Does Academic Commitment Affect the Learners' Progress through Academic Buoyancy? A Structural Equation Model

academ-Abstract : This study aims to test the pre-hypothesized model of the connection between these variables together. The research method was a correlational and structural equation modeling type. The statistical population consisted of all female pre-university students in Bandar Abbas in the educational year of 1396-1977 (1633 students) and the sampling method was multi - phase. The sample size was 600 people. Data collection tools were Hosseinchari and Dehghanizadeh Educational Well-being Questionnaire (391), and Human-Vogel & Rabe Academic Commitment (2015), and an announced high school final exam score. 562 questionnaires were included in the study. Spearman correlation test and factor analysis in AMOS software were used for analysis. Results of a simple correlation between variables indicated a significant relationship between academic commitment and academic achievement (r = 0.097, P≤0.05), academic achievement and investment dimension (R = 0.129, P≤ 0.01), academic satisfaction and academic achievement dimension (R = 0.098, P≤0.05), and academic commitment to academic achievement level (R = 0.147, P≤0.01). There was also a significant relationship between the dimension of commitment replacement and educational achievement (R = 0.132, P≤0.01). The analysis of standard and non-standard coefficients showed that except for the relationship between the dimensions of commitment and the overall score of commitment that was expected, other ways were not significant. Despite the results above, the model fit indices (RMSEA, CFI, GFI, AGFI, NFI, IFI, IFI, TLI,) were favorable and indicated the average model fit to the data. This study examined the assumptions of using AMOS software to check the hypotheses of the study. Normal ity was one of the assumptions of using structural equation modeling. Multivariate outliers were also checked (C.R = 2.49). According to the results in this study, there was no multicollinearity and the test of normality