درخت حوزه‌های تخصصی

This study investigates the immediate impact of reflective practices on the language assessment literacy of Iranian English as a Foreign Language (EFL) teachers. Combining quantitative assessment literacy measures with qualitative analysis of reflective practices, the research draws on the theoretical frameworks of Alderson, Fulcher, and Schön. Empirical insights from Akbari, Farrokhi, Shahnazari, and Karami and Rahimi provide a contextual backdrop within the Iranian EFL educational context. Using a mixed-methods design involving 50 EFL teachers, the study employs adapted assessment literacy measurement tools and reflective practices assessment tools. The results, analyzed through descriptive and inferential statistics, paired t-tests, and qualitative exploration, highlight improvements in specific areas such as choosing appropriate assessment methods and using results for decision-making. Implications point towards integrating reflective practices into professional development, while future research avenues include exploring long-term effects, contextual variations, and technology integration.Implications point towards integrating reflective practices into professional development, while future research avenues include exploring long-term effects, contextual variations, and technology integration.This study investigates the immediate impact of reflective practices on the language assessment literacy of Iranian English as a Foreign Language (EFL) teachers. Combining quantitative assessment literacy measures with qualitative analysis of reflective practices, the research draws on the theoretical frameworks of Alderson, Fulcher, and Schön. Empirical insights from Akbari, Farrokhi, Shahnazari, and Karami and Rahimi provide a contextual backdrop within the Iranian EFL educational context.

The present research had a dual objective: first, to identify the components for organizational Development within the structure of the education system in Iran, and second, to propose a model for organizational transformation in the same context. To this end, a qualitative and interpretive approach was employed using grounded theory methodology. Data were collected through a semi-structured interview protocol. The research field included education specialists, from whom 22 individuals were invited for interviews through snowball sampling until theoretical saturation was reached. The transcripts of the interviews were analyzed after being transcribed into written text, using the three-stage systematic coding model of Strauss and Corbin (open, axial, and selective coding). The findings indicated that the main and effective components in the structural transformation of education encompassed the following 11 axial codes: management style, authority and division of tasks, formality, job satisfaction, professionalism, religious value system, justice, supervision and evaluation, management and planning, human resources, and educational budget. The results of the research showed that, considering the importance of transformation in the structure of the education system and the various problems and obstacles identified by education elites regarding structural transformation, attention should be paid to the aforementioned identified components and the proposed model of the research to facilitate change

This study investigates the crucial components propelling the integration of green technology and blockchain technology within electronic education (e-learning). Employing a mixed-methods research design, the inquiry blends quantitative and qualitative methodologies for comprehensive analysis. The qualitative phase draws upon the expertise of 125 purposefully sampled academic experts, subject-area specialists, and e-learning professionals through semi-structured interviews. Content analysis dissects these qualitative data, while structural equation modeling and factor analysis illuminate the quantitative dimension. The findings unveil five key components orchestrating green technology development in e-learning with blockchain integration: causal conditions, central phenomena, strategies, background conditions, and intervening conditions. Further analysis within each component identifies critical sub-components, informed by expert insights. Collectively, the study's predictor variables, encompassing both green technology development components and blockchain technology utilization, demonstrate a significant predictive influence (0.36, p < 0.01) on the mediator variable, green technology development. Additionally, they exhibit a nuanced yet statistically significant predictive effect (0.16, p > 0.05) on the criterion variable, e-learning and educational software performance enhancement. These positive and direct associations suggest a robust model for integrating blockchain technology to propel green technology advancements within e-learning. The proposed five-component model sheds light on the interplay between key factors, emphasizing the substantial impact of its application in guiding effective integration strategies.