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ABSTRACTIt is difficult to devise a statistical test to detect one student copying from another. Many prior efforts falsely accuse students of cheating. A general methodology based on the quantal choice model of decision theory overcomes these problems. Three steps are involved: (1) for each item estimate the probability and the variance that a given respondent will select each response, (2) for pairs of respondents, these probabilities determine the expected number of matches, and (3) compare the critical value to the number of items matched. Methods differ based on the probability estimation technique. Four methods (simple frequencies, Frary, Tideman, and Watts modification [8], logit, and multinomial probit) are compared on theoretical and empirical grounds. Theory and results show that it is crucial to incorporate the variance of the probability estimates. The probit model has theoretical advantages over the other methods and produces more accurate results.

ABSTRACTOnline education and computer‐assisted instruction (CAI) have existed for years, but few general tools exist to help instructors create and evaluate lessons. Are these tools sufficient? Specifically, what elements do instructors want to see in online testing tools? This study asked instructors from various disciplines to identify and evaluate the importance of several features that they want to see in testing tools. Along with standard elements, the respondents evaluated the importance of more advanced elements including adaptive responses and programmability, which would be used to add responsiveness and intelligence to provide more tailored questions and assistance. A latent variable analysis of the detailed model was performed and the results reveal that several advanced features not commonly available today would be useful to many instructors—particularly to handle higher level courses. Instructors teaching lower level courses tended to emphasize basic testing and simple grading features. The features were grouped into nine categories: question formats, feedback, programmability, grading, question bank, page display capabilities, platform, data analysis, and security. The results of the study examine the relative importance of the categories as well as the detail items within each category.

ABSTRACTTeaching and learning database design is difficult for both instructors and students. Students need to solve many problems with feedback and corrections. A Web‐based specialized expert system was created to enable students to create designs online and receive immediate feedback. An experiment testing the system shows that it significantly enhances student learning. The system also provides a more neutral learning environment in terms of personal factors such as gender and prior class work.

ABSTRACTA model evaluating consumer preferences for multiattribute products is derived. The model possesses the following features: (1) the method works for existing products; (2) the input data require only overall product rankings and attribute rankings; (3) the distribution of part worths (utility) for particular attributes is derived and used to judge the trade‐offs among different attributes; (4) the procedure can be implemented with existing software; and (5) the attributes do not need to be quantifiable.

ABSTRACTUsing a regression approach to discriminant analysis is often incorrect because it forces the use of a binary dependent variable which violates virtually any distributional assumption for a linear model. However, assuming a Laplace distribution in an LP framework leads to a theoretical foundation for MSD discriminant analysis.