The Predictive Factors and Model Construction of the Teaching Willingness of Post-2000s Pre-service Teachers Majoring in Early Childhood Education--A Mixed Method Study

The Predictive Factors and Model Construction of the Teaching Willingness of Post-2000s Pre-service Teachers Majoring in Early Childhood Education--A Mixed Method Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Predictive Factors and Model Construction of the Teaching Willingness of Post-2000s Pre-service Teachers Majoring in Early Childhood Education--A Mixed Method Study Wenli Zhang, Ran Wang, Lifan Hu, Shuangqi Li, Wenwuyu Gao This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6349583/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Career prospects exert a great impact on the teaching willingness of pre-service teachers. In this context, their career development must explore teaching willingness and its related predictive factors. This exploration is also beneficial for building a stable and high-quality team of teachers. Methods Given the Chinese cultural background and the characteristics of post-2000s pre-service teachers, this study adopts a mixed method to investigate the teaching willingness of 878 post-2000s pre-service teachers majoring in early childhood education in eastern China. Results The results found that (1) there are five types of teaching willingness among pre-service teachers: positive-stable type, negative-maintaining type, continuous-enhancing type, continuous-declining type, and fluctuating type. (2) Based on the Grounded Theory, this study identifies 12 predictive factors from four dimensions: individual, interpersonal, organizational, and background. Building upon these factors, we established a theoretical model wherein the interpersonal, organizational, and background dimensions predict teachers’ teaching willingness through the individual dimension. (3) Quantitative study is applied based on large-scale questionnaires, which shows that five key factors, including self-efficacy, family influence, undergraduate education, job characteristics, and government policies, play a core role in the teaching willingness of pre-service teachers majoring in early childhood education, while self-efficacy is a mediation variable for the other four factors. Conclusions Accordingly, it is suggested to improve the teaching willingness of pre-service teachers majoring in early childhood education by enhancing their self-efficacy from four aspects, namely family influence, undergraduate education, job characteristics, and government policies. post-2000s pre-service teachers early childhood education teaching willingness mixed study Figures Figure 1 Figure 2 Figure 3 1. Background Pre-service teachers' teaching willingness holds significant importance for their future career choice and professional growth [ 1 ], since it is the driving force for them to transit from ordinary people to professionals [ 2 ]. In other words, pre-service teachers’ teaching willingness directly affects whether they will engage in the teaching profession in the future and whether they can remain in positions as excellent teachers. Teaching willingness refers to an individual's inner attitude towards engaging in a teaching profession. It is a dominant and comprehensive manifestation of their professional cognition or identity [ 3 ]. According to the Ecosystem theory, individual development is dynamically changed under the influence of the ecosystem, and so is the teaching willingness of pre-service teachers [ 4 ]. Previous studies on teaching willingness were carried out from a constant perspective while ignoring the variability of predictive factors [ 5 ]. Thus, these studies started from a static perspective, overlooking the variability of predictive factors.Therefore, this study adopts a dynamic perspective aimed at revealing the predictive factors and categories of the teaching willingness of pre-service teachers, which can explain the performance of pre-service teachers' teaching willingness, and then provide a reference for educational guidance. Most research is based on existing questionnaires [ 6 ], which only roughly help understand teaching willingness through already-known predictive factors. For example, some scholars have explored the predictive factors using the FIT-Choice theoretical model [ 7 ]. However, whether there are still unknown factors affecting pre-service teachers' teaching willingness has not been well explored. This study is based on the FIT-Choice theoretical model, and it diversified and openly explores the predictive factors affecting the teaching willingness of post-2000s pre-service teachers. Five predictive factors for “choose teacher career” are concluded in this model, like social experience, teaching motivation, career cognition, and career choice satisfaction [ 8 ]. In the context of Chinese culture, some scholars have discussed the teaching willingness of pre-service teachers from the perspectives of individual internal factors and external factors, and the research shows that the former includes professional identity [ 5 ], individual interest [ 2 ], individual ability and altruism [ 9 ], the latter contains occupational treatment [ 10 ], teacher education quality and significant others. Previous studies mainly focused on subject teachers, such as those in sex education curricula [ 11 ], inclusive curricula[ 12 ], educational philosophy curricula [ 13 ], and pre-service teachers in primary school [ 2 ], but little on those majoring in early childhood education programs. It is well-known that early childhood education is an important part of China's basic education and public service system. High-quality and stable teachers are the core elements of the high-quality development of early childhood education. Therefore, a high-quality early childhood education system in the new era will be the new direction and challenge for China's early childhood education in the current and future years [ 14 ]. According to the latest education statistics released by the Ministry of Education of China, 220,000 pre-service teachers will finish their education in 2022, and the number is expected to increase to about 240,000 in 2023 [ 15 ]. Despite that, the Basic Situation of National Education Development in 2023 released by the Development Planning Department manifests that it records a decrease of 49,300 in terms of the number of full-time teachers in preschools compared with the previous year [ 16 ], which is a reflection of a problem in the development of our preschool teachers. Thus, it is necessary to explore the predictive factors and types of the teaching willingness of pre-service teachers majoring in early childhood education (Abbreviation, PSTECE) in China, to promote the professional growth of preschool teachers [ 2 ]. Although previous studies have explored pre-service teachers' teaching willingness from different perspectives, there are still some shortcomings. First, the former studies were carried out using only a single method. Only a small amount of them were combined with qualitative studies to supplement and explain quantitative studies. However, direct use of existing questionnaires suffers from time lag and may not authentically and comprehensively reveal the true predictive factors. Therefore, exploratory research should be conducted before qualitative research. Second, previous studies have paid insufficient attention to whether factors affecting pre-service teachers' willingness to teach differ across generations. Empirical evidence has shown a discrepancy in the employment intention between the post-2000s and that of the post-1980s and post-1990s. Therefore, the study on the teaching willingness of the post-2000s and related predictive factors is conducive to figuring out their employment psychology. Third, most of the previous research is characterized by single content. They were concerned with those significant factors predicting pre-service teachers' willingness to teach through quantitative research but failed to effectively reveal the types of pre-service teachers' willingness and the action path of core factors. Therefore, this study attempts to take PSTECE as the research object. By adopting a mixed method research model, starting with qualitative methods followed by quantitative methods, this study intends to validate the theoretical model of relevant predictive factors from multiple perspectives, thereby enhancing the reliability of conclusions. 2. Methods This study adopts a mixed-method research to explore the teaching willingness of post-2000s PSTECEs. Considering the particularity of the research background and the characteristics of post-2000s pre-service teachers, this study begins with qualitative research using semi-structured interviews to explore the type of teaching willingness and the predictive factors of teaching willingness and build a theoretical model. To confirm whether the qualitative results can be generalized to large-scale samples, a quantitative study is used to verify the theoretical model of the predictive factors. 3. Qualitative Research 3.1. Qualitative sample An objective sampling method was adopted in this study. Forty-one pre-service teachers, from freshmen to seniors, were selected as qualitative research objects, including thirty-four females and seven males. They were all voluntary participants and could withdraw at any time during the interview. They were signed into an agreement by the research team before the formal interview began. The interview was conducted from November 2023 to January 2024, with a single interview lasting 30–60 minutes. The specific information is shown in Table 1 . Table 1 Information of interviewees. Interviewee Sex Grade Interviewee Gender Grade P1 female Junior P21 female Junior P2 female Senior P22 male Junior P3 female Senior P23 male Senior P4 female Senior P24 female Junior P5 female Junior P25 female Junior P6 female Junior P26 female Junior P7 male Senior P27 female Sophomore P8 female Junior P28 male Sophomore P9 male Senior P29 female Sophomore P10 female Senior P30 female Sophomore P11 female Junior P31 female Freshman P12 female Junior P32 male Freshman P13 female Senior P33 female Freshman P14 male Junior P34 female Freshman P15 female Junior P35 female Freshman P16 female Junior P36 female Freshman P17 female Junior P37 female Freshman P18 female Junior P38 female Freshman P19 female Senior P39 female Freshman P20 male Junior P40 female Freshman P41 female Freshman 3.2. Qualitative data collection An interview outline was drawn up after reviewing some relevant domestic and international research results on factors affecting pre-service teachers’ teaching willingness and after repeated deliberation by members of the research team and experts. On this basis, it was decided that this study would focus on two aspects, namely “the willingness to teach kids of preschool” and “the main reasons and predictive factors for the decision”. Questions include “Do you have the willingness to teach kids of preschool at present?”, “What is the reason for your unwillingness?, “What are the main difficulties at present?”, “Do you have other career intentions?”... For more reliable qualitative data, three pre-service teachers of different grades were randomly selected for pre-interview before the formal one, which led to the correction of problems that were difficult to understand. In formal interviews, interviewers flexibly adjust questions according to interviewees to ensure the abundance and breadth of qualitative materials. In this study, the interviews were recorded with an audio recording after obtaining the informed consent of the interviewees, and then the recordings were converted into text. For those ambiguous points, the interviewees were immediately contacted for a brief supplementary interview. Finally, a total of 41 interview texts, totaling 138,000 words, were obtained. 3.3. Qualitative data analysis Based on grounded theory, this study transcoded 138,000 texts collected from semi-structured interviews, and the Chinese version of Nvivo 12.0 was used to encode the interview texts at three levels. It finally led to a theoretical framework on the teaching willingness of PSTECEs and its predictive factors. A coding team with four researchers (including two university lecturers and two senior preschool teachers) collectively coded the three interview records after labeling 41 interview texts as P1-P41 in the order of interview to clarify the coding requirements. Second, the interview texts were analyzed word by word and sentence by sentence independently, and the ambiguous and inconsistent parts were discussed in two centralized meetings every week to ensure the reliability of the qualitative analysis. In this study, we obtained an internal consistency of 89.8%. After all the work had been finished, 1/3 of the interview data wsa then randomly selected according to the theory saturation principle to test the theoretical model after the three-level coding. Besides, additional interviews with randomly selected five pre-service teachers showed no concepts and factors outside the current scope. Therefore, it can be concluded that the content structure of the predictive factors is theoretically saturated. 3.3.1. Open coding After preliminary analysis of a large number of texts, the researchers labeled the sentences related to teaching willingness, which initially generated several related concepts. To ensure their relevance and universality, the team eliminated concepts that appear only once or are not closely related to the topic. By combining similar concepts, 30 representative open encodings finally came into being, some of which are shown in Table 2 . Table 2 Examples of open coding. Raw material One-level coding I especially like preschool children, and it is wonderful to stay with them. I have always dreamed of being a teacher since childhood, because this sacred job can help children to grow up. (P9) like children, love to teach, help children grow up I took a lot of skills classes in my freshman year, which were difficult. I believe I am not suited to this kind of class; The internship is also tiring... We were not allowed to drink colored drinks in the preschool, and the principal was very strict and I was a little afraid. (P19) curriculum arrangement, internship intensity, institute system, leadership style I am willing to be a teacher of early childhood education if there is an authorized strength. However, it is too competitive to fight for an authorized strength. Besides, teachers are lowly paid for hard work. Thus, I don’t want to be a teacher anymore. (P15) quota for authorized strength, competitive intensity, job salary, job intensity, 3.3.2. Axial coding Axial coding aims to integrate preliminary concepts into more organized information, providing a structured perspective for in-depth analysis of this topic. Through systematic organization and correlation of the concepts generated from open coding, a total of 12 categories were extracted, which are self-efficacy, internal motivation, external motivation, achievement motivation, family influence, peer influence, undergraduate education, internship preschool, job characteristics, employment demand, government policies, and network media (see Table 3 ). 3.3.3. Selective coding Selective coding helps to deeply understand the structural dimension and interaction of predictive factors of this topic. Selective coding takes roots in socio-ecological theory, a theory that focuses on the interrelationship between the environment and human behavior [ 17 ]. Based on the main axial coding, this study summarized the policy, network media, employment demand, and other main axis coding into the background dimension, which was finally refined to four selective coding dimensions: the individual dimension, the interpersonal dimension, the organizational dimension, and the background dimension. Then, a coding table of factors affecting the teaching willingness of these pre-service teachers was created, as shown in Table 3 . Table 3 Coding of predictive factors on teaching willingness of PSTECEs. Selective coding Axial coding Open coding A1Individual dimension B1 self-efficacy C1 suitable personality; C2 excellent teaching ability B2 Intern motivation C3 love children; C4 love to be a teacher B3 External motivation C5 career stability; C6 career fringe benefits B4 Achievement motivation C7 help children grow up; C8 contribute to society A2Interpersonal dimension B5 Family influence C9 parent support; C10 relative recognition B6 Peer influence C11 indirect influence from the experience of friends; C12 direct influence from the words and deeds of classmates A3Organizational dimension B7 Undergraduate education experience C13 curriculum arrangement; C14 teacher education; C15 theory and practice B8 internship preschool C16 internship work experience; C17 internship unit system; C18 internship tutor guidance; C19 internship unit atmosphere A4Background dimension B9 Job characteristics C20 job salary; C21 promotion space; C22 work intensity; C23 social recognition B10 Employment demand C24 new recruitment demand; C25 competition intensity B11 Government policy C26 quota for authorized strength; C27 performance policy B12 Network media C28 rich information; C29 public opinion influence 3.4. Research on the type of teaching willingness and the construction of the theoretical model 3.4.1. Types of the teaching willingness of post-2000s PSTECEs Based on the overall analysis of the interview texts, this study concludes five types of teaching willingness of post-2000s PSTECEs, that is: positive-stable type, negative-maintaining type, continuous-enhancing type, continuous-declining type, and fluctuating type. The first four types are consistent with the results of relevant studies [ 18 ], while the last one is a new type found in this study. On this basis, a distribution diagram of these change patterns is synthesized in Fig. 1 . (1) Positive - stable type: consistent and firm in teaching The positive - stable type refers to those who are willing to engage in early childhood education before entering or in the early stages of university. During theoretical learning and practical training, these pre-service teachers consistently maintain a positive attitude and high level of teaching willingness. Besides, they have a deep passion for and are willing to pursue early childhood education. Among the 41 PSTECEs interviewed, four PSTECEs belong to this type, with interest being a key factor that was mentioned. Their love for children and identity as teachers play a crucial role in their choice of college major and employment directions. They developed an early sense of identification with teaching from a young age. Their passion and love encourage them to form the initial career plan. Two interviewed PSTECEs were introduced in the interview: I particularly like children, so I volunteered to choose this major at the very beginning. I have already planned to work in a preschool. And from freshman to senior, I have always been willing to engage in early childhood education ... Since I was a child, I have shown great adoration for the profession of teacher, so I applied for this major. I personally like this profession, and I think it is a sacred job. Moreover, I like children, so I also like to be a teacher. (2) Negative-maintaining type: out of force and refusing to teach students This type refers to Early Childhood Education not being their first choice. They are forced to choose this major due to various reasons such as “parents’ recommendation”, “insufficient scores” and “major selection restriction”. Although these PSTECEs have experienced systematic teaching education, they have never changed their teaching unwillingness, and some of them even admit that they will never work as a teacher in the future. Such a statement is not surprising, as individuals with a positive occupational identity and high self-efficacy are more likely to pursue their profession [ 19 ]. P1 and P9 depicted how they chose this major because they had no other options: I was adjusted to this major after the college entrance examination...but I have little patience...At the beginning (of enrollment), I have not considered being a preschool teacher... “After the college entrance examination, I applied for this major because my mother recommended this stable job to me. She said that it would be easy to find a job after graduation if I chose this major. But given the declining birth rate, things might change for me. In the future, I do not plan to engage in early childhood education.”... (3) Continuous-enhancing type: a higher sense of willingness with each passing day This type of PSTECEs sees enhancement in their interest in this major after constantly updating their cognition and concepts through theoretical learning, skill training, and practical exercise in college. Their teaching willingness grows from weak or nonexistent to strong. According to the field theory, pre-service teachers will establish professional identity in the academic field and practice field of pre-service teaching, which helps reshape their teaching willingness [ 20 , 21 ]. P22 and P26 are representatives of this type: I was kind of willing to teach in preschools from the beginning of the freshman year, but I truly fell in love with the major since I began to acquire related knowledge, including piano, dance, etc. I don’t want to give up the major that I have studied for so many years. Instead, I would like to gain something... Other industries don’t seem to fit me so well. At first, I wasn’t interested in it, but later on, I found some interest. When I was doing my internship in preschool, I saw many cute children, so I gradually fell in love with this major... By the time I graduate, I will have received seven years of early childhood education (5 + 2 mode, namely five years of vocational college and then two years of undergraduate education after a successful promotion). If I give up, I just waste these seven years. (4) Continuous-declining type: continuous impact and low willingness This type means that post-2000s PSTECEs suffer from many things like difficult employment, low wages, and heavy work burdens, so their already low willingness is on a continuous decline, even disappearing due to the updated and reorganized cognition. They feel anxious when there is a cognitive conflict. To this end, they try to find a new solution to the cognitive conflict [ 22 , 23 ]. P19 and P23 depicted the story of their cognitive transformation: Everything went well in the freshman year. But everything changed after I interned in preschool. It is horrible that the interpersonal environment and working environment in the preschool are not very good. The most critical fact is that what kids learn at preschool is different from what we learn at university(educational methods, educational ideas)... Teachers are exhausted from working in preschool, and I am, too. I have no confidence in this profession. At the beginning of my freshman year, I wished to engage in this field in the future, and I also have related experience. However, things get worse for this industry. With fewer and fewer job choices, I now want to undertake further education in Physical Education. (5) Fluctuating type: erratic and gloomy willingness This type of post-2000s PSTECEs is easily subject to many factors along with changes in the ecological environment, such as peer group, internship experience, learning achievement, etc., which lead to uncertain determination to engage in this career. Field-dependent cognitive style and field-independent cognitive style are well known to us [ 24 ], PSTECE with fluctuating willingness belong to the field-dependent type, and their teaching willingness is easily affected by the external changeable environment. P16 and P3 described why their teaching intentions were volatile: I still wanted to be a preschool teacher in my freshman year, but I changed my mind when I found the low salary... Preschool teachers live a miserable life because of great conflicts with the leaders. The leaders assign tasks such as environment creation, but without enough materials provided and with too much time...Occasionally, I feel satisfied since it is a time with kids, and there are also winter and summer vacations.Things will be better if the pay is higher. When P16 first entered the college, he laid a basic foundation for this major, and we can see his higher teaching willingness. However, things have changed since his sophomore year when he learned about the lives of teachers in this industry during his internship. Back to school, P16 occasionally experienced increased teaching willingness because of some “professional benefits” such as winter and summer vacations and the time with children. The main factors for P16 are salary and work intensity. P3 shared the same experience but with different predictive factors: “In my first year in college, I also wanted to become a preschool teacher. At that time, I felt piano and dance were interesting, and it was wonderful to stay with children during the internship. However, acquiring skills in these fields was challenging, and I didn't have any advantages, which prompted me to change my career plan...But during the epidemic, when I saw many companies closing down and people facing the risk of unemployment, I felt that it is stable to work as a teacher since our children always have to go to school no matter what happens.” P3 presented higher teaching willingness because of his curiosity for courses like piano and dance, as well as the happy time with kids at the very beginning. But as these courses got more difficult, P3 tended to show lower willingness because he believeed that this job no longer suited him. Nevertheless, the depression of many industries during the epidemic re-kindled his teaching willingness because of the stability of this profession. To sum up, there are five types of teaching willingness of pre-2000s PSTECEs. These types of teaching intentions are influenced by a variety of factors, including background dimension, organizational dimension, interpersonal dimension, and individual dimension. 3.4.2. Model construction of predictive factors of the teaching willingness of post-2000s PSTECEs Based on the theory of social ecology, this study focuses on teaching willingness and related factors, aiming to figure out the results through the grounded theory. On this basis, a related model is constructed in Fig. 2 . This model divides the predictive factors into background factors from the macro perspective, organizational and interpersonal factors from the Mesosystem perspective, and individual factors from the micro perspective. The first perspective acts on the second one and further influences the individual factors in a chain way. Finally, they affect the individual’s willingness to teach. The model for this topic is preliminarily constructed through qualitative research. The theoretical model not only explores the predictive factors of teaching willingness but also identifies the types of teaching intentions. However, whether the model mechanism is valid remains to be tested. Therefore, this study also adopts a quantitative research method to test its equation structure. 4 Quantitative Research 4.1. Quantitative Sample In this study, a cluster sampling method was adopted on PSTECEs from five colleges and universities in Jiangsu, Anhui, Jiangxi, and Shanghai. A total of 950 questionnaires were sent out ,and 890 were recovered, with a recovery rate of 93.7%. After checking on all the recovered questionnaires, 12 invalid questionnaires (short answering time or obvious regular answering) were deleted, which led to a final 878 valid questionnaires with an effective rate of 92.4%. The objects are of age from 19 to 22 years old, with an average age of M = 20.44 ± 1.408. There are 64 males and 814 females, among which freshmen to seniors account for 20.54%, 32.69%, 39.73%, and 7.04%, respectively. 4.2. Research method A questionnaire titled “The teaching willingness of post-2000s PSTECEs” was based on the theoretical structure model obtained by qualitative research in this study. The questionnaire consists of two parts:personal basic information, and teaching willingness. All items are scored with a five-point Likert scale, ranging from 1 for “completely disagree” to 5 for “completely agree”. There are six items in the first part, which aims to investigate the basic information of the research objects such as sex, age, grade, and the changing trend of teaching willingness. The second part is based on the three-level code obtained by the interview, referring to the FIT-Choice scale [ 25 ], a total of 55 items. This part is mainly composed of four dimensions, including individual dimension, interpersonal dimension, organizational dimension, and background dimension, with Cronbach’s α coefficients of 0.938, 0.830, 0.954, and 0.831, respectively. The individual dimension includes four sub-dimensions. They are self-efficacy (3 items, e.g., “I think I am suitable to be a preschool teacher”), internal motivation (4 items such as: “I want to find a job related to early childhood education”), external motivation (5 items, for example: “I like being a teacher because I have long holidays”), and achievement motivation (4 items, e.g., “ Working in an industry of early childhood education helps me to cultivate my children”). Specific subdimensions of Cronbach’s α are at 0.830–0.891. Specifically, it includes two sub-dimensions of the interpersonal dimension, involving family influence (3 items, for example: “My parents take being a preschool teacher as an enviable career”) and peer influence (3 items, such as: “My friends encourage me to be a preschool teacher”). The Cronbach’s α ranged from 0.797 to 0.806. For the organizational dimension, it includes undergraduate education (10 items, e.g., I am satisfied with the teaching in our school) and internship units (5 items, such as, The internship tutor helps me a lot to improve my teaching practice ability). Specific subdimensions of Cronbach’s α were 0.865–0.937. The background dimension includes job characteristics (7 items, such as: “The job as a preschool teacher offers me a stable income”), employment demand (2 items, such as: “I think there is little demand for new preschool teachers at present”), government policies (5 items, such as: “The current early childhood education related policies cannot encourage me to become an early childhood education teacher”, and the network media (The Internet allows me to reach resources related to early childhood education). For these four sub-dimensions, their Cronbach’s α ranges from 0.776 to 0.899. 4.3. Data analysis Firstly, SPSS29.0 was used to conduct a common method bias test, descriptive analysis, correlation analysis, and regression analysis on the data obtained from the questionnaire survey. Then, based on the theoretical model constructed by qualitative research, Amos24.0 was adopted to construct a structural equation model for the core variables to test the validity of the path associations. 4.4. Quantitative research results and model testing 4.4.1. Common method bias test The questionnaire in this study is measured anonymously, and some items are scored reversely, which tries to control the common method bias. All variables (61 items) in this study are tested with the Harman single-factor test and exploratory factor analysis. According to the results, there are 12 factors with eigenvalues greater than 1 in the unrotated condition. In addition, the variance explained by the first factor records 34.382%, which is below the critical value of 40% [ 26 ]. All these factors show no serious common method bias in this study. 4.4.2. Descriptive statistics and correlation analysis of each variable KMO and Bartlett’s sphericity test were used to analyze the validity of the obtained data. The obtained KMO value of 0.967 indicates a good correlation for the data matrix. Bartlett’s sphericity test results show that X 2 /df = 0.976, p < 0.001, reaching a significant level. Confirmatory factor analysis and statistical technology of the structural equation model were applied to fit and verify the model of predictive factors of the topic. According to the results, X 2 /df = 1.140, GFI = 0.927, AGFI = 0.918, SRMR = 0.027, RMSEA = 0.013, CFI = 0.992, IFI = 0.981, TLI = 0.992. All of the fit indexes of the model reach the standard, indicating a sound overall fit. The mean value, standard deviation, and correlation coefficient among variables in this study are shown in Table 4 below. There is a high level of correlation ( r = 0.633–0.732) for the four dimensions of teaching willingness. The teaching willingness shows a significant positive correlation (r = 0.222–0.850) with four dimensions and 12 factors, among which peer influence, undergraduate education, job characteristics, and government policies are the most influential factors (r = 0.340–0.625). However, it is negatively correlated with grade and age but insignificantly correlated with sex. Since grade and age are correlated with willingness, they are controlled in the follow-up study. Table 4 Mean value, standard deviation and correlation coefficient among variables. M SD 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 level of teaching willingness (1) 3.633 0.889 1 grade(2) 2.330 0.878 0.340 *** 1 age(3) 20.44 1.408 -0.194 *** 0.738 *** 1 sex(4) 1.930 0.260 0.029 -0.015 -0.063 * 1 self-efficiency(5) 3.612 0.926 0.417 *** -0.279 *** -0.187 *** 0.031 1 internal motivation(6) 3.611 0.870 0.469 *** -0.352 *** -0.25 1*** 0.055 0.351 *** 1 external motivation(7) 3.624 0.895 0.422 *** -0.330 *** -0.230 *** 0.034 0.325 *** 0.326 *** 1 achievement motivation(8) 3.660 0.882 0.457 *** -0.359 *** -0.232 *** 0.030 0.277 *** 0.384 *** 0.317 *** 1 individual dimension(9) 3.627 0.630 0.625 *** -0.467 *** -0.318 *** 0.053 0.701 *** 0.724 *** 0.698 *** 0.697 *** 1 family influence(10) 3.657 0.855 0.478 *** -0.346 *** -0.223 *** 0.080 ** 0.343 *** 0.437 *** 0.359 *** 0.411 *** 0.549 *** 1 Peer influence(11) 3.682 0.871 0.507 *** -0.393 *** -0.230 *** 0.023 0.416 *** 0.455 *** 0.392 *** 0.421 *** 0.597 *** 0.436 *** 1 interpersonal dimension(12) 3.669 0.731 0.581 *** -0.437 *** -0.267 *** 0.061 0.448 *** 0.527 *** 0.443 *** 0.491 *** 0.676 *** 0.844 *** 0.850 *** 1 undergraduate education(13) 3.661 0.831 0.504 *** -0.403 *** -0.244 *** 0.034 0.408 *** 0.427 *** 0.425 *** 0.395 *** 0.587 *** 0.437 *** 0.490 *** 0.548 *** 1 internship unit(14) 3.699 0.790 0.486 *** -0.337 *** -0.223 *** 0.027 0.362 *** 0.431 *** 0.378 *** 0.438 *** 0.570 *** 0.420 *** 0.489 *** 0.537 *** 0.468 *** 1 organizational dimension(15) 3.680 0.694 0.578 *** -0.433 *** -0.273 *** 0.036 0.450 *** 0.501 *** 0.469 *** 0.485 *** 0.675 *** 0.500 *** 0.571 *** 0.633 *** 0.865 *** 0.849 *** 1 job characteristics(16) 3.705 0.773 0.551 *** -0.420 *** -0.304 *** 0.026 0.407 *** 0.503 *** 0.412 *** 0.495 *** 0.643 *** 0.483 *** 0.528 *** 0.596 *** 0.525 *** 0.495 *** 0.596 *** 1 employment demand(17) 3.617 0.960 0.391 *** -0.315 *** -0.230 *** 0.053 0.222 *** 0.321 *** 0.268 *** 0.361 *** 0.414 *** 0.319 *** 0.363 *** 0.402 *** 0.346 *** 0.347 *** 0.404 *** 0.419 *** 1 government policies(18) 3.710 0.797 0.551 *** -0.413 *** -0.274 *** 0.022 0.385 *** 0.488 *** 0.432 *** 0.488 *** 0.634 *** 0.481 *** 0.523 *** 0.593 *** 0.518 *** 0.493 *** 0.590 *** 0.620 *** 0.433 *** 1 network media(19) 3.720 0.867 0.488 *** -0.375 *** -0.239 *** 0.057 * 0.416 *** 0.483 *** 0.401 *** 0.507 *** 0.640 *** 0.485 *** 0.525 *** 0.597 *** 0.523 *** 0.541 *** 0.621 *** 0.576 *** 0.393 *** 0.538 *** 1 background dimension(20) 3.688 0.667 0.623 *** -0.480 *** -0.330 *** 0.052 0.448 *** 0.564 *** 0.475 *** 0.583 *** 0.732 *** 0.556 *** 0.610 *** 0.688 *** 0.601 *** 0.591 *** 0.696 *** 0.813 *** 0.738 *** 0.808 *** 0.794 *** 1 * p < 0.1 ** p < 0.05 *** p < 0.01 4.4.3. Regression analysis of each variable Based on correlation analysis, this study started from four dimensions, namely, individual dimension, interpersonal dimension, organizational dimension, and background dimension. Then, it took 12 predictive factors as predictive variables and the level of teaching willingness as the dependent variable. Finally, a regression analysis was conducted, the results of which are shown in Table 5 . The analysis of variance results that F = 54.387, p < 0.001, indicating that at least one of the 12 predictive factors would have an impact on teaching willingness. The model R 2 of 0.486 implies that the 12 predictive factors can well explain 48.6% of the change in teaching willingness. Besides, the D-W value records 2.201, and VIF is less than 3.3, which indicates no multi-collinearity [ 27 ]. As can be seen from Table 5 , many factors play a role in predicting teaching willingness except for network media, grade, age, and sex. Other factors are self-efficacy at the individual dimension ( β = 0.092, P < 0.001), family influence at the interpersonal dimension ( β = 0.107, P < 0.001), undergraduate education at the organizational dimension ( β = 0.103, P < 0.01), as well as job characteristics and government policies ( β = 0.132, P < 0.001) at the background dimension ( β = 0.134, P < 0.01), exert greater influence on the teaching willingness of post-2000s PSTECEs. How these factors influence teaching willingness will be explained in the following part. Table 5 Regression coefficients among variables. Non-normalized coefficient Normalized coefficient t p Collinearity diagnosis β Standard error β VIF Tolerance constant -1.066 0.482 - -2.212 0.027 - - self-efficacy 0.092 0.028 0.096 3.336 < 0.001 1.389 0.720 internal motivation 0.090 0.032 0.088 2.845 0.005 1.608 0.622 external motivation 0.085 0.029 0.086 2.969 0.003 1.409 0.710 achievement motivation 0.091 0.031 0.091 2.936 0.003 1.600 0.625 family influence 0.107 0.032 0.103 3.324 < 0.001 1.598 0.626 peer influence 0.090 0.034 0.089 2.682 0.007 1.827 0.547 undergraduate education 0.103 0.035 0.097 2.952 0.003 1.801 0.555 internship unit 0.099 0.036 0.088 2.745 0.006 1.718 0.582 job characteristics 0.134 0.042 0.117 3.222 0.001 2.194 0.456 employment demand 0.070 0.026 0.075 2.639 0.008 1.362 0.734 government policies 0.132 0.040 0.119 3.336 < 0.001 2.123 0.471 network media -0.021 0.036 -0.020 -0.580 0.562 2.087 0.479 grade -0.016 0.041 -0.016 -0.403 0.687 2.726 0.367 age 0.041 0.023 0.065 1.776 0.076 2.256 0.443 gender -0.018 0.084 -0.005 -0.211 0.833 1.018 0.983 R 2  0.486 adjusted R 2  0.477 D-W value 2.021 F  54.387 *** Dependent variable: the level of teaching willingness *** p < 0.01 4.4.4. Testing of the structural equation model The path coefficients are shown in Fig. 3 . The study found that family influence, undergraduate education, job characteristics, government policies, and self-efficacy on teaching willingness have standardized path coefficients of 0.162, 0.163, 0.201, 0.214, and 0.130, respectively, all significant at the 0.1% level. This reveals that these factors have a direct and significant prediction on the teaching willingness of post-2000 PSTECEs. Moreover, family influence, undergraduate education, job characteristics, and government policies, their standardized path coefficients on self-efficacy record 0.114, 0.208, 0.171, and 0.117, respectively, with a significant situation at the level of 0.1%. This indicates that these factors have significant effects on self-efficacy. To explore the mediation effect of self-efficacy, 5000 samples were repeatedly selected with the Bias-Corrected Bootstrap method for the analysis of the effect values of each mediation path, which leads to 95% confidence intervals. The results are shown in Table 6 . 95% confidence intervals of all paths do not contain 0, indicating a significant mediation effect. Among them, The four indirect paths present significant results, with the mediation effect accounting for 10.9% of the total effect. Specifically, “family influence → self-efficacy → teaching willingness” mediation path is established , β = 0.015, P < 0.001, 95%CI=[0.006–0.033]; the number for “undergraduate education →self-efficacy→ teaching willingness” shows β = 0.029, P < 0.001, 95%CI=[0.014–0.052]; the one for “job characteristics → self-efficacy → teaching willingness” reaches β = 0.026, P < 0.001, 95%CI=[0.009–0.052]; while the one for “government policies → self-efficacy → teaching willingness” presents values of β = 0.029, P < 0.001, 95%CI = [0.014–0.051]. Table 6 Path coefficient analysis of the mediation model. Effect Paths β SE p LLCI ULCI Indirect effect process Family influence → Self-efficacy 0.114 0.038 0.000 0.052 0.187 Undergraduate education → Self-efficacy 0.208 0.041 0.000 0.135 0.292 Job characteristics → Self-efficacy 0.171 0.048 0.000 0.091 0.257 Government policies → Self-efficacy 0.117 0.047 0.001 0.042 0.199 Self-efficacy → Teaching willingness 0.130 0.028 0.000 0.062 0.203 Family influence → Self-efficacy → Teaching willingness 0.015 0.006 0.000 0.006 0.033 Undergraduate education → Self-efficacy → Teaching willingness 0.029 0.010 0.000 0.014 0.052 Job characteristics → Self-efficacy → Teaching willingness 0.026 0.011 0.000 0.009 0.052 Government policies → Self-efficacy →Teaching willingness 0.029 0.009 0.000 0.014 0.051 *** p < 0.01 5. Discussion This study combines both qualitative and quantitative research methods to explore the teaching willingness of PSTECEs, which were born in the 2000s. The qualitative research reveals the diversity of factors that predict teaching willingness and types of teaching willingness of PSTECEs. Drawing from grounded theory, a model was developed to depict these factors, thereby expanding upon the FIT-Choice model. Subsequently, a quantitative study was undertaken to validate the qualitative findings, revealing that self-efficacy, family influence, undergraduate education, job characteristics, and government policies are the most influential factors. Accordingly, a mediation model test was then conducted to further confirm the overall consistency between the quantitative research results and the qualitative research results. Employing multiple methods throughout this study ensures the reliability and robustness of the research conclusions. 5.1. Types of the teaching willingness of post-2000s PSTECEs In this study, 41 PSTECEs are interviewed and classified into five categories: positive-stable type, negative-maintaining type, continuous-enhancing type, continuous-declining type, and fluctuating type. Among them, there are few pre-service teachers of positive-stable type and negative-maintaining type, with 6 and 5 respectively, and more pre-service teachers of continuous-declining type and fluctuating type, with 12 and 15 respectively, and the least continuous-enhancing pre-service teachers. According to the prior study, the global recession and employment difficulties encourage more and more pre-service teachers to look for stable jobs, indicating the major of teacher education has a significant role in promoting the growth of their teaching willingness [ 28 ]. However, interviews with PSTECEs indicate that they do not seem to be attached to stable jobs because “personality development” is the primary factor that affects their willingness to teach. Moreover, it turns out that PSTECEs of the positive-stable type and negative-maintaining type have something in common, which is to measure their suitability as preschool teachers from aspects such as ideal educational motivation, appropriate teacher personality, and teaching ability [ 29 ]. For example, some believe, “I am not suitable to be a preschool teacher given my personality P (9/39)”. Besides, this study also expands the research results of the categories of this topic with one more type, namely the fluctuating type. According to the study, their teaching willingness does not always follow a linear way and presents a fluctuating situation. This study investigated the largest number of such PSTECEs( the fluctuating type)in the sample, more than one-third of the total sample. According to the interview, it can be seen that the post-2000s PSTECEs have the characteristics of pragmatism, innovation, freedom, flexibility, and a diverse personality. They will quickly understand and make judgments on various factors in the employment environment. Some negative factors in the work of preschool teachers, such as heavy work burden, difficulty for parents to get along with, and low salary will make the post-2000s PSTECEs refuse to pursue this job, although it is a decent and stable job in the outside world. On the contrary, in the environment of employment difficulties and economic downturn, some favorable factors in the work of preschool teachers are set off, such as having a winter vacation, which makes the post-2000s pre-service teachers more willing to teach. People’s development needs are subject to various factors, and one’s employment intention is not achieved overnight but in the process of dynamic change [ 30 ]. With the change in development environment and time, factors such as personal mental maturity, self-cognition, personal planning, and self-expectation are growing and changing, thus leading to fluctuating teaching willingness. 5.2. Predictive factors of the teaching willingness of post-2000s PSTECEs Based on grounded theory, this study constructed a theoretical model of the teaching willingness to predict factors of the post-2000s PSTECEs, including individual dimension, interpersonal dimension, organizational dimension and background dimension, and 29 predictive factors. The interpersonal dimension, organizational dimension, and background dimension influence the teaching willingness through the individual dimension. The results of this study confirm the validity of some previous studies. Previous studies take career affection, job accomplishment, teaching satisfaction, and peer recognition as the predictive factors [ 31 , 32 ], while believing that factors such as social status and salary are more emphasized by preschool teachers [ 33 ]. These studies focus on organizational factors at the individual dimension and interpersonal dimension, but this study expands the research to organizational and contextual factors. New predictive factors are added to this study, such as employment demand, government policies, network media, etc., which are some new considerations for these post-2000s pre-service teachers. It is believed that such a case is a result of the unique personality of post-2000s teachers and the rapid development of the external environment. These rational and pragmatic post-2000s PSTECEs are typical realists [ 34 ], who mention that “If there are jobs with higher wages, I will give up early childhood education.” The score of this question ( M = 3.93) well confirms this view. A 2019 survey on the treatment of teachers of preschool in 9 provinces in eastern, central, and western China reveals an average monthly take-home pay for teachers of 3,178.54 yuan ( $ 439.15, while those without tenure-track enjoy a lower proportion of social security [ 35 ]. Despite annually increased income, this is never the case with preschool teachers. From the perspective of the cost of living,PSTECE thinks that “Very little salary income is not enough to support my daily expenses. (P11).” At present, China still lags behind in the reform of the personnel management system of preschool teachers, which restricts the effective supplement of preschool teachers to a large extent [ 34 ]. Moreover, given the declining birth rate and worse population aging, many preschools have decreased their demand for recruits year after year [ 36 ]. Many preschools do not recruit new teachers or the number of new teachers being recruited is minimal, which leads to very few professional employment opportunities for PSTECEs, so the competition is very fierce. Meanwhile, the rapid development of network media offers new ideas for pre-service teachers’ employment. For example, the online shopping platform, media platform, online course platform, etc, all provide a new direction for pre-service teachers ’ entrepreneurship and employment. One of them says, “Now many students are in urgent demand of online courses, such as online Chinese teachers, which offer an appreciable salary (P17).” 5.3. Influence path of the teaching willingness of post-2000s PSTECEs Through quantitative analysis, this study also reveals the core role of self-efficacy, family influence, undergraduate education, job characteristics and government policies, and the mediation role of self-efficacy. Compared with previous studies with “education quality”, “local sentiments” and “public service motivation” as intermediary variables [ 37 , 38 ], this study broadens and complements relevant studies on the path of change of their teaching willingness. According to the self-efficacy theory proposed by Bandura, individuals’ self-efficacy is affected by some complicated factors, including social persuasion, alternative experience, their own experience of success or failure, and their own physiological and emotional factors [ 39 ]. This theory is consistent with the “mechanism model of predictive factors” in this study. In this study, parents or important family members generally persuade PSTECEs with language that “people with introverted (impatient) character are not suitable for preschool work (P23/P19)”, which reduces PSTECEs’ self-efficacy and thus affects their teaching willingness. Undergraduate PSTECEs undergo a critical period to experience their success or failure, and some frustrating experiences will negatively affect their self-efficacy and their teaching willingness. For example, some say that “In the second semester of freshman year, there were a lot of skills courses, which took me a lot of time but did not pay off. I think I am not suitable for this career (P31)”. In this study, pre-service teachers mainly understand job characteristics and government policies through substitute experience. The so-called substitute experience means that the greater the similarity between the individual and the replacement, the more convincing the success or failure experience of the replacement is to the individual [ 40 ]. “My cousin and I applied for the same major. She has worked for three or four years, during which she often suffered long overtime and high work intensity, and she also had to deal with the relationship with the leader. Not being a tactful person, I cannot do well in this position (P17)”. “PSTECEs of last grade mentioned that now the Education Bureau only requires a very small number of preschool teachers, which will be worse with the decline of the birth rate. Even with scholarships every year, a person as excellent as she failed the application, not to mention a person like me (P36)”. It can be seen from the interview that the success or failure experiences of important others with the same learning and life experiences have a significant impact on the self-efficacy of pre-service teachers, which further affects their teaching willingness. Mixed methods are applied in this study to examine the predictive factors and change paths of teaching willingness, while the consistency between the quantitative and the qualitative research results enhances the reliability of the research conclusions. 5.4. Research limitations and prospects Due to the limitation of research conditions, this study has shortcomings. Regarding the research samples, attention is mainly given to pre-service teachers in China. However, the generalization of the conclusions requires further exploration through the study of a larger and more diverse sample study. In terms of research approach, this cross-sectional study cannot verify the causal relationship among variables, which requires longitudinal studies or experimental manipulation methods to further verify the causal relationship among variables. Regarding research content, this study mainly investigated the teaching willingness of PSTECEs but failed to explore the changing trend of teaching willingness. Therefore, future studies may emphasize both the development and change trend of teaching willingness through a latent variable growth modeling. 5.5. Research implication This study focuses on exploring the types and predictive factors of teaching willingness of teachers born after the year 2000, which can be an empirical basis for future intervention and improvement of this topic. Theoretically, qualitative research is applied to discuss the theoretical model of predictive factors, which are more multi-faceted and diversified compared with previous studies. Additionally, starting from the unique educational and cultural background of China,this study expands the FIT-Choice theoretical model and combines the pragmatic, individualistic, and innovative characteristics of China's post-2000s with the literature-rich.Practically, different types of teaching willingness are identified, which helps to take targeted intervention for PSTECEs with low willingness. Moreover, some factors that play a core role in teaching willingness are identified, which supports the government and schools in formulating talent-related optimization policies. To establish a stable and high-quality team of preschool teachers, based on the findings of this study, we suggest that four factors (family, undergraduate education, job characteristics, and government policies) should be enhanced to improve the self-efficacy of PSTECEs. In terms of family education, parents should correctly understand the status and role of preschool education and help PSTECEs improve their understanding of their ability and character. As for undergraduate education and job characteristics, schools should guide PSTECEs to establish reasonable career expectations and improve their clear understanding of the salary and work content, thus avoiding their rebellious psychology due to the psychological gap. Regarding government policies, they should prioritize the universal and inclusive nature of preschool education, coupled with improved financial support mechanisms and personnel management systems, ensuring preschool teachers have adequate life security and job satisfaction. 5.6. Research conclusions This study expands the FIT-Choice theoretical model from the organizational and background dimensions. We found that (1) The teaching willingness of these teachers can be divided into five categories: positive-stable type, negative-maintaining type, continuous-enhancing type, continuous-declining type, and fluctuating type. (2) Based on the grounded theory, 12 predictive factors of 4 dimensions are identified, including individual, interpersonal, organizational, and background dimensions, and then a theoretical model is set up, namely, interpersonal, organizational, and background dimensions affect the teaching willingness through the individual dimension. (3) We combined the questionnaire survey to verify the qualitative research findings. Five variables (self-efficacy, family influence, undergraduate education, job characteristics, and government policies) are key predictors in predicting teaching willingness; external factors can also predict teaching willingness through self-efficacy. By identifying the core factors, some countermeasures and suggestions for future intervention and improvement are proposed. List of abbreviations Not applicable. Declarations Ethics approval and consent to participate This study was approved by the Institutional Review Board (IRB) of Changzhou Institute of Technology(Approval No. 2024CIT0302).The procedures employed in this study adhere to the principles of the Declaration of Helsinki and were conducted with the informed consent of all participants. Consent for publication Not applicable. Competing interests The authors declare that they have no competing interests. Funding This research received no external funding. Author Contribution Wenli Zhang analyzed the date and wrote the main manuscript text. Ran Wang, Lifan Hu, and Shuangqi Li collected the date.Wenwuyu Gao prepared all figures in the manuscript. All authors reviewed the manuscript. Acknowledgement We are thankful to the faculty and staff from Changzhou Institute of Technology, Shanghai Normal University Tianhua College, and Anhui Finance and Trade Vocational College for their guidance and support throughout this research. Data Availability The data are not publicly available due to ethical restrictions.Data are available from the corresponding author upon reasonable request. Data from ‘Changzhou Institute of Technology’ are available under license [No. 2024CIT0302]; contact ‘ [email protected] ’ for access. References Li J, Zhu M. Study on the influence mechanism of normal university students' teaching willingness from the perspective of field theory: on the investigation and analysis of two normal universities. Chinese Higher Education Research. 2024;2024:79-85. Jiang Y. A survey on the teaching willingness of students of primary education major in undergraduate colleges. Teacher Education Research. 2008:62-7. Zhang H, Lin Y, Cui S. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6349583","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":452307115,"identity":"c830f8a3-e8cc-4d9c-a6b9-8ce7de859bc0","order_by":0,"name":"Wenli 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College","correspondingAuthor":false,"prefix":"","firstName":"Ran","middleName":"","lastName":"Wang","suffix":""},{"id":452307117,"identity":"e06ff2d5-f5db-4799-a402-bad6543e2bd7","order_by":2,"name":"Lifan Hu","email":"","orcid":"","institution":"Anhui Finance And Trade Vocational College","correspondingAuthor":false,"prefix":"","firstName":"Lifan","middleName":"","lastName":"Hu","suffix":""},{"id":452307118,"identity":"04f0c3af-ab2e-49bb-87dc-2e3d6fa05bd7","order_by":3,"name":"Shuangqi Li","email":"","orcid":"","institution":"Shanghai Normal University Tianhua College","correspondingAuthor":false,"prefix":"","firstName":"Shuangqi","middleName":"","lastName":"Li","suffix":""},{"id":452307119,"identity":"2573e8ac-5b66-4284-b936-85cb03661869","order_by":4,"name":"Wenwuyu Gao","email":"","orcid":"","institution":"Changzhou Institute of Technology","correspondingAuthor":false,"prefix":"","firstName":"Wenwuyu","middleName":"","lastName":"Gao","suffix":""}],"badges":[],"createdAt":"2025-04-01 05:23:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6349583/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6349583/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":82324946,"identity":"55009a61-69f4-4fad-8ca0-bd47a990b0e1","added_by":"auto","created_at":"2025-05-09 06:06:05","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":154151,"visible":true,"origin":"","legend":"\u003cp\u003ePattern distribution of changes in the teaching willingness of post-2000s PSTECE\u003c/p\u003e","description":"","filename":"figure1.tif.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6349583/v1/d4405bdacae17572e2746e70.jpg"},{"id":82324938,"identity":"9171d738-06c2-457a-89cf-848b08ad02d2","added_by":"auto","created_at":"2025-05-09 06:06:05","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":165193,"visible":true,"origin":"","legend":"\u003cp\u003eModel and influence factors of the teaching willingness of post-2000s PSTECE\u003c/p\u003e","description":"","filename":"figure2.tif.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6349583/v1/63db5a618458a6c542c62930.jpg"},{"id":82324967,"identity":"ab447797-bb73-4411-90bb-f483709e19df","added_by":"auto","created_at":"2025-05-09 06:06:06","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":129036,"visible":true,"origin":"","legend":"\u003cp\u003eThe path of influence of each factor on teaching willingness\u003c/p\u003e","description":"","filename":"figure3.tif.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6349583/v1/f8c1eaf35d42cc1df40d1aac.jpg"},{"id":109060012,"identity":"de9bb0d4-fe25-46cc-8297-76ac542e0bc7","added_by":"auto","created_at":"2026-05-12 08:14:36","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1172857,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6349583/v1/ae8dddda-8a00-47a1-803b-86d28bb3d334.pdf"},{"id":82324947,"identity":"32f9b95d-1364-41ec-8d92-bf32b10da2ae","added_by":"auto","created_at":"2025-05-09 06:06:05","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":52060,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterialinterviewoutlinequestionnaire.docx","url":"https://assets-eu.researchsquare.com/files/rs-6349583/v1/cd24b65f22629c382f58586d.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Predictive Factors and Model Construction of the Teaching Willingness of Post-2000s Pre-service Teachers Majoring in Early Childhood Education--A Mixed Method Study","fulltext":[{"header":"1. Background","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003ePre-service teachers' teaching willingness holds significant importance for their future career choice and professional growth [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], since it is the driving force for them to transit from ordinary people to professionals [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. In other words, pre-service teachers\u0026rsquo; teaching willingness directly affects whether they will engage in the teaching profession in the future and whether they can remain in positions as excellent teachers. Teaching willingness refers to an individual's inner attitude towards engaging in a teaching profession. It is a dominant and comprehensive manifestation of their professional cognition or identity [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. According to the Ecosystem theory, individual development is dynamically changed under the influence of the ecosystem, and so is the teaching willingness of pre-service teachers [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Previous studies on teaching willingness were carried out from a constant perspective while ignoring the variability of predictive factors [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Thus, these studies started from a static perspective, overlooking the variability of predictive factors.Therefore, this study adopts a dynamic perspective aimed at revealing the predictive factors and categories of the teaching willingness of pre-service teachers, which can explain the performance of pre-service teachers' teaching willingness, and then provide a reference for educational guidance.\u003c/p\u003e \u003cp\u003eMost research is based on existing questionnaires [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], which only roughly help understand teaching willingness through already-known predictive factors. For example, some scholars have explored the predictive factors using the FIT-Choice theoretical model [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. However, whether there are still unknown factors affecting pre-service teachers' teaching willingness has not been well explored. This study is based on the FIT-Choice theoretical model, and it diversified and openly explores the predictive factors affecting the teaching willingness of post-2000s pre-service teachers. Five predictive factors for \u0026ldquo;choose teacher career\u0026rdquo; are concluded in this model, like social experience, teaching motivation, career cognition, and career choice satisfaction [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. In the context of Chinese culture, some scholars have discussed the teaching willingness of pre-service teachers from the perspectives of individual internal factors and external factors, and the research shows that the former includes professional identity [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], individual interest [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], individual ability and altruism [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], the latter contains occupational treatment [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], teacher education quality and significant others.\u003c/p\u003e \u003cp\u003ePrevious studies mainly focused on subject teachers, such as those in sex education curricula [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], inclusive curricula[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], educational philosophy curricula [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], and pre-service teachers in primary school [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], but little on those majoring in early childhood education programs. It is well-known that early childhood education is an important part of China's basic education and public service system. High-quality and stable teachers are the core elements of the high-quality development of early childhood education. Therefore, a high-quality early childhood education system in the new era will be the new direction and challenge for China's early childhood education in the current and future years [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. According to the latest education statistics released by the Ministry of Education of China, 220,000 pre-service teachers will finish their education in 2022, and the number is expected to increase to about 240,000 in 2023 [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Despite that, the Basic Situation of National Education Development in 2023 released by the Development Planning Department manifests that it records a decrease of 49,300 in terms of the number of full-time teachers in preschools compared with the previous year [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], which is a reflection of a problem in the development of our preschool teachers. Thus, it is necessary to explore the predictive factors and types of the teaching willingness of pre-service teachers majoring in early childhood education (Abbreviation, PSTECE) in China, to promote the professional growth of preschool teachers [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAlthough previous studies have explored pre-service teachers' teaching willingness from different perspectives, there are still some shortcomings. First, the former studies were carried out using only a single method. Only a small amount of them were combined with qualitative studies to supplement and explain quantitative studies. However, direct use of existing questionnaires suffers from time lag and may not authentically and comprehensively reveal the true predictive factors. Therefore, exploratory research should be conducted before qualitative research. Second, previous studies have paid insufficient attention to whether factors affecting pre-service teachers' willingness to teach differ across generations. Empirical evidence has shown a discrepancy in the employment intention between the post-2000s and that of the post-1980s and post-1990s. Therefore, the study on the teaching willingness of the post-2000s and related predictive factors is conducive to figuring out their employment psychology. Third, most of the previous research is characterized by single content. They were concerned with those significant factors predicting pre-service teachers' willingness to teach through quantitative research but failed to effectively reveal the types of pre-service teachers' willingness and the action path of core factors. Therefore, this study attempts to take PSTECE as the research object. By adopting a mixed method research model, starting with qualitative methods followed by quantitative methods, this study intends to validate the theoretical model of relevant predictive factors from multiple perspectives, thereby enhancing the reliability of conclusions.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e"},{"header":"2. Methods","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThis study adopts a mixed-method research to explore the teaching willingness of post-2000s PSTECEs. Considering the particularity of the research background and the characteristics of post-2000s pre-service teachers, this study begins with qualitative research using semi-structured interviews to explore the type of teaching willingness and the predictive factors of teaching willingness and build a theoretical model. To confirm whether the qualitative results can be generalized to large-scale samples, a quantitative study is used to verify the theoretical model of the predictive factors.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e"},{"header":"3. Qualitative Research","content":"\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Qualitative sample\u003c/h2\u003e \u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eAn objective sampling method was adopted in this study. Forty-one pre-service teachers, from freshmen to seniors, were selected as qualitative research objects, including thirty-four females and seven males. They were all voluntary participants and could withdraw at any time during the interview. They were signed into an agreement by the research team before the formal interview began. The interview was conducted from November 2023 to January 2024, with a single interview lasting 30\u0026ndash;60 minutes. The specific information is shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eInformation of interviewees.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInterviewee\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGrade\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eInterviewee\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eGrade\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003efemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eJunior\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003efemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eJunior\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003efemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSenior\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003emale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eJunior\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003efemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSenior\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003emale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSenior\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003efemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSenior\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003efemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eJunior\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003efemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eJunior\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003efemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eJunior\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003efemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eJunior\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003efemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eJunior\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSenior\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003efemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSophomore\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003efemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eJunior\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003emale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSophomore\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSenior\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003efemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSophomore\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003efemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSenior\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003efemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSophomore\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003efemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eJunior\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003efemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFreshman\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003efemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eJunior\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003emale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFreshman\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003efemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSenior\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003efemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFreshman\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eJunior\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003efemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFreshman\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003efemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eJunior\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003efemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFreshman\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003efemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eJunior\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003efemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFreshman\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003efemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eJunior\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003efemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFreshman\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003efemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eJunior\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003efemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFreshman\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003efemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSenior\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003efemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFreshman\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eJunior\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003efemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFreshman\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003efemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFreshman\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Qualitative data collection\u003c/h2\u003e \u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eAn interview outline was drawn up after reviewing some relevant domestic and international research results on factors affecting pre-service teachers\u0026rsquo; teaching willingness and after repeated deliberation by members of the research team and experts. On this basis, it was decided that this study would focus on two aspects, namely \u0026ldquo;the willingness to teach kids of preschool\u0026rdquo; and \u0026ldquo;the main reasons and predictive factors for the decision\u0026rdquo;. Questions include \u0026ldquo;Do you have the willingness to teach kids of preschool at present?\u0026rdquo;, \u0026ldquo;What is the reason for your unwillingness?, \u0026ldquo;What are the main difficulties at present?\u0026rdquo;, \u0026ldquo;Do you have other career intentions?\u0026rdquo;...\u003c/p\u003e\u003cp\u003eFor more reliable qualitative data, three pre-service teachers of different grades were randomly selected for pre-interview before the formal one, which led to the correction of problems that were difficult to understand. In formal interviews, interviewers flexibly adjust questions according to interviewees to ensure the abundance and breadth of qualitative materials. In this study, the interviews were recorded with an audio recording after obtaining the informed consent of the interviewees, and then the recordings were converted into text. For those ambiguous points, the interviewees were immediately contacted for a brief supplementary interview. Finally, a total of 41 interview texts, totaling 138,000 words, were obtained.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Qualitative data analysis\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eBased on grounded theory, this study transcoded 138,000 texts collected from semi-structured interviews, and the Chinese version of Nvivo 12.0 was used to encode the interview texts at three levels. It finally led to a theoretical framework on the teaching willingness of PSTECEs and its predictive factors.\u003c/p\u003e \u003cp\u003eA coding team with four researchers (including two university lecturers and two senior preschool teachers) collectively coded the three interview records after labeling 41 interview texts as P1-P41 in the order of interview to clarify the coding requirements. Second, the interview texts were analyzed word by word and sentence by sentence independently, and the ambiguous and inconsistent parts were discussed in two centralized meetings every week to ensure the reliability of the qualitative analysis. In this study, we obtained an internal consistency of 89.8%. After all the work had been finished, 1/3 of the interview data wsa then randomly selected according to the theory saturation principle to test the theoretical model after the three-level coding. Besides, additional interviews with randomly selected five pre-service teachers showed no concepts and factors outside the current scope. Therefore, it can be concluded that the content structure of the predictive factors is theoretically saturated.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e3.3.1. Open coding\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eAfter preliminary analysis of a large number of texts, the researchers labeled the sentences related to teaching willingness, which initially generated several related concepts. To ensure their relevance and universality, the team eliminated concepts that appear only once or are not closely related to the topic. By combining similar concepts, 30 representative open encodings finally came into being, some of which are shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eExamples of open coding.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRaw material\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOne-level coding\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI especially like preschool children, and it is wonderful to stay with them. I have always dreamed of being a teacher since childhood, because this sacred job can help children to grow up. (P9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003elike children, love to teach, help children grow up\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI took a lot of skills classes in my freshman year, which were difficult. I believe I am not suited to this kind of class; The internship is also tiring... We were not allowed to drink colored drinks in the preschool, and the principal was very strict and I was a little afraid. (P19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ecurriculum arrangement, internship intensity, institute system, leadership style\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI am willing to be a teacher of early childhood education if there is an authorized strength. However, it is too competitive to fight for an authorized strength. Besides, teachers are lowly paid for hard work. Thus, I don\u0026rsquo;t want to be a teacher anymore. (P15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003equota for authorized strength, competitive intensity, job salary, job intensity,\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e3.3.2. Axial coding\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eAxial coding aims to integrate preliminary concepts into more organized information, providing a structured perspective for in-depth analysis of this topic. Through systematic organization and correlation of the concepts generated from open coding, a total of 12 categories were extracted, which are self-efficacy, internal motivation, external motivation, achievement motivation, family influence, peer influence, undergraduate education, internship preschool, job characteristics, employment demand, government policies, and network media (see Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003e3.3.3. Selective coding\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eSelective coding helps to deeply understand the structural dimension and interaction of predictive factors of this topic. Selective coding takes roots in socio-ecological theory, a theory that focuses on the interrelationship between the environment and human behavior [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Based on the main axial coding, this study summarized the policy, network media, employment demand, and other main axis coding into the background dimension, which was finally refined to four selective coding dimensions: the individual dimension, the interpersonal dimension, the organizational dimension, and the background dimension. Then, a coding table of factors affecting the teaching willingness of these pre-service teachers was created, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCoding of predictive factors on teaching willingness of PSTECEs.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSelective coding\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAxial coding\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOpen coding\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eA1Individual dimension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB1 self-efficacy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eC1 suitable personality; C2 excellent teaching ability\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB2 Intern motivation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eC3 love children; C4 love to be a teacher\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB3 External motivation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eC5 career stability; C6 career fringe benefits\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB4 Achievement motivation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eC7 help children grow up; C8 contribute to society\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eA2Interpersonal dimension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB5 Family influence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eC9 parent support; C10 relative recognition\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB6 Peer influence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eC11 indirect influence from the experience of friends; C12 direct influence from the words and deeds of classmates\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eA3Organizational dimension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB7 Undergraduate education experience\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eC13 curriculum arrangement; C14 teacher education; C15 theory and practice\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB8 internship preschool\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eC16 internship work experience; C17 internship unit system; C18 internship tutor guidance; C19 internship unit atmosphere\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eA4Background dimension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB9 Job characteristics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eC20 job salary; C21 promotion space; C22 work intensity; C23 social recognition\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB10 Employment demand\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eC24 new recruitment demand; C25 competition intensity\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB11 Government policy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eC26 quota for authorized strength; C27 performance policy\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB12 Network media\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eC28 rich information; C29 public opinion influence\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.4. Research on the type of teaching willingness and the construction of the theoretical model\u003c/h2\u003e \u003cdiv id=\"Sec11\" class=\"Section3\"\u003e \u003ch2\u003e3.4.1. Types of the teaching willingness of post-2000s PSTECEs\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eBased on the overall analysis of the interview texts, this study concludes five types of teaching willingness of post-2000s PSTECEs, that is: positive-stable type, negative-maintaining type, continuous-enhancing type, continuous-declining type, and fluctuating type. The first four types are consistent with the results of relevant studies [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], while the last one is a new type found in this study. On this basis, a distribution diagram of these change patterns is synthesized in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e(1) Positive - stable type: consistent and firm in teaching\u003c/p\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe positive - stable type refers to those who are willing to engage in early childhood education before entering or in the early stages of university. During theoretical learning and practical training, these pre-service teachers consistently maintain a positive attitude and high level of teaching willingness. Besides, they have a deep passion for and are willing to pursue early childhood education. Among the 41 PSTECEs interviewed, four PSTECEs belong to this type, with interest being a key factor that was mentioned. Their love for children and identity as teachers play a crucial role in their choice of college major and employment directions. They developed an early sense of identification with teaching from a young age. Their passion and love encourage them to form the initial career plan. Two interviewed PSTECEs were introduced in the interview:\u003c/p\u003e \u003cp\u003e \u003cem\u003eI particularly like children, so I volunteered to choose this major at the very beginning. I have already planned to work in a preschool. And from freshman to senior, I have always been willing to engage in early childhood education\u003c/em\u003e...\u003c/p\u003e \u003cp\u003eSince I was a child, I have shown great adoration for the profession of teacher, so I applied for this major. I personally like this profession, and I think it is a sacred job. Moreover, I like children, so I also like to be a teacher.\u003c/p\u003e \u003cp\u003e(2) Negative-maintaining type: out of force and refusing to teach students\u003c/p\u003e \u003cp\u003eThis type refers to Early Childhood Education not being their first choice. They are forced to choose this major due to various reasons such as \u0026ldquo;parents\u0026rsquo; recommendation\u0026rdquo;, \u0026ldquo;insufficient scores\u0026rdquo; and \u0026ldquo;major selection restriction\u0026rdquo;. Although these PSTECEs have experienced systematic teaching education, they have never changed their teaching unwillingness, and some of them even admit that they will never work as a teacher in the future. Such a statement is not surprising, as individuals with a positive occupational identity and high self-efficacy are more likely to pursue their profession [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. P1 and P9 depicted how they chose this major because they had no other options:\u003c/p\u003e \u003cp\u003eI was adjusted to this major after the college entrance examination...but I have little patience...At the beginning (of enrollment), I have not considered being a preschool teacher...\u003c/p\u003e \u003cp\u003e \u003cem\u003e\u0026ldquo;After the college entrance examination, I applied for this major because my mother recommended this stable job to me. She said that it would be easy to find a job after graduation if I chose this major. But given the declining birth rate, things might change for me. In the future, I do not plan to engage in early childhood education.\u0026rdquo;...\u003c/em\u003e \u003c/p\u003e \u003cp\u003e(3) Continuous-enhancing type: a higher sense of willingness with each passing day\u003c/p\u003e \u003cp\u003eThis type of PSTECEs sees enhancement in their interest in this major after constantly updating their cognition and concepts through theoretical learning, skill training, and practical exercise in college. Their teaching willingness grows from weak or nonexistent to strong. According to the field theory, pre-service teachers will establish professional identity in the academic field and practice field of pre-service teaching, which helps reshape their teaching willingness [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. P22 and P26 are representatives of this type:\u003c/p\u003e \u003cp\u003e \u003cem\u003eI was kind of\u003c/em\u003e willing \u003cem\u003eto teach in preschools from the beginning of the freshman year, but I truly fell in love with the major since I began to acquire related knowledge, including piano, dance, etc. I don\u0026rsquo;t want to give up the major that I have studied for so many years. Instead, I would like to gain something... Other industries don\u0026rsquo;t seem to fit me so well.\u003c/em\u003e\u003c/p\u003e \u003cp\u003e \u003cem\u003eAt first, I wasn\u0026rsquo;t interested in it, but later on, I found some interest. When I was doing my internship in preschool, I saw many cute children, so I\u003c/em\u003e gradually \u003cem\u003efell in love with this major... By the time I graduate, I will have received seven years of early childhood education (5\u0026thinsp;+\u0026thinsp;2 mode, namely five years of vocational college and then two years of undergraduate education after a successful promotion). If I give up, I just waste these seven years.\u003c/em\u003e\u003c/p\u003e \u003cp\u003e(4) Continuous-declining type: continuous impact and low willingness\u003c/p\u003e \u003cp\u003eThis type means that post-2000s PSTECEs suffer from many things like difficult employment, low wages, and heavy work burdens, so their already low willingness is on a continuous decline, even disappearing due to the updated and reorganized cognition. They feel anxious when there is a cognitive conflict. To this end, they try to find a new solution to the cognitive conflict [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. P19 and P23 depicted the story of their cognitive transformation:\u003c/p\u003e \u003cp\u003eEverything went well in the freshman year. But everything changed after I interned in preschool. It is horrible that the interpersonal environment and working environment in the preschool are not very good. The most critical fact is that what kids learn at preschool is different from what we learn at university(educational methods, educational ideas)... Teachers are exhausted from working in preschool, and I am, too. I have no confidence in this profession.\u003c/p\u003e \u003cp\u003eAt the beginning of my freshman year, I wished to engage in this field in the future, and I also have related experience. However, things get worse for this industry. With fewer and fewer job choices, I now want to undertake further education in Physical Education.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e\u003cp\u003e(5) Fluctuating type: erratic and gloomy willingness\u003c/p\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThis type of post-2000s PSTECEs is easily subject to many factors along with changes in the ecological environment, such as peer group, internship experience, learning achievement, etc., which lead to uncertain determination to engage in this career. Field-dependent cognitive style and field-independent cognitive style are well known to us [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], PSTECE with fluctuating willingness belong to the field-dependent type, and their teaching willingness is easily affected by the external changeable environment. P16 and P3 described why their teaching intentions were volatile:\u003c/p\u003e \u003cp\u003eI still wanted to be a preschool teacher in my freshman year, but I changed my mind when I found the low salary... Preschool teachers live a miserable life because of great conflicts with the leaders. The leaders assign tasks such as environment creation, but without enough materials provided and with too much time...Occasionally, I feel satisfied since it is a time with kids, and there are also winter and summer vacations.Things will be better if the pay is higher.\u003c/p\u003e \u003cp\u003eWhen P16 first entered \u003cem\u003ethe\u003c/em\u003e college, he laid a basic foundation for this major, and we can see his higher teaching willingness. However, things have changed since his sophomore year when he learned about the lives of teachers in this industry during his internship. Back to school, P16 occasionally experienced increased teaching willingness because of some \u0026ldquo;professional benefits\u0026rdquo; such as winter and summer vacations and the time with children. The main factors for P16 are salary and work intensity. P3 shared the same experience but with different predictive factors:\u003c/p\u003e \u003cp\u003e \u003cem\u003e\u0026ldquo;In my first year in college, I also wanted to become a preschool teacher. At that time, I felt piano and dance were interesting, and it was wonderful to stay with children during the internship. However, acquiring skills in these fields was challenging, and I didn't have any advantages, which prompted me to change my career plan...But during the epidemic, when I saw many companies closing down and people facing the risk of unemployment, I felt that it is stable to work as a teacher since our children always have to go to school no matter what happens.\u0026rdquo;\u003c/em\u003e \u003c/p\u003e \u003cp\u003eP3 presented higher \u003cem\u003eteaching\u003c/em\u003e willingness because of his curiosity for courses like piano and dance, as well as the happy time with kids at the very beginning. But as these courses got more difficult, P3 tended to show lower willingness because he believeed that this job no longer suited him. Nevertheless, the depression of many industries during the epidemic re-kindled his teaching willingness because of the stability of this profession.\u003c/p\u003e \u003cp\u003eTo sum up, there are five types of teaching willingness of pre-2000s PSTECEs. These types of teaching intentions are influenced by a variety of factors, including background dimension, organizational dimension, interpersonal dimension, and individual dimension.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e \u003ch2\u003e3.4.2. Model construction of predictive factors of the teaching willingness of post-2000s PSTECEs\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eBased on the theory of social ecology, this study focuses on teaching willingness and related factors, aiming to figure out the results through the grounded theory. On this basis, a related model is constructed in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e2\u003c/span\u003e. This model divides the predictive factors into background factors from the macro perspective, organizational and interpersonal factors from the Mesosystem perspective, and individual factors from the micro perspective. The first perspective acts on the second one and further influences the individual factors in a chain way. Finally, they affect the individual\u0026rsquo;s willingness to teach.\u003c/p\u003e \u003cp\u003eThe model for this topic is preliminarily constructed through qualitative research. The theoretical model not only explores the predictive factors of teaching willingness but also identifies the types of teaching intentions. However, whether the model mechanism is valid remains to be tested. Therefore, this study also adopts a quantitative research method to test its equation structure.\u003c/p\u003e \u003c/div\u003e"},{"header":"4 Quantitative Research","content":"\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e4.1. Quantitative Sample\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eIn this study, a cluster sampling method was adopted on PSTECEs from five colleges and universities in Jiangsu, Anhui, Jiangxi, and Shanghai. A total of 950 questionnaires were sent out ,and 890 were recovered, with a recovery rate of 93.7%. After checking on all the recovered questionnaires, 12 invalid questionnaires (short answering time or obvious regular answering) were deleted, which led to a final 878 valid questionnaires with an effective rate of 92.4%. The objects are of age from 19 to 22 years old, with an average age of M\u0026thinsp;=\u0026thinsp;20.44\u0026thinsp;\u0026plusmn;\u0026thinsp;1.408. There are 64 males and 814 females, among which freshmen to seniors account for 20.54%, 32.69%, 39.73%, and 7.04%, respectively.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e4.2. Research method\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eA questionnaire titled \u0026ldquo;The teaching willingness of post-2000s PSTECEs\u0026rdquo; was based on the theoretical structure model obtained by qualitative research in this study. The questionnaire consists of two parts:personal basic information, and teaching willingness. All items are scored with a five-point Likert scale, ranging from 1 for \u0026ldquo;completely disagree\u0026rdquo; to 5 for \u0026ldquo;completely agree\u0026rdquo;. There are six items in the first part, which aims to investigate the basic information of the research objects such as sex, age, grade, and the changing trend of teaching willingness. The second part is based on the three-level code obtained by the interview, referring to the FIT-Choice scale [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], a total of 55 items. This part is mainly composed of four dimensions, including individual dimension, interpersonal dimension, organizational dimension, and background dimension, with Cronbach\u0026rsquo;s α coefficients of 0.938, 0.830, 0.954, and 0.831, respectively.\u003c/p\u003e \u003cp\u003eThe individual dimension includes four sub-dimensions. They are self-efficacy (3 items, e.g., \u0026ldquo;I think I am suitable to be a preschool teacher\u0026rdquo;), internal motivation (4 items such as: \u0026ldquo;I want to find a job related to early childhood education\u0026rdquo;), external motivation (5 items, for example: \u0026ldquo;I like being a teacher because I have long holidays\u0026rdquo;), and achievement motivation (4 items, e.g., \u0026ldquo; Working in an industry of early childhood education helps me to cultivate my children\u0026rdquo;). Specific subdimensions of Cronbach\u0026rsquo;s α are at 0.830\u0026ndash;0.891. Specifically, it includes two sub-dimensions of the interpersonal dimension, involving family influence (3 items, for example: \u0026ldquo;My parents take being a preschool teacher as an enviable career\u0026rdquo;) and peer influence (3 items, such as: \u0026ldquo;My friends encourage me to be a preschool teacher\u0026rdquo;). The Cronbach\u0026rsquo;s α ranged from 0.797 to 0.806.\u003c/p\u003e \u003cp\u003eFor the organizational dimension, it includes undergraduate education (10 items, e.g., I am satisfied with the teaching in our school) and internship units (5 items, such as, The internship tutor helps me a lot to improve my teaching practice ability). Specific subdimensions of Cronbach\u0026rsquo;s α were 0.865\u0026ndash;0.937.\u003c/p\u003e \u003cp\u003eThe background dimension includes job characteristics (7 items, such as: \u0026ldquo;The job as a preschool teacher offers me a stable income\u0026rdquo;), employment demand (2 items, such as: \u0026ldquo;I think there is little demand for new preschool teachers at present\u0026rdquo;), government policies (5 items, such as: \u0026ldquo;The current early childhood education related policies cannot encourage me to become an early childhood education teacher\u0026rdquo;, and the network media (The Internet allows me to reach resources related to early childhood education). For these four sub-dimensions, their Cronbach\u0026rsquo;s α ranges from 0.776 to 0.899.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e4.3. Data analysis\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eFirstly, SPSS29.0 was used to conduct a common method bias test, descriptive analysis, correlation analysis, and regression analysis on the data obtained from the questionnaire survey. Then, based on the theoretical model constructed by qualitative research, Amos24.0 was adopted to construct a structural equation model for the core variables to test the validity of the path associations.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e4.4. Quantitative research results and model testing\u003c/h2\u003e \u003cdiv id=\"Sec18\" class=\"Section3\"\u003e \u003ch2\u003e4.4.1. Common method bias test\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe questionnaire in this study is measured anonymously, and some items are scored reversely, which tries to control the common method bias. All variables (61 items) in this study are tested with the Harman single-factor test and exploratory factor analysis. According to the results, there are 12 factors with eigenvalues greater than 1 in the unrotated condition. In addition, the variance explained by the first factor records 34.382%, which is below the critical value of 40% [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. All these factors show no serious common method bias in this study.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section3\"\u003e \u003ch2\u003e4.4.2. Descriptive statistics and correlation analysis of each variable\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eKMO and Bartlett\u0026rsquo;s sphericity test were used to analyze the validity of the obtained data. The obtained KMO value of 0.967 indicates a good correlation for the data matrix. Bartlett\u0026rsquo;s sphericity test results show that \u003cem\u003eX\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e/df\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.976, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, reaching a significant level. Confirmatory factor analysis and statistical technology of the structural equation model were applied to fit and verify the model of predictive factors of the topic. According to the results, \u003cem\u003eX\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e/df\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.140, GFI\u0026thinsp;=\u0026thinsp;0.927, AGFI\u0026thinsp;=\u0026thinsp;0.918, SRMR\u0026thinsp;=\u0026thinsp;0.027, RMSEA\u0026thinsp;=\u0026thinsp;0.013, CFI\u0026thinsp;=\u0026thinsp;0.992, IFI\u0026thinsp;=\u0026thinsp;0.981, TLI\u0026thinsp;=\u0026thinsp;0.992. All of the fit indexes of the model reach the standard, indicating a sound overall fit.\u003c/p\u003e \u003cp\u003eThe mean value, standard deviation, and correlation coefficient among variables in this study are shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e below. There is a high level of correlation (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.633\u0026ndash;0.732) for the four dimensions of teaching willingness. The teaching willingness shows a significant positive correlation (r\u0026thinsp;=\u0026thinsp;0.222\u0026ndash;0.850) with four dimensions and 12 factors, among which peer influence, undergraduate education, job characteristics, and government policies are the most influential factors (r\u0026thinsp;=\u0026thinsp;0.340\u0026ndash;0.625). However, it is negatively correlated with grade and age but insignificantly correlated with sex. Since grade and age are correlated with willingness, they are controlled in the follow-up study.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMean value, standard deviation and correlation coefficient among variables.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"23\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c16\" colnum=\"16\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c17\" colnum=\"17\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c18\" colnum=\"18\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c19\" colnum=\"19\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c20\" colnum=\"20\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c21\" colnum=\"21\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c22\" colnum=\"22\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c23\" colnum=\"23\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c14\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c15\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c16\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c17\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c18\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c19\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c20\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c21\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c22\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c23\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003elevel of teaching willingness (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.633\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.889\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003egrade(2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.330\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.878\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.340\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eage(3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.408\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.194\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.738\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003esex(4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.930\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.260\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.029\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.063\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eself-efficiency(5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.612\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.926\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.417\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.279\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.187\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003einternal motivation(6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.611\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.870\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.469\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.352\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.25\u003csup\u003e1***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.055\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.351\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eexternal motivation(7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.624\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.895\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.422\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.330\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.230\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.034\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.325\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.326\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eachievement motivation(8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.660\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.882\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.457\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.359\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.232\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.277\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.384\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.317\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eindividual dimension(9)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.627\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.630\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.625\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.467\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.318\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.053\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.701\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.724\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.698\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.697\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003efamily influence(10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.657\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.855\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.478\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.346\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.223\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.080\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.343\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.437\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.359\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.411\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.549\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePeer influence(11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.682\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.871\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.507\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.393\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.230\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.416\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.455\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.392\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.421\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.597\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.436\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003einterpersonal dimension(12)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.669\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.731\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.581\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.437\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.267\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.061\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.448\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.527\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.443\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.491\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.676\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.844\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.850\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eundergraduate education(13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.661\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.831\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.504\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.403\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.244\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.034\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.408\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.427\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.425\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.395\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.587\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.437\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.490\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.548\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003einternship unit(14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.699\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.790\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.486\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.337\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.223\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.027\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.362\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.431\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.378\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.438\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.570\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.420\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.489\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.537\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.468\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eorganizational dimension(15)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.680\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.694\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.578\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.433\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.273\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.450\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.501\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.469\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.485\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.675\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.500\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.571\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.633\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.865\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0.849\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ejob characteristics(16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.705\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.773\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.551\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.420\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.304\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.407\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.503\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.412\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.495\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.643\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.483\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.528\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.596\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.525\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0.495\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e0.596\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eemployment demand(17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.617\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.391\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.315\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.230\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.053\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.222\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.321\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.268\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.361\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.414\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.319\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.363\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.402\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.346\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0.347\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e0.404\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e0.419\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003egovernment policies(18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.710\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.797\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.551\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.413\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.274\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.385\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.488\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.432\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.488\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.634\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.481\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.523\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.593\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.518\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0.493\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e0.590\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e0.620\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e0.433\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003enetwork media(19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.720\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.867\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.488\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.375\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.239\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.057\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.416\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.483\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.401\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.507\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.640\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.485\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.525\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.597\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.523\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0.541\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e0.621\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e0.576\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e0.393\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e0.538\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ebackground dimension(20)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.688\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.667\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.623\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.480\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.330\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.052\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.448\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.564\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.475\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.583\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.732\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.556\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.610\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.688\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.601\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0.591\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e0.696\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e0.813\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e0.738\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e0.808\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e0.794\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c23\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"23\"\u003e* \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.1 ** \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 *** \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section3\"\u003e \u003ch2\u003e4.4.3. Regression analysis of each variable\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eBased on correlation analysis, this study started from four dimensions, namely, individual dimension, interpersonal dimension, organizational dimension, and background dimension. Then, it took 12 predictive factors as predictive variables and the level of teaching willingness as the dependent variable. Finally, a regression analysis was conducted, the results of which are shown in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. The analysis of variance results that F\u0026thinsp;=\u0026thinsp;54.387, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, indicating that at least one of the 12 predictive factors would have an impact on teaching willingness. The model R\u003csup\u003e2\u003c/sup\u003e of 0.486 implies that the 12 predictive factors can well explain 48.6% of the change in teaching willingness. Besides, the D-W value records 2.201, and VIF is less than 3.3, which indicates no multi-collinearity [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. As can be seen from Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, many factors play a role in predicting teaching willingness except for network media, grade, age, and sex. Other factors are self-efficacy at the individual dimension (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.092, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), family influence at the interpersonal dimension (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.107, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), undergraduate education at the organizational dimension (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.103, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), as well as job characteristics and government policies (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.132, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) at the background dimension (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.134, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), exert greater influence on the teaching willingness of post-2000s PSTECEs. How these factors influence teaching willingness will be explained in the following part.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRegression coefficients among variables.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eNon-normalized coefficient\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNormalized coefficient\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eCollinearity diagnosis\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eβ\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStandard error\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eβ\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eVIF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eTolerance\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003econstant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-1.066\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.482\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-2.212\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.027\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eself-efficacy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.092\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.028\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.096\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.336\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.389\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.720\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003einternal motivation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.090\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.088\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.845\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.608\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.622\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eexternal motivation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.085\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.029\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.086\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.969\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.409\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.710\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eachievement motivation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.091\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.091\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.936\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.625\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003efamily influence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.107\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.324\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.598\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.626\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epeer influence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.090\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.034\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.089\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.682\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.827\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.547\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eundergraduate education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.035\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.097\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.952\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.801\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.555\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003einternship unit\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.099\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.088\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.745\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.718\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.582\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ejob characteristics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.042\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.117\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.222\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.194\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.456\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eemployment demand\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.070\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.075\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.639\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.362\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.734\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003egovernment policies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.132\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.040\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.119\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.336\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.123\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.471\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003enetwork media\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.580\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.562\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.087\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.479\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003egrade\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.403\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.687\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.726\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.367\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.065\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.776\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.076\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.256\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.443\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003egender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.084\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.211\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.833\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.983\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eR\u003c/em\u003e\u0026nbsp;\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c8\" namest=\"c2\"\u003e \u003cp\u003e0.486\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eadjusted \u003cem\u003eR\u003c/em\u003e\u0026nbsp;\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c8\" namest=\"c2\"\u003e \u003cp\u003e0.477\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD-W value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c8\" namest=\"c2\"\u003e \u003cp\u003e2.021\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eF\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c8\" namest=\"c2\"\u003e \u003cp\u003e54.387\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003eDependent variable: the level of teaching willingness\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003e\u003csup\u003e***\u003c/sup\u003e \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section3\"\u003e \u003ch2\u003e4.4.4. Testing of the structural equation model\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe path coefficients are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e3\u003c/span\u003e. The study found that family influence, undergraduate education, job characteristics, government policies, and self-efficacy on teaching willingness have standardized path coefficients of 0.162, 0.163, 0.201, 0.214, and 0.130, respectively, all significant at the 0.1% level. This reveals that these factors have a direct and significant prediction on the teaching willingness of post-2000 PSTECEs. Moreover, family influence, undergraduate education, job characteristics, and government policies, their standardized path coefficients on self-efficacy record 0.114, 0.208, 0.171, and 0.117, respectively, with a significant situation at the level of 0.1%. This indicates that these factors have significant effects on self-efficacy.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eTo explore the mediation effect of self-efficacy, 5000 samples were repeatedly selected with the Bias-Corrected Bootstrap method for the analysis of the effect values of each mediation path, which leads to 95% confidence intervals. The results are shown in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e. 95% confidence intervals of all paths do not contain 0, indicating a significant mediation effect. Among them, The four indirect paths present significant results, with the mediation effect accounting for 10.9% of the total effect. Specifically, \u0026ldquo;family influence \u0026rarr; self-efficacy \u0026rarr; teaching willingness\u0026rdquo; mediation path is established ,\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.015, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, 95%CI=[0.006\u0026ndash;0.033]; the number for \u0026ldquo;undergraduate education \u0026rarr;self-efficacy\u0026rarr; teaching willingness\u0026rdquo; shows \u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.029, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, 95%CI=[0.014\u0026ndash;0.052]; the one for \u0026ldquo;job characteristics \u0026rarr; self-efficacy \u0026rarr; teaching willingness\u0026rdquo; reaches \u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.026, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, 95%CI=[0.009\u0026ndash;0.052]; while the one for \u0026ldquo;government policies \u0026rarr; self-efficacy \u0026rarr; teaching willingness\u0026rdquo; presents values of \u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.029, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, 95%CI = [0.014\u0026ndash;0.051].\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePath coefficient analysis of the mediation model.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEffect\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePaths\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eβ\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eSE\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLLCI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eULCI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"7\" rowspan=\"8\"\u003e \u003cp\u003eIndirect effect process\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFamily influence \u0026rarr; Self-efficacy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.052\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.187\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUndergraduate education \u0026rarr; Self-efficacy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.208\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.292\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJob characteristics \u0026rarr; Self-efficacy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.171\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.048\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.091\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.257\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGovernment policies \u0026rarr; Self-efficacy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.117\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.042\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.199\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSelf-efficacy \u0026rarr; Teaching willingness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.130\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.028\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.062\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.203\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFamily influence \u0026rarr; Self-efficacy \u0026rarr; Teaching willingness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.033\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUndergraduate education \u0026rarr; Self-efficacy \u0026rarr; Teaching willingness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.029\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.052\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJob characteristics \u0026rarr; Self-efficacy \u0026rarr; Teaching willingness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.052\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGovernment policies \u0026rarr; Self-efficacy \u0026rarr;Teaching willingness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.029\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.051\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003csup\u003e***\u003c/sup\u003e \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"5. Discussion","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThis study combines both qualitative and quantitative research methods to explore the teaching willingness of PSTECEs, which were born in the 2000s. The qualitative research reveals the diversity of factors that predict teaching willingness and types of teaching willingness of PSTECEs. Drawing from grounded theory, a model was developed to depict these factors, thereby expanding upon the FIT-Choice model. Subsequently, a quantitative study was undertaken to validate the qualitative findings, revealing that self-efficacy, family influence, undergraduate education, job characteristics, and government policies are the most influential factors. Accordingly, a mediation model test was then conducted to further confirm the overall consistency between the quantitative research results and the qualitative research results. Employing multiple methods throughout this study ensures the reliability and robustness of the research conclusions.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section2\"\u003e \u003ch2\u003e5.1. Types of the teaching willingness of post-2000s PSTECEs\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eIn this study, 41 PSTECEs are interviewed and classified into five categories: positive-stable type, negative-maintaining type, continuous-enhancing type, continuous-declining type, and fluctuating type. Among them, there are few pre-service teachers of positive-stable type and negative-maintaining type, with 6 and 5 respectively, and more pre-service teachers of continuous-declining type and fluctuating type, with 12 and 15 respectively, and the least continuous-enhancing pre-service teachers. According to the prior study, the global recession and employment difficulties encourage more and more pre-service teachers to look for stable jobs, indicating the major of teacher education has a significant role in promoting the growth of their teaching willingness [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. However, interviews with PSTECEs indicate that they do not seem to be attached to stable jobs because \u0026ldquo;personality development\u0026rdquo; is the primary factor that affects their willingness to teach. Moreover, it turns out that PSTECEs of the positive-stable type and negative-maintaining type have something in common, which is to measure their suitability as preschool teachers from aspects such as ideal educational motivation, appropriate teacher personality, and teaching ability [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. For example, some believe, \u0026ldquo;I am not suitable to be a preschool teacher given my personality P (9/39)\u0026rdquo;.\u003c/p\u003e \u003cp\u003eBesides, this study also expands the research results of the categories of this topic with one more type, namely the fluctuating type. According to the study, their teaching willingness does not always follow a linear way and presents a fluctuating situation. This study investigated the largest number of such PSTECEs( the fluctuating type)in the sample, more than one-third of the total sample. According to the interview, it can be seen that the post-2000s PSTECEs have the characteristics of pragmatism, innovation, freedom, flexibility, and a diverse personality. They will quickly understand and make judgments on various factors in the employment environment. Some negative factors in the work of preschool teachers, such as heavy work burden, difficulty for parents to get along with, and low salary will make the post-2000s PSTECEs refuse to pursue this job, although it is a decent and stable job in the outside world. On the contrary, in the environment of employment difficulties and economic downturn, some favorable factors in the work of preschool teachers are set off, such as having a winter vacation, which makes the post-2000s pre-service teachers more willing to teach. People\u0026rsquo;s development needs are subject to various factors, and one\u0026rsquo;s employment intention is not achieved overnight but in the process of dynamic change [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. With the change in development environment and time, factors such as personal mental maturity, self-cognition, personal planning, and self-expectation are growing and changing, thus leading to fluctuating teaching willingness.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003e5.2. Predictive factors of the teaching willingness of post-2000s PSTECEs\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eBased on grounded theory, this study constructed a theoretical model of the teaching willingness to predict factors of the post-2000s PSTECEs, including individual dimension, interpersonal dimension, organizational dimension and background dimension, and 29 predictive factors. The interpersonal dimension, organizational dimension, and background dimension influence the teaching willingness through the individual dimension. The results of this study confirm the validity of some previous studies. Previous studies take career affection, job accomplishment, teaching satisfaction, and peer recognition as the predictive factors [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], while believing that factors such as social status and salary are more emphasized by preschool teachers [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. These studies focus on organizational factors at the individual dimension and interpersonal dimension, but this study expands the research to organizational and contextual factors.\u003c/p\u003e \u003cp\u003eNew predictive factors are added to this study, such as employment demand, government policies, network media, etc., which are some new considerations for these post-2000s pre-service teachers. It is believed that such a case is a result of the unique personality of post-2000s teachers and the rapid development of the external environment. These rational and pragmatic post-2000s PSTECEs are typical realists [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e], who mention that \u0026ldquo;If there are jobs with higher wages, I will give up early childhood education.\u0026rdquo; The score of this question (\u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3.93) well confirms this view. A 2019 survey on the treatment of teachers of preschool in 9 provinces in eastern, central, and western China reveals an average monthly take-home pay for teachers of 3,178.54 yuan (\u003cspan\u003e$\u003c/span\u003e439.15, while those without tenure-track enjoy a lower proportion of social security [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Despite annually increased income, this is never the case with preschool teachers. From the perspective of the cost of living,PSTECE thinks that \u0026ldquo;Very little salary income is not enough to support my daily expenses. (P11).\u0026rdquo; At present, China still lags behind in the reform of the personnel management system of preschool teachers, which restricts the effective supplement of preschool teachers to a large extent [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Moreover, given the declining birth rate and worse population aging, many preschools have decreased their demand for recruits year after year [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Many preschools do not recruit new teachers or the number of new teachers being recruited is minimal, which leads to very few professional employment opportunities for PSTECEs, so the competition is very fierce. Meanwhile, the rapid development of network media offers new ideas for pre-service teachers\u0026rsquo; employment. For example, the online shopping platform, media platform, online course platform, etc, all provide a new direction for pre-service teachers \u0026rsquo; entrepreneurship and employment. One of them says, \u0026ldquo;Now many students are in urgent demand of online courses, such as online Chinese teachers, which offer an appreciable salary (P17).\u0026rdquo;\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec25\" class=\"Section2\"\u003e \u003ch2\u003e5.3. Influence path of the teaching willingness of post-2000s PSTECEs\u003c/h2\u003e \u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThrough quantitative analysis, this study also reveals the core role of self-efficacy, family influence, undergraduate education, job characteristics and government policies, and the mediation role of self-efficacy. Compared with previous studies with \u0026ldquo;education quality\u0026rdquo;, \u0026ldquo;local sentiments\u0026rdquo; and \u0026ldquo;public service motivation\u0026rdquo; as intermediary variables [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e], this study broadens and complements relevant studies on the path of change of their teaching willingness. According to the self-efficacy theory proposed by Bandura, individuals\u0026rsquo; self-efficacy is affected by some complicated factors, including social persuasion, alternative experience, their own experience of success or failure, and their own physiological and emotional factors [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. This theory is consistent with the \u0026ldquo;mechanism model of predictive factors\u0026rdquo; in this study. In this study, parents or important family members generally persuade PSTECEs with language that \u0026ldquo;people with introverted (impatient) character are not suitable for preschool work (P23/P19)\u0026rdquo;, which reduces PSTECEs\u0026rsquo; self-efficacy and thus affects their teaching willingness. Undergraduate PSTECEs undergo a critical period to experience their success or failure, and some frustrating experiences will negatively affect their self-efficacy and their teaching willingness. For example, some say that \u0026ldquo;In the second semester of freshman year, there were a lot of skills courses, which took me a lot of time but did not pay off. I think I am not suitable for this career (P31)\u0026rdquo;. In this study, pre-service teachers mainly understand job characteristics and government policies through substitute experience. The so-called substitute experience means that the greater the similarity between the individual and the replacement, the more convincing the success or failure experience of the replacement is to the individual [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. \u0026ldquo;My cousin and I applied for the same major. She has worked for three or four years, during which she often suffered long overtime and high work intensity, and she also had to deal with the relationship with the leader. Not being a tactful person, I cannot do well in this position (P17)\u0026rdquo;. \u0026ldquo;PSTECEs of last grade mentioned that now the Education Bureau only requires a very small number of preschool teachers, which will be worse with the decline of the birth rate. Even with scholarships every year, a person as excellent as she failed the application, not to mention a person like me (P36)\u0026rdquo;. It can be seen from the interview that the success or failure experiences of important others with the same learning and life experiences have a significant impact on the self-efficacy of pre-service teachers, which further affects their teaching willingness.\u003c/p\u003e\u003cp\u003eMixed methods are applied in this study to examine the predictive factors and change paths of teaching willingness, while the consistency between the quantitative and the qualitative research results enhances the reliability of the research conclusions.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section2\"\u003e \u003ch2\u003e5.4. Research limitations and prospects\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eDue to the limitation of research conditions, this study has shortcomings. Regarding the research samples, attention is mainly given to pre-service teachers in China. However, the generalization of the conclusions requires further exploration through the study of a larger and more diverse sample study. In terms of research approach, this cross-sectional study cannot verify the causal relationship among variables, which requires longitudinal studies or experimental manipulation methods to further verify the causal relationship among variables. Regarding research content, this study mainly investigated the teaching willingness of PSTECEs but failed to explore the changing trend of teaching willingness. Therefore, future studies may emphasize both the development and change trend of teaching willingness through a latent variable growth modeling.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec27\" class=\"Section2\"\u003e \u003ch2\u003e5.5. Research implication\u003c/h2\u003e \u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThis study focuses on exploring the types and predictive factors of teaching willingness of teachers born after the year 2000, which can be an empirical basis for future intervention and improvement of this topic. Theoretically, qualitative research is applied to discuss the theoretical model of predictive factors, which are more multi-faceted and diversified compared with previous studies. Additionally, starting from the unique educational and cultural background of China,this study expands the FIT-Choice theoretical model and combines the pragmatic, individualistic, and innovative characteristics of China's post-2000s with the literature-rich.Practically, different types of teaching willingness are identified, which helps to take targeted intervention for PSTECEs with low willingness. Moreover, some factors that play a core role in teaching willingness are identified, which supports the government and schools in formulating talent-related optimization policies.\u003c/p\u003e\u003cp\u003eTo establish a stable and high-quality team of preschool teachers, based on the findings of this study, we suggest that four factors (family, undergraduate education, job characteristics, and government policies) should be enhanced to improve the self-efficacy of PSTECEs. In terms of family education, parents should correctly understand the status and role of preschool education and help PSTECEs improve their understanding of their ability and character. As for undergraduate education and job characteristics, schools should guide PSTECEs to establish reasonable career expectations and improve their clear understanding of the salary and work content, thus avoiding their rebellious psychology due to the psychological gap. Regarding government policies, they should prioritize the universal and inclusive nature of preschool education, coupled with improved financial support mechanisms and personnel management systems, ensuring preschool teachers have adequate life security and job satisfaction.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec28\" class=\"Section2\"\u003e \u003ch2\u003e5.6. Research conclusions\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThis study expands the FIT-Choice theoretical model from the organizational and background dimensions. We found that (1) The teaching willingness of these teachers can be divided into five categories: positive-stable type, negative-maintaining type, continuous-enhancing type, continuous-declining type, and fluctuating type. (2) Based on the grounded theory, 12 predictive factors of 4 dimensions are identified, including individual, interpersonal, organizational, and background dimensions, and then a theoretical model is set up, namely, interpersonal, organizational, and background dimensions affect the teaching willingness through the individual dimension. (3) We combined the questionnaire survey to verify the qualitative research findings. Five variables (self-efficacy, family influence, undergraduate education, job characteristics, and government policies) are key predictors in predicting teaching willingness; external factors can also predict teaching willingness through self-efficacy. By identifying the core factors, some countermeasures and suggestions for future intervention and improvement are proposed.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"List of abbreviations","content":"\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e \u003cp\u003eThis study was approved by the Institutional Review Board (IRB) of Changzhou Institute of Technology(Approval No. 2024CIT0302).The procedures employed in this study adhere to the principles of the Declaration of Helsinki and were conducted with the informed consent of all participants.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis research received no external funding.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eWenli Zhang analyzed the date and wrote the main manuscript text. Ran Wang, Lifan Hu, and Shuangqi Li collected the date.Wenwuyu Gao prepared all figures in the manuscript. All authors reviewed the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe are thankful to the faculty and staff from Changzhou Institute of Technology, Shanghai Normal University Tianhua College, and Anhui Finance and Trade Vocational College for their guidance and support throughout this research.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data are not publicly available due to ethical restrictions.Data are available from the corresponding author upon reasonable request. Data from \u0026lsquo;Changzhou Institute of Technology\u0026rsquo; are available under license [No. 2024CIT0302]; contact \u0026lsquo;[email protected]\u0026rsquo; for access.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eLi J, Zhu M. 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A study on normal and non-normal students\u0026rsquo; teaching willingness: a case study of N Normal University. \u003cem\u003eMaster\u0026rsquo;s thesis. \u003c/em\u003eNanjing: Nanjing Normal University. 2020.\u003c/li\u003e\n\u003cli\u003eMpotos N, Vekeman E, Monsieurs K, Derese A, Valcke M. Knowledge and willingness to teach cardiopulmonary resuscitation: a survey amongst 4273 teachers. Resuscitation. 2013;84:496-500.\u003c/li\u003e\n\u003cli\u003eKılın\u0026ccedil; A, Watt HM, Richardson PW. Factors influencing teaching choice in Turkey. Asia-Pacific Journal of Teacher Education. 2012;40:199-226.\u003c/li\u003e\n\u003cli\u003eK\u0026ouml;nig J, Rothland M. Motivations for choosing teaching as a career: Effects on general pedagogical knowledge during initial teacher education. Asia-Pacific journal of teacher education. 2012;40:289-315.\u003c/li\u003e\n\u003cli\u003eYu R. Investigation on value orientation and teaching choice intention of normal college students. 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The mechanism of dynamic change of non-public normal university students\u0026rsquo; teaching willingness: An empirical study based on planned behavior theory. Hunan: Hunan Normal University. 2021.\u003c/li\u003e\n\u003cli\u003eGeorge SV, Richardson PW, Watt HM. Early career teachers\u0026rsquo; self-efficacy: A longitudinal study from Australia. Australian Journal of Education. 2018;62:217-33.\u003c/li\u003e\n\u003cli\u003eBourdieu P. The field of cultural production. Cambridge:Polity. 1993:35-46.\u003c/li\u003e\n\u003cli\u003eLi Q, Zhao J, Liu W. \u0026quot;Stay at a respectful distance\u0026rdquo; : career identity and teaching choice of public funded normal students in preschool education from the perspective of Field Theory. Science of Education. 2022.\u003c/li\u003e\n\u003cli\u003eLee G, Kwon J, Park SS, Kim JW, Kwon HG, Park HK. Development of an instrument for measuring cognitive conflict in secondary‐level science classes. 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A study on teachers\u0026rsquo; education quality recognition and its influence on their teaching willingness. Song H., Wang H., and Zhang Q. 2018;17:48-54.\u003c/li\u003e\n\u003cli\u003eLiu J, Fang X. Rural teaching willingness and policy improvement of post-2000s normal college students. Contemporary Youth Research. 2021:45-51.\u003c/li\u003e\n\u003cli\u003eLi Y. Teaching willingness of rural kindergarten teachers and its influence factors. Preschool Education Research. 2018:36-48.\u003c/li\u003e\n\u003cli\u003eYu Y. Employment mentality and career development strategies of post-2000s college students. People\u0026rsquo;s Forum. 2023:75-8.\u003c/li\u003e\n\u003cli\u003ePang L, Wang H. Policy thinking on innovating and improving the establishment and personnel system of preschool teachers in China under the new situation. Journal of Beijing Normal University (Social Science Edition). 2023:62-9.\u003c/li\u003e\n\u003cli\u003eQiao X. The past, present and future of population aging in China. Social Policy Research. 2024:47-63+133.\u003c/li\u003e\n\u003cli\u003eYan J, Chen C. A study on the influence factors and the relationship between the teaching willingness of state-funded normal physical education students: An empirical analysis based on structural equation model. Journal of Guangzhou University of Physical Education. 2022:26-34.\u003c/li\u003e\n\u003cli\u003ePang C, Tang Z. The influence of public service motivation on normal university students\u0026rsquo; willingness to teach in rural areas. Exploration of Higher Education. 2023:46-52.\u003c/li\u003e\n\u003cli\u003eBandura A. Self-efficacy mechanism in human agency. American psychologist. 1982;37:122.\u003c/li\u003e\n\u003cli\u003eJiang Y, Ye M. Research on influence factors of general self-efficacy of higher vocational college students. Chinese Adult Education. 2009:101-2.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"post-2000s pre-service teachers, early childhood education, teaching willingness, mixed study","lastPublishedDoi":"10.21203/rs.3.rs-6349583/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6349583/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eCareer prospects exert a great impact on the teaching willingness of pre-service teachers. In this context, their career development must explore teaching willingness and its related predictive factors. This exploration is also beneficial for building a stable and high-quality team of teachers.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eGiven the Chinese cultural background and the characteristics of post-2000s pre-service teachers, this study adopts a mixed method to investigate the teaching willingness of 878 post-2000s pre-service teachers majoring in early childhood education in eastern China.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe results found that (1) there are five types of teaching willingness among pre-service teachers: positive-stable type, negative-maintaining type, continuous-enhancing type, continuous-declining type, and fluctuating type. (2) Based on the Grounded Theory, this study identifies 12 predictive factors from four dimensions: individual, interpersonal, organizational, and background. Building upon these factors, we established a theoretical model wherein the interpersonal, organizational, and background dimensions predict teachers\u0026rsquo; teaching willingness through the individual dimension. (3) Quantitative study is applied based on large-scale questionnaires, which shows that five key factors, including self-efficacy, family influence, undergraduate education, job characteristics, and government policies, play a core role in the teaching willingness of pre-service teachers majoring in early childhood education, while self-efficacy is a mediation variable for the other four factors.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eAccordingly, it is suggested to improve the teaching willingness of pre-service teachers majoring in early childhood education by enhancing their self-efficacy from four aspects, namely family influence, undergraduate education, job characteristics, and government policies.\u003c/p\u003e","manuscriptTitle":"The Predictive Factors and Model Construction of the Teaching Willingness of Post-2000s Pre-service Teachers Majoring in Early Childhood Education--A Mixed Method Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-09 06:05:59","doi":"10.21203/rs.3.rs-6349583/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"8b061793-313f-44d9-98df-e54790d4503d","owner":[],"postedDate":"May 9th, 2025","published":true,"recentEditorialEvents":[{"type":"decision","content":"Rejected","date":"2026-05-12T08:02:37+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-11T02:23:01+00:00","index":96,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-05-12T08:13:39+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-09 06:05:59","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6349583","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6349583","identity":"rs-6349583","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}