Stochastic ordering using the latent trait and the sum score in polytomous IRT models

In a restricted class of item response theory (IRT) models for polytomous items the unweighted total score has monotone likelihood ratio (MLR) in the latent trait. MLR implies two stochastic ordering (SO) properties, denoted SOM and SOL, which are both weaker than MLR, but very useful for measurement with IRT models. Therefore, these SO properties are investigated for a broader class of IRT models for which the MLR property does not hold.In this study, first a taxonomy is given for nonparametric and parametric models for polytomous items based on the hierarchical relationship between the models. Next, it is investigated which models have the MLR property and which have the SO properties. It is shown that all models in the taxonomy possess the SOM property. However, counterexamples illustrate that many models do not, in general, possess the even more useful SOL property.Hemker's research was supported by the Netherlands Research Council, Grant 575-67-034. Junker's research was supported in part by the National Institutes of Health, Grant CA54852, and by the National Science Foundation, Grant DMS-94.04438.     

Need probability affects retention: A direct demonstration

Recent memory theory has emphasized the concept ofneed probability—that is, the probability that a given piece of learned information will be tested at some point in the future. It has been proposed that, in real-world situations, need probability declines over time and that the memory-loss rate is calibrated to match the progressive reduction in need probability (J. R. Anderson & Schooler, 1991). The present experiments were designed to examine the influence of the slope of the need-probability curve on the slope of the retention curve. On each of several trials, subjects memorized a list of digits, then retained the digits in memory for 1, 2, 4, 8, or 16 sec. Some trials ended with a recall test; other trials ended with the message, “no test.” In Experiment 1, the likelihood of encountering a memory test (i.e., the need probability) was made to either increase or decrease as the retention interval increased; in Experiment 2, need probability either was flat (invariant across retention intervals) or decreased as the retention interval increased. The results indicated that the shape of the need-probability curve influenced the slope of the retention curve (Experiment 1) and that the effect became larger as the experimental session progressed (Experiment 2). The findings support the notion that memory adapts to need probabilities and that the rate of forgetting is influenced by the slope of the need-probability curve. In addition, all of the forgetting curves approximated a power function, suggesting that need probability influences the slope but not the form of forgetting.     

Hippocampal synaptic plasticity during instrumental learning

present research examined the role of hippocampal NMDA-dependent synaptic potentiation on appetitive instrumental conditioning under a continuous reinforcement schedule. In the first experiment, low (.025 mg.kg) or moderate (.05 mg/kg) dosages of the NMDA receptor antagonist, MK801, failed to increase the number of training days required to reach acquisition criterion; number of training days required to reach criterion for extinction were also unaffected. In the second experiment, a higher dosage (.10 mg/kg) of MK801 or induction of long-term potentiation failed to alter the number of responses occurring during acquisition. These data suggest that hippocampal synaptic potentiation does not play a prominent role in instrumental learning with simple contingency conditions. It is suggested that hippocampal LTP reflects a perceptual process that contributes differentially to spatial cognition, classical and instrumental conditioning.     

Neural Network Models and Mechanisms of Strategy Development

The focus of this paper is mechanisms that may be responsible for intellectual and developmental differences in the cognitive strategies of typical and atypical children, including those with mental retardation. The discussion of these mechanisms is based on behavioral experiments on external memory strategies and on a set of neural network models designed for these tasks. Following the review of the external memory research, the rationale for using neural network models, how they have been used in other research, and their specific application to intellectual and developmental differences in external memory, including the results of several simulations, are reviewed. This is followed by a discussion of the mechanisms of intellectual differences and developmental change included in the models and some challenges for this type of modeling. Neural network modeling is discussed as an asset to research on cognitive development.     

Guest editors'' commentary: Japanese socialization research in review

This focus section has presented Japanese research on a variety of socialization agents and contexts, including mothering, fathering, peers and multiple-caretakers in families and institutions. The reader is encouraged to compare the papers, discover the theoretical and applied implications of each study for child development in the reader's own culture, and to pursue collaborations with the outstanding young Japanese contributors. We conclude with brief comments on each of the five articles, discussing their limitations, most significant findings, theoretical importance, and implications for subsequent research.