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Item Processing Patterns of Test-Takers in a Multiple-Choice Reading Comprehension Test

Insights from an Eye-Tracking Study

Bibliographic Data

ID22006097
AuthorsDerya Akbaş (0000-0001-9852-4782, Adnan Menderes University, corresponding author), Ergün Cihat Çorbacı (0000-0002-7874-956X, Sinop University), Nilufer Kahraman (0000-0003-2523-0155, Gazi University, Ankara, Türkiye)
Year2026
Volume16
Issue1
Publication date2026-01-01
Open AccessYes
TypeARTICLE
VenueSAGE Open (JOURNAL)
Journal identifiersISSN: 2158-2440 • E-ISSN: 2158-2440
PublisherSAGE Publications (PUBLISHER • US)
DOI10.1177/21582440261420311
OpenAlexW7128737846
LanguageEN
References cited46

This study explores how test-takers process multiple-choice questions in a reading comprehension test using eye-tracking data. A total of 159 participants completed a 10-item English test, while their eye movements were recorded with the Smart Eye Aurora eye tracker. The study first examined item processing patterns using latent profile analysis and then compared test performance across these groups. To identify processing patterns, latent profile models (ranging from one to four classes) were tested for each item based on average log process times across defined Areas of Interest (AOIs) for text lines and answer choices. Results showed that a two-class model (fast- and slow-pacing) provided the best fit for five items, while a three-class model (fast-, moderate-, and slow-pacing) best fit the remaining items. Items with two subgroups were typically moderately difficult (short) or easy (long), while items with three subgroups varied in difficulty and length. Additionally, test-takers in fast-pacing group were more likely to answer items correctly and achieved higher total scores than those in other groups, particularly for highly discriminating and moderately difficult or easy items. Overall, these findings highlight the importance of examining item processing patterns to better understand how individuals interact with multiple-choice test items. Item characteristics—such as difficulty, discrimination, and length—play a crucial role in shaping processing behaviors, providing deeper insights into the cognitive aspects of eye movement patterns during test-taking

Cognition · Comprehension · Eye movement · Information processing · Reading comprehension · Neurobiology of Language and Bilingualism · Reading and Literacy Development · Visual and Cognitive Learning Processes

  • Insights into Second Language Reading

    Open Access•Keiko Koda•Insights into Second Language…•2005

  • Informative tools for characterizing individual differences in learning

    Open Access•Marian Hickendorff, Peter A Edelsbrunner et al.•Learning and Individual Differences•2018

  • Likelihood Ratio Tests for Model Selection and Non-Nested Hypotheses

    Quang Vuong, Quang H Vuong•Econometrica•1989

  • Response Time Effort

    Steven L Wise, Xiaojing Kong•Applied Measurement in Education•2005

  • A Latent Transition Mixture Model Using the Three-Step Specification

    Karen Nylund‐gibson, Karen Nylund-Gibson et al.•Structural Equation Modeling: A…•2014

  • Best practices in eye tracking research

    Open Access•Benjamin T Carter, Steven G Luke•International Journal of…•2020

  • Anxiety and Performance

    Michael W Eysenck, Manuel G Calvo•Cognition & Emotion•1992

  • Anxiety, Processing Efficiency, and Cognitive Performance

    Nazanin Derakshan, Michael W Eysenck•European Psychologist•2009

  • Finite Mixture Models

    Open Access•Geoffrey J McLachlan, Geoffrey McLachlan et al.•Finite Mixture Models (Wiley…•2000

  • Finding latent groups in observed data

    Open Access•Sarah L Ferguson, E Whitney G Moore et al.•International Journal of…•2020

  • Factor Analysis and AIC

    Open Access•Hirotugu Akaike•Psychometrika•1987

  • Estimating the Dimension of a Model

    Gideon Schwarz•The Annals of Statistics•1978

  • Ten frequently asked questions about latent class analysis.

    Open Access•Karen Nylund‐gibson, Andrew Young Choi•Translational Issues in…•2018

  • Testing the number of components in a normal mixture

    Yungtai Lo•Biometrika•2001

  • Dual-Process Theories of Higher Cognition

    Open Access•Jonathan St B T Evans, Keith E Stanovich•Perspectives on Psychological…•2013

  • Auxiliary Variables in Mixture Modeling

    Tihomir Asparouhov, Bengt Muthén•Structural Equation Modeling: A…•2014

  • Investigating cognitive processes in different item formats in reading tests through eye-tracking and verbal protocols

    Open Access•Hatice Akgün, Aylin Ünaldı•Studies in Language Assessment•2022

  • Reading Development, Word Length and Frequency Effects

    Open Access•Sabrina Gerth, Julia Festman•Frontiers in Communication•2021

  • Measuring (meta)cognitive processes in multimedia learning

    Open Access•Lisa Stark, Andreas Korbach et al.•Journal of Computer Assisted…•2024

  • Twelve tips for applying the think-aloud method to capture cognitive processes

    Open Access•Babu Noushad, Pascal W M Van Gerven et al.•Medical Teacher•2024

  • The cognitive processing of candidates during reading tests

    Open Access•Stephen Bax•Language Testing•2013

  • Investigating the construct measured by banked gap-fill items

    Open Access•Gareth McCray, Tineke Brunfaut•Language Testing•2018

  • A Systematic Review of Eye-Tracking Technology in Second Language Research

    Open Access•Xin Hu, Vahid Aryadoust•Languages•2024

  • Using eye-tracking research to investigate language test validity and design

    Open Access•Stephen Bax, Sathena Chan•System•2019

  • Using Eye‐Tracking Measures to Predict Reading Comprehension

    Open Access•Diane C Mézière, Lili Yu et al.•Reading Research Quarterly•2023

  • Validity of psychological assessment

    Samuel Messick•American Psychologist•1995

  • Latent Class Modeling with Covariates

    Open Access•Jeroen K Vermunt•Political Analysis•2010

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