Chain Mediating Effects of Student Engagement and Academic Achievement on University Identification

Abstract

This study aimed to examine the relationship between the classroom environment (CE) and university identification (UI) and the chain mediating effects of student engagement and academic achievement (AA). 4,463 Chinese university students were assessed using the classroom environment and UI scales, and measures of student engagement. Results show: (1) a significant positive correlation between a supportive CE, high student engagement, high AA, and high UI; (2) AA plays a mediating role between CE and UI, while student engagement mediates CE and UI; and (3) student engagement and AA play a chain mediating role between CE and UI. This study verified that a positive CE helps strengthen university students’ UI, and student engagement, AA, and a series of intermediary roles had a chain mediating effect. Universities should create a positive CE and encourage building good interpersonal relationships between students and others to further increase AA and UI among students.

Plain Language Summary

How classroom environment impact on university identification?

Purpose This study aimed to examine the relationship between the classroom environment (CE) and university identification (UI), and the chain mediating effects of student engagement and academic achievement (AA). Methods 4,463 Chinese university students were assessed using Hayes SPSS PROCESS macro (Model 5) to test all hypotheses . Conclusions The finding indicate: (1) a significant positive correlation between a supportive CE, high student engagement, high AA, and high UI; (2) AA plays a mediating role between CE and UI while student engagement mediates CE and UI; and (3) student engagement and AA play a chain mediating role between CE and UI. Therefore, CE directly affects students’ UI while indirectly affecting UI levels through the chain intermediary role of student engagement and AA. Implications This study illustrated the process of how CE influences students’ UI. The indirect path (CE–student engagement—–AA—–UI) is significant and UI is highly sensitive to the positive impact of CE. Thus, administrators in public universities should emphasize factors such as identification and sense of belonging experienced by students within these institutions. limitations of your study The regional differences of the small sample size used, restricting the generalizability of the study results.

Keywords

university students classroom environment university identification student engagement academic achievement

Classroom environment (CE), also known as the classroom atmosphere, refers to the shared perception of students and teachers. CE determines potential factors for student development and learning and is considered an essential element of educational quality that cannot be overlooked by student leadership (Lyons et al., 2018). Previous studies demonstrated that CE significantly correlates with students’ curriculum learning engagement (Ross, 2020). Furthermore, students who value and feel a sense of belonging to the school are more likely to exhibit behaviors of enhanced school engagement to experience deeper learning and improve their academic performance (Voelkl, 2012).

University identification (UI) refers to university students’ stronger feelings of belonging, honor, and happiness with respect to their institutions, which yield a greater degree of identification with the university (Fraser & Treagust, 1986). Previous studies confirmed that students’ recognition of school-related values has a significant predictive effect on student engagement (Archambault et al., 2013; Tam et al., 2012; Willms, 2003). Therefore, the indirect influence of CE on students’ UI should be prioritized and examined empirically.

Previous studies indicate that caring and supportive CEs can influence school identification among students. Thus, if students feel cared for and free to participate actively in class activities, they perceive a positive and supportive school atmosphere, which enhances their sense of belonging to and value for the school (Virtanen et al., 2021). Therefore, it is vital to understand how participation among students can be sustained and fostered through CEs. In the present study, the “black box” concept is analyzed to assess the relationship between CE and student engagement, academic achievement (AA), and UI in the context of chain mediators.

Thus, the current study reviews the literature related to CE and UI to determine the chain mediating effect of student engagement and AA in these relationships. This study contributes to literature by investigating whether CE directly and positively affects students’ UI and also indirectly affects UI through the chain intermediary role of student engagement and AA.

Literature Review

Relationship Between Classroom Environment and University Identification

Despite extensive research on university atmosphere, studies underscoring the association between UI and CE are limited (M. Wang, 2016). Strong school identification can provide a high degree of school satisfaction and promote students’ positive development (Paricio et al., 2020). School satisfaction is a key mitigative factor for preventing school dropout (Simonsen & Rundmo, 2020). Previous research suggests that CEs can impact students’ school experiences, thus improving or reducing their sense of school identification (Burns et al., 2019). Furthermore, several studies explore perceived CEs at the individual level (e.g., Shernoff et al., 2017; S. Wang & Zhang, 2020; Yin et al., 2020).

A recent study applied multilevel regression modeling to analyze teacher feedback, behavior engagement, and school identification (Monteiro et al., 2021) and found that effective feedback is an essential tool for teachers to create supportive CEs. Furthermore, it has been reported that a highly supportive CE can improve learning, promote performance, and enhance students’ motivation and participation (Virtanen et al., 2021). Therefore, a high degree of CE can also have an impact on students’ participation and school identity (Voelkl, 2012). Consistent with previous studies (e.g., Burns et al., 2019; Monteiro et al., 2021), this study proposes that CE will significantly impact students’ UI.

H1: CE will positively influence the students’ UI.

Student Engagement and AA Independently Mediate the Relationship Between CE and UI

Student engagement refers to the level of attention, curiosity, interest, optimism, and enthusiasm that students show in learning or receiving education. This extends to the degree of motivation required for their learning and educational progress (Cavanagh, 2012). Prior studies have shown that students’ perception of CE is crucial for their engagement (Cavanagh, 2012; Tas, 2016; S. Wang & Zhang, 2020). Empirical research has shown that in a classroom learning environment, student engagement serves as a mediating variable associated with CE influence on student learning (Shernoff et al., 2017). Furthermore, several researchers have found that CE directly impacts AA (e.g., Brock et al., 2008; Shan et al., 2014).

Direct and indirect effects on the correlation between CE and AA have been observed across studies. It has been found that a positive and supportive classroom climate correlates with improved academic performance (Fraser & Kahle, 2007; Gietz & McIntosh, 2014; Ma, 2003) and classroom behavior (DiLalla & Mullineaux, 2008). Other scholars have found that teacher support, peer interaction (Fraser & Kahle, 2007), and classroom participation are also important factors affecting student engagement (Archambault et al., 2013). A positive CE can improve engagement among students; thus, it is relevant to understand how it is likely to impact students’ engagement and school identification.

The University Classroom Environment Inventory questionnaire comprises information on peers, teachers, and classroom participation closely related to student development (Fraser & Treagust, 1986). This CE scale reflects factors that have an impact on AA among university students. Tas (2016) underscored that many perceived learning environment variables were positively correlated with student engagement, while motivation factors significantly predicted student engagement. Moreover, researchers have observed a functional relationship between the physical environment, with decreased disruptive behavior and increased academic engagement (Guardino & Antia, 2012). Therefore, this study predicts that CE features will influence the extent of students’ active participation in learning. Furthermore, students will be able to improve their level of engagement with their studies and focus on their learning, thus increasing their internal psychological resources through this process.

Existing literature has found established relationships between students’ CE, student engagement, and AA. Particularly, teachers who created a feeling of community by interacting and developing positive relationships with students influenced enhanced engagement with and passion for learning among students, increasing the likelihood of them attaining improved AA (Shan et al., 2014). Research suggests that a student’s perception of the teacher’s demand (i.e., challenge and control) is bound up with students’ academic outcome and growth (Sandilos et al., 2017). The student-teacher relationship comprises one dimension of students’ perception of CE, and had certain differential predictive effects on their convergent thinking levels (Y. Zhang et al., 2021). Furthermore, several researchers have suggested that AA is significantly associated with student engagement, which mediated the effect of all independent factors (e.g., general deviance, poor family socialization, deviant affiliations, and gender) on students’ dropout (Battin-Pearson et al., 2000). Moreover, beliefs about post-graduate earnings are influenced substantially by decreased enjoyment of school due to poor performance (Stinebrickner & Stinebrickner, 2014).

As per the participation-identification model, students’ attachment and emotional connection with people in the school can determine their interests and values. The participation component is a visible indicator of students’ engagement with the school (Fredricks et al., 2004). A recent study revealed that students’ disengagement from upper secondary education can be prevented by promoting student participation and identification (Virtanen et al., 2021). Consequently, students experience a sense of belonging to the school when they have a high degree of identification. Moreover, students will value their school and consider their education important and beneficial if they are supported and accepted by the school (K. V. Finn & Frone, 2004). Previous research showed that students’ study engagement levels have a significant effect on their UI. Students with high levels of study engagement are inclined to increase their UI (Virtanen et al., 2021). Carvalho et al. (2020) further confirmed an association between CE and increased school identification through increased behavioral engagement.

Divergent thinking is the phase during which the highest number of new ideas are generated (Plucker & Makel, 2010). It is a key part of the creative process (Kaya & Acar, 2019), and also the main cognitive strategy used by designers to generate multiple ideas (Lazar, 2018). Crilly and Cardoso (2017) noted that divergent thinking contributes to the discovery of new ways of solving design problems, and demonstrated a positive correlation between divergent thinking and creative ability. Therefore, divergent thinking is crucial for cultivating creativity. This finding suggests that teachers could structure CEs to enhance creativity levels among students by establishing positive student relationships.

According to the above literature review and theoretical discussion, CE will affect students’ engagement and AA, increasing the students’ UI in China. Hence, the current study proposed the following hypotheses:

H2: Student engagement will mediate the positive influence of CE on UI.

H3: AA will mediate the positive influence of CE on UI.

The Chain Mediating Effects of Student Engagement and AA

School identification refers to an individual’s sense of belonging to a school and realization of the emotional significance and value of being a school member (Bizumic et al., 2009). Identification with a university commences with students’ participation in school-related activities. Students with higher participation in school-related activities are more likely to achieve better AA, which in turn can further enhance students’ school identification and make them more willing to actively and seriously participate in academic activities. In a virtuous cycle, appreciating school-related outcomes reinforces the sense of belonging, inducing increased participation (J. D. Finn, 1989; J. D. Finn & Zimmer, 2012). Holen et al. (2018) proposed that teacher-student relationship would mediate the mental health problems that can be mitigated by student engagement. These results suggest that the student-teacher relationship could be a potential mitigative mechanism (Holen et al., 2018).

Virtanen et al. (2021) found that increased engagement in school activities toward the end of primary school enhanced greater identification (i.e., feelings of appreciation and belonging to the school) at the end of lower secondary school. Furthermore, they discovered that AA was instrumental in mediating the above-mentioned association (Virtanen et al., 2021). Moreover, it has been speculated that school-related cognitions and affect could indirectly influence school identification in a plausible manner (M. T. Wang et al., 2017).

Considering family-school partnership variables, previous studies revealed that environmental factors promote student engagement and enhance the likelihood of a successful outcome at school (Christenson et al., 2012). From these findings, this study hypothesizes that increased student engagement can improve UI. Furthermore, the dimension of UI applied in this study is used and adopted widely across several studies. Meyer and Allen (1991) found that in addition to increasing AA, the feeling of belonging to institutions, which enhanced enthusiasm to attend in learning activity, was observed in the students with UI. This contributed significantly to positive learning outcomes and study engagement.

Based on previous research, the current study aims to verify the relationship between CE and UI and determine the chain mediation effects of student engagement and AA. Therefore, this study developed the following hypothesis:

H4: Student engagement and AA exhibit chain mediating influence of CE on UI.

Figure 1 shows the hypothetical model of the relationships between CE, student engagement, AA, and UI.

Figure 1.

Conceptual model.

Materials and Methods

Participants

The study participants comprised 4,463 students from six universities in five cities in Guangdong Province, China, of whom 2,300 (51.5%) were females, and 2,163 (48.5%) were males. Since the expansion of college enrollment in 2009, the proportion of female college students has increased to more than 50%, reversing the gender gap in Chinese higher education (Goldin et al., 2006). Among participants, 668 (15.0%) were seniors, 662 (14.8%) were juniors, 1,162 (26%) were sophomores, and 1,971 (44.2%) were freshmen. The study included 1,889 (42.3%) students from a Double First-Class university, while 2,574 (57.7%) were from normally ranked universities. Furthermore, 2,127 (47.7%) students were from the humanities and social science faculty, 2,090 (46.8%) were from the faculty of sciences and engineering, and 246 (5.5%) were from the medical and other faculties. In the context of family types, 3,954 (88.6%) participants came from two-parent families while 509 (11.4%) participants came from other types of family arrangements. Geographically, 2,677 (60.0%) students were from rural areas and 1,786 (40.0%) were from cities. Regarding family income, 195 (4.4%) students came from families with a monthly salary of less than CNY 5,000, 711 (15.9%) indicated CNY 5000 to 9999, 1,844 (41.4%) came from families who earned CNY 10,000 to 14,999, 1,644 (36.8%) earned CNY 15,000 to 19,999, and 69 (1.5%) earned more than CNY 20,000.

Data Collection

A web-based questionnaire was developed upon correspondence with colleagues at the target universities. Thereafter, the corresponding colleagues sent a link (www.wenjuan.com) to all eligible university students through WeChat and QQ groups, (two widely-used social media platforms in China). All participants completed and provided their informed consent form before accessing and answering any questionnaire items, as per the design of the process. To ensure the validity of the research results, participants needed to: 1.) be enrolled at a college or university at the time of completing the survey, and 2.) each participant could only complete one questionnaire to avoid repetition and redundancy. Questionnaires were excluded if they: 1.) were answered in less than 100 seconds and 2.) contained missing values.

Measures

The participants completed the survey in Chinese. The survey consisted of sections on the CE, student engagement, AA, UI, and sociodemographic information regarding family background,age, and gender, and required approximately 20 to 30 minutes to complete.

Student Engagement Scale

Student engagement was examined through a scale adapted from the Students’ Engagement Scale (21 items, Cronbach’s α = .737) (Reeve & Tseng, 2011). The scale is divided into four subscales, namely, agentic, behavioral, emotional, and cognitive engagement. The items were translated and adapted into Chinese by D. Zhang et al. (2018), and are rated on a five-point Likert scale ranging from 1 (strongly disapprove) to 5 (strongly approve). Confirmatory factor analysis in this study showed that the construct validity of the questionnaire was good: × 2/df = 3.46, CFI = 0.97, TLI = 0.95, and RMSEA = 0.032. In our sample, internal consistency was α = .88.

University Classroom Environment Scale (UCES)

Fraser and Treagust (1986) adapted the University Classroom Environment Scale (UCES) from the University and University Classroom Environment Inventory. This scale includes 47 items divided across eight sub-dimensions: student cohesiveness, classroom involvement, teacher support, task orientation, classmates’ cooperation, equality, teacher leadership, and teacher creation. Students responded to the UCES using a 5-point Likert-type scale (1 = strongly disapprove, 5 = strongly approve). Higher scores indicate better university classroom environments; the internal consistency was α = 0.89, with subscale coefficients ranging between 0.72 and 0.86. Confirmatory factor analysis showed that the construct validity of the scale was good: ×2/df = 3.11, CFI = 0.95, TLI = 0.96, and RMSEA = 0.045.

University Identification Scale (UIS)

This study adapted the University Identification Scale (UIS) from the organization identification scale of Mael and Ashforth (1992). This scale has a single dimension with 6 items. A sample item is: “When someone praises (name of university/university), it feels like a personal compliment.” Items were ranked on a 5-point Likert-type scale (1 = strongly disapprove, 5 = strongly approve), and the overall scale had an internal consistency coefficient of 0.87. Confirmatory factor analysis showed that the construct validity of the scale was good: ×2/df = 4.78, CFI = 0.97, TLI = 0.98, and RMSEA = 0.038.

Academic Achievement

The respondents’ AA measures were the GPA of their courses in the last semester. We standardized all the GPA distributions within the courses to exclude the biases of the regions, universities, and teachers. For the empirical analyses, as endogenous indicators, these test scores were subsequently transformed as standardized scores.

Analysis Strategy

All hypotheses were tested using the Hayes SPSS PROCESS macro (Model 5; Hayes, 2013a, 2013b). Preliminarily, descriptive and Spearman’s rho correlations were computed for the measured variables. Then, based on the relevant criteria, a stepwise regression analysis was applied to test H1 (Baron & Kenny, 1986). Chain mediating model was carried out to estimate how student engagement and AA mediated the relationship between CE and UI.The obtained correlations identify meaningful relationships that were included in the causal model tested with chain mediating analysis.

In order to maximize the coverage of our model to the data we observe, we used the Maximum Likelihood Estimation method to estimate the regression/path coefficients, and the relative confidence intervals were computed with bootstrap sampling (number of bootstrap samples = 5000).The SPSS PROCESS macro (Model 5) was used for the chaining mediating model; SPSS 24.0 was used for all other statistical testing.

Results

Descriptive Statistics and Correlation Analysis

Table 1 displays the correlation matrix and descriptive statistics of the variables. The construct validity of each dimension was assessed based on item-to-scale correlations that were well-correlated with each other. In this study, the correlations of all variables were observed at the 0.01 level (two-tailed), so there were strong correlations among all variables. The above analysis results regarding the correlation between variables were consistent with the research hypotheses.

Table 1.

Descriptive Statistical Analysis and Correlation Analysis Results Among the Variables.

Variable	1	2	3	4	5	6	7	8	9	10	11
Gender^a	1
Family type^b	.147	1
Household register^c	−.176	−.139	1
School type^d
985 Universities	.070	−.063	−.017	1
211 Universities	.502	.240	−.257	−.146	1
Discipline^e
Science and Engineering	.179	−.156	.062	.202	−.087	1
Medicine and others	−.112	−.045	.130	−.071	−.086	−.231	1
University identification	−.012	−.039	.062*	.027	−.165	.029	.118	1
Student Engagement	−.091	−.153	.126	.098	−.167	.222	.195	.317	1
Classroom environment	−.142	−.025	−.071	−.001	−.082	.117	−.004	.171	.238	1
Academic achievement	−.077	−.073	−.028	.048	−.047	0	.079	.328	.376	.180	1
Mean	—	—	—	—	—	—	—	3.18	3.60	3.45	2.77
SD	—	—	—	—	—	—	—	1.17	.84	.56	.71

Note. *Black and bold numbers represent significant correlation.

Gender is a dummy variable, male = 1, female = 0.

Family type is a dummy variable, two-parent family = 1, other = 0.

Household registration is a dummy variable, rural = 1, city = 0.

School type is a dummy variable, with ordinary universities and universities as the reference.

Discipline is a dummy variable, taking the humanities and social sciences as the reference variable.

Hypothesis Testing

The coefficients of stepwise regression analysis and results of significance hypothesis testing are presented in Table 2, which shows that CE positively influenced UI (M7, β = 0.512). This result verifies H1. After incorporating the mediating variables, the data analysis showed that CE positively impacted student engagement (M2, β = 0.346,) and AA (M4, β = 0.331). Furthermore, student engagement and AA had statistically significant impacts on UI (M8, β = 0. 405; M9, β = 0.092). This finding confirms H2 and H3. Thus, CE and UI have a partial mediated correlation on student engagement and AA. Figure 2 is based on M2, M5, and M10 in Table 2, which depicts the chain mediation of the above variables.

Table 2.

Results of the Hypothesis Testing.

Variables	Student engagement			AA			UI
Variables	M1	M2	M3	M4	M5	M6	M7	M8	M9	M10
Controlled variables
Gender^a	−0.096*	−0.074	−0.43***	−0.409***	−0.384***	−0.43***	−0.104	−0.07	−0.066	−0.054
Family type^b	−0.132*	−0.139**	0.044	0.038	0.084	0.044	−0.157*	−0.1	−0.16*	−0.105
Household register^c	0.06	0.059	−0.265***	−0.267***	−0.286***	−0.265***	−0.101*	−0.13**	−0.077	−0.11*
School type^d
985	0.133*	0.126*	−0.089	−0.097	−0.138***	−0.089	0.143	0.092	0.152	0.099
211	−0.091	−0.035	−0.024	0.029	0.041	−0.024	0.1	0.114	0.097	0.112
Discipline^e
Science and engineering	0.368***	0.347***	0.4***	0.38***	0.266***	0.4***	−0.001	−0.141**	−0.035	−0.155**
Medicine &others	0.533***	0.464***	0.102	0.036	−0.117	0.102	0.127	−0.061	0.124	−0.054
Independent variables
CE		0.346***		0.331***	0.217**		0.512***	0.371***	0.481***	0.36***
Mediating variables
Student engagement					0.330***			0.405***		0.388***
AA									0.092***	0.052*
R²	0.141	0.21	0.055	0.078	0.109	0.055	0.121	0.207	0.135	0.211
ΔR²	0.136	0.205	0.05	0.072	0.102	0.05	0.115	0.201	0.128	0.204
F-value	28.222***	40.011***	10.034***	12.721***	16.3602	10.034***	20.703***	34.820***	20.703***	32.151***

Note. n = 1214.

Gender is a dummy variable, male = 1, female = 0.

Family type is dummy variable, two-parent family = 1, other = 0.

Household registration is dummy variable, rural = 1, city = 0.

School type is dummy variable, with ordinary universities and universities as reference.

Discipline as dummy variable, taking humanities and social sciences as reference variable.

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

Figure 2.

The mediating effect of student engagement and academic achievement on the relationship between classroom environment and university identification.

With a 95% confidence interval and a sample capacity of 1,000, two mediators (student engagement and AA) were applied in causal order to examine H4. UI was considered as the dependent variable (Y), with student engagement as the first mediator (W1) and AA as the second mediator (W2), while CE was the independent variable (X). The following three indirect effects were observed in the two mediation chain models.

Ind1: X→W1→Y; Ind2: X→W2→Y; Ind3: X→W1→W2→Y.

As presented in Table 2 and corresponding to the hypotheses, the coefficients of student engagement impacts on AA and UI were found to be statistically significant (M5, β = 0.330; M10, β = 0.388), while AA had positive impacts on UI (M10, β = −0.052). The chain mediation effects were determined from CE to UI, which were significant corresponding to the joint significance test (Taylor et al., 2008).

The following indirect effects were observed (Table 3). The indirect effect of Ind3 was statistically significant (b = 0.117, SE = `0.002, 95 % CI [0.067, 0.169]), and the total indirect effect was also found to be significant (b = 0.151, SE = 0.024, 95% CI [0.106, 0.020]). The results confirmed the hypothesis that a series of effects mediated the positive impact of CE on UI. As shown in Table 3, CE positively influenced student engagement, which in turn positively impacted AA, finally influencing UI, thus supporting H4.

Table 3.

Mediation Model: Indirect Effect Between CE and UI through student engagement and AA.

Effect	b	SE	95% CI
Total effect	0.512***	0.044	[0.426, 0.597]
Indirect effect	0.151***	0.024	[0.106, 0.020]
Direct effect	0.360***	0.044	[0.275, 0.446]
Ind1: X→W1→Y	0.134***	0.014	[0.090, 0.183]
Ind2: X→W2→Y	0.017**	0.005	[ 0.002,0.038]
Ind3:X→W1→W2→Y	0.117**	0.002	[0.067, 0.169]

Note. n = 4,463; Bootstrap resample = 5000, b is a nonstandard regression coefficient, SE is a Standard Error, and CI is a confidence interval.

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

Discussion

This study constructed a chaining mediating model to assess role of student engagement and AA on the relationship between CE and students’ UI. Furthermore, this results identified the mechanisms underlying the effect of CE on UI, as well as the conditions within which this effect occurs. Student engagement, AA, and a series of intermediary roles served as chaining mediators in the correlation between CE and UI. Similarly, Virtanen et al. (2021) stated that students’ participation in the classroom increased engagement with their studies and positively affected school identification, and is also concurrent with Sandilos et al. (2017). While student engagement had a positive effect on AA, several studies have found that student engagement increased with the improvement of AA (Johnson-Smith, 2014; Shernoff et al., 2017; Simonsen & Rundmo, 2020; Stinebrickner & Stinebrickner, 2014). Thus, this study underscored the positive impact of CE on UI through the chain mediation of student engagement and AA.

This study verified that CE positively influences the UI, thus validating Hypothesis 1. This finding is consistent with existing studies (Ahn et al., 2020; Phuntsho & Dhendup, 2020) and suggests that a positive CE is a stimulus to strengthen university students’ UI.

The findings demonstrated that student engagement can mediate the positive effect of a classroom on UI. This finding validates Hypothesis 2 and is consistent with earlier theoretical and empirical research (Carvalho et al., 2020; Shernoff et al., 2017). Furthermore, this shows that student engagement is the constructive factor underlying the positive adaptation induced by CE. Moreover, individuals with favorable CEs exhibit increased trust in their universities. Thus, they are more likely to be motivated in their studies, while students with adverse CEs are less motivated to achieve academic goals (Yin et al., 2020). This study also shows that student engagement can positively affect AA (K. V. Finn & Frone, 2004). In contrast, Guiling (2005) found no significant relationship between CE variables and academic engagement.

Students with a high level of study engagement are often proud of and encouraged by their learning. Thus, they are more likely to regard difficulties that arise during their studies as challenges instead of pressure (Bizumic et al., 2009). Furthermore, a high level of study engagement helps university students adjust their study attitudes and reduce the psychological effort required to alleviate the pressure of studying. Moreover, engagement plays a positive role in learning satisfaction and organizational commitment, thus promoting further engagement with their studies (Simonsen & Rundmo, 2020). Therefore, student engagement mediates the relationship between CE and UI.

A mediating effect of AA was also observed between CE and UI. Specifically, AA as a mediating variable explains the boundary mediation that influences the relationship between CE and UI. These results demonstrate the mediating effect of AA, validating Hypothesis 3, which is consistent with previous studies (Jeno et al., 2018; Yin et al., 2020).

Implications

In this study, a two-serial mediator model was established to probe for the influencing mechanism of CE on UI. The two-serial mediation model between CE and UI is complex due to the seven indirect effects with one direct effect. Exploring the causal connections between chain mediating variables is essential to comprehend the mechanism through which CE influences UI. Furthermore, this relationship is crucial for identifying the student engagement required to increase the level of AA exhibited in public universities in China.

A two-serial-mediator model was conducted in this study, which presumed the presence of causal chains among these mediating variables with factual causal connections (Hayes, 2012). Furthermore, the causal chain mediating effects were testified (i.e., student engagement → AA), consistent with previous studies that revealed a positive correlation between student engagement and AA (Johnson-Smith, 2014; Tomaszewski et al., 2020), which positively affects students’ UI (Balfanz et al., 2007; Paricio et al., 2020). For the participation-identification model, the chain causality between student engagement and AA was confirmed as mentioned above. Therefore, the theoretical framework presented in this study indicates that CE has a positive effect on student engagement, which enhances AA and, in turn, promotes UI.

The mechanism underlying the effect of CE on university students’ UI was explored in this study, confirming the chaining effects of student engagement and AA. In contrast to previous studies that focused on student’ professional identity, the positive role of student engagements and AA on UI was examined thoroughly, providing an essential complement to existing research. The contribution of this study has several practical implications for interventions underscoring the risk of university students’ UI. The healthy development of higher education affects the interests of many relevant stakeholders. Therefore, an in-depth understanding of the positive impacts of CE in public universities can help administrators develop effective interventions, create harmonious CEs, and promote the sustainable and healthy development of higher education.

The common problem of UI often impedes the development of higher education in Chinese universities. The findings of this study provide several practical recommendations for the management of higher education. First, this study can help administrators understand the detrimental impact of an unfavorable CEs. The positive relationship between CE and UI suggests that universities should improve classroom atmospheres by providing students with moral encouragement, increasing incentives, enhancing their surroundings, and clarifying the university students’ professional status. In addition, CEs characterized by respect, trust, and encouragement ought to be created for students. Moreover, university students should be guided and encouraged to build good interpersonal relationships with their advisers, faculty, peers, other teachers, and parents. These efforts can help students develop healthy coping mechanisms for stress and challenges in the university, improve their AA, replenish their enthusiasm and motivation for learning, as well as avoid declining engagement.

Furthermore, this study illustrates the process of how CE influences students’ UI. The indirect path (CE–student engagement–AA–UI) is significant, and UI is highly sensitive to the positive impact of CE. Thus, administrators in public universities should emphasize factors such as identification and sense of belonging experienced by students within these institutions. Faculty leaders and administrators can then help students improve their AA by providing incentives and creating a positive CE, further enhancing AA and increasing UI among students.

Finally, this study recommends conducting student-based study interventions, which can improve university students’ resilience in the face of obstacles and difficulties. This can significantly improve student engagement, which can form a foundation for their future work and increase their confidence.

Limitations and Future Research

Study Limitations

The first limitation of this study is the regional differences of the small sample size used, restricting the generalizability of the results. The second limitation relates to the presentation of a simple chaining mediation model, as only student engagement and AA were assessed as mediators without analyzing the other variables.

Directions for Future Research

First, future researchers need to expand the area sampled to increase the generalizability of the results to other parts of China. Second, researchers should prioritize male university students who may reveal different mechanisms influencing student engagement. Third, involving several types of universities could improve the general applicability of the model. Fourth, future research ought to incorporate diverse mediating factors.

Conclusions

The study shows that a positive CE can strengthen university students’ UI, in which the student engagement, AA, and a series of intermediary roles served as chaining mediators. CE has a positive effect on UI through the chain mediating role of student engagement and AA. Corresponding to the theoretical model analysis, university students who feel poorly treated in the classroom unconsciously classify themselves as classroom outsiders who lack a sense of belonging, thus leading to a reduced level of UI, which has theoretical and practical significance for interventions addressing the problem of students’ UI. Furthermore, university students who have the sense of being supported by teachers are more inclined to continue studying at their university. Students with good CEs tend to have stronger learning motivation, better learning attitudes, and higher degree of learning satisfaction.

Appendix1. University Identification Scale (UIS)

1. When someone criticizes my university, it feels like a personal insult.

2. I’m very interested in what others think about my university.

3. When I talk about my university, I usually say “we” rather than “they.”

4. My university’s successes are my successes.

5. When someone praises my university, it feels like a personal compliment.

6. If a story in the media criticized my university, I would feel embarrassed.

2. Student Engagement Scale

Items to assess agentic engagement.

1. During class, I ask questions.

2. I tell the teacher what I like and what I don’t like.

3. I let my teacher know what I’m interested in.

4. During class, I express my preferences and opinions.

Items to assess behavioral engagement

1. I listen carefully in class.

2. I try very hard in school.

3. The first time my teacher talks about a new topic, I listen very carefully.

4. I work hard when we start something new in class.

5. I pay attention in class.

Items to assess emotional engagement

1. I enjoy learning new things in class.

2. When we work on something in class, I feel interested.

3. When I am in class, I feel curious about what we are learning.

4. Class is fun.

Items to assess cognitive engagement

1. When doing schoolwork, I try to relate what I’m learning to what I already know.

2. When I study, I try to connect what I am learning with my own experiences.

3. I try to make all the different ideas fit together and make sense when I study.

4. I make up my own examples to help me understand the important concepts I study.

5. Before I begin to study, I think about what I want to get done.

6. When I’m working on my schoolwork, I stop once in a while and go over what I have been doing.

7. As I study, I keep track of how much I understand, not just if I am getting the right answers.

8. If what I am working on is difficult to understand, I change the way I learn the material.

Footnotes

Acknowledgements

We would like to extend our heartfelt thanks to Jing Deng, Chang Liu, and Zhang Tian, for their invaluable assistance throughout the entire process. Their dedication, expertise, and continuous support have greatly contributed to the successful completion of this study.

Declaration of Conflicting Interests

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

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was funded by the National Social Science (Educational Project) Foundation of China, Grant/Award Number: BMA220222. Funding body had no influence on study design, data collection, data analysis, data interpretation or writing the manuscript.

Ethical Approval

This study was approved by the Human Subjects Ethics Sub-committee of the Shantou University (Project number 09400288).

Consent to Participate and Publish

Written consent to participate and publish was obtained from all participants at baseline.

ORCID iD

Yongtao Gan

Data Availability Statement

The data that support the findings of this study are available on request from the corresponding author.

References

Ahn

H. S.

Kim

Lee

(2020). College major satisfaction differences in the relationships between student engagement and academic achievement. Learner Centered Teaching Research, 20(11), 641–661. https://doi.org/10.22251/jlcci.2020.20.11.641

Archambault

Pagani

L. S.

Fitzpatrick

(2013). Transactional associations between classroom engagement and relations with teachers from first through fourth grade. Learning & Instruction, 23, 1–9. https://doi.org/10.1016/j.learninstruc.2012.09.003

Balfanz

Herzog

Mac Iver

D. J.

(2007). Preventing student disengagement and keeping students on the graduation path in urban middle-grades schools: Early identification and effective interventions. Educational Psychologist, 42(4), 223–235. https://doi.org/10.1080/00461520701621079

Baron

R. M.

Kenny

D. A.

(1986). The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51, 1173–1182. https://doi.org/10.1037/0022-3514.51.6.1173

Battin-Pearson

Newcomb

M. D.

Abbott

R. D.

Hill

K. G.

Catalano

R. F.

Hawkins

J. D.

(2000). Predictors of early high school dropout: A test of five theories. Journal of Educational Psychology, 92(3), 568–582. https://doi.org/10.1037/0022-0663.92.3.568

Bizumic

Reynolds

K. J.

Turner

J. C.

Bromhead

Subasic

(2009). The role of the group in individual functioning: School identification and the psychological well-being of staff and students. Applied Psychology-An International Review-Psychologie Appliquee-Revue Internationale, 58(1), 171–192. https://doi.org/10.1111/j.1464-0597.2008.00387.x

Brock

L. L.

Nishida

T. K.

Chiong

Grimm

K. J.

Rimm-Kaufman

S. E.

(2008). Children’s perceptions of the classroom environment and social and academic performance: A longitudinal analysis of the contribution of the responsive classroom approach. Journal of School Psychology, 46(2), 129–149. https://doi.org/10.1016/j.jsp.2007.02.004

Burns

E. C.

Martin

A. J.

Collie

R. J.

(2019). Examining the yields of growth feedback from science teachers and students’ intrinsic valuing of science: Implications for student- and school-level science achievement. Journal of Research in Science Teaching, 56(8), 1060–1082. https://doi.org/10.1002/tea.21546

Carvalho

Santos

N. N.

Antonio

Martins

D. S. M.

(2020). Supporting students’ engagement with teachers’ feedback: The role of students’ school identification. Educational Psychology, 41(7), 863–882. https://doi.org/10.1080/01443410.2020.1849564

10.

Cavanagh

(2012). Associations between the classroom learning environment and student engagement in learning 1: A rasch model approach. Australian Association for Research in Education. http://www1.aare.edu.au

11.

Christenson

S. L.

Wylie

Reschly

A. L.

(2012). Handbook of research on student engagement. Springer.

12.

Crilly

Cardoso

(2017). Where next for research on fixation, inspiration and creativity in design? Design Studies, 50, 1–38. https://doi.org/10.1016/j.destud.2017.02.001

13.

DiLalla

L. F.

Mullineaux

P. Y.

(2008). The effect of classroom environment on problem behaviors: A twin study. Journal of School Psychology, 46(2), 107–128. https://doi.org/10.1016/j.jsp.2007.02.001

14.

Finn

J. D.

(1989). Withdrawing from school. Review of Educational Research, 59(2), 117–142. https://doi.org/10.2307/1170412

15.

Finn

J. D.

Zimmer

K. S.

(2012). Student engagement: What is it? Why does it matter? In Christenson

S. L.

Reschly

A. L.

Wylie

(Eds.), Handbook of research on student engagement (pp. 97–131). Springer Science + Business Media.

16.

Finn

K. V.

Frone

M. R.

(2004). Academic performance and cheating: Moderating role of school identification and self-efficacy. Journal of Educational Research, 97(3), 115–122. https://doi.org/10.3200/JOER.97.3.115-121

17.

Fraser

B. J.

Kahle

J. B.

(2007). Classroom, home and peer environment influences on student outcomes in science and mathematics: An analysis of systemic reform data. International Journal of Science Education, 29(15), 1891–1909. https://doi.org/10.1080/09500690601167178

18.

Fraser

B. J.

Treagust

D. F.

(1986). Validity and use of an instrument for assessing classroom psychosocial environment in higher education. Higher Education, 15(1–2), 37–57.

19.

Fredricks

J. A.

Blumenfeld

P. C.

Paris

A. H.

(2004). School engagement: Potential of the concept, state of the evidence. Review of Educational Research, 74(1), 59–109.

20.

Gietz

McIntosh

(2014). Relations between student perceptions of their school environment and academic achievement. Canadian Journal of School Psychology, 29(3), 161–176.

21.

Goldin

Katz

Kuziemko

(2006). The homecoming of American college women: A reversal of the college gender gap. Journal of Economic Perspectives, 20(4), 133–156.

22.

Guardino

Antia

S. D.

(2012). Modifying the classroom environment to increase engagement and decrease disruption with students who are deaf or hard of hearing. Journal of Deaf Studies and Deaf Education, 17(4), 518–533. https://doi.org/10.1093/deafed/ens026

23.

Guiling

S. F.

(2005). Engagement, classroom environment, academic outcomes, and American Indian middle school students [Doctoral dissertation, University of Missouri – Columbia].

24.

Hayes

A. F.

(2012). Process: A versatile computational tool for observed variable mediation, moderation, and conditional process modeling. Retrieved January 9, 2022, from http://www.afhayes.com/public/process2012.pdf

25.

Hayes

A. F.

(2013a). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. Journal of Educational Measurement, 51, 335–337.

26.

Hayes

A. F.

(2013b). Introduction to mediation, moderation, and conditional process analysis. Guilford Press.

27.

Holen

Waaktaar

Sagatun

(2018). A chance lost in the prevention of school dropout? Teacher-student relationships mediate the effect of mental health problems on noncompletion of upper-secondary school. Scandinavian Journal of Educational Research, 62(5), 737–753. https://doi.org/10.1080/00313831.2017.1306801

28.

Jeno

L. M.

Danielsen

A. G.

Raaheim

(2018). A prospective investigation of students’ academic achievement and dropout in higher education: A self-determination theory approach. Educational Psychology, 38(9), 1163–1184. https://doi.org/10.1080/01443410.2018.1502412

29.

Johnson-Smith

T. R.

(2014). Student engagement and academic achievement in technology enhanced and traditional classroom environments [Doctor of dissertation in Liberty University]. https://digitalcommons.liberty.edu/cgi/viewcontent.cgi?article=1934&context=doctoral

30.

Kaya

Acar

(2019). The impact of originality instructions on cognitive strategy use in divergent thinking. Thinking Skills and Creativity, 33, 100581. https://doi.org/10.1016/j.tsc.2019.100581

31.

Lazar

(2018). The cognitive neuroscience of design creativity. Journal of Experimental Neuroscience, 12, 1–6. https://doi.org/10.1177/1179069518809664

32.

Lyons

Brown

Bourke-Taylor

(2018). The classroom environment questionnaire (CEQ): Development and preliminary structural validity. Australian Occupational Therapy Journal, 65(5), 363–375. https://doi.org/10.1111/1440-1630.12474

33.

H. K.

(2003). The relation of academic achievement, family and classroom social environment, and peer interactions to prosocial and antisocial behavior of Chinese children. Psychologia, 46(3), 163–173. https://doi.org/10.2117/psysoc.2003.163

34.

Mael

Ashforth

B. E.

(1992). Alumni and their alma mater: A partial test of the reformulated model of organizational identification. Journal of Organizational Behavior, 13(2), 103–123.

35.

Meyer

J. P.

Allen

N. J.

(1991). A three-component conceptualization of organizational commitment. Human Resources Management Review, 1, 61–89. https://doi.org/10.1016/1053-4822(91)90011-Z

36.

Monteiro

Carvalho

Santos

N. N.

(2021). Creating a supportive classroom environment through effective feedback: Effects on students’ school identification and behavioral engagement. Frontiers in Education, 6, 661736. https://doi.org/10.3389/feduc.2021.661736

37.

Paricio

Herrera

Rodrigo

M. F.

Viguer

(2020). Association between group identification at school and positive youth development: Moderating role of rural and urban contexts. Frontiers in Psychology, 11, 1971. https://doi.org/10.3389/fpsyg.2020.01971

38.

Phuntsho

Dhendup

(2020). The relationship between school climate, student engagement, and academic achievement in higher secondary school. Bhutan Journal of Research & Development, 3, 98–125. https://doi.org/10.13140/RG.2.2.28798.00327/2

39.

Plucker

J. A.

Makel

M. C.

(2010). Assessment of creativity. In Kaufman

J. C.

Sternberg

R. J.

(Eds.), The Cambridge handbook of creativity (pp. 48–73). Cambridge University Press.

40.

Reeve

Tseng

C. M.

(2011). Agency as a fourth aspect of students’ engagement during learning activities. Contemporary Educational Psychology, 36, 257–267. https://doi.org/10.1016/j.cedpsych.2011.05.002

41.

Ross

K. L.

(2020). Ghosts in the classroom: Passive disengagement and its implications for teachers [Master of Philosophy thesis, Queensland University of Technology]. https://eprints.qut.edu.au/174651/

42.

Sandilos

L. E.

Rimm-Kaufman

S. E.

Cohen

J. J.

(2017). Warmth and demand: The relation between students’ perceptions of the classroom environment and achievement growth. Child Development, 88(4), 1321–1337. https://doi.org/10.1111/cdev.12685

43.

Shan

S. Q.

C. Y.

Shi

J. H.

Wang

Cai

H. L.

(2014). Impact of effective communication, achievement sharing and positive classroom environments on learning performance. Systems Research and Behavioral Science, 31(3), 471–482. https://doi.org/10.1002/sres.2285

44.

Shernoff

D. J.

Ruzek

E. A.

Sinha

(2017). The influence of the high school classroom environment on learning as mediated by student engagement. School Psychology International, 38(2), 201–218. https://doi.org/10.1177/0143034316666413

45.

Simonsen

I. E.

Rundmo

(2020). The role of school identification and self-efficacy in school satisfaction among Norwegian high-school students. Social Psychology of Education, 23(6), 1565–1586. https://doi.org/10.1007/s11218-020-09595-7

46.

Stinebrickner

(2014). Academic performance and university dropout: Using longitudinal expectations data to estimate a learning model. Journal of Labor Economics, 32(3), 601–644. https://doi.org/10.1086/675308

47.

Tam

F. W.

Zhou

Harel-Fisch

(2012). Hidden school disengagement and its relationship to youth risk behaviors: A cross-sectional study in China. International Journal of Education, 4(2), 87–106.

48.

Tas

(2016). The contribution of perceived classroom learning environment and motivation to student engagement in science. European Journal of Psychology of Education, 31(4), 557–577. https://doi.org/10.1007/s10212-016-0303-z

49.

Taylor

A. B.

Mackinnon

Tein

J-Y.

(2008). Tests of the three-path mediated effect. Organizational Research Methods, 11(2), 241–269. https://doi.org/10.1177/1094428107300344

50.

Tomaszewski

Xiang

Western

(2020). Student engagement as a mediator of the effects of socioeconomic status on academic performance among secondary school students in australia. British Educational Research Journal, 46(3), 610–630. https://doi.org/10.1002/berj.3599

51.

Virtanen

T. E.

Räikkönen

Lerkkanen

M. K.

Määttä

Vasalampi

(2021). Development of participation in and identification with school: Associations with truancy. The Journal of Early Adolescence, 41(3), 394–423. https://doi.org/10.1177/0272431620919155

52.

Voelkl

K. E.

(2012). School identification. In Christenson

S. L.

Reschly

A. L.

Wylie

(Eds.), Handbook of research on student engagement (pp. 193–218). Springer.

53.

Wang

(2016).The study of relationship among campusatmosphere, school identification,perceived social support and psychological capital [Master’s thesis of Guangxi University for Nationalities].

54.

Wang

M. T.

Fredricks

Hofkens

Linn

J. S.

(2017). Conceptualization and assessment of adolescents’ engagement and disengagement in school: A multidimensional school engagement scale. European Journal of Psychological Assessment, 3, 1–15. https://doi.org/10.1027/1015-5759/a000431

55.

Wang

Zhang

(2020). Perceived teacher feedback and academic performance: The mediating effect of learning engagement and moderating effect of assessment characteristics. Assessment & Evaluation in Higher Education, 45, 973–987. https://doi.org/10.1080/02602938.2020.1718599

56.

Wang

Yin

Zhang

(2017). Environment matters: Exploring the relationships between the classroom environment and university students’ affect in mathematics learning in China. Asia Pacific Education Review, 18, 321–333. https://doi.org/10.1007/s12564-017-9478-5

57.

Willms

J. D.

(2003). Student engagement in school: A sense of belonging and participation. OECD.

58.

Yin

H. B.

Shi

Tam

W. W. Y.

G. S.

(2020). Linking university mathematics classroom environments to student achievement: The mediation of mathematics beliefs. Studies in Educational Evaluation, 66, 100905.

59.

Zhang

Cui

Wang

D. I.

Zhao

(2018). Can self-supporting teaching promote students’ learning engagement? — Based on the subject teaching experiment. Primary and Secondary School Management, 5, 35–38. https://doi.org/10.3969/j.issn.1002-2384.2018.05.011

60.

Zhang

Rosen

Chen

Cheng

Liu

(2021). Students’ perception of classroom environment in China and its relationship to creativity of students who have visual impairments. Journal of Developmental and Physical Disabilities, 33, 65–84. https://doi.org/10.1007/s10882-020-09733-1