درخت حوزه‌های تخصصی

Education systems in the world are enduring COVID-19 induced perturbations and consequences. Given the growing use of E-learning during COVID-19 epidemic and expansion of Internet-based infrastructure, the need for a resilient approach to e-learning systems is deeply felt. This paper aims to address the issue of how to provide a model for evaluating the resilience of E-learning in Iranian virtual universities during the outbreak of coronavirus employing an Adaptive Neuro-Based Fuzzy Inference System (ANFIS). In the present paper, 5 substantial factors including individual, assessment and support, content, agility, and technology were identified as inputs, and e-learning resilience was considered as single output. Moreover, ANFIS was employed to model the resilience of E-learning systems. Findings revealed almost medium to low degree of resilience for the e-learning system established in Iran’s virtual university. Statistical analysis demonstrated that there was no meaningful difference between experts’ opinions and our proposed procedure for E-learning resilience measurement. The proposed model showed significant sensitivity to changes in agility. Therefore, agility should be considered as the first priority in achieving the desired level of resilience for the e-learning systems of the Iranian virtual university.

Media literacy is a topic that is concerned with the audience's power of understanding of the way in which media works and how they make sense thereof, and seeks to make this analysis a habit and a task for the audience. In this regard, present research provides a model for promotion of public relations with an emphasis on media literacy among managers and employees of Mazandaran Gas Company. In this paper, the data were sorted out through three stages after introduction of the concept media literacy using the qualitative method of grounded theory and holding 15 in-depth, semi-structured interviews with the academics and experts of the field, and following a content analysis. Based on the findings, the model is made up of five components: 1. The elements promoting media literacy at three macro (i.e. formulation of educational rubrics, changing educational methods, culture building with media literacy potential, adopting a problem-oriented approach, creating a national Internet, coherence and consistency in policy making and planning, and media content monitoring), intermediate (i.e. group interaction with colleagues and management training), and micro (i.e. technological knowledge, cognitive knowledge, media knowledge, and content production); 2. Decisive factors (categories of macro, intermediate, and macro level factors); 3. Interfering factors (including government intervention, lack of legislation or regulations); 4. Strategies (including policy and planning strategies, educational strategies, and culture- and discourse building strategies; 5. Consequences (i.e. economic, social, cultural, political, technological, communication, environmental, and individual-behavioral consequences).

This research was aimed at develop and validate an influencer behavior model in social media marketing. The statistical population in the qualitative section consisted of Academic and organizational experts including social media marketing experts. A sample of qualitative sample was used for purposeful sampling and in a small part of the compilation sampling. The data collection tool was interviewed in the qualitative section and in the quantitative section the questionnaire was used. Data were analyzed using confirmatory statistical analysis. The results identified 17 components and 90 indicators that 4 components of influencing the behavior of influencers in social media marketing. Finally, the research model consisting of influential and influential factors was presented and its degree of appropriateness was appropriate.