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Haudek, Kevin C.; Prevost, Luanna B.; Moscarella, Rosa A.; Merrill, John; Urban-Lurain, Mark – CBE - Life Sciences Education, 2012
Students' writing can provide better insight into their thinking than can multiple-choice questions. However, resource constraints often prevent faculty from using writing assessments in large undergraduate science courses. We investigated the use of computer software to analyze student writing and to uncover student ideas about chemistry in an…
Descriptors: Chemistry, Biology, Introductory Courses, Science Instruction
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Cechinel, Cristian; Sanchez-Alonso, Salvador; Garcia-Barriocanal, Elena – Computers & Education, 2011
The continuously growth of learning resources available in on-line repositories has raised the concern for the development of automated methods for quality assessment. The current existence of on-line evaluations in such repositories has opened the possibility of searching for statistical profiles of highly-rated resources that can be used as…
Descriptors: Discriminant Analysis, Educational Resources, Classification, Automation
Moffitt, Kevin Christopher – ProQuest LLC, 2011
The three objectives of this dissertation were to develop a question type model for predicting linguistic features of responses to interview questions, create a tool for linguistic analysis of documents, and use lexical bundle analysis to identify linguistic differences between fraudulent and non-fraudulent financial reports. First, The Moffitt…
Descriptors: Cues, Verbs, Natural Language Processing, Discriminant Analysis
Meshbane, Alice; Morris, John D. – 1997
A method for comparing the cross-validated classification accuracy of Fisher's linear classification functions (FLCFs) and the least absolute deviation is presented under varying data conditions for the two-group classification problem. With this method, separate-group as well as total-sample proportions of current classifications can be compared…
Descriptors: Classification, Comparative Analysis, Computer Software, Correlation
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Koslowsky, Meni – Educational and Psychological Measurement, 1985
The technique of generalizing sample results in a classification study to large subpopulations of unequal sizes was examined. The usual output from the discriminant analysis routine in the Statistical Package for the Social Sciences was extended to handle the present statistical problems. Advantages of the technique were discussed. (Author/DWH)
Descriptors: Classification, Computer Software, Discriminant Analysis, Generalization