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Patel, Nirmal; Sharma, Aditya; Shah, Tirth; Lomas, Derek – Journal of Educational Data Mining, 2021
Process Analysis is an emerging approach to discover meaningful knowledge from temporal educational data. The study presented in this paper shows how we used Process Analysis methods on the National Assessment of Educational Progress (NAEP) test data for modeling and predicting student test-taking behavior. Our process-oriented data exploration…
Descriptors: Learning Analytics, National Competency Tests, Evaluation Methods, Prediction
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Wang, Chun; Fan, Zhewen; Chang, Hua-Hua; Douglas, Jeffrey A. – Journal of Educational and Behavioral Statistics, 2013
The item response times (RTs) collected from computerized testing represent an underutilized type of information about items and examinees. In addition to knowing the examinees' responses to each item, we can investigate the amount of time examinees spend on each item. Current models for RTs mainly focus on parametric models, which have the…
Descriptors: Reaction Time, Computer Assisted Testing, Test Items, Accuracy
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Feng, Mingyu, Ed.; Käser, Tanja, Ed.; Talukdar, Partha, Ed. – International Educational Data Mining Society, 2023
The Indian Institute of Science is proud to host the fully in-person sixteenth iteration of the International Conference on Educational Data Mining (EDM) during July 11-14, 2023. EDM is the annual flagship conference of the International Educational Data Mining Society. The theme of this year's conference is "Educational data mining for…
Descriptors: Information Retrieval, Data Analysis, Computer Assisted Testing, Cheating
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Levy, Roy; Mislevy, Robert J. – International Journal of Testing, 2004
The challenges of modeling students' performance in computer-based interactive assessments include accounting for multiple aspects of knowledge and skill that arise in different situations and the conditional dependencies among multiple aspects of performance. This article describes a Bayesian approach to modeling and estimating cognitive models…
Descriptors: Computer Assisted Testing, Markov Processes, Computer Networks, Bayesian Statistics
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Wang, Xiaohui; Bradlow, Eric T.; Wainer, Howard – ETS Research Report Series, 2005
SCORIGHT is a very general computer program for scoring tests. It models tests that are made up of dichotomously or polytomously rated items or any kind of combination of the two through the use of a generalized item response theory (IRT) formulation. The items can be presented independently or grouped into clumps of allied items (testlets) or in…
Descriptors: Computer Assisted Testing, Statistical Analysis, Test Items, Bayesian Statistics
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von Davier, Matthias – ETS Research Report Series, 2005
Probabilistic models with more than one latent variable are designed to report profiles of skills or cognitive attributes. Testing programs want to offer additional information beyond what a single test score can provide using these skill profiles. Many recent approaches to skill profile models are limited to dichotomous data and have made use of…
Descriptors: Models, Diagnostic Tests, Language Tests, Language Proficiency
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Stricker, Lawrence J.; Rock, Donald A.; Lee, Yong-Won – ETS Research Report Series, 2005
This study assessed the factor structure of the LanguEdge™ test and the invariance of its factors across language groups. Confirmatory factor analyses of individual tasks and subsets of items in the four sections of the test, Listening, Reading, Speaking, and Writing, was carried out for Arabic-, Chinese-, and Spanish-speaking test takers. Two…
Descriptors: Factor Structure, Language Tests, Factor Analysis, Semitic Languages