reading-assessment
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- PaperDOAJ — Language assessment1 Jul 2026
The impact of computer-based testing on EFL university students’ reading and listening skills test performance and test anxiety levels
Andrew Ghaly
A study of 40 EFL university students found no significant difference in reading and listening test performance between computer-based testing (CBT) and paper-and-pencil formats. However, test anxiety levels were significantly higher in the CBT group, suggesting the need for pre-test familiarization sessions when adopting digital assessments.
Original abstract
This study investigated the impact of computer-based testing (CBT) on upper-intermediate EFL university students’ test performance in reading and listening, and on their test anxiety levels. Forty students at the English Language Centre of Pharos University in Alexandria (N = 40) were randomly assigned to a control group taking paper-and-pencil tests or an experimental group taking the same tests in a computer-based format. Three reading and three listening tests, each developed according to Cambridge B1 specifications, were administered over eight weeks. Students’ text anxiety was assessed using the Test Anxiety Inventory questionnaire and semi-structured interviews. The results revealed no statistically significant differences in reading or listening performance between groups; however, test anxiety levels were significantly higher among CBT participants (t = −8.99, p < 0.001). The findings suggest that while CBT can be used interchangeably with traditional paper-based tests, additional measures such as pre-test orientation and digital familiarization sessions are essential to mitigate increased anxiety from CBT. For practitioners, this study highlights the importance of preparing and orienting EFL learners before transitioning to computer-based assessment environments.
- PaperDOAJ — Language assessment1 Jul 2026
A LINEAR LOGISTIC TEST MODEL (LLTM) APPLICATION IN FOREIGN LANGUAGE TESTING
Jose Fabián Elizondo-González, Peyman Jahanbin
Applied the Linear Logistic Test Model (LLTM) to a reading comprehension subtest of an English certification exam, using a Q-matrix of cognitive predictors. The model accounted for 77% of item difficulty variance, with inferences and subtask complexity as key factors. LLTM makes item difficulty more interpretable and informs test development.
Original abstract
This study applies the Linear Logistic Test Model (LLTM) to the reading comprehension subtest of an English certification exam developed by the Foreign Language Assessment Program (PELEx, for its acronym in Spanish). A Q-matrix operationalized cognitive and linguistic predictors, such as paraphrasing and inferential reasoning, to explain item difficulty. Delta-squared results showed that the Q-matrix accounted for 77% of the variance in item difficulty, with “Inferences” and “Subtask Complexity” being key contributors. While overlaps in item difficulty coefficients reflected the nested nature of the Common European Framework of Reference for Languages (CEFR) levels, this progression aligns with the framework’s principles. The findings show that LLTM can make item difficulty more interpretable in reading assessment, while also helping to identify which item features merit further refinement in future test development.