درخت حوزه‌های تخصصی

Purpose: The aim of this study was to investigate the role of individual and collective components on the formation of social trust in high school students. Methodology: The present study in terms of applied purpose and in terms of performance, it was mixed (qualitative and quantitative). The research population in the qualitative section was experts, experts and specialists in the field of education and training and in the quantitative section were the principals and deputies of the second secondary school in Tehran in the academic year 2019-20, whose number was 380. The research sample in the qualitative section according to the principle of theoretical saturation were 15 people who were selected by purposive sampling method and in the quantitative section according to Cochran’s formula were 190 people who were selected by multi-stage cluster sampling method. To collect data, review of research texts and literature, semi-structured interview and researcher-made questionnaire (110 items) were used. The validity of the interview was confirmed by a review of 10 faculty members and its reliability was calculated by the subject internal agreement coefficient of 0.86. It was obtained from 0.70. Data were analyzed in SPSS and AMOS software by content analysis, factor analysis and structural equation modeling. Findings: Findings showed that in the formation of social trust, two components, individual and collective, played a role. Determination, self-control and collective component had nine dimensions of social commitment, social participation, social support, social respect, and social discipline, loyalty to values, behavioral validity, social development and friendly relations. Conclusion: The results showed that individual and collective components played an effective role in the formation of social trust in high school students

Purpose: The purpose of this study was to present a comprehensive model of empowerment in the Social Security Organization. Methodology: This research was based on the applied purpose and in terms of quantitative and qualitative research method (mixed) and in terms of data collection was descriptive-survey. The statistical population of the study consisted of two groups of experts and thinkers. The first group consisted of university professors whose field of study and field of study was related to the field of research and the second group included organizational experts with a master's degree or higher with managerial and experimental backgrounds related to human resources in the qualitative section after counting the criteria and indicators extracted. From the theoretical foundations, a researcher-made questionnaire based on the Looshe and Likert spectrum was prepared and after passing the Delphi survey, a conceptual model was extracted. Then, in the quantitative part, exploratory factor analysis method was used to identify the model factors and confirmatory factor analysis method was used to fit the model. In order to check the validity of the questions, purposive sampling method was used among organizational and academic experts, of which 15 people were included as a statistical sample. In the second and third stages of validity of the questions, to strengthen the screening process, the snowball method was used to compile the sample, which after saturating the data of 32 final experts for the exploration section and building a conceptual model participated. Statistical analysis was performed using SPSS software to cluster the indicators and create research components and Smart PLS software to confirm the research model. Findings: The results of this study identified 11 components and 37 indicators as the most important factors of comprehensive empowerment and showed that individuals will be empowered individually when intra-individual intelligence, creativity-oriented education, psychological self-knowledge, internal performance, knowledge-based decision making and individual self-efficacy. Together, they will be empowered in the collective, team, and organizational spheres when the culture of bureaucracy, internal reward, fundamental self-efficacy, and interactive policy come together. Conclusion: After exploratory factor analysis and component classification, the fit of the model obtained from the previous step was investigated and confirmed with a good fit.

Purpose: This study uses TAM theory to better understand variables that are indicative of MOOCs’ courses’ completion rates; furthermore, this paper scrutinizes the quantitative relationship between MOOC platform usage and learning satisfaction. Methodology: This was an applied research in a virtual community called Coursera where people all over the world participate. The research design was quantitative and the questionnaire link was posted on the Coursera, with convenience sampling. Data collection process started from November 12, 2020 until February 23, 2021, and 234 users of the selected MOOC platform (Coursera) participated to evaluate the proposed model. A multivariable systematic technique (PLS) was applied to analyze the model. To conduct the reliability test, individual item loadings and internal consistency were consulted. Convergent validity of the model was measured via the Structural Equation Model (SEM). The examination of the SEM was incorporated an evaluation of the path coefficients and R2 values. Findings: The loadings of all measurement items are larger than 0.792, indicating sound internal reliability of the dataset. Moreover, the Cronbach's alpha values are all > 0.7 which proves the internal consistency of the research model. In this research, the range of CR is 0.838 to 0.947 and the range of AVEs 0.634–0.857, both exceeding the threshold values for desirable convergent validity. To obtain discriminant validity, the square root of AVE should be larger than the correlation among the constructs. The value of each AVE’s square root is greater than the off-diagonal components. The model explains 21.1% of the variance in perceived usefulness, 20.9% in perceived ease of use, 26.9% in attitude to use, 20.0% in MOOC platform actual usage and 24.2% of the variance in learning satisfaction. The path coefficient from quantity and quality of knowledge (β=0.261, p<0.01) and perceived feedback (β=0.215, p<0.01) to PU are positive. The results show that perceived feedback (β=0.275, p<0.01), perceived complexity (β=-0.367, p<0.01) significantly and meaningfully affect PEOU. The PU showed a positive and strong effect on attitude to use (β=0.271, p<0.01), MOOC platform actual usage (β=0.360, p<0.01), and learning satisfaction (β=0.277, p<0.01). Conclusion: The results indicated that the quantity and quality of the knowledge and perceived feedback have a positive and significant impact on the perceived usefulness of MOOCs. The perceived complexity as a negative construct was found to be an important indicator of MOOC platforms usage.