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Ethan Kutlu; Hyoju Kim; Bob McMurray – Developmental Science, 2026
A critical aspect of spoken language development is learning to categorize the sounds of the child's language(s). This process was thought to develop early during infancy to set the stage for the later development of higher-level aspects of language (e.g., vocabulary, syntax). However, many recent studies have shown that speech categorization…
Descriptors: Oral Language, Language Acquisition, Vocabulary Development, Child Language
Cui, Yang; Chu, Man-Wai; Chen, Fu – Journal of Educational Data Mining, 2019
Digital game-based assessments generate student process data that is much more difficult to analyze than traditional assessments. The formative nature of game-based assessments permits students, through applying and practicing the targeted knowledge and skills during gameplay, to gain experiences, receive immediate feedback, and as a result,…
Descriptors: Educational Games, Student Evaluation, Data Analysis, Bayesian Statistics
Schochet, Peter Z.; Chiang, Hanley S. – Journal of Educational and Behavioral Statistics, 2013
This article addresses likely error rates for measuring teacher and school performance in the upper elementary grades using value-added models applied to student test score gain data. Using a realistic performance measurement system scheme based on hypothesis testing, the authors develop error rate formulas based on ordinary least squares and…
Descriptors: Classification, Measurement, Elementary School Teachers, Elementary Schools
PDF pending restorationvan der Linden, Wim J. – 1986
Differences between traditional linear regression and a Bayesian approach to classification are discussed. Classification consists of assigning subjects to one of several available treatments on the basis of their test scores when the success of each treatment is measured by a different criterion. Formulating this problem as an empirical Bayes…
Descriptors: Achievement Tests, Bayesian Statistics, Classification, Decision Making
Vos, Hans J. – 1994
As part of a project formulating optimal rules for decision making in computer assisted instructional systems in which the computer is used as a decision support tool, an approach that simultaneously optimizes classification of students into two treatments, each followed by a mastery decision, is presented using the framework of Bayesian decision…
Descriptors: Achievement Tests, Bayesian Statistics, Classification, Computer Managed Instruction

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