The grammars of natural languages may be learned by using genetic algorithm systems such as LUST (Linguistics Using Sexual Techniques) that reproduce and mutate grammatical rules and parts-of-speech tags. In document retrieval or filtering systems, applying tags to the list of terms representing a document provides additional information about…

Discusses computational studies of learning in artificial neural networks and findings that may provide insights into the learning abilities of the human brain. Describes efforts to test theories about brain information processing, using artificial neural networks. Vignettes include information concerning how a neural network represents…

Describes a computer algorithm used in South Carolina public schools that links year-to-year student test records. The process of matching data files is explained, computer matches are compared with matches based on numeric student identification numbers to determine accuracy, and other applications in support of educational research are…

Discussion of clustering of documents and queries in information retrieval systems focuses on the use of a genetic algorithm to adapt subject descriptions so that documents become more effective in matching relevant queries. Various types of clustering are explained, and simulation experiments used to test the genetic algorithm are described. (27…

A method is presented and illustrated for simultaneously generating multiple tests with similar characteristics from the item bank by using binary programing techniques. The parallel tests are created to match an existing seed test item for item and to match user-supplied taxonomic specifications. (SLD)

The algorithm developed by B. A. Schneider (1980) for analysis of paired comparisons of psychological intervals is replaced by one proposed by R. M. Johnson. Monte Carlo simulations of pairwise dissimilarities and pairwise conjoint effects show that Johnson's algorithm can provide good metric recovery. (SLD)

Based on Piaget's theory that children acquire number concepts by constructing them from within, the authors conclude that teaching algorithms harms mathematics learning. A better approach is allowing them to construct their own logico-mathematical knowledge and invent their own efficient procedures. (JOW)

Presents a description and evaluation of a microcomputer-based system designed to diagnose errors in basic algorithmic procedures made by students in a college remedial mathematics class. The paper-and-pencil diagnostic test is described, and results of pretests and posttests for the computer group and control group are discussed. (five…

Two algorithms that automatically select subsets of variables (PACE algorithm) and reference variables (Fabin estimators), respectively, used for the noniterative estimators are presented. The PACE algorithm is based on a nonsymmetric matrix sweep operator. A Monte Carlo experiment compares the relative performance of these estimators and others.…

Describes the use of loglinear statistical models in the field of informetrics, especially for the analysis of information systems. A detailed example is given of developing a model based on loglinear analysis to determine book acquisition patterns in libraries, including mathematical considerations and algorithms. (19 references) (LRW)

A mathematical formula is introduced for the effect of integrating data. A method is then derived to eliminate the effect from correlations of variables, including mean composites, thus allowing for a clustering algorithm that requires allocation of variables according to the magnitude of their correlations. Examples illustrate the procedure. (SLD)

A probabilistic choice model, based on L. L. Thurstone's Law of Comparative Judgment Case V, is developed for paired comparisons data about psychological stimuli. The model assumes that each stimulus is measured on a small number of physical variables. An algorithm for estimating parameters is illustrated with real data. (SLD)

Polynomial algorithms are presented that are used to solve selected problems in test theory, and computational results from sample problems with several hundred decision variables are provided that demonstrate the benefits of these algorithms. The algorithms are based on optimization theory in networks (graphs). (SLD)

A model for solving very large item selection problems is presented. The model builds on binary programming applied to test construction. A heuristic for selecting items that satisfy the constraints in the model is also presented, and various problems are solved using the model and heuristic. (SLD)

Examines solutions presented by preservice teachers for solving graphical and numerical problems involving the arithmetic mean. Participants presented two methods: algorithmic computation and balancing deviations about the mean. A significant difference was found between science and mathematics preservice teachers in the use of balancing…