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Article

The Impact of Student-Teacher Policy Perception on Employment Intentions in Rural Schools for Educational Sustainable Development Based on Push–Pull Theory: An Empirical Study from China

by
Siyu Chen
1,*,
Ran Wang
2,
Tingting Wang
1 and
Wenxian Zhou
1
1
School of Education, South China Normal University, Guangzhou 510000, China
2
Longhua Second Primary School, Shenzhen 518000, China
*
Author to whom correspondence should be addressed.
Sustainability 2022, 14(11), 6639; https://doi.org/10.3390/su14116639
Submission received: 26 April 2022 / Revised: 23 May 2022 / Accepted: 26 May 2022 / Published: 28 May 2022
(This article belongs to the Special Issue Approach and Policy in Higher Education for Sustainability)
Browse Figure
Versions Notes

Abstract

:
Governments and professional organizations around the world have realized that successful recruitment and retention policies are vital to address the shortage of teachers in rural and remote areas. To the best of our knowledge, despite extensive advocacy of policies and discussions pertaining to their implications, an academic investigation into how student teachers perceive the policies and how their policy perception influences rural employment intentions has rarely been performed. Herein, this study is devoted to investigating the impact of policy perception on student-teacher rural employment intentions. In this study, the participants consist of undergraduate and postgraduate students at Chinese universities who specialize in preparing teachers of all disciplines. A questionnaire survey and quantitative analysis based on commercially available software Questionnaire Star, SPSS 26.0, Amos 26.0 and RMediation package were performed in data acquisition and analysis. It was found that student-teacher perception of the supporting policy Rural Revitalization Strategy was a little below average. High policy perception leads to an increase in the intentions of student teachers to seek employment in rural areas, and social support and positive job perception mediate the linkage between policy perception and rural employment intentions. It was also found that a difference in academic qualifications, census registration, and unpaid teaching satisfaction exists in the intentions to teach in rural schools. Such effects can be explained by the push–pull theory. Finally, this study provides recommendations for governments, universities, rural schools, and families.

1. Introduction

Teachers are the most crucial school-related factor impacting the academic achievements of students and educational sustainable development (ESD) [1,2,3]. However, due to geographical isolation, limited access to professional development activities, low salary, and engagement in teaching a variety of subjects [4], large rural areas in many countries are experiencing a decrease in the number of teachers and are facing a serious challenge of recruiting and retaining qualified teachers [5], which has impeded sustainable development of the whole society. To curb this problem and to prevent the deterioration of the situation, many countries and universities have introduced relevant policies and spent a substantial amount of resources to train, recruit, and retain qualified teachers, especially for rural areas [6,7,8], such as the National Outstanding Teacher in Disadvantaged School Program launched by Australia [9] and the Rural Revitalization Strategy (RRS) introduced by China [10].
The RRS was introduced in the 19th National Congress of the Communist Party of China in 2017, which was a critical decision to enhance sustainable rural development [11]. The key to rural revitalization is to win the fight against poverty, which is inseparable from a strong support of professional and technical talents cultivated through education. The RRS has emphasized the significance of education in poverty alleviation and taken active steps to promote sustainable rural education [12]. First, it has prioritized the ESD and the implementation of policies in rural areas. Second, to encourage and attract excellent university graduates and in-service teachers to apply for jobs in rural schools, a series of subprojects was also introduced, namely Plans of Talents Support, San Zhi Yi Fu (Taking Community-level Posts in Education, Agriculture, Health Care, and Poverty Relief) and Special-Posts Teacher Project. Third, to eliminate the apprehensions of teachers with respect to the inaccessibility of and isolation from cities, the RRS emphasizes building infrastructure and developing social security system in rural areas, including the implementation of the Digital Village Strategy, popularizing telemedicine and distance education, and fortifying the construction of primary medical care.
Supporting policies like the RRS have been proven to be effective to alleviate rural teacher shortages and to speed up sustainable and coordinated progress of rural and urban areas over time [13]. However, the output of any policy is affected by one or more problems in the process of implementation and may not always meet the expectations and objectives of the policymakers [14]. For example, some student teachers leave after teaching for a short period of time. This has a negative impact on the local teachers, and hence the rural schools have to face the burden [15]. Previous studies on these issues have focused on an analysis of policy contents [11], case studies of policy implementation [16], teacher development against the background of the policies [17], strategies to execute policies [18], indicators to evaluate effects [19,20], and constraints of the policies [21]. Previous research has found that college student policy perception had a significant positive effect on their job search [22,23], but the influencing mechanism is yet to be explored. In addition, issues related to policy perception, social support, job perception, or intentions have been studied in some other disciplines, but there are few existing studies that fully demonstrated their relationship. In recent years, China has enacted a series of policies to support the recruitment and retention of rural teachers and produced some effects; therefore, it is an appropriate country for investigation and for providing experience for other countries to foster ESD.
The general question of this study is thus how exactly Chinese student-teacher perception of supporting policies (RRS in particular) influence intentions to teach in rural schools. In order to answer this question of how (the influencing mechanism), there needs to be an analysis of what (the status quo of Chinese student-teacher policy perception and rural employment intentions) and why (factors that influence Chinese student-teacher rural employment intentions). For that reason, this study focuses on three questions: (I) What is the Chinese student-teacher perception of the supporting policy, the RRS, and intentions to teach in rural schools? (Ⅱ) What are the push and pull factors that influence Chinese student-teacher intentions to teach in rural schools? (Ⅲ) How does policy perception affect rural employment intentions? This study aims to fill the literature gap with research findings and provide governments, universities, schools, and families with empirical evidence to enhance development for sustainability.
The following sections of the article are arranged as follows: In Section 2, we reviewed the latest research literature on rural employment of teachers, policy perception, social support, and job perception. This is followed by a discussion of the samples, methods, and details pertaining to the study data in Section 3. The quantitative analysis of the data was performed using SPSS 26.0 and Amos 26.0, and the influence of student-teacher perception of the policy (RRS) on their employment intention in rural China is shown in Section 4. Discussions about the results, limitations, implications, and conclusions are presented in Section 5 and Section 6.

2. Conceptual Framework

The present study regards student-teacher rural employment intention as a kind of migration. In migration studies, the push–pull (PP) theory is the dominant paradigm [24]; thus, this framework is appropriate to explore student-teacher decisions to teach in rural areas for ESD with a few slight modifications. The PP theory holds that people’s migration from one place to another is influenced by PP factors [25]. Push factors refer to negative factors that force people to leave their origin, while pull factors refer to positive factors that draw people to a destination [25]. Specifically, in the current research, negative or low policy perception, a lack of social support, and negative job perception were proposed as push effects, while positive or high policy perception, proper social support, and positive job perception were proposed as pull effects. Although policies and rural employment literature have revealed some insightful observations on rural schools and teacher development, previous studies that adequately demonstrate student-teachers moving to teach in rural areas are rare. Thus, quantitatively exploring factors and their effects on student-teacher determination to teach in rural schools by adopting the PP theory has both theoretical and practical values.

2.1. Policy Perception and Rural Employment Intentions

It has been perceived that individuals seek out and respond to impulse-related stimuli. Policy perception is a psychosocial condition in which people gain information about their knowledge of policy choices that support targeted behaviors and assess whether a policy system is aiding in the achievement of policy goals [26]. Policy perception is also a description of how policies affect people’s evaluation, identification, and experience of future policy changes [27]. The perception of the pros and cons of the policies is likely to make individuals support or oppose them, make judgments, and adopt certain behaviors [28]. Research showed that students who were “very familiar with the free student-teachers policy” had a higher intention of working in rural areas [29]. Specifically, individuals with higher policy perception are able to evaluate objectively and reasonably whether the fulfillment of their demands of employment is facilitated by the support provided by the policy, influence their employment plans and choices, thereby generating a stronger willingness to work in rural areas [27].
“Intention” refers to people’s mental state that guides them to take action and predicts their future behaviors [30]. Employment intention is the mental state that guides people to adopt specific job-hunting behaviors [31]. It is generated by the continuous stimulation of various employment motivations and satisfaction of employment needs [32]. It is related to the individuals’ cultural background, personalities, abilities, life experiences, characteristics of the occupation, and social recognition [33]. Extant studies on employing university graduates in rural schools have revealed that rural areas are facing the serious challenge of a low intention of teachers to work in rural schools and of particularly high attrition rates of rural teachers [11,34]. About 33% of teachers quit their job within the first three years [35]. Although the correlation between perception and employment intentions has been tested before, what is not yet clear is the impact of student-teacher perception of incentive policies (such as RRS) on intentions to teach in rural schools through a quantitative analysis. As per our knowledge based on the available literature, the following assumptions were proposed:
Hypothesis 1 (H1).
Chinese student teachers have a relatively low perception of the supporting policy RRS.
Hypothesis 2 (H2).
Chinese student-teacher perception of the supporting policy RRS has a positive effect on their intentions to teach in rural schools.
Hypothesis 3 (H3).
Chinese student-teacher intentions to teach in rural schools are different depending on genders, family types, high school elective courses, academic qualifications, census registration, and unpaid teaching satisfaction.

2.2. Social Support

Social support mainly refers to people’s feelings pertaining to respect, care, resources, and help provided by social groups they belong to [36] and by important others, such as family members, relatives, peers, colleagues, and neighbors [37]. According to Werner et al. [38], the policy perception of graduates influences the policy perception of their stakeholders. In turn, stakeholder recognition and support affect the job choice of the graduates [39]. However, there is little evidence for the relationship between social support and rural employment intentions of student teachers. Thus, this study investigated how support from important others (parents, classmates, and friends) influences student-teacher intentions to teach in rural schools. Another assumption was proposed as follows:
Hypothesis 4 (H4).
Social support that Chinese student-teachers receive has a positive effect on their employment intentions, and it mediates the relationship between student-teacher perception of RRS and intentions to teach in rural areas.

2.3. Job Perception

A person’s job perception is the result of higher-order cognitive information processing reflecting the psychological impact of a job event on him or her. Furthermore, this higher-order processing is influenced by his or her individual characteristics as well as his or her job-related experiences [40]. Previous studies have found that a positive relationship exists between job perception and employment intention. The more positive the job perception is, the higher the employment intention will be [41]. However, little attention has been paid to the special cohort of student-teachers, their perception of rural teaching, and its impact on rural employment intentions. According to the PP theory, this study classified student-teacher perception of working and teaching in rural schools as positive and negative [42]. The former refers to student-teacher perception of professional development, teaching environment, and promotion opportunities if they work in rural communities, attracting graduates to become rural teachers. The latter refers to student-teacher perception of pressure and the cost of teaching in rural areas, pushing graduates away from rural schools. Based on the literature, we proposed that job perception influenced rural employment intentions, and it was the mediating variable between perception of RRS and employment intentions in rural schools. The following assumptions were made:
Hypothesis 5a (H5a).
Chinese student-teacher positive job perception increases their employment intentions to teach in rural areas, and it mediates the relationship between the perception of RRS and intentions to teach in rural schools.
Hypothesis 5b (H5b).
Chinese student-teacher negative job perception decreases their employment intentions to teach in rural areas, and it mediates the relationship between the perception of RRS and intentions to teach in rural schools.
The theoretical model of this study is depicted in Figure 1.

3. Research Design

The major objective of this study was to assess the effects of Chinese student-teacher policy perception on their rural teaching intentions. Thus, quantitative research was adopted, which collected information from student-teachers using a random sampling method and giving out online questionnaires. Data were analyzed through descriptive and inferential analysis aiming at data cleaning, theoretical model testing, and examining multiple effects. Results are presented in numerical form and carefully understood to predict student-teacher intentions to work in rural schools accordingly.

3.1. Data Collection and Analysis

Adapted from the valid questionnaire developed by Liu [43], the questionnaire used in this study after pretest contained six latent variables, including personal information, previous experience teaching in rural schools, perception of RRS (i.e., policy perception), social support from parents, classmates, and friends, perception of teaching in rural schools (i.e., job perception), and intentions to teach in rural schools (i.e., rural employment intentions). All participants were asked to fill in the questionnaire anonymously and thanked for their answers. Confidentiality of their opinion was protected. The questionnaire was used to collect data, and SPSS 26.0, AMOS 26.0 and RMediation package were used for the quantitative data analysis.

3.2. Sampling

Random sampling was adopted to select student-teacher participants from Chinese universities who excel in pre-service and in-service teacher education. A popular professional and paid online application Questionnaire Star was used to distribute and collect the questionnaires. With the help of several university teachers and students, the QR code and link to our questionnaire were sent to student teachers in their universities and colleges. A total of 676 questionnaires were distributed, and 675 were returned, with a recovery rate of 99.8%. As shown in Table 1, the participants included 101 males and 574 females, which reflected the unbalanced gender ratio in the education major. Among them, 175 came from one-child families. A total of 332 participants had selected science and engineering in high school, while 343 had chosen liberal arts. There were 504 undergraduates and 171 graduate students. A total of 292 participants came from urban areas, and 383 came from rural areas.

3.3. Reliability

A reliability analysis was used to examine the stability of the collected data, and conclusions were drawn from the questionnaire [44]. Cronbach’s alpha (α) is a common indicator of reliability. As shown in Table 2, α of dimensions of social support, positive job perception, and negative job perception were 0.729, 0.851, and 0.671, respectively, and α of the total questionnaire was 0.729. All were greater than 0.65, indicating that the questionnaire was reliable [45].

3.4. Validity

Validity refers to the degree to which the results reflect what is being examined, and it is ascertained through confirmatory factor analysis (CFA) [44]. Before that, exploratory factor analysis (EFA) of the questionnaire was carried out using SPSS 26.0 to determine whether the data were suitable for CFA. As shown in Table 3, the KMO value of the data was 0.734 (> 0.70), and the p-value was less than 0.001, which revealed that the data passed the Bartlett’s Spherical Test and were suitable for factor analysis [46].
Second, CFA was conducted using AMOS 26.0 software. Using the criteria proposed by Thakkar (2020) [44], this study assessed model fit by examining the following fit indicators: Goodness of Fit Index (GFI), Adjusted Goodness of Fit Index (AGFI), Root Mean Square Error of Approximation (RMSEA), Standardized Residual Mean Root (SRMR), Normed Fit Index (NFI), Tucker–Lewis Index (TLI), Comparative Fit Index (CFI), Incremental Fit Index (IFI), Chi-square/Degree of Freedom (CIMN/DF), and Parsimonious Normed Fit Index (PNFI). Their values represented a good fit for the model (Table 4).
Third, Table 5 depicts the Factor Loading (FL) value, Composite Reliability (CR) value and Average Variance Extracted (AVE) value of three variables and their corresponding items. The CR value of the three variables was greater than 0.80 [47]. In addition, except for the working cost, the FL values of family support, classmate support, friend support, professional development, working environment, promotion opportunities, and working pressure were 0.674, 0.903, 0.881, 0.686, 0.838, 0.724, and 0.973, respectively, being greater than 0.50 [48].
Fourth, Table 6 shows the correlation coefficient matrix of the factors. Discriminant Validity (DV) refers to the fact that an item theoretically measures the factor to be tested and has no association with the other factors [44]. Zhu and Kraemer (2005) proposed that when the square root of all factors’ AVE is greater than the correlation coefficient between the factor and other factors, meaning DV of the factor is achieved [49]. In Table 6, the square root of AVE values for social support, positive job perception, and negative job perception were 0.826, 0.752 and 0.770, respectively, indicating good DV of the measurement model.
To summarize, through a reliability and validity analysis, the data collected in the questionnaire were reliable and valid and could be used to test theoretical hypotheses.

4. Results

4.1. Status Quo of Chinese Student-Teacher Perception of the Supporting Policy and Intentions to Teach in Rural Schools

From the skewness and kurtosis of each variable, the data came from a normal distribution (Table 7). The table revealed that 43.9% participants had an intention to teach in rural schools. The average value of perception of RRS, social support, positive job perception, and negative job perception was 2.790 (SD = ± 0.793), 2.238 (SD = ± 0.667), 2.497 (SD = ± 0.610), and 2.434 (SD = ± 0.642), respectively. Excluding participants who did not participate in unpaid teaching previously, the average value of previous unpaid teaching satisfaction of those who had participated was 3.257 (SD = ± 0.667), which was at a middle-upper level.

4.2. Correlations between Factors That Influence Student-Teacher Rural Employment Intentions

The Pearson Correlation Coefficient is known as a good method to measure the association or the statistical relationship between variables. As evident from Table 8, rural employment intentions of Chinese student teachers were positively correlated with policy perception (r = 0.165, p = 0.001), positive job perception (r = 0.296, p = 0.001), social support (r = 0.484, p = 0.001), unpaid teaching satisfaction (r = 0.089, p =0.05), current academic qualifications (r = 0.185, p = 0.001), and census registration (r = 0.157, p = 0.001). The correlation between rural employment intentions and other variables (including gender, family type, high school elective courses) was not significant. Second, as to the relationship between independent variables, intermediary variables, and control variables, policy perception was positively related with positive job perception (r = 0.173, p = 0.001), social support (r = 0.152, p = 0.001), unpaid teaching participation (r = 0.172, p = 0.001), and unpaid teaching satisfaction (r = 0.209, p = 0.001). Third, a significant positive correlation was observed between positive job perception and negative job perception (r = 0.141, p = 0.001), social support (r = 0.409, p = 0.001), and academic qualifications (r = 0.139, p = 0.001).

4.3. Effects of Perception of RRS on Rural Employment Intentions

The model of the relationship among variables assumed in this study depicts a mediation effect. The dependent variable “rural employment intention” was a dichotomous variable; therefore, this study drew on the test method and process of the mediating effect proposed by [50,51,52] and used SPSS 26.0 to examine the overall impact of Chinese student-teacher perceptions of RRS on their rural employment intentions, its direct impact on social support and job perception, and direct impact of job perception and social support on rural employment intentions (Table 9). The product of coefficients test was then used in the “RMediation” analysis package to verify that the asymmetric confidence intervals (CIs) for the mediation effect contained 0, and if not, that the mediation effect was significant [53] (Table 10).
First, as shown in Table 9, the total impact of Chinese student-teacher perception of RRS on rural employment intentions (β = 0.352, SE = 0.111, OR = 1.422) was significant at p = 0.05, indicating that with every 1 unit increase in policy perception, the probability of intentions to teach in rural schools is likely to increase by e0.352-1= 42.2%.
Second, as shown in Table 9, the direct effect of student-teacher perception of RRS on their rural employment intentions (β = 0.269, SE = 0.125, OR = 1.308) was significant at p = 0.05, indicating that with every 1 unit increase in policy perception, the probability of intention is likely to increase by e0.269-1= 30.8%. The direct effect of social support on rural employment intentions (β = 1.675, SE = 0.192, OR = 5.339) was significant at p = 0.05, indicating that when social support increases by 1 unit, the probability of teaching in rural schools is likely to increase by e1.675-1= 433.9%. The direct effect of student-teacher positive job perception on their rural employment intentions (β = 0.532, SE = 0.177, OR = 1.702) was significant at p = 0.01, indicating that when positive job perception increases by 1 unit, the probability of teaching in rural schools would increase by e0.532-1 = 70.2%. Student-teacher negative job perception had no significant direct effect on their willingness to teach in rural schools (β = −0.285, SE = 0.152, OR = 0.752).
Third, with respect to other variables, as indicated in Table 9, as compared to the undergraduates, the graduate students had higher rural employment intentions and positive job perception and received more social support. As compared to the urban university student teachers, rural university student teachers had higher rural employment intentions and positive job perception and received more social support. In addition, satisfaction with unpaid teaching in rural schools significantly affected social support that Chinese student teachers could receive and positive and negative job perception. Other variables had no significant effect on rural employment intentions, social support, and positive and negative job perception.
Fourth, as shown in Table 10, with regard to the mediating effect of social support on the relationship between Chinese student-teacher perception of RRS and rural employment intentions, the following results were obtained: (β = 0.131, SE = 0.054, OR = 1.140), and the 95% confidence interval [0.028, 0.242] did not contain 0, indicating that social support had a partial mediating effect (37.21%) on the relationship between the perception of RRS and rural employment intentions. As to the mediating effect of positive job perception on the relationship between Chinese student-teacher perception of RRS and rural employment intentions (β = 0.060, SE = 0.026, OR = 1.062), the 95% confidence interval [0.017, 0.116] did not contain 0, showing that positive job perception had a partial mediating effect (17.04%) on the relationship between the perception of RRS and rural employment intentions. As the 95% confidence interval [−0.043, 0.005] contained 0, there was no mediating effect of negative job perception on the relationship between policy perception and rural employment intentions.

5. Discussions

This study investigated an unrevealed but pivotal dimension of student-teacher rural employment intentions (i.e., policy perception). Microdata were collected to explore Chinese student-teacher perception of RRS, intentions to teach in rural schools, and impacts of push and pull factors influencing their intentions. Our empirical analysis has yielded the following results:
First, Chinese student-teacher perception of RRS was a little below average. This finding indicates that a number of student teachers have insufficient knowledge of RRS and the teaching profession and lack concepts of serving rural education. This finding corroborates the ideas of Liu et al (2020), who revealed that only 7.6% of Chinese rural teachers were familiar with supporting policies, while 40.6% of special-post teachers and 51.4% of postgraduate teachers in rural education knew little about them [54]. In addition, the student teachers in our study showed that they received some support from parents, classmates, and friends and believed that rural teacher professional development and promotion were encouraging to some extent, that the working environment was acceptable, and that the working pressure and cost in rural areas were relatively low. This speaks to the previous findings that according to applied psychology, employees intend to work if provided with more rewards and less stresses, but this is not always the case, especially for those who want to be teachers. Many pre-service and in-service teachers expressed that they became teachers because they wanted to make a difference in their students, and the value of this job went beyond the trade-off between job rewards and cost [55].
Second, our analysis shows that Chinese student-teacher perception of RRS positively influenced their intentions to teach in rural areas through mediation effects of social support and positive job perception. These findings suggest that the student teachers who have a positive perception of RRS are more likely to understand the policy implementation, more confident to adapt to the policy change, and more willing to incorporate the policy into their life. On the contrary, student teachers who negatively perceive the policy and regard it as “deceptious” “unsustainable”, and “unacceptable” are less likely to respect the policy and comply with it. These findings are consistent with previous work [27,56,57], which showed that to a great extent, the policy propaganda highlights the understanding, faith, and gratification of student teachers, and these feelings are required for the successful execution and compliance with the policy. Thus, to facilitate acceptance of the policy by the student teachers, their family members and friends, policy propaganda, and sufficient time are needed for “diffusion” and adaptation to occur [58]. By allowing more people to become involved in the policy development and advocacy, the propaganda efforts would be more fruitful. If members of the public are allowed sufficient time to assess how the policy affects them, they can acclimatize themselves to it.
Our analysis also highlights that the more support student teachers receive from their family, friends, and classmates, the greater their intention will be to teach in rural areas. These results conform with those reported in earlier studies, which have demonstrated that social cognitive factors, such as support from others and organizations, play an important role in employee job satisfaction, organizational commitment, professional identity, and career decisions, particularly for those working in underprivileged districts [55,59,60,61,62]. In other words, if policies, such as the RRS, are introduced without due regard to social factors, they cannot exert a sufficient impact and encourage people to seek employment as teachers in rural schools.
As to positive job perception, our quantitative analysis revealed that when Chinese student teachers provide higher ratings to “career development,” “work environment,” and “promotion opportunities” of rural teachers, they are likely to be more willing to work in rural schools. In addition, though negative job perception is not a significant predictor of employment intentions [63], Chinese student-teacher work pressure and cost of living still exist and should be taken into consideration. According to positive psychology, distinguishing one’s mental assets is a crucial move toward a meaningful life [64]. If a positive outlook is adopted by the student teachers with respect to the policy, then they are likely to be more confident with regard to its possible disadvantages and are likely to be more willing to tackle difficulties and facilitate adaptation.
Third, our analysis revealed that a difference in academic qualifications, census registration, and unpaid teaching satisfaction exists in Chinese student-teacher intentions to teach in rural schools. Specifically, compared to undergraduates, graduate students received more social support, perceived their jobs more positively, and possessed higher intentions to teach for ESD. This finding also accords with earlier observations, which showed that in many rural areas of China, substantial remuneration was provided to graduate students in the form of higher positions and salaries, faster promotion, and more opportunities. In addition, because of pressure due to the existing competitive situation, more and more university students apply for postgraduate entrance examinations instead of applying for a job. According to the statistical data reported by the Ministry of Education of China, about 4.57 million students participated in the exam in 2022, reaching an all-time high in China [65]. Therefore, better working conditions and treatment of undergraduates need to be provided. Otherwise, many of them will refuse to search for jobs, let alone teach in rural areas.
Moreover, compared to urban participants, rural participants receive more social support, perceive their job more positively, and are more willing to go back to teach in rural schools. This result matches that found in previous studies, which have speculated that because the economic status of rural teachers is lower than their peers in the cities [66], student teachers growing up in cities are more sensitive to the difference and have less intention to work in rural areas [55]. In this way, the government, universities, and teacher educators need to cultivate the “rural sense” of student teachers to help them develop stable emotions toward ESD. In addition, future policies could probably focus on urban students and their parents and improve their perception of the rural districts. Furthermore, national and township governments should not only attract teachers outside the towns, but also make great efforts to cultivate and retain local teachers as they might have deeper feelings for their hometowns.
Compared to those without unpaid teaching experience, Chinese student-teacher participants with unpaid teaching experience and satisfaction with it have higher rural employment intentions. Thus, opportunities to undertake internships in rural schools could be provided for student teachers to help them gain knowledge of rural education.
The generalizability of our results is subject to certain limitations that also suggest future research directions. First, most of our participants were females. Future studies can be performed with a more evenly distributed sample having approximately the same number of males and females. Second, this study examined the roles of policy perception, social support, and job perception in influencing rural employment intentions. Future studies can investigate other variables. Third, the sample was limited to Chinese student teachers. Future work could be carried out with a broader and larger sample size.
The findings of our study have several important implications for future practice and other countries, which are also facing a shortage, loss, and low quality of rural teachers [67]. National and regional governments and rural schools need to continue to publicize the related supporting policies such as RRS and focus on building platforms for rural teacher employment and development, improving their working conditions, such as reducing class size and shortening working hours by reducing teacher errands and increasing their perception of their status of income. Universities and teacher educators need to foster student-teacher readiness to analyze the idea of ESD and contemplate the meaning of teaching in rural schools for children, for oneself, and for society as a whole. Members of student-teacher social networks need to improve their perception of related policies, communicate with student teachers, and encourage them to serve the poor areas.

6. Conclusions

This study empirically investigated the student-teacher policy perception of RRS and rural employment intentions, examined two categories of antecedents for intentions to teach in rural schools: push (i.e., low policy perception and negative job perception) and pull factors (high policy perception, social support, and positive job perception), and explored the push and pull effects of these variables. These findings clearly portray what constitutes the push and pull forces and contribute to our understanding of the role of policy perception, social support, and job perception in student-teacher decisions to teach in rural schools for ESD.

Author Contributions

Conceptualization, S.C. and R.W.; methodology, R.W. and T.W.; software, S.C., R.W. and W.Z.; validation, R.W., T.W. and W.Z.; formal analysis, S.C. and R.W.; investigation, S.C., R.W. and T.W.; resources, S.C., R.W. and T.W.; data curation, S.C. and R.W.; writing—original draft preparation, S.C., R.W., T.W. and W.Z.; writing—review and editing, S.C.; visualization, S.C. and R.W.; supervision, S.C.; project administration, S.C.; funding acquisition, S.C. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Humanities and Social Science Foundation of the Ministry of Education of China (Grant No. 20YJC880005), Projects funded by China Postdoctoral Science Foundation (Grant No. 2020T130213; Grant No. 2020M682741), and Social Science Foundation of Guangdong Province, China (Grant No. GD18YJY01).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Acknowledgments

The authors express their special thanks to all the participants and three anonymous reviewers for their comments on improving the manuscript.

Conflicts of Interest

The authors declare no conflict of interest.

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Sustainability 14 06639 g001 550
Figure 1. Theoretical framework.
Figure 1. Theoretical framework.
Sustainability 14 06639 g001
Table
Table 1. Demographic characteristics of the sample.
Table 1. Demographic characteristics of the sample.
VariableFrequencyPercentageVariableFrequencyPercentage
Gender Year
Male10115.0%Freshman12919.1%
Female57485.0%Sophomore11717.3%
One-child family Junior15222.5%
Yes17525.9%Senior659.60%
No50074.1%First-year graduate7411.0%
High school elective courses Second-year graduate6810.1%
Science33249.2%Third-year graduate263.90%
Literature and history34350.8%Others446.50%
Academic qualifications Census registration
Undergraduate50474.7%Urban29243.3%
Graduate17125.3%Rural38356.7%
Table
Table 2. Results of reliability analysis.
Table 2. Results of reliability analysis.
VariableDimensionαVariableDimensionαVariableDimensionα
Social supportFamily Support0.851Positive job perceptionCareer Development0.671Negative job perceptionWork Pressure0.643
Classmate SupportWork EnvironmentCost of Living
Friend SupportPromotion OpportunitiesTotal α 0.729
Table
Table 3. Results of validity analysis.
Table 3. Results of validity analysis.
KMO ValueBartlett’s Spherical Test
Approximate Chi-SquareDegree of FreedomSignificance
0.7341753.26628<0.001
Table
Table 4. Evaluation of Model Fit.
Table 4. Evaluation of Model Fit.
Model Fit IndicesRecommended ValueActual Values (Modified)
GFI>0.900.986
AGFI>0.900.968
RMSEA<0.08, good; <0.05, excellent0.047
SRMR<0.050.035
NFI>0.900.978
TLI>0.900.977
CFI>0.900.987
IFI>0.900.987
CIMN/DF1–32.496
PNFI>0.500.559
Table
Table 5. FL, CR, and AVE.
Table 5. FL, CR, and AVE.
VariableDimensionFLCRAVE
Social support①Family Support0.674 ***0.8640.682
②Classmate Support0.903 ***
③Friend Support0.881 ***
Positive job perception①Career Development0.686 ***0.7950.566
②Working Environment0.838 ***
③Promotion Opportunities0.724 ***
Negative job perception①Work Pressure0.973 ***0.7240.593
② Cost of Living0.489 *
Note: ***: p ≤ 0.001; *: p ≤ 0.05.
Table
Table 6. AVE Correlation Coefficient Matrix.
Table 6. AVE Correlation Coefficient Matrix.
abc
AVE0.6820.5660.593
Social support0.826
Positive job perception0.452 ***0.752
Negative job perception0.0530.165 ***0.770
Note: ***: p ≤ 0.001.
Table
Table 7. Mean, minimum, and maximum of constructs.
Table 7. Mean, minimum, and maximum of constructs.
VariableMeanStandard Deviation (SD)MinimumMaximumSkewnessKurtosis
Rural employment intentions0.4390.4970.0001.0000.248−1.944
Policy perception2.7900.7931.0005.000−0.094−0.047
Social support2.2380.6670.8204.100−0.071−0.017
Positive job perception2.4970.6100.9903.990−0.299−0.188
Negative job perception2.4340.6420.7303.660−0.410−0.239
Satisfaction with unpaid teaching3.2570.6671.0005.000−0.3470.971
Table
Table 8. Correlations between variables.
Table 8. Correlations between variables.
Variable abcdefghijkl
Rural employment intentionsa1
Policy perceptionb0.165 ***1
Positive job perceptionc0.296 ***0.173 ***1
Negative job perceptiond−0.0250.082 *0.141 ***1
Social supporte0.484 ***0.152 ***0.409 ***0.0361
Unpaid teaching participationf0.0460.172 ***−0.0410.050.0231
Unpaid teaching satisfactiong0.089 *0.209 ***0.0160.079 *0.086 *0.971 ***1
Genderh−0.065−0.032−0.014−0.008−0.112 **0.134 ***0.110 **1
One-child familyi0.025−0.0450.047−0.0020.011−0.018−0.0370.140 ***1
Academic qualificationsj0.185 ***0.0310.139 ***−0.0390.228 ***−0.123 **−0.103 **−0.092 *0.0521
High school elective coursesk−0.116 **0.036−0.081 *−0.035−0.093 *0.0720.070.152 ***−0.021−0.157 ***1
Census registrationl0.157 ***0.0420.0590.0020.121 **0.0230.0240.0190.377 ***−0.007−0.04l
Note: ***: p ≤ 0.001; **: p ≤ 0.01; *: p ≤ 0.05.
Table
Table 9. Regression Coefficient Matrix.
Table 9. Regression Coefficient Matrix.
Rural Employment IntentionsRural Employment IntentionsPositive Job PerceptionNegative Job PerceptionSocial Support
Non. Std. Coeff.
(SE)		OR
(SE)		Non. Std. Coeff.
(SE)		OR
(SE)		Non. Std. Coeff.
(SE)		Std. Coeff.
(SE)		Non. Std. Coeff.
(SE) 		Std. Coeff.
(SE)		Non. Std. Coeff.
(SE)		Std. Coeff.
(SE)
Policy perception0.352 **1.422 **0.269 *1.308 *0.112 ***0.146 ***0.0470.0580.078 *0.093 *
(0.111)(0.158)(0.125)(0.163)(0.029)(0.029)(0.032)(0.032)(0.031)(0.031)
Positive job perception 0.532 **1.702 **
(0.177)(0.302)
Negative job perception −0.2850.752
(0.152)(0.114)
Social support 1.675 ***5.339 ***
(0.192)(1.022)
Academic qualifications (Undergraduates as the standard)
Graduate0.894 ***2.445 ***0.489 *1.631 *0.146 **0.104 **−0.077−0.0520.310 ***0.202 ***
(0.206)(0.502)(0.231)(0.378)(0.053)(0.053)(0.058)(0.058)(0.056)(0.056)
Unpaid teaching participation (did not take part in unpaid teaching as the standard)
Unpaid Teaching−3.112 ***0.0445 ***−1.6520.192−1.164 ***−0.888 ***−0.622 **−0.451 **−1.251 ***−0.873 ***
(0.890)(0.0396)(1.032)(0.198)(0.205)(0.205)(0.224)(0.224)(0.218)(0.218)
Unpaid Teaching Satisfaction1.027 ***2.792 ***0.5871.7980.336 ***0.861 ***0.207 **0.503 **0.403 ***0.943 ***
(0.266)(0.741)(0.309)(0.556)(0.061)(0.061)(0.067)(0.067)(0.065)(0.065)
High school elective courses (Science and Engineering as the standard)
Literature and history−0.395 *0.673 *−0.3670.693−0.083−0.068−0.061−0.048−0.070−0.053
(0.169)(0.114)(0.189)(0.131)(0.046)(0.046)(0.050)(0.050)(0.049)(0.049)
Census registration (Urban as the standard)
Rural0.716 ***2.047 ***0.618 **1.855 **0.0400.032−0.014−0.0110.161 **0.120 **
(0.184)(0.376)(0.206)(0.383)(0.049)(0.049)(0.054)(0.054)(0.052)(0.052)
Gender (Male as the standard)
Female−0.1790.836−0.0150.9850.0480.028−0.001−0.000−0.129−0.069
(0.237)(0.198)(0.268)(0.264)(0.065)(0.065)(0.071)(0.071)(0.069)(0.069)
One child (One-child family as the standard)
Not one child−0.1200.887−0.1520.8590.0640.0460.0240.017−0.018−0.012
(0.211)(0.187)(0.237)(0.204)(0.056)(0.056)(0.062)(0.062)(0.060)(0.060)
Constant term−1.973 ***0.139 ***−5.995 ***0.00249 ***2.028 *** 2.365 *** 1.837 ***
(0.435)(0.0606)(0.785)(0.00196)(0.115) (0.126) (0.122)
Pseudo R2/R20.0915 0.2439 0.099 0.025 0.148
adj. R2- - 0.088 0.014 0.138
F84.71 *** 225.75 *** 9.165 *** 2.178 * 14.459 ***
Number675 675 675 675 675
Note: ***: p ≤ 0.001; **: p ≤ 0.01; *: p ≤ 0.05; β: Regression Coefficient; SE: Standard Error; OR: Odds Ratio.
Table
Table 10. Test of hypotheses.
Table 10. Test of hypotheses.
PathPoint EstimationEffect Value(Standard Error)95% CIsMediation Effect (%)
Non. Std. Coeff.Std. Coeff /ORNon. Std. Coeff.
Policy perception→Rural employment intentionsc0.352 ** (0.111)1.422 ** (0.158)
Policy perception → Positive job perceptiona10.112 *** (0.029)0.146 *** (0.029)
Positive job perception → Rural employment intentionsb10.532 ** (0.177)1.702 ** (0.302)
Policy perception → Negative job perceptiona20.047 (0.032)0.058 (0.032)
Negative job perception → Rural employment intentionsb20.285 (0.152)0.752 (0.114)
Policy perception → Social supporta30.078 * (0.031)0.093 * (0.031)
Social support → Rural employment intentionsb31.675 *** (0.192)5.339 *** (1.022)
Policy perception → Rural employment intentionsc’0.269 * (0.125)1.308 * (0.163)
Policy perception → Positive job perception → Rural employment intentionsa1*b10.060 (0.026)-[0.017, 0.116]17.04%
Policy perception → Negative job perception → Rural employment intentionsa2*b2−0.013 (0.013)-[−0.043, 0.005]-
Policy perception → Social support → Rural employment intentionsa3*b30.131 (0.054)-[0.028, 0.242]37.21%
Note: ***: p ≤ 0.001; **: p ≤ 0.01; *: p ≤ 0.05.
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Chen, S.; Wang, R.; Wang, T.; Zhou, W. The Impact of Student-Teacher Policy Perception on Employment Intentions in Rural Schools for Educational Sustainable Development Based on Push–Pull Theory: An Empirical Study from China. Sustainability 2022, 14, 6639. https://doi.org/10.3390/su14116639

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Chen S, Wang R, Wang T, Zhou W. The Impact of Student-Teacher Policy Perception on Employment Intentions in Rural Schools for Educational Sustainable Development Based on Push–Pull Theory: An Empirical Study from China. Sustainability. 2022; 14(11):6639. https://doi.org/10.3390/su14116639

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Chen, Siyu, Ran Wang, Tingting Wang, and Wenxian Zhou. 2022. "The Impact of Student-Teacher Policy Perception on Employment Intentions in Rural Schools for Educational Sustainable Development Based on Push–Pull Theory: An Empirical Study from China" Sustainability 14, no. 11: 6639. https://doi.org/10.3390/su14116639

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