درخت حوزه‌های تخصصی

Plagiarism is considered as a serious problem in academia around the world. The issue of plagiarism has recently received global inquiry in different fields of science, especially in foreign language (L2) academic writing. To meticulously assess the Iranian academics for plagiarism at both theory and practice grounds, developing an accountable instrument seemed to be inevitable. To bridge the gap, in phase 1 of the study, a conceptual framework for Iranian academics’ grasp of plagiarism and its components was designed after a thorough review of literature. In phase 2, a number of M.A. graduates and graduate students (n = 224) in six State and Islamic Azad universities in Iran were recruited to partake in piloting the newly-designed plagiarism questionnaire. After a two-step revising the inefficient items (n = 11), the final draft of the developed questionnaire with 36 items was administered with the main sample of participants (n = 288). An Exploratory Factor Analysis was performed to identify the components of the instrument, followed by Confirmatory Factor Analysis to measure its construct validity. As a result, the final draft of the Sociocultural Plagiarism Questionnaire contained 31 Likert-point and 5 multiple choice items in four components of awareness (10 items), attitude (8 items), sociocultural beliefs (8 items), and perception (5 Likert-point and 5 multiple choice items), which were suggested as having fundamental contributions to the Iranian academic writers’ sensitivity to plagiarism. Findings of the study suggested that (a) the Iranian academic writers’ normative sociocultural beliefs can probably reduce their sensitivity to plagiarism, (b) while the Iranian academics might have relatively high awareness and deep perception about plagiarism, their attitude toward plagiarism seems relatively neutral or even insensitive.

In regard to recent revolution in the education domain, English Language Teaching (ELT) assigns a sociopolitical dimension to itself in the light of Critical Pedagogy. The present study, in line with the recent educational revolution, aimed to investigate the effectiveness of critical thinking on improving EFL learners’ productive skills. The statistical population consisted of 164 pre-intermediate attendees of EFL in an English Language Institute in the city of Babol selected for taking an Oxford Placement Test (OPT). The participants were 80 Iranian pre-intermediate EFL students within 10-20-year range, enrolled in Shokouh English language institute in Babol, who were randomly divided into two experimental and two control groups of (N=20) for each group during summer 2018 through the non-probability sampling design. Then, IELTS pre-intermediate speaking and writing tests were taken as the pre-test to make sure that they have failed to have a previous knowledge of objective structures. Unlike the control group, the participants in the experimental group were told to apply critical thinking instructions in learning speaking and writing skills. After intervention, the same pretest was taken to the participants in both groups as the posttest to determine the result of gaining the medical aid. Independent and paired sample t-tests were run to answer the research questions. The results indicated that critical thinking is highly contributive in learning productive skills. The findings of this study can be applied in methodological issues.

This study aimed to overcome the researchers' extreme attention to essentially qualitative methods in research on language learners' imagined communities and move towards quantification in order to achieve a more tangible image of this construct. To do so, the present researchers followed three main phases. First, a hypothesized model of language learners' imagined communities with eight components was developed for the Iranian context based on the wide-ranging readings of the literature on imagined communities, consultations with experts and interviews with language learners. Second, a questionnaire was developed and validated based on the model to represent its components. Finally, the data collected through the questionnaire were fed into the model to see to what extent the model fit the data. The initial results showed poor values; however, the model was trimmed by removing one item from the questionnaire, and final statistical indices showed that the model was fit.