Predicting the difficulty of EFL reading comprehension tests based on linguistic indices

• Published in: Asian-Pacific Journal of Second and Foreign Language Education Vol. 8; no. 1; pp. 41 - 15
• Main Authors: Rafatbakhsh, Elaheh, Ahmadi, Alireza
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 08.12.2023; Springer; Springer Nature B.V; SpringerOpen
• Subjects: Applied Linguistics; College Entrance Examinations; Computational linguistics; Corpus linguistics; Correlation; Difficulty Level; Education; English (Second Language); English as a second language tests; Entrance examinations; Foreign Countries; Graduate studies; Language Education; Language Tests; Masters Programs; Predictor Variables; Readability; Readability Formulas; Reading Comprehension; Reading difficulty; Reading Tests; Scores; Second Language Instruction; Second Language Learning; Second language reading; Teaching and Teacher Education; Technology in the teaching and assessment of writing; Test Validity; Test validity and reliability; Iran; Computational linguistics; Corpus linguistics; Readability; Reading difficulty; Reading comprehension
• ISSN: 2363-5169; 2363-5169
• DOI: 10.1186/s40862-023-00214-4

Estimating the difficulty of reading tests is critical in second language education and assessment. This study was aimed at examining various text features that might influence the difficulty level of a high-stakes reading comprehension test and predict test takers’ scores. To this end, the responses provided by 17,900 test takers on the reading comprehension subsection of a major high-stakes test, the Iranian National University Entrance Exam for the Master’s Program were examined. Overall, 63 reading passages in different versions of the test from 2017 to 2019 were studied with a focus on 16 indices that might help explain the reading difficulty and test takers’ scores. The results showed that the content word overlap index and the Flesch-Kincaid Reading Ease formula had significant correlations with the observed difficulty and could therefore be considered better predictors of test difficulty compared to other variables. The findings suggest the use of various indices to estimate the reading difficulty before administering tests to ensure the equivalency and validity of tests.