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Stella Y. Kim; Sungyeun Kim – Educational Measurement: Issues and Practice, 2025
This study presents several multivariate Generalizability theory designs for analyzing automatic item-generated (AIG) based test forms. The study used real data to illustrate the analysis procedure and discuss practical considerations. We collected the data from two groups of students, each group receiving a different form generated by AIG. A…
Descriptors: Generalizability Theory, Automation, Test Items, Students
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Yaosheng Lou; Kimberly F. Colvin – Discover Education, 2025
Predicting student performance has been a critical focus of educational research. With an effective predictive model, schools can identify potentially at-risk students and implement timely interventions to support student success. Recent developments in educational data mining (EDM) have introduced several machine learning techniques that can…
Descriptors: Educational Research, Data Collection, Performance, Prediction
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Gregory Chernov – Evaluation Review, 2025
Most existing solutions to the current replication crisis in science address only the factors stemming from specific poor research practices. We introduce a novel mechanism that leverages the experts' predictive abilities to analyze the root causes of replication failures. It is backed by the principle that the most accurate predictor is the most…
Descriptors: Replication (Evaluation), Prediction, Scientific Research, Failure
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Hongwen Guo; Matthew S. Johnson; Daniel F. McCaffrey; Lixong Gu – ETS Research Report Series, 2024
The multistage testing (MST) design has been gaining attention and popularity in educational assessments. For testing programs that have small test-taker samples, it is challenging to calibrate new items to replenish the item pool. In the current research, we used the item pools from an operational MST program to illustrate how research studies…
Descriptors: Test Items, Test Construction, Sample Size, Scaling
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Ting Zhang; Paul Bailey; Yuqi Liao; Emmanuel Sikali – Large-scale Assessments in Education, 2024
The EdSurvey package helps users download, explore variables in, extract data from, and run analyses on large-scale assessment data. The analysis functions in EdSurvey account for the use of plausible values for test scores, survey sampling weights, and their associated variance estimator. We describe the capabilities of the package in the context…
Descriptors: National Competency Tests, Information Retrieval, Data Collection, Test Validity
Christine G. Casey, Editor – Centers for Disease Control and Prevention, 2024
The "Morbidity and Mortality Weekly Report" ("MMWR") series of publications is published by the Office of Science, Centers for Disease Control and Prevention (CDC), U.S. Department of Health and Human Services. Articles included in this supplement are: (1) Overview and Methods for the Youth Risk Behavior Surveillance System --…
Descriptors: High School Students, At Risk Students, Health Behavior, National Surveys
Mariann Lemke; Dan Murphy; Aaron Soo Ping Chow; Angela Acuña – WestEd, 2024
Beginning with the 2020/21 school year, the Massachusetts Department of Elementary and Secondary Education (DESE) began an ongoing effort to collect and analyze literacy screening assessment data from schools and districts participating in certain state grants to inform improvement efforts. Grantee schools and districts that provide literacy…
Descriptors: Grants, Benchmarking, At Risk Students, Reading Difficulties
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Mihyun Son; Minsu Ha – Education and Information Technologies, 2025
Digital literacy is essential for scientific literacy in a digital world. Although the NGSS Practices include many activities that require digital literacy, most studies have examined digital literacy from a generic perspective rather than a curricular context. This study aimed to develop a self-report tool to measure elements of digital literacy…
Descriptors: Test Construction, Measures (Individuals), Digital Literacy, Scientific Literacy
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Rodney McCrowre; Burcu Adivar – Industry and Higher Education, 2024
This study aims to analyse the impact of demographic and educational factors on in digital upskilling. We address the relationship between digital skills, critical thinking skills and the student learning experience in courses with embedded upskilling programs. Statistical analysis and exploratory research are used to analyse the data collected by…
Descriptors: Digital Literacy, Skill Development, Competence, Critical Thinking