مطالب

The Coronavirus disease (Covid-19) is one of the infectious and contagious ones called 2019-nCoV acute respiratory disease. Its outbreak was first reported on December 31, 2019, in the Chinese city of Wuhan that quickly spread throughout the country within a few weeks and spread to several other countries, including Italy, the United States, and Germany, within a month. This disease was officially reported in Iran on February 19, 2020. It is important to detect and analyze high risk zones and establish regulations according to the data and the analyses of Geographic Information System (GIS) in epidemiological situations. Meanwhile, the GIS, with its location nature, can be effective in preventing the breakdown of Covid-19 by displaying and analyzing the dangerous zones where people infected with the disease. In fact, recognizing regions based on the risk of getting the disease can influence social restriction policies and urban movement rules in order to prepare daily and weekly plans in different urban regions. In this applied and analytical research, high and low risk zones of Tehran have been identified by using the random forest algorithm which is used for both classification and regression. The algorithm builds decision trees on data samples and then predicts data from each of them, and finally chooses the best solution. In this research, 7 effective criteria have been used in the level of risk of regions toward Covid-19 virus, which is: subway paths and bus for rapid transits, hospitals, administrative and commercial complexes, passageways, population densities and urban traffic. After providing the map of high-risk zones of Covid-19, the Receiver Operating Characteristic curve (ROC) has been used for evaluation. The area under the curve (AUC) obtained from ROC shows an accuracy of 98.8%, which means the high accuracy of this algorithm in predicting high and low zones toward getting the Covid-19 disease.

The present study aimed at investigating the effect of CALL on intermediate EFL learners’ vocabulary learning and comparing it with traditional teaching method. To this end, a quasi-experimental design was used in which 80 students were chosen based on their performance in an Oxford Placement Test (OPT), and were randomly assigned to the experimental and control groups. Six reading comprehension passages consisting of 72 new words were selected from the book “504 essential words” and used as the pretest of the study. Then, the experimental group received twelve sessions of treatment which was teaching vocabulary through different tools in the computer such as related pictures, video, textual highlights, PowerPoint slides, or Narsis software while the control group received the traditional way of teaching such as providing oral pronunciation of words, explaining their parts of speech, and offering a direct translation of words in Persian. Afterward, both groups attended the post-test of vocabulary at the end of the study. The scores of learners in pretest and posttest were analyzed statistically via running independent T-test. The findings revealed that CALL instruction was more effective in enhancing learners’ vocabulary learning in comparison to the traditional vocabulary instruction. The findings indicated that the experimental group had a better performance than that of the control group, and the learners in the CALL group learned more vocabulary than the learners in the traditional group. The findings of this research have implications for teachers and learners as teachers can use CALL in EFL classes to help them be independent learners, and make vocabulary learning more attractive and enjoyable to learners. The findings can help material developers and syllabus designers to consider the importance of CALL while planning textbooks and materials.