درخت حوزه‌های تخصصی

The present study aimed at investigating the effect of peer and teacher scaffolding through a process approach in a technology-enhanced environment on vocabulary learning among high and low self-regulated learners. Participants of the study were 120 English as a Foreign Language (EFL) learners who were selected based on their scores on a sample copy of the Oxford Placement Test (OPT). The participants were divided into three groups each consisting of 40 learners. One group of the participants received peer scaffolding; the second group was exposed to teacher scaffolding via the Telegram app based on process approach principles, while the third group served as the control group. The control group received conventional vocabulary teaching in such a way that the Telegram app was not employed. The learners in the control group were also provided with vocabulary exercises in the vocabulary book (English Vocabulary in Use). Data were collected through a sample copy of OPT, a vocabulary test, and a self-regulation questionnaire. The results of a one-way ANOVA revealed that both peer and teacher scaffolding significantly affected vocabulary learning. However, there was no significant difference between peer and teacher scaffolding in terms of their effects on vocabulary learning. The results of a two-way ANOVA indicated that the main effect of treatment on vocabulary learning was significant; however, there was no statistically significant difference between the effects of the two treatment modalities on students’ vocabulary learning.

The present research has been done with a view to designing content marketing model at social media for boosting green marketing. As regards purpose, it is an applied research,and in terms of approach an exploratory survey, and typically, it can be subsumed under a qualitative research. The analysis approach of this research is meta-synthesis. The statistical community consists of academic and scholarly articles published between 2016-2021/1395-1401 on the pertinent area of this study at Iran`s and foreign trustworthy databases. According to our findings, 1740 articles were retrieved, 324 abstracts were sieved and 186 abstracts were investigated. It was established that the titles of 1416 articles were irrelevant, and consequently they were omitted. 138 articles were deleted once their abstracts had been reviewed and found irrelevant and 95 articles were left out after a survey of their contents. The criteria used were size of the statistical sample, theoretical sufficiency (theoretical saturation), and finally 56 articles were accepted. The outcome of this process was 49 codes, 23 concepts and 10 categories. The Kappa index was used to guarantee the quality of our research. The amount of the index was calculated using the SPSS software at the significant level of 0/000 number 0/806. According to the evaluation and the extracted concepts and categories in the present research, the content marketing model of social media (Instagram) for boosting green marketing was designed based on three groups of factors: causal, mediating and consequential. The results of the findings show that in the process of content marketing of social media for boosting green marketing, a set of variables play a causal role, and can act as stimulants or propelling agents, and if the causal and mediating factors come properly about, this can culminate in the boosting of the service or product`s brand and an appropriate competitive advantage regarding green marketing in the organizations will also emerge.

The ‘Subsidy Targeting Project’ was introduced by the government of Iran in 2010 to ease the impact of removing price subsidies (carried out as part of recent economic liberalization reforms). Under this scheme, regardless of their socio-economic characteristics, Iranian citizens residing in Iran receive the same amount of cash rebate (currently 455,000 Iranian Rials per month). This paper uses the equivalence scales approach to query the fairness of this policy exercise. We use Iran’s Household Expenditure and Income Surveys datasets for 1984-2007 (compiled annually by the Statistical Centre of Iran) to estimate the Engel-curve-based equivalence scales which take account of the main household features: size, geographic location, and a number of characteristics of head of household. Our estimates suggest a clear profile of redistribution which questions the fairness of disregarding households’ characteristics in such a large scale redistribution exercise which was primarily designed to offset the welfare impacts of removing price subsidies. JEL Classification: I30, I31, I32, I38