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Ranger, Jochen; Schmidt, Nico; Wolgast, Anett – Educational and Psychological Measurement, 2023
Recent approaches to the detection of cheaters in tests employ detectors from the field of machine learning. Detectors based on supervised learning algorithms achieve high accuracy but require labeled data sets with identified cheaters for training. Labeled data sets are usually not available at an early stage of the assessment period. In this…
Descriptors: Identification, Cheating, Information Retrieval, Tests
Franz Classe; Christoph Kern – Educational and Psychological Measurement, 2024
We develop a "latent variable forest" (LV Forest) algorithm for the estimation of latent variable scores with one or more latent variables. LV Forest estimates unbiased latent variable scores based on "confirmatory factor analysis" (CFA) models with ordinal and/or numerical response variables. Through parametric model…
Descriptors: Algorithms, Item Response Theory, Artificial Intelligence, Factor Analysis
Sijia Huang; Dubravka Svetina Valdivia – Educational and Psychological Measurement, 2024
Identifying items with differential item functioning (DIF) in an assessment is a crucial step for achieving equitable measurement. One critical issue that has not been fully addressed with existing studies is how DIF items can be detected when data are multilevel. In the present study, we introduced a Lord's Wald X[superscript 2] test-based…
Descriptors: Item Analysis, Item Response Theory, Algorithms, Accuracy
Yongze Xu – Educational and Psychological Measurement, 2024
The questionnaire method has always been an important research method in psychology. The increasing prevalence of multidimensional trait measures in psychological research has led researchers to use longer questionnaires. However, questionnaires that are too long will inevitably reduce the quality of the completed questionnaires and the efficiency…
Descriptors: Item Response Theory, Questionnaires, Generalization, Simulation

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