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Bosch, Nigel – Journal of Educational Data Mining, 2021
Automatic machine learning (AutoML) methods automate the time-consuming, feature-engineering process so that researchers produce accurate student models more quickly and easily. In this paper, we compare two AutoML feature engineering methods in the context of the National Assessment of Educational Progress (NAEP) data mining competition. The…
Descriptors: Accuracy, Learning Analytics, Models, National Competency Tests
White, Sheida; Kim, Young Yee; Chen, Jing; Liu, Fei – National Center for Education Statistics, 2015
This study examined whether or not fourth-graders could fully demonstrate their writing skills on the computer and factors associated with their performance on the National Assessment of Educational Progress (NAEP) computer-based writing assessment. The results suggest that high-performing fourth-graders (those who scored in the upper 20 percent…
Descriptors: National Competency Tests, Computer Assisted Testing, Writing Tests, Grade 4
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McCurry, Doug – Assessing Writing, 2010
This article considers the claim that machine scoring of writing test responses agrees with human readers as much as humans agree with other humans. These claims about the reliability of machine scoring of writing are usually based on specific and constrained writing tasks, and there is reason for asking whether machine scoring of writing requires…
Descriptors: Writing Tests, Scoring, Interrater Reliability, Computer Assisted Testing
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Page, Ellis Batten – Journal of Experimental Education, 1994
National Assessment of Educational Progress writing sample essays from 1988 and 1990 (495 and 599 essays) were subjected to computerized grading and human ratings. Cross-validation suggests that computer scoring is superior to a two-judge panel, a finding encouraging for large programs of essay evaluation. (SLD)
Descriptors: Computer Assisted Testing, Computer Software, Essays, Evaluation Methods
McGuire, Dennis P. – 1984
Efficient methods of using the Statistical Package for the Social Sciences (SPSS) to analyze National Assessment of Educational Progress (NAEP) data files are discussed. One error in the NAEP SPSS file is discussed, and another error (which may be system-dependent) is mentioned. In addition, purely mathematical methods are used to address the…
Descriptors: Achievement Tests, Computer Software, Educational Assessment, Elementary Secondary Education
Nandakumar, Ratna – 1992
The phenomenon of simultaneous differential item functioning (DIF) amplification and cancellation and the role of the SIBTEST computer program in detecting it were studied. A variety of simulated test data was generated for this purpose. In addition, the following real test data were used: (1) American College Testing program data for 2,115 males…
Descriptors: Black Students, Comparative Testing, Computer Simulation, Computer Software
National Assessment of Educational Progress, Princeton, NJ. – 1987
This document contains the codebooks and data record layouts for the 1985-86 Public-Use Data Tapes, Version 1.0. The Public-Use data tapes are created by the National Assessment of Educational Progress (NAEP) to provide outside researchers access to NAEP data. This book provides coded data collected on and from third graders and 9-year-olds via…
Descriptors: Academic Achievement, Computer Software, Computer Storage Devices, Databases
Johnson, Eugene G.; And Others – 1987
This document is the users' guide for Version 1.0 of the Public-Use data tapes compiled by the National Assessment of Educational Progress (NAEP), 1985-86. The Public-Use tapes are produced to allow outside researchers access to the NAEP data. The tapes accompanying this guide, one for grade 3/age 9, one for grade 7/age 13, and one for grade…
Descriptors: Academic Achievement, Computer Software, Computer Storage Devices, Data Analysis