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Wang, Lin; Qian, Jiahe; Lee, Yi-Hsuan – ETS Research Report Series, 2018
Educational assessment data are often collected from a set of test centers across various geographic regions, and therefore the data samples contain clusters. Such cluster-based data may result in clustering effects in variance estimation. However, in many grouped jackknife variance estimation applications, jackknife groups are often formed by a…
Descriptors: Item Response Theory, Scaling, Equated Scores, Cluster Grouping
Khayi, Nisrine Ait; Rus, Vasile – International Educational Data Mining Society, 2019
In this paper, we applied a number of clustering algorithms on pretest data collected from 264 high-school students. Students took the pre-test at the beginning of a 5-week experiment in which they interacted with an intelligent tutoring system. The primary goal of this work is to identify clusters of students exhibiting similar knowledge…
Descriptors: High School Students, Cluster Grouping, Prior Learning, Intelligent Tutoring Systems
Spybrook, Jessaca; Kelcey, Ben; Dong, Nianbo – Society for Research on Educational Effectiveness, 2016
Cluster randomized trials (CRTs), or studies in which intact groups of individuals are randomly assigned to a condition, are becoming more common in evaluation studies of educational programs. A specific type of CRT in which clusters are randomly assigned to treatment within blocks or sites, known as multisite cluster randomized trials (MSCRTs),…
Descriptors: Statistical Analysis, Computation, Randomized Controlled Trials, Cluster Grouping
Guasch, Marc; Haro, Juan; Boada, Roger – Psicologica: International Journal of Methodology and Experimental Psychology, 2017
With the increasing refinement of language processing models and the new discoveries about which variables can modulate these processes, stimuli selection for experiments with a factorial design is becoming a tough task. Selecting sets of words that differ in one variable, while matching these same words into dozens of other confounding variables…
Descriptors: Factor Analysis, Language Processing, Design, Cluster Grouping
Niu, Ke; Niu, Zhendong; Zhao, Xiangyu; Wang, Can; Kang, Kai; Ye, Min – International Educational Data Mining Society, 2016
User clustering algorithms have been introduced to analyze users' learning behaviors and help to provide personalized learning guides in traditional Web-based learning systems. However, the explicit and implicit coupled interactions, which means the correlations between user attributes generated from learning actions, are not considered in these…
Descriptors: Web Based Instruction, Student Needs, User Needs (Information), Mathematics
Weiss, Michael J.; Lockwood, J. R.; McCaffrey, Daniel F. – Journal of Research on Educational Effectiveness, 2016
In the "individually randomized group treatment" (IRGT) experimental design, individuals are first randomly assigned to a treatment arm or a control arm, but then within each arm, are grouped together (e.g., within classrooms/schools, through shared case managers, in group therapy sessions, through shared doctors, etc.) to receive…
Descriptors: Randomized Controlled Trials, Error of Measurement, Control Groups, Experimental Groups