reading-comprehension
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- PaperLanguage Testing10 Jun 2026
Beyond Traditional Differential Item Functioning Detection: A Rasch Tree Approach to Evaluating Item Fairness in a Large-Scale German Reading Comprehension Test
Farshad Effatpanah, Olga Kunina-Habenicht, Katharina Antonia Michiko Tremmel, Philipp Sonnleitner
Applied the Rasch tree model to detect differential item functioning in a large-scale German reading comprehension test for fifth graders, analyzing responses from 4,252 students across gender, socioeconomic status, immigration status, and personality. The method identified four splitting nodes with eleven items showing moderate to large DIF without requiring pre-specified groups, revealing how covariate combinations impact test performance.
Original abstract
A key psychometric phenomenon in educational testing is differential item functioning (DIF), which evaluates whether specific test items function differently across subgroups of examinees who have the same level of the underlying (latent) ability. DIF happens when examinees with the same latent trait have different probabilities of correctly responding to a test item, influenced by their subgroup membership. This study aims to illustrate the application of the recursive partitioning Rasch tree model, shortly called the Rasch tree, to examine DIF in a large-scale German reading comprehension test for fifth-grade elementary students across gender, socioeconomic status, immigration status, personality disposition, and the need for cognition. Unlike the conventional DIF detection methods, the Rasch tree does not require a pre-specification of groups for exploring DIF, and continuous covariates can be easily included in the analysis. To investigate DIF of the test, item responses of 4,252 students were analyzed. The Rasch tree analysis generated nine non-predefined nodes, with slightly different patterns of item difficulties. Eleven items were flagged as exhibiting moderate and large DIF in the four splitting nodes. No splits were produced based on the need for cognition. The results indicated that the combination of the covariates impacted students’ test performance.
- PaperELT Journal27 May 2026
The trap of procedural reading in ELT
Mfanukhona Wonderboy Kunene
In English language teaching, learners often read texts primarily to find answers rather than construct meaning, a pattern termed procedural reading. This comment piece explores how repeated comprehension tasks shape this behavior and limit deeper comprehension. It offers practical ways for teachers to rebalance task design to support both exam performance and meaningful engagement.
Original abstract
In many English language teaching classrooms, learners approach reading texts primarily as sources of answers rather than as opportunities to construct meaning. This comment piece describes this pattern as procedural reading: a form of engagement shaped by repeated exposure to comprehension tasks that reward efficient answer location. While such strategies are adaptive in assessment-oriented contexts, they may narrow learners’ conception of reading and limit opportunities for deeper comprehension. Drawing on classroom observations, I explores how common task formats can influence reading behaviour and reader orientation. I then outline practical ways for teachers to rebalance task design to support both exam performance and meaningful engagement with texts. The aim is not to reject efficiency, but to restore balance between answer-focused and meaning-focused reading.
- PaperETS Research Report Series13 Mar 2026
Toward an Automatic Method for Generating Topical Vocabulary Test Forms for Specific Reading Passages
Michael Flor, Zuowei Wang, Paul Deane, Tenaha O'Reilly
The K-tool automatically generates topical vocabulary tests to measure students' background knowledge for specific reading passages. It detects the topic of a text and produces vocabulary items with high topic association and distractor words with low association. Designed for native English-speaking middle and high school students, the system aims to predict reading comprehension readiness.
Original abstract
Background knowledge is typically needed for successful comprehension of topical and domain-specific reading passages, such as in the STEM domains. However, there are few automated measures of student knowledge that can be readily deployed and scored in time to make predictions on whether a given student will likely be able to understand a specific content-area text. In this research report, we present our effort in developing the K-tool, an automated system for generating topical vocabulary tests that measure students’ background knowledge related to a specific text. The system automatically detects the topic of a given text and produces topical vocabulary items based on their relationship with the topic. This information is used to automatically generate background knowledge forms that contain words that are highly related to the topic and words that share similar features but do not share high associations to the topic. Prior research has indicated that performance on such tasks can help determine whether a student is likely to understand a particular text based on their knowledge state. The described system is intended for use with middle and high school student populations of native speakers of English. It is designed to handle single reading passages and is not dependent on any corpus or text collection. In this report, we describe the system architecture and present an initial evaluation of the system outputs. Suggested citation: Flor, M., Wang, Z., Deane, P., & O’Reilly, T. (2025). Toward an automatic method for generatingtopical vocabulary test forms for specific reading passages (Research Report No. RR-26-02). ETS.
- PaperLanguage Learning & Technology1 Jan 2026
The role of arousal in L2 readers’ engagement and comprehension during pedagogical agent–guided online reading
Jack Drobisz, Sanghoon Park, Glenn Smith
Investigated how arousal conditions (perceptual vs. inquiry, high vs. low) in pedagogical agent-guided online reading affect L2 learners' situational interest, cognitive load, and reading comprehension. A randomized 2x2 factorial design with 157 L2 readers showed that inquiry arousal significantly influenced germane cognitive load and reading comprehension, and interacted with perceptual arousal on germane cognitive load. Findings highlight inquiry arousal as a key design factor for pedagogical agent-guided L2 reading tasks.
Original abstract
Reading comprehension is essential for second language (L2) learners’ academic success, yet many struggle in English–speaking schools due to their various backgrounds and limited lexical knowledge. Prior research highlights the importance of attitude and motivation in promoting the use of reading strategies, but little work has examined how multimedia design can support these factors. In this study, we designed four arousal conditions of pedagogical agent–guided online reading materials in which four pedagogical agents induced two types of arousal (perceptual vs. inquiry) in two levels (high vs. low) through the manipulation of their background images, gestures, voices, and delivered messages. Using a randomized 2 x 2 factorial design, we examined how the study conditions influenced L2 readers’ situational interest, cognitive load and reading comprehension. A total of 157 L2 readers participated in the study and were randomly assigned to one of the four conditions. Two–way ANOVA results revealed significant main effects of inquiry arousal on germane cognitive load and reading comprehension, as well as an interaction between inquiry and perceptual arousal on germane cognitive load. These findings suggest that inquiry arousal is a key design consideration for pedagogical agent–guided reading tasks for L2 learners.