درخت حوزه‌های تخصصی

Purpose: Considering the role of leadership in achieving the education missions, present research done with the aim of designing a suitable leadership model to achieve new missions of higher education. Methodology: This study in terms of purpose was applied and in terms of implementation was exploratory combined (qualitative and quantitative). The research population in the qualitative part was the higher education experts and in the quantitative part were the personnel of Islamic Azad University of Tehran province in 2018-19 academic years. The research sample in the qualitative part according to the theoretical saturation principle were estimated 13 people who were selected by purposive sampling method and in the quantitative part according to Cochran’s formula were estimated 385 people who were selected by cluster random sampling method with respect to classes (number of staff in universal branches). To collected data in the qualitative part used from interview and in the quantitative part used from researcher-made questionnaire (51 items) which the its content validity was confirmed by experts and its convergent validity by average variance extracted indicator was confirmed and its reliability was obtained by Cronbach’s alpha method 0.84. To analyze data were used from methods of open, axial and selective coding and exploratory factor analysis in SPSS-22 software. Findings: The findings of the qualitative part showed that suitable leadership had 79 concepts, 63 categories and 7 dimensions and new missions of higher education dad 20 concepts, 15 categories and 3 dimensions. The findings of the quantitative part showed that the suitable leadership model to achieve new missions of higher education had 51 indicators or items and 15 components. Also, a suitable leadership model to achieve new missions of higher education was designed and approved by experts. Conclusion: Based on the findings of the present study, higher education specialists and planners can design and implement programs to realization the new missions of higher education.

Purpose: The main purpose of this study was to develop a model of factors affecting students' creativity and to evaluate its validity. Methodology: The research design was an exploratory (qualitative-quantitative) mix. In the qualitative part of the target population, all teachers of the sixth grade of elementary school in the 5th district of Tehran and professors of psychology and educational sciences were prestigious universities in the country, which were selected by purposive sampling of 10 teachers and 10 specialists. In a small part of the population considered in this study, all female primary school students in the sixth grade of the 5th district of Tehran in the year 1998-97, 350 of them were selected as a sample and in random clusters. In the qualitative part of the research, a semi-structured interview was used to obtain information and in the quantitative part, a researcher-made questionnaire was used. The validity and reliability of the questionnaire were confirmed. Factors with very minor changes in exploratory and confirmatory factor analyze using LISREL software and SPSS / 26 were accepted. Findings: The research findings showed that seven main factors namely students' interests and abilities, teacher characteristics, textbook content, learning style, educational space and school facilities, family and management style and principals' attitudes are effective in students' creativity. Conclusion: In general, since the first step in upgrading and improving any structures is to identify the factors affecting it, the findings of the present study help to develop theories of creativity, design of educational interventions, and general policies.

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.