Discusses automatic thesaurus construction and characterizes the statistical behavior of terms by using an inference network. Highlights include low-frequency terms and data sparseness, Bayesian networks, collocation maps and term similarity, constructing a thesaurus from a collocation map, and experiments with test collections. (Author/LRW)

Formulates optimal sequential rules for mastery testing using an approach derived from Bayesian sequential decision theory to consider both threshold and linear loss structures. Adopts the binomial probability distribution as the psychometric model. Provides an empirical example for concept-learning in medicine. (SLD)

For complex educational assessments, there is an increasing use of item families, which are groups of related items. Calibration or scoring in an assessment involving item families requires models that can take into account the dependence structure inherent among the items that belong to the same item family. This article extends earlier works in…

Explains how the Gibbs sampler can be applied to obtain a sample from the posterior distribution over the parameters of a structural equation model. Presents statistics to use to summarize marginal posterior densities and model checks using posterior predictive p-values. (SLD)

Nonlinear latent variable models are specified that include quadratic forms and interactions of latent regressor variable as special cases. To estimate the parameters, the models are put in a Bayesian framework with conjugate priors for the parameters. The proposed estimation methods are illustrated by two simulation studies. (SLD)

The collection of repeated measures in psychological research is one of the most common data collection formats employed in survey and experimental research. The behavioral decision theory literature documents the existence of the dynamic evolution of preferences that occur over time and experience due to learning, exposure to additional…

A scheme is described for locally Bayesian parameter updating in models structured as successions of component functions. The essential idea is to back-propagate the target data to interior modules, such that an interior component's target is the input to the next component that maximizes the probability of the next component's target. Each layer…

The DA-T Gibbs sampler is proposed by Maris and Maris (2002) as a Bayesian estimation method for a wide variety of "Item Response Theory (IRT) models". The present paper provides an expository account of the DA-T Gibbs sampler for the 2PL model. However, the scope is not limited to the 2PL model. It is demonstrated how the DA-T Gibbs…

This study examines how high school students were affected by having an openly gay teacher and compares its results to a previous study (Rofes, 2000). The author's lesbian, gay, or bisexual students experienced a sense of relief that they could finally feel comfortable about themselves, as well as feeling happy that others in the school were…

Research suggests effective classroom ICT integration occurs through needs-based, collaborative professional development (Chandra-Handa, 2001; Cuttance, 2001; Figg, 2000; Gibson, Oberg, & Pelz, 1999; Gross, 2000; Haughey, 2002). A community of practice (CoP) (Wenger, 1998; Wenger, McDermott, & Snyder, 2002) can be an effective mode of such…

This study investigated statistical methods for identifying errors in Bayesian networks (BN) with latent variables, as found in intelligent cognitive assessments. BN, commonly used in artificial intelligence systems, are promising mechanisms for scoring constructed-response examinations. The success of an intelligent assessment or tutoring system…

Presents a Bayesian approach to the evaluation of person fit in item response theory (IRT) models. Works the procedure in detail for the three parameter normal ogive model, but shows that the procedure can be generalized to many other IRT models. (SLD)

A model for simultaneous optimization of combinations of test-based decisions in psychology and education is proposed using Bayesian decision theory. Weak and strong rules are distinguished for a decision model that consists of a combination of placement and mastery decisions. (SLD)

Fully and partially ranked data arise in a variety of contexts. From a Bayesian perspective, attention has focused on distance-based models; in particular, the Mallows model and extensions thereof. In this paper, a class of prior distributions, the "Binary Tree," is developed on the symmetric group. The attractive features of the class are: it…

A specific application of a general paradigm described by R. D. Cook (1986) and R. McCulloch (1985) in assessing local influence is given. Snow geese flock size is estimated as "X" by an observer and "Y" by a photograph. "Y" is believed to be the true flock size. The problem is to obtain true flock size "Z"…