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Journal of Experimental… | 6 |
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Baldwin, Lee | 1 |
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DuCette, Joseph | 1 |
Hynes, Kevin | 1 |
Moy, Mabel L. Y. | 1 |
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Wolk, Stephen | 1 |
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Moy, Mabel L. Y.; Barcikowski, Robert S. – Journal of Experimental Education, 1974
The purpose of this study was to help determine optimum item sampling plans for use in school evaluation projects. (Author)
Descriptors: Data Analysis, Evaluation Methods, Guidelines, Item Sampling

Asher, William; Hynes, Kevin – Journal of Experimental Education, 1982
An evaluation of open education was shown to produce misleading results due to probable regression phenomena. These questionable results are now spread throughout the literature of education, sociology, and psychology. Researchers are advised to review, not merely summarize, prior articles. (Author/PN)
Descriptors: Data Analysis, Evaluation Methods, Open Education, Regression (Statistics)

Blumberg, Carol Joyce; Porter, Andrew C. – Journal of Experimental Education, 1983
The general class of continuous growth models are described and examples representative of growth models suggested for various types of academic and/or physical growth are given. The fan spread hypothesis is discussed in relationship to natural growth models, as well as differential linear growth. (PN)
Descriptors: Achievement Gains, Data Analysis, Evaluation Methods, Hypothesis Testing

DuCette, Joseph; Wolk, Stephen – Journal of Experimental Education, 1972
Test format can influence test performance as well as the nature and extent of general classroom achievement. (Authors)
Descriptors: Data Analysis, Essay Tests, Evaluation Methods, Graduate Students

Owens, Mary Seymour – Journal of Experimental Education, 1971
The purpose of this study was to compare the perceptions of teacher competence within and among three groups of educators as measured by the interview scales of the Instrument for the Observation of Teaching Activities (IOTA). (Auhor)
Descriptors: Analysis of Variance, Data Analysis, Evaluation Methods, Interviews

Baldwin, Lee; And Others – Journal of Experimental Education, 1984
Within-class regression is a method, developed in this paper, of comparing a large number of nonequivalent groups. This study indicated that within-class regression was a less biased method of data analysis and will yield more accurate estimates of treatment effects than analysis of covariance. (PN)
Descriptors: Analysis of Covariance, Data Analysis, Educational Research, Evaluation Methods