TY - JOUR
T1 - Statistical Applications in Educational Measurement
AU - Chang, Hua Hua
AU - Wang, Chun
AU - Zhang, Susu
N1 - Publisher Copyright:
© 2021 Annual Reviews Inc.. All rights reserved.
Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2021/3/7
Y1 - 2021/3/7
N2 - Educational measurement assigns numbers to individuals based on observed data to represent individuals educational properties such as abilities, aptitudes, achievements, progress, and performance. The current review introduces a selection of statistical applications to educational measurement, ranging from classical statistical theory (e.g., Pearson correlation and the Mantel-Haenszel test) to more sophisticated models (e.g., latent variable, survival, and mixture modeling) and statistical and machine learning (e.g., high-dimensional modeling, deep and reinforcement learning). Three main subjects are discussed: evaluations for test validity, computer-based assessments, and psychometrics informing learning. Specific topics include item bias detection, high-dimensional latent variable modeling, computerized adaptive testing, response time and log data analysis, cognitive diagnostic models, and individualized learning.
AB - Educational measurement assigns numbers to individuals based on observed data to represent individuals educational properties such as abilities, aptitudes, achievements, progress, and performance. The current review introduces a selection of statistical applications to educational measurement, ranging from classical statistical theory (e.g., Pearson correlation and the Mantel-Haenszel test) to more sophisticated models (e.g., latent variable, survival, and mixture modeling) and statistical and machine learning (e.g., high-dimensional modeling, deep and reinforcement learning). Three main subjects are discussed: evaluations for test validity, computer-based assessments, and psychometrics informing learning. Specific topics include item bias detection, high-dimensional latent variable modeling, computerized adaptive testing, response time and log data analysis, cognitive diagnostic models, and individualized learning.
KW - adaptive learning
KW - cognitive diagnostic models
KW - computerized adaptive testing
KW - educational measurement
KW - reliability
KW - response time
KW - validity
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U2 - 10.1146/annurev-statistics-042720-104044
DO - 10.1146/annurev-statistics-042720-104044
M3 - Article
AN - SCOPUS:85102383334
SN - 2326-831X
VL - 8
SP - 439
EP - 461
JO - Annual Review of Statistics and Its Application
JF - Annual Review of Statistics and Its Application
ER -