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In a recent article in CEJEME, Yang et al. simulate latent profile analysis of different treatments of ordinal scales with different response options at different sample sizes under maximum likelihood and Bayesian estimations.

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October 23, 2025 at 5:47 PM
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In a recent article in CEJEME, Suna and Özer examine how Al and ML can reinforce or reduce bias in educational assessments, proposing strategies for more equitable and transparent evaluation models.

Learn more: doi.org/10.59863/YPK...

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The Human Complimentary Usage of AI and ML for Fair and Unbiased Educational Assessments
In recent years, artificial intelligence (AI) and machine learning (ML) algorithms have played an influential role in advancing educational assessment. As a means of improving equal opportunities in e...
doi.org
April 2, 2025 at 5:04 PM
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In a recent article in CEJEME, Pan and Sinharay propose a novel approach using autoencoders and BERT to detect compromised items in computerized linear testing.

Learn more: doi.org/10.59863/XSS...

#AIinEducation #TestSecurity
Detecting Compromised Items in Computerized Linear Testing: A Novel Approach Using Autoencoders and BERT
Item compromise is a significant concern in the testing industry. We propose a novel approach for detecting compromised items in computerized linear testing by analyzing response times and scores. Our...
doi.org
December 27, 2024 at 4:05 PM
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In a recent article in CEJEME, Zheng et al. survey the measurement community, analyzing how ML is used in educational measurement and identifying key gaps between ML methodologies and fundamental measurement principles.

Learn more: doi.org/10.59863/GVZ...

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MxML (Exploring the Relationship between Measurement and Machine Learning): Survey of the Measurement Community
The field of educational measurement (hereafter shortened as measurement) has seen rapid growth in applications of machine learning (ML) recently. However, it is imperative to examine potential gaps b...
doi.org
March 25, 2025 at 6:00 PM
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NCME's Chinese/English Journal of Educational Measurement and Evaluation (CEJEME) is pleased to announce the publication of a new Special Issue on Big Data Sources in Educational Measurement!

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September 15, 2026 at 2:12 PM
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📚️ A recent CEJEME article provides a practical, step-by-step guide to building an NLP pipeline for assessment data.

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May 29, 2026 at 2:21 PM
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In a recent article in CEJEME, Huang et al. synthesize 29 studies on automated essay scoring and 14 on automated writing feedback generation.

Learn more: doi.org/10.59863/FAM...

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An Early Review of Generative Language Models in Automated Writing Evaluation: Advancements, Challenges, and Future Directions for Automated Essay Scoring and Feedback Generation
Automated writing evaluation (AWE) has long supported assessment and instruction, yet existing systems struggle to capture deeper rhetorical and pedagogical aspects of student writing. Recent advances...
doi.org
September 11, 2025 at 12:08 PM
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In a recent article in CEJEME, Mardones-Segovia et al. provide foundational knowledge on the steps needed for using NLP in educational measurement tasks.

Learn more: doi.org/10.59863/SDY...

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Natural Language Processing Pipeline for Assessment Data: An R-Based Tutorial
Natural language processing (NLP) has become an increasingly popular approach for analyzing textual responses in educational assessments. An important part of NLP involves cleaning and structuring exa...
doi.org
September 5, 2025 at 3:50 PM
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In a recent article in CEJEME, Ober et al. present five unique school and program models to support students and educators while fostering meaningful connections more optimally within the school community.

Learn more: doi.org/10.59863/XIK...

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Aligning Models of Competency-based Education with Skills for the Future
Essential competencies such as collaboration and critical thinking, integral to long-term success, have been notably absent from traditional curricula, as the current instructional materials largely f...
doi.org
July 21, 2025 at 3:40 PM
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Call for Papers for the Special Issue on Big Data Sources in Educational Measurement:
shorturl.at/0H1QC

#EducationalMeasurement #Psychometrics #EdTech #CEJEME
Call for Papers: Special Issue on Big Data Sources in Educational Measurement
Call for Papers: Special Issue on Big Data Sources in Educational Measurement Chinese/English ...
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July 2, 2025 at 1:00 PM
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📢 The Chinese/English Journal of Educational Measurement and Evaluation (CEJEME) — an official journal of NCME — invites submissions for a special issue focused on big data sources in educational measurement. View the Call for Papers for detailed instructions and timeline.
July 2, 2025 at 1:00 PM
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In a recent article in CEJEME, He et al. apply clustering and network analysis to learning management system (LMS) event logs, identifying patterns in student engagement and their connection to academic success.

Learn more: doi.org/10.59863/FZR...

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Uncovering Dimensions of Learning Management System Event Logs: Insights from Exploratory Factor Analysis, Psychometric Network Analysis, and Consensus Hierarchical Clustering
Log data extracted from learning management systems (LMS) have become an increasingly valuable resource for understanding students’ learning behaviors. These data are unobtrusive, cost-effective, and ...
doi.org
March 31, 2025 at 7:43 PM
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In a recent article in CEJEME, Guo et al. investigate NAEP data to evaluate the effectiveness of digital tools in math assessments, offering insights into tool usage, student performance, and time management.

Learn more: doi.org/10.59863/YCH...

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Toward Better Digital Tool Designs to Assist Students on Math Assessments
Digital tools in digitally based math assessments are designed to help students solve math problems more effectively. However, inappropriate use of these tools can lead to negative outcomes. Using pro...
doi.org
March 26, 2025 at 5:25 PM
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In a recent article in CEJEME, Oyeniran compares two machine learning packages in R—caret and tidymodels.

Learn more: doi.org/10.59863/XXD...

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Comparison of Machine Learning Packages in R: An Application with Open Dataset
Machine learning has become a prominent approach for prediction in many fields of endeavor, including education. Python and R have become leading software while different packages have been developed ...
doi.org
December 30, 2024 at 8:45 PM
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In a recent article in CEJEME, Ormerod and Kwako explore how open-source, small-scale generative language models can be used with ‘GPU-poor’ computers for automated text scoring and feedback.

Learn more: doi.org/10.59863/OKU...

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Automated Text Scoring in the Age of Generative AI for the GPU-poor
Abstract Current research on generative language models (GLMs) for automated text scoring (ATS) has focused almost exclusively on querying proprietary models via Application Programming Interfaces (AP...
doi.org
December 23, 2024 at 1:55 PM
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In a recent article in CEJEME, Bulut et al. explore the integration of AI in educational measurement. They highlight transformative opportunities and ethical challenges such as fairness, bias, and transparency.

Learn more: doi.org/10.59863/MIQ...

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The Rise of Artificial Intelligence in Educational Measurement: Opportunities and Ethical Challenges
The integration of artificial intelligence (AI) in educational measurement has transformed assessment methods, allowing for automated scoring, swift content analysis, and personalized feedback through...
doi.org
December 20, 2024 at 1:35 PM