The authors present a computational model that builds a holographic lexicon representing both word meaning and word order from unsupervised experience with natural language. The model uses simple convolution and superposition mechanisms to learn distributed holographic representations for words. The structure of the resulting lexicon can account…

This submission contains the Proceedings of the 2011 Annual Meeting of the Canadian Mathematics Education Study Group (CMESG), held at Memorial University of Newfoundland in St. John's, Newfoundland. The CMESG is a group of mathematicians and mathematics educators who meet annually to discuss mathematics education issues at all levels of learning.…

We describe the development of a course to teach modeling and mathematical analysis skills to students of biology and to teach biology to students with strong backgrounds in mathematics, physics, or engineering. The two groups of students have different ways of learning material and often have strong negative feelings toward the area of knowledge…

We discuss the introduction and teaching of partial differential equations (heat and wave equations) via modeling physical phenomena, using a new approach that encompasses constructing difference equations and implementing these in a spreadsheet, numerically solving the partial differential equations using the numerical differential equation…

We present results of an investigation of university students' development of mathematical models of motion in a physical science course for preservice teachers and graduate students in science and mathematics education. Although some students were familiar with the standard concepts of position, velocity, and acceleration from physics classes,…

Interventions that aim to promote social competence, reduce problem behavior, and improve school climate are common at all levels of schooling. This whole-school focus, coupled with researchers' concerns about contamination or spillover effects in evaluations that randomly assign classrooms or students to conditions, as well as advances in…

A mathematical model of operant choice, the generalized matching law was used to analyze play-calling data from the 2004 National Football League season. In all analyses, the relative ratio of passing to rushing plays was examined as a function of the relative ratio of reinforcement, defined as yards gained, from passing versus rushing. Different…

This research derives simplified formulas for computing the standard error of the frequency estimation method for equating score distributions that are continuized using a uniform or Gaussian kernel function (P. W. Holland, B. F. King, and D. T. Thayer, 1989; Holland and Thayer, 1987). The simplified formulas are applicable to equating both the…

Most researchers using analysis of variance (ANOVA) use a fixed-effects model. However, a random- or mixed-effects model may be a more appropriate fit for many research designs. One benefit of the random- and mixed-effects models is that they yield more generalizable results. This paper focuses on the similarities and differences between the…

The redundancy statistic (Rd) is discussed in relation to canonical correlation analysis. The index is a measure of the variance of one set of variables predicted from the linear combination of the other set of variables. A small data set (N=6) from the work of D. Clark (1975) was analyzed using SPSS-X. Two sets of two variables each were…

A model of word occurrences in documents is presented in the context of a model information system. (Author/PF)

A statistical description of a text retrieval system allows the derivation of a unique and measurable performance criterion that, in turn, may be used in discussing various parameters of systems performance. (Author/PF)

THIS VOLUME DEALS WITH THE BIVARIATE NORMAL DISTRIBUTION. THE AUTHOR MAKES A DISTINCTION BETWEEN DISTRIBUTION AND DENSITY FROM WHICH HE DEVELOPS THE CONSEQUENCES OF THIS DISTINCTION FOR HYPOTHESIS TESTING. OTHER ENTRIES IN THIS SERIES ARE ED 003 044 AND ED 003 045. (JK)

Multicollinearity refers to the presence of highly intercorrelated independent variables in structural equation models, that is, models estimated by using techniques such as least squares regression and maximum likelihood. There is a problem of multicollinearity in both the natural and social sciences where theory formulation and estimation is in…