درخت حوزه‌های تخصصی

New generation of English textbooks, Vision Series, has been introduced and taught in Iranian high schools since 2017. This study aimed to scrutinize the correspondence between the recommendations suggested in the English teachers’ guides (TGs) of Vision Series and the actual teaching practices of Iranian high school English teachers. It follows a descriptive and correlational design, enjoying both qualitative and quantitative research methods. Participants of the present study included three groups: English teachers, high school students, and supervisors of English teachers in Iranian Ministry of Education. A total number of 100 high school English teachers, teaching in Sistan and Balouchestan Province, filled out a researcher-made piloted questionnaire. Out of them, 3 male and 3 female English teachers were later invited for an oral semi-structured interview. The second group of participants were 48 high school students. The last group of participants were 2 supervisors of English teachers in Iranian Ministry of Education. The researchers also participated in and observed two female teachers' English classes. By and large, the results of supervisors’ interviews and class observations were negative about the correspondence between actual teaching of Vision Series and recommendations of TG for most sections of the book. By contrast, the results of teachers' and students' questionnaires demonstrated that English teachers' teaching was perceived to be consistent with the recommendations of TG in more than half of the cases. The interviews with teachers indicated that half of the interviewees believed that they followed the suggestions of the TG. The implications of findings, especially for English teachers, are also discussed.

To explore the characteristics of the items of the Teaching English as a Foreign Language (TEFL) MA Admission Test (henceforth TMAAT) as a high-stakes test in Iran, the current research utilized a three-parameter logistic Item Response Theory (IRT) calibration of the test items. The three-parameter logistic IRT model is the most comprehensive among the three models of IRT for it takes into account all the three effective parameters of item difficulty, item discrimination, and guessing simultaneously. The data were a random selection of 1000 TMAAT candidates taking the test in 2020 collected from Iran’s National Organization of Educational Testing (NOET). The software used to analyze the data was jMetrik (Version 4.1.1), which is the newest version so far. As the results indicated, the TMAAT worked well in discriminating the higher and lower ability candidates and preventing the candidates from guessing the responses by chance, but it was not much acceptable regarding the difficulty level of the items as the items were far too difficult for the test-takers. The most important beneficiaries of the present investigation are test developers, testing experts, and policy-makers in Iran since they are responsible to improve the quality of the items in such a high-stakes test.