Path Analysis of Psychological Capital Affecting Teachers' Innovative Behavior Based on Structural Equation

Based on the hypothesis test of the theoretical model of teachers' innovative work behavior, this paper conducts multi-group analysis with psychological capital as the adjustment variable. The results show that the professional values, professional recognition and teaching ability of low psychological capital teachers have greater influence on innovative work behaviors; the influence of high and low psychological capital on teachers' innovative work behavior is mainly reflected in the effect of professional values on professional identity. In addition, the development of psychological capital and the establishment of the professional values of setting high moral values and cultivate person, which will help the construction of Chinese teacher human resources. 1. Literature review In 1996, Amabile first proposed the behavior of individual innovation work, which is considered as the process of individual's successful transformation of creative ideas into behaviors. Since then, many researchers have carried out a lot of research on the behavior of innovative work, but there are big differences in the definition of teachers' innovative work behavior. The concept of innovative work behavior applied in this paper is the expansion and extension of the organizational field in the field of education. There are many researches on innovative work behaviors in the organizational field. Zhou and George proposed that individual innovation work behaviors include not only innovative ideas but also the promotion, development and implementation of innovative ideas. Liu Yun and Shi Jintao believe that innovative work behavior is a process in which individuals generate, introduce and apply beneficial, novel ideas or things in related work activities. It can be seen that innovative work behavior can be understood as a series of behaviors in which individuals generate novel ideas or schemes in their work, solve practical problems at work and achieve positive effects, including the generation, development and implementation of innovative ideas and so on. 2. Data collection and reliability and validity test 2.1 Data collection and screening The research data mainly comes from the network research of teachers' system. According to the regional and economic development level, the teachers of primary and secondary schools and kindergartens in three prefecture-level cities in western China, central and eastern China are selected to research their professional values, professional recognition, psychological capital, teaching ability and innovative work behavior and other aspects. The measurement of psychological capital uses the PCQ-24 scale. The sample data was 235,660 copies and the valid data was 156,062 copies. (According to the lie test title score > 3, the social appeal topic score > 5, the answer time < 1 second, determine the invalid questionnaire). 2.2 Reliability and validity test Using SPSS21.0 software, the reliability and validity of the 11 observed variables and 2 latent variables were tested. The results are shown in Table 1. 2018 International Conference on Education, Psychology, and Management Science (ICEPMS 2018) Copyright © (2018) Francis Academic Press, UK DOI: 10.25236/icepms.2018. 125 --571-Table 1. Reliability and validity analysis results P value KMO value Cronbach’s Alpha Professional values 0.000 0.842 0.855 Professional recognition 0.000 0.664 0.670 Teaching ability 0.000 0.500 0.899 3. Test of theoretical models 3.1 Model fit and matching degree According to the model hypothesis and the effective sample, there are three groups of ten observation variables in the study, which correspond to the three latent variables of professional values, professional recognition and teaching ability, and the innovative work behavior is the external manifestation of these three internal factors. In this paper, AMOS21.0 software is used as the analysis tool to fit the structural equations of the hypothesis model. The results show that the estimated parameters are good and are significant at p<0.001 level (Table 1). The chi-square value fit is not suitable due to the large number of samples[16]. Rong Taisheng and Hou Jietai considered the model fitting and matching degree test. In addition to the chi-square value, SRMR has more reference value than RMR (SRMR<0.05). In this study, SRMR, RMSEA, GFI, RFI, etc. all met the good matching degree results, and the overall good fit between the model and the data was good (see Table 2). Figure 1. Theoretical model fitting results Table 2. Summary of overall model fit test results Statistics Adapted standard or threshold Test result data Matching degree judgment GFI >0.9 0.959 Yes AGFI >0.9 0.934 Yes RMR <0.05 0.026 Yes SRMR <0.05 0.0431 Yes RMSEA <0.08 0.075 Yes NFI >0.9 0.951 Yes CFI >0.9 0.951 Yes IFI >0.9 0.951 Yes PNFI >0.5 0.709 Yes PCFI >0.5 0.709 Yes