SD Skewness Kurtosis Confirmatory factor analysis Bivariate correlations
CR > 0.6 AVE > 0.4 1 2 3 4 5 6
Note. **p < 0.01. 1, 2, 3, 4, 5, 6 stand for teacher support, peer support, growth mindset in chemistry, grit in chemistry, perseverance, and passion, respectively.
Teacher support 3.51 0.918 −0.235 −0.629 0.89 0.67 1
Peer support 3.55 0.914 −0.263 −0.456 0.91 0.68 0.203** 1
Growth mindset 3.57 0.814 −0.243 −0.458 0.86 0.61 0.437** 0.411** 1
Grit 3.49 0.846 −0.355 −0.132 0.90 0.52 0.383** 0.394** 0.506** 1
Perseverance 3.47 0.934 −0.361 −0.306 0.86 0.61 0.339** 0.379** 0.449** 0.903** 1
Passion 3.50 0.939 −0.366 −0.327 0.87 0.62 0.353** 0.334** 0.466** 0.904** 0.633** 1
Satisfaction 3.11 0.867 −0.032 −0.346 0.86 0.61 0.440** 0.428** 0.499** 0.451** 0.407** 0.408**

Examining for the chain mediation model

In this research, AMOS 26.0 was adopted with the aim of analyzing the proposed model. The results of model fit indices exhibited that the model of this research offered a good fit to the data: χ2/df = 2.125, GFI = 0. 970, AGFI = 0.963, CFI = 0.986, TLI = 0.984, RMSEA = 0.028, and SRMR = 0.024. Besides, as indicated in Fig. 2, the findings exhibited that peer support, teacher support, growth mindset in chemistry, and grit in chemistry all positively and directly predicted chemistry learning satisfaction (peer support: β = 0.230, p < 0.001; teacher support: β = 0.246, p < 0.001; growth mindset: β = 0.233, p < 0.001; and grit: β = 0.189, p < 0.01). Besides, it revealed that peer and teacher support held a positive and direct association with growth mindset in chemistry (peer support: β = 0.368, p < 0.001; teacher support: β = 0.418, p < 0.001) and grit in chemistry (peer support: β = 0.232, p < 0.001; teacher support: β = 0.203, p < 0.001). Moreover, growth mindset in chemistry positively and directly predicted grit in chemistry (β = 0.410, p < 0.001).
image file: d5rp00074b-f2.tif
Fig. 2 Structural model of teacher support, peer support, growth mindset in chemistry, grit in chemistry, and chemistry learning satisfaction. Note. All Beta coefficients are significant at the 0.001 level.

In accordance with the suggestion of Hayes (2015), we adopted the bootstrap method to investigate the mediating influences. Table 3 shows that none of the 95% confidence intervals (CIs) for any of the study's paths included 0, demonstrating that both direct and indirect paths held significant effects (Hayes, 2015). According to the mediation effect analysis, the total effects of peer and teacher support on chemistry learning satisfaction were 0.387 (95% CI was 0.340–0.437) and 0.414 (95% CI was 0.367–0.460), respectively, while the direct effects of peer and teacher support on chemistry learning satisfaction were 0.230 (95% CI was 0.172–0.285) and 0.246 (95% CI was 0.188–0.305), respectively. This exhibited that peer and teacher support can significantly promote chemistry learning satisfaction, thus substantiating hypotheses 1 and 2.

Table 3 Bootstrapping outcomes for the direct and indirect influences of teacher and peer support on learning satisfaction via growth mindset and grit
Path Effect value SE value 95% Bootstrap CI p
Lower Upper
Note. 2000 bootstrap samples. CI = confidence interval.
Direct effects
Teacher support → satisfaction 0.246 0.030 0.188 0.305 <0.001
Peer support → satisfaction 0.230 0.028 0.172 0.285 <0.001
Indirect effects
Teacher support → growth mindset → satisfaction 0.097 0.017 0.066 0.133 <0.001
Teacher support → grit → satisfaction 0.038 0.010 0.021 0.063 <0.001
Teacher support → growth mindset → grit → satisfaction 0.032 0.008 0.019 0.050 <0.001
Peer support → growth mindset → satisfaction 0.085 0.015 0.058 0.115 <0.001
Peer support → grit → satisfaction 0.044 0.011 0.025 0.069 <0.001
Peer support → growth mindset → grit → satisfaction 0.028 0.007 0.016 0.045 <0.001
Total effects
Teacher support → satisfaction 0.414 0.024 0.367 0.460 <0.001
Peer support → satisfaction 0.387 0.024 0.340 0.437 <0.001

Additionally, the results revealed that teacher and peer support impacted chemistry learning satisfaction in three indirect ways: (a) support → growth mindset in chemistry → chemistry learning satisfaction; (b) support → grit → chemistry learning satisfaction; and (c) support → growth mindset in chemistry → grit → chemistry learning satisfaction. To be specific, the mediating influences of grit in chemistry between the associations of teacher and peer support with chemistry learning satisfaction were 0.038 (95% CI was 0.021–0.063) and 0.044 (95% CI was 0.025–0.069), respectively. This revealed that grit in chemistry holds the mediating effect on the associations of teacher and peer support on chemistry learning satisfaction, thus substantiating hypotheses 3 and 4. The mediating impacts of growth mindset in chemistry between the associations of teacher and peer support with chemistry learning satisfaction were 0.097 (95% CI was 0.066–0.133) and 0.085 (95% CI was 0.058–0.115), respectively. This revealed that growth mindset in chemistry holds the mediating effect on the associations of teacher and peer support on chemistry learning satisfaction, thus substantiating hypotheses 5 and 6. The serial mediating impacts of grit in chemistry and growth mindset in chemistry between the associations of teacher and peer support with chemistry learning satisfaction were 0.032 (95% CI was 0.019–0.050) and 0.028 (95% CI was 0.016–0.045), respectively. This revealed that growth mindset in chemistry and grit in chemistry hold the chain-mediating effect on the associations of teacher and peer support on chemistry learning satisfaction, thus verifying hypotheses 7 and 8.

Discussion

The associations of teacher and peer support with chemistry learning satisfaction

Consistent with hypotheses 1 and 2 of this study, the findings exhibited that both peer and teacher support have a significant and positive influence on chemistry learning satisfaction. As the bio-ecological theory of human development stated, the main mechanisms through which developmental outcomes are produced are proximal processes within the environment, including interpersonal relationships and social support, compared to general social environments (Bronfenbrenner, 1979). Thus, for high school students spending most of their time at school, teacher and peer support serve as proximal processes, promoting students' capability to attain desired outcomes (Bowen et al., 2008), thereby increasing their learning satisfaction (Kuo et al., 2014; Cheng and Chau, 2016). Notably, this research indicated that teacher support held a stronger direct effect on chemistry learning satisfaction than did peer support. Consistent with these findings, some studies have indicated that teacher support is more crucial than peer support for students when it comes to school-related matters (Wang and Eccles 2012). This is probably because teachers' instructional behaviors and characteristics are more vital and direct factors than peers, and it has been found to be highly relevant for students' level of interest and enjoyment in the classroom (Wang and Eccles, 2012), which is closely related to students learning satisfaction. Chemistry teaching is a goal-directed activity, and teachers provide goals in educational settings (Jenkins 2006; Högström et al., 2010) and guidance that students require to perceive and understand what they are expected to perceive and learn (Högström et al., 2010). That is, what the teachers say and how the teachers act is vital in ensuring that chemistry learning meets both the teacher's and students' expectations, resulting in effective, efficient, motivating, and pleasurable chemical learning experiences (Dohrn and Dohn, 2018), which is helpful to raise chemistry literacy and inspire students to learn chemistry (European Commission, 2015; Hu et al., 2022).

The mediating effects of (a) growth mindset in chemistry and (b) grit in chemistry

The results of this research exhibited that the relationships between peer and teacher support and chemistry learning satisfaction were mediated by both (a) growth mindsets in chemistry and (b) grit in chemistry. Specifically, this study demonstrated that growth mindset in chemistry acted as a mediator of the link between teacher support and chemistry learning satisfaction (β = 0.097); growth mindset in chemistry also had a mediating effect in the connection between peer support and chemistry learning satisfaction (β = 0.085), thus verifying Hypotheses 3 and 4.

According to Haimovitz and Dweck's (2017) model of how adults affect students' mindsets, the words and deeds of teachers can shape students' growth mindsets by enhancing their motivation and confidence for learning and encouraging them to concentrate on the learning process. In addition to teachers, peers also hold a significant role in fostering growth mindset cultures in schools. King (2020) proposed the concept of “social contagion” of mindsets and found that peer growth mindsets can spread among students when they have positive interactions with their peers, such as when they feel that their peers are supporting and encouraging them. In other words, students are inclined to hold a growth mindset when their close peers are convinced that intelligence can be developed. Furthermore, attribution theory holds that individuals try to explain their experiences and that their responses are then influenced by these explanations (Dweck and Leggett, 1988; Dweck, 1999). In keeping with this theory, people who have growth mindsets tend to view failure or difficulty in educational environments more positively (Zarrinabadi et al., 2022) because they believe that hard work can improve their intelligence (such as chemical knowledge or understanding). Thus, compared to people who interpret stress more negatively, those who view it more positively tend to exhibit greater satisfaction in their learning process. Yao et al. (2024) revealed that students who possess growth mindsets have a greater likelihood of exhibiting happiness and excitement during their educational experiences as well as higher degrees of satisfaction throughout the learning process.

Additionally, the results showed that the connection between teacher support and chemistry learning satisfaction was mediated by grit in chemistry (β = 0.038); grit in chemistry had a mediating impact in the link between peer support and chemistry learning satisfaction (β = 0.044), which verified Hypotheses 5 and 6. In social-cognitive theories (Bandura, 2001), individuals’ cognitive processes and structures are developed through the interaction with the environment, which contributes to the average behavioral tendencies and the development of personality traits. Since students in China spend a large amount of a day in school with their teachers and peers, the interactions with them are likely to play vital roles in students' development of personality traits. This finding also echoes previous studies. For instance, in the studies of Sadoughi and Hejazi (2023), teachers were discovered to help create a safe, friendly, encouraging, and dynamic learning environment, which can motivate students' chemistry literacy and competencies and sustain their enthusiasm in chemistry learning. Orson et al. (2020) also showed that students can develop dispositions and learning mindsets for persistence through experiences of successfully overcoming fear and enduring distress with the support of peers. Furthermore, the emotion regulation theory pointed out that cognitive reappraisal can modify how individuals appraise a situation to decrease negative emotion (Gross, 2015). Additionally, it was discovered that grit holds a tendency to confront obstacles with a growth-oriented viewpoint and can favorably inspire positive reappraisal (Sun and Mu, 2023). To be specific, those who possess a high degree of grit hold a tendency to view the goal-related challenges as chances to sharpen their problem-solving abilities, especially when facing very difficult and exhausting tasks (e.g., writing chemical equations correctly or solving stoichiometric problems). These positive interpretations catalyze a sense of personal accomplishment and thus may promote students' learning satisfaction (Altintas and Canbulat, 2024).

Furthermore, it is noteworthy that when grit in chemistry or growth mindset in chemistry was severed as a mediator, peer support had a greater standardized predictive coefficient for chemistry learning satisfaction than did teacher support. One explanation might be the fact that chemistry is an activity-based subject that stresses laboratory learning as a crucial component of chemistry education (Hofstein and Lunetta, 2004). Meanwhile, in chemistry education, especially in chemistry labs, collaborative learning, which is peer-based, has been strongly advocated (Arrington et al., 2008). In collaborative learning, students typically collaborate to complete a task or solve an issue, have productive conversations, and negotiate with one another to reach a consensus in order to advance their profound comprehension of chemical topics and theories (Ding and Harskamp, 2011). Projects including laboratory collaboration can help students develop their critical and independent thinking abilities, which support their growth mindset in chemistry. Additionally, discussions with peers expose students to different viewpoints (Hwang and Hu, 2013), which helps students see the obstacles to problem-solving and may encourage them to keep continuing and maintain their enthusiasm for tackling chemistry difficulties (Ding and Harskamp, 2011), exhibiting great dredges of grit in chemistry. In contrast, because of China's relatively high class size, teachers often gave suggestions or assistance in chemistry lab learning to certain students or groups rather than giving instructions to all of the students. Peers may therefore take a more prominent role than teachers in helping students build their grit and growth mindsets in the context of chemistry. Taken together, it seems reasonable that peers possess a greater influence on students' growth mindset and grit in the context of chemistry learning and thus promote higher degrees of chemistry learning satisfaction.

The serial mediating influence of (a) growth mindset in chemistry and (b) grit in chemistry

The current study's findings demonstrated that (a) growth mindset in chemistry and (b) grit in chemistry held a serial mediating effect in the association between peer support and chemistry learning satisfaction (β = 0.028); (a) growth mindset in chemistry and (b) grit also hold a serial mediating impact in the link between teacher support and chemistry learning satisfaction (β = 0.032), validating hypotheses 7 and 8. Prior research (Haimovitz and Dweck, 2017; Yu et al., 2022) has demonstrated that teacher support is connected with strong students' growth mindsets, which are connected with high degrees of grit (Limeri et al., 2020; Fan et al., 2024). Sun and Mu (2023) pointed out that students who possess high degrees of grit have a greater tendency to interpret challenges and difficulties in a growth-oriented perspective, which is beneficial for fostering students' learning satisfaction (Altintas and Canbulat, 2024). Relevant studies also demonstrated that peer support can make a positive impact on growth mindset among students (King, 2020) and thus produce the same positive effect in the chain mediation model of this study.

Implications for practice

This research's results possess certain applications for raising high school students' chemistry learning satisfaction. To begin with, our research findings pointed out that peer and teacher support possessed a beneficial influence on students' chemistry learning satisfaction. Thus, it is feasible to raise students' satisfaction with chemistry learning by encouraging peer and teacher support in the chemistry learning environment. Teachers should embrace a student-centered approach to education and teaching strategies that complement it, such as inquiry-based learning, collaborative learning, and formative assessment, to assist students in learning chemistry more effectively and foster a positive and encouraging learning environment that boosts their sense of chemistry accomplishment and fulfillment. Besides, positive peer interaction and collaborations should be encouraged in chemistry classes. Students should be provided chances to collaborate in chemistry classes to complete tasks or projects, which may help build up their senses of a chemistry learning community and mutually supporting connections. Also, students should be encouraged to actively assist their peers, for instance, by sharing resources, recognizing one another for the effort, and working together to solve difficulties (An and Guo, 2024), which boost students’ confidence and beliefs in scientific competence to complete assignments effectively.

Furthermore, the independent and chain mediation of (a) growth mindset in chemistry and (b) grit in chemistry provides new insights into improving students' chemistry learning satisfaction. As the economic theory of human capital development (Cunha and Heckman, 2007) stated, grit and growth mindset can be “self-reinforcing and cross-fertilizing,” which indicates that educators can indirectly promote grit among students through cultivating a growth mindset in chemistry and then improve their satisfaction with the chemistry learning experience. To be specific, it is advised that teachers should value students’ viewpoints and thoughts, commend students’ hard work and efforts in chemistry learning, and stress process-focused and effortful learning (Zarrinabadi et al., 2022), which can help convey to students a belief that overcoming challenging assignments is more significant compared with gliding to success on simple ones (Zarrinabadi et al., 2022). Besides, educators and school administrators should attach importance to cultivating grit among students and encourage organizing activities that foster it, including teaching students how to manage setbacks and embracing failure in science learning as a chance to learn and improve, which further stimulates their enthusiasm and interest in the chemistry field.

Limitations and further research

Although this research reported encouraging findings regarding how peer and teacher support, grit in chemistry, and growth mindsets in chemistry impact chemistry learning satisfaction among high school students, there still are some limitations that should be mentioned. On the one hand, this research was carried out by utilizing a cross-sectional approach, which results in it being challenging to deduce cause and effect inferences from the results. Besides, as Maxwell and Cole (2007) stated, there are some biases to testing the mediation effects with a cross-sectional design. Therefore, in the future, longitudinal studies can be adopted with the purpose of further improving the findings of mediating interactions and investigating the causal associations among these variables. On the other hand, this study conducted the data collection by utilizing existing questionnaires and some demographic questions, all of which are self-report measures. Owing to the social-desirability response bias and participants' test anxiety, self-report measures might affect the validity of the results. Therefore, in further investigations, qualitative and mixed-methods approaches can be utilized, such as observations and interviews, to reduce the influence of subjectivity. Besides, data can be gathered from multiple types of sources, including peers and teachers, to obtain a deeper understanding about the associations of peer and teacher support with chemistry learning satisfaction among students.

Data availability

The raw data used to support the conclusions in this study will not be made publicly available due to privacy and ethical concerns. Sensitive information in the data may jeopardize research participants' privacy. However, upon reasonable request, the original author, Qian Huangfu, will provide the anonymized data that support the study's key conclusions. A data access agreement that outlines the data's permitted uses and guarantees participant confidentiality must be signed by researchers who want to use the data. Please get in touch with chemqian16@swu.edu.cn for further information about the data's specifics and access requirements.

Conflicts of interest

There are no competing interests to disclose.

Appendix

Tables 4–6.
Table 4 Standardized factor loadings for the grit in chemistry scale
Variables Items Standardized factor loading
Perseverance 1 0.799
2 0.772
3 0.771
4 0.774
Passion 1 0.777
2 0.767
3 0.812
4 0.790

Table 5 Standardized factor loadings for each individual factor of the grit in chemistry scale
Variables Items Standardized factor loading
Perseverance 1 0.811
2 0.782
3 0.749
4 0.775
Passion 1 0.778
2 0.765
3 0.811
4 0.788

Table 6 Standardized factor loadings for teacher support, peer support, growth mindset in chemistry and chemistry learning satisfaction scales
Variables Items Standardized factor loading
Teacher support 1 0.825
2 0.819
3 0.810
4 0.808
Peer support 1 0.825
2 0.808
3 0.850
4 0.818
5 0.820
Growth mindset in chemistry 1 0.774
2 0.797
3 0.786
4 0.769
Chemistry learning satisfaction 1 0.709
2 0.775
3 0.816
4 0.816

Acknowledgements

This work was supported by the National Social Science Fund of China, CSA240318.

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