2024 : 11 : 24
Farhad Mazlum Zavaregh

Farhad Mazlum Zavaregh

Academic rank: Assistant Professor
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Education: PhD.
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Faculty: 1
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Research

Title
Reading Comprehension Questions in Iranian High School Textbooks and University Entrance Examinations: A Comparative Study
Type
Thesis
Keywords
English textbooks, reading comprehension questions, Konkour
Year
2024
Researchers Mehrdad Seifi(Student)، Farhad Mazlum Zavaregh(PrimaryAdvisor)، Mostafa Janebi Enayat(Advisor)، Fatemeh Poorebrahim(Advisor)

Abstract

Assessing reading comprehension is one of the key topics of English language assessment studies in general. One line of such inquiries is examining post-reading comprehension questions designed by classroom teachers, local and international material designers, and test designers involved in high-stakes language testing. In Iran, students answer such questions in English textbooks developed by Iran’s Ministry of Education and need to prepare for similar questions in the high-stakes national-level University Entrance Exam (Konkour) designed by Iran’s National Organization of Educational Testing. The purpose of this study is twofold. First, it aims to investigate post-reading comprehension questions developed by Iranian material designers in the Ministry and those designed by Konkour test developers. Second, it intends to compare the comprehension questions in public sector textbooks and Konkour in terms of question types. To this end, all reading comprehension questions of Vision Series, developed by the Ministry and taught nationwide, and those of Konkour (2019-2022) were included in the data. Freeman’s Taxonomy—developed specifically for the L2 reading context—was used to examine and categorize comprehension questions. The Taxonomy consists of three major question types, namely Content, Language, and Affect each with sub-types for further categorization. Descriptive content analysis of data entailed counting and categorizing comprehension questions in Vision 1, 2, and 3 followed by a similar analysis of Konkour questions. The overall results showed Content type was the most dominant in Vision Series followed by Language and Affect types. Intra-level analyses revealed that the highest percentage of occurrence in Visions belonged to Textually Implicit questions followed by Textually Explicit and Inferential Comprehension of the Content-type. For the Language type, Lexical questions dominate the Vision Series with no trace of Reorganization and Form types. Affect Quest