Multiplicative validity generalization model: Accuracy of estimates as a function of sample size and mean, variance, and shape of distribution of true validities.

Used simulation techniques to study the accuracy of estimates of the mean, variance, and lower credibility value of true validities produced by the independent multiplicative model and by a modified dependent model that takes the correlation between range restriction and criterion reliability artifacts into account. Sample sizes (n?=?50 or 100) and the number of studies/analyses (50) were selected to be consistent with the typical parameters found in 129 validity generalization analyses. The mean, standard deviation, and shape of the true validity distributions were systematically varied. It is concluded that the independent and modified dependent estimates were typically accurate, although the credibility estimates were affected by the extremely skewed distributions. The mean and variance estimates from both models were not affected by distribution shape. Results support the applicability of the 1st 2 authors' (see record 1981-27033-001) models and F. L. Schmidt and J. E. Hunter's (see record 1978-11448-001) noninteractive model. Some limitations of the "bare-bones" sampling-error-only approach are noted. (9 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Learning-forgetting independence, unidimensional memory models, and feature models: Comment on Bogartz (1990).

In his recent articles, R. S. Bogartz (see record 1990-09037-001) offered a definition of what it means for forgetting rate to be independent of degree of original learning. He showed that, given this definition, independence is confirmed by extant data. Bogartz criticized G. R. Loftus's (see record 1986-05498-001) proposed method for testing independence. In this commentary, we counter Bogartz's criticisms and then offer 2 observations. First, we show that Loftus's horizontal-parallelism test distinguishes between 2 interesting classes of memory models: unidimensional models wherein the memory system's state can be specified by a single number and multidimensional models wherein at least 2 numbers are required to specify the memory system's state. Independence by Loftus's definition is implied by a unidimensional model. Bogartz's definition, in contrast, is consistent with either model. Second, to better understand the constraints on memory mechanisms dictated by the mathematics of the models under consideration, we develop a simple but general feature model of learning and forgetting. We demonstrate what constraints must be placed on this model to make learning and forgetting rate independent by Loftus's and by Bogartz's definitions. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Time and learning.

Views the student's time spent in learning as a potent variable underlying differences in learning achievement between nations, states, and communities, various classroom subjects, and various classroom conditions. The J. B. Carroll (see record 1963-08222-001) model, which posits that individual students differ in the amount of time needed to reach criterion on a given learning unit, led to the development of the learning mastery instructional approach. Proponents of this approach maintain that by individualizing the learning rate with a fixed set of materials (sequential units) and by providing necessary individual help and additional time, most students would be able to reach the criterion of mastery for each learning unit. R. Glaser (1968) and R. C. Atkinson (1968) conducted research on human variation in mastery learning. They found that early in a course or term (a) the elapsed time (time presumably working on the task) necessary for different students to reach criterion varied by a ratio of 1:5, while (b) the actual time spent on the task necessary for different students to reach criterion varied by a ratio of 3:1. Reductions in both ratios later in the course or term, particularly the actual time on task ratio, suggested that the mastery approach facilitated both more efficient learning and more efficient time usage. It is concluded that an understanding of time and its use in school learning would be helpful in the effort to decrease human variability in learning. (19 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

An adaptive approach to human decision making: Learning theory, decision theory, and human performance.

Describes a general model of decision rule learning, the rule competition model, composed of 2 parts: an adaptive network model that describes how individuals learn to predict the payoffs produced by applying each decision rule for any given situation and a hill-climbing model that describes how individuals learn to fine tune each rule by adjusting its parameters. The model was tested and compared with other models in 3 experiments on probabilistic categorization. The 1st experiment was designed to test the adaptive network model using a probability learning task, the 2nd was designed to test the parameter search process using a criterion learning task, and the 3rd was designed to test both parts of the model simultaneously by using a task that required learning both category and cutoff criteria. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Multiple monotone regression.

Multiple monotone regression is a set of models and methods that can be applied when researchers do not think that the relationships among their measured variables can be adequately described by a multiple linear regression model. The relations among weak monotonic, additive, and additive monotonic models are discussed. As an example, the models are applied to data from the present author's (see record 1982-27256-001) study of visual information processing. (17 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Storage and retrieval of associative clusters: A stages-of-learning analysis of associative memory traces.

In this research, the assumptions underlying the unitary trace theory of item representation and acquisition were tested in two cued-recall experiments in which the degree of preexperimental knowledge (typicality) was manipulated. Subjects learned lists of word triads (each of which consisted of a single cue and two targets) to a stringent acquisition criterion. In Experiment 1, typicality was manipulated in the absence of semantic relationships between members of the associative clusters. In Experiment 2, semantic relationships were present among cluster members, and preexperimental knowledge was manipulated by varying the degree of intracluster category membership as measured by whether cue and target items were typical or atypical category exemplars. In both experiments a mathematical model that embodies stages-of-learning distinctions was used to analyze the acquisition data. The results indicated that (1) cues and targets were represented in a single holistic memory trace, and (2) the manipulation of the degree of preexperimental knowledge affected both trace storage and retrieval learning, but had only a minimal impact on retrieval performance between the time a trace was stored and the time retrieval learning was complete. It was argued that these findings are consistent with a single unitary trace interpretation, namely, the modified storage-retrieval model. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Supporting students' motivation, engagement, and learning during an uninteresting activity.

The present study examined the capacity of 2 different theoretical models of motivation to explain why an externally provided rationale often supports students' motivation, engagement, and learning during relatively uninteresting learning activities. One hundred thirty-six undergraduates (108 women, 28 men) worked on an uninteresting 20-min lesson after either receiving or not receiving a rationale. Participants who received the rationale showed greater identified regulation, interest-enhancing strategies, behavioral engagement, and conceptual learning. Structural equation modeling was used to test 3 alternative explanatory models to understand why the rationale produced these benefits--an identified regulation model based on self-determination theory, an interest regulation model based on interest-enhancing strategies research, and an additive model that integrated both models. The data fit all 3 models; however, only the model that included rationale-enhanced identified regulation uniquely fostered students' engagement and hence their learning. Findings highlight the role that externally provided rationales can play in helping students generate the autonomous motivation they need to engage constructively in and learn from uninteresting, but personally important, lessons. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Criterion models and construct validity for criteria.

Reviews methods for measuring criteria and ascertaining underlying criterion constructs. 3 criterion measurement models (the ultimate criterion model, the multiple criterion model, and a "general" criterion model) for the determinants of managerial effectiveness were examined and attempts made toward integration. The 3 models were than compared to a formal construct validation model. Strengths and weaknesses in both the constructs provided by each of the criterion models and the construct validation procedures are discussed. It is recommended that future criterion research utilize an integrated multiple and general criterion model, and construct validation procedures more extensive than the multitrait-multimethod matrix. (39 ref.) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Signal detection theory and generalized linear models.

Generalized linear models are a general class of regressionlike models for continuous and categorical response variables. Signal detection models can be formulated as a subclass of generalized linear models, and the result is a rich class of signal detection models based on different underlying distributions. An example is a signal detection model based on the extreme value distribution. The extreme value model is shown to yield unit slope receiver operating characteristic (ROC) curves for several classic data sets that are commonly given as examples of normal or logistic ROC curves with slopes that differ from unity. The result is an additive model with a simple interpretation in terms of a shift in the location of an underlying distribution. The models can also be extended in several ways, such as to recognize response dependencies, to include random coefficients, or to allow for more general underlying probability distributions. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Optimizing the Prediction Accuracy of Concrete Compressive Strength Based on a Comparison of Data-Mining Techniques

This study attempts to optimize the prediction accuracy of the compressive strength of high-performance concrete (HPC) by comparing data-mining methods. Modeling the dynamics of HPC, which is a highly complex composite material, is extremely challenging. Concrete compressive strength is also a highly nonlinear function of ingredients. Several studies have independently shown that concrete strength is determined not only by the water-to-cement ratio but also by additive materials. The compressive strength of HPC is a function of all concrete content, including cement, fly ash, blast-furnace slag, water, superplasticizer, age, and coarse and fine aggregate. The quantitative analyses in this study were performed by using five different data-mining methods: two machine learning models (artificial neural networks and support vector machines), one statistical model (multiple regression), and two metaclassifier models (multiple additive regression trees and bagging regression trees). The methods were developed and tested against a data set derived from 17 concrete strength test laboratories. The cross-validation of unbiased estimates of the prediction models for performance comparison purposes indicated that multiple additive regression tree (MART) was superior in prediction accuracy, training time, and aversion to overfitting. Analytical results suggested that MART-based modeling is effective for predicting the compressive strength of varying HPC age.     

Complementary medicine: a review of immunomodulatory effects of Chinese herbal medicines

Normal aging selectively impairs some forms of learning. For example, aging rabbits require more than twice as many trials to acquire 500-ms trace eyeblink conditioning than do young rabbits. N-methyl-D-aspartate (NMDA) receptor antagonists also impair trace conditioning. The effects of daily D-cycloserine (DCS; a partial agonist of the NMDA receptor-glycine site) treatment were tested on trace conditioning of young or aging rabbits using a conservative quantitative approach. DCS dose dependently improved acquisition, maximally reducing trials to criterion by approximately 50%. Dose-response curves were right-shifted by aging (twice the dose was required to achieve the same enhancement compared with controls). DCS did not affect nonassociative performance but sharpened the conditioned stimulus tone intensity discrimination. DCS thus can functionally modulate NMDA receptors in normal aging, enhance associative learning at all ages, and reduce or reverse age-dependent learning deficits.     

Relative estimates of combination weights, decision criteria, and internal noise based on correlation coefficients

A means by which relative combination weights may be determined is described for a signal detection model in which the decision variable is a weighted linear combination of several independent, normally distributed random variables, Xi's. The first theorem presents the correlation between the binary response variables--signal versus no signal--and the component Xi. The second theorem presents a parallel result for the case that additive internal noise is present. Thus in psychophysical experiments, the relative combination weights may be obtained by correlating the observers' responses and the input random variables. Third, three numerical methods which allow the evaluation of the relative magnitude of the decision criterion and the variance of a hypothetical additive internal noise are considered.     

Limitations of exemplar models of multi-attribute probabilistic inference.

Observers were presented with pairs of objects varying along binary-valued attributes and learned to predict which member of each pair had a greater value on a continuously varying criterion variable. The predictions from exemplar models of categorization were contrasted with classic alternative models, including generalized versions of a "take-the-best" model and a weighted-additive model, by testing structures in which interactions between attributes predicted the magnitude of the criterion variable. Under typical training conditions, observers showed little sensitivity to the attribute interactions, thereby challenging the predictions from the exemplar models. In a condition involving highly extended training, observers eventually learned the relations between the attribute interactions and the criterion variable. However, an analysis of the observers' response times for making their paired-comparison decisions also challenged the exemplar model predictions. Instead, it appeared that most observers recoded the interacting attributes into emergent configural cues. They then applied a set of hierarchically organized rules based on the priority of the cues to make their decisions. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Age- and dose-dependent facilitation of associative eyeblink conditioning by {d}-cycloserine in rabbits.

Normal aging selectively impairs some forms of learning. For example, aging rabbits require more than twice as many trials to acquire 500-ms trace eyeblink conditioning than do young rabbits. N-methyl-{d}-aspartate (NMDA) receptor antagonists also impair trace conditioning. The effects of daily {d}-cycloserine (DCS; a partial agonist of the NMDA receptor-glycine site) treatment were tested on trace conditioning of young or aging rabbits using a conservative quantitative approach. DCS dose dependently improved acquisition, maximally reducing trials to criterion by ≈50%. Dose-response curves were right-shifted by aging (twice the dose was required to achieve the same enhancement compared with controls). DCS did not affect nonassociative performance but sharpened the conditioned stimulus tone intensity discrimination. DCS thus can functionally modulate NMDA receptors in normal aging, enhance associative learning at all ages, and reduce or reverse age-dependent learning deficits. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Additional evidence for intact appetitive trace conditioning in hippocampal-lesioned rats.

Hippocampal lesions impair aversive trace conditioning but do not interfere with appetitive Pavlovian trace conditioning of the licking response (LR). This experiment examined whether learning to discriminate the events occurring in the home cage and in the training chamber could account for the differential effects of hippocampal lesions on aversive and appetitive trace conditioning. Performance of rats with excitotoxic lesions of the hippocampus was compared to that of sham-operated rats in LR trace conditioning. The unconditional stimulus (US) “cola soft drink” was delivered only in the training chamber. Thus, as in aversive conditioning procedures, the hedonic properties of the US and the resulting behaviors and motivational states occurred only in that environment. The results failed to reveal learning differences between lesioned rats and controls. Our findings and those of other reports concur that trace conditioning with an appetitive US is independent of the hippocampal system. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Unsupervised concept learning and value systematicitiy: A complex whole aids learning the parts.

Ease of learning new concepts may best be understood by simultaneously considering models of learning and theories of how "good" systems of categories are organized. The authors tested the effects on learning of value systematicity, a proposed organizing principle: If 1 attribute is predictive of another, it should predict still more. This principle derives from focused sampling in the internal feedback model (D. Billman & E. Heit, 1988) of unsupervised, or observational, learning. In 3 experiments, the authors tested how the organization of structure in input (value systematicity) affected unsupervised learning of categories about alien animals. Across all experiments, learning a target rule was easier in conditions with high value systematicity, relative to several low systematicity controls. The authors compare results to predictions of several learning models and consider the links between learning and the resulting category structure. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Hippocampectomy disrupts auditory trace fear conditioning and contextual fear conditioning in the rat

The hippocampus is believed to be an important structure for learning tasks that require temporal processing of information. The trace classical conditioning paradigm requires temporal processing because the conditioned stimulus (CS) and the unconditioned stimulus (US) are temporally separated by an empty trace interval. The present study sought to determine whether the hippocampus was necessary for rats to perform a classical trace fear conditioning task in which each of 10 trials consisted of an auditory tone CS (1 5-s duration) followed by an empty 30-s trace interval and then a fear-producing floor-shock US (0.5-s duration). Several weeks prior to training, animals were anesthetized and given aspiration lesions of the neocortex (NEO; n = 6), hippocampus and overlying neocortex (HIPP; n = 7), or no lesions at all (control; n = 6). Approximately 24 h after trace conditioning, NEO and control animals showed a significant decrease in movement to a CS-alone presentation that was indicative of a conditioned fear response. Animals in the HIPP group did not show conditioned fear responses to the CS alone, nor did a pseudoconditioning group (n = 7) that was trained with unpaired CSs and USs. Furthermore, all groups except the HIPP group showed conditioned fear responses to the original context in which they received shock USs. One week later, HIPP, NEO, and control animals received delay fear-conditioning trials with no trace interval separating the CS and US. Six of seven HIPP animals could perform the delay version, but none could perform the trace version. This result suggests that the trace fear task is a reliable and useful model for examining the neural mechanisms of hippocampally dependent learning.     

Confirming the X-linked handedness gene as recessive, not additive: Reply to Corballis (2001).

M. C. Corballis (see record 2001-18918-006) has proposed a model for handedness that follows the unified distributional model of G. V. Jones and M. Martin (see record 1999-15930-008) in its assumption that genetic variation relating to handedness is located only on the X chromosome but differs from the unified distributional model in its assumption that the relation between genotype and phenotype is of an additive rather than a recessive type. The accounts provided by the two models are compared for four major sets of findings. It is concluded that the empirical evidence favors the X linked recessive model proposed by G. V. Jones and M. Martin (see record 1999-15930-008). (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Review of Stochastic models for learning.

Reviews the book "Stochastic models for learning" by R. R. Bush and F. Mosteller (see record 1955-15028-000). This contribution to learning theory analyzes the results of many learning experiments in terms of a probabilistic hypothesis after setting up a general theoretical model from which specific models to fit particular results can be derived. While this book is not an applied book except in the sense that mathematical techniques of much power are applied to basic psychological problems, it represents a distinct advance in the scientific analysis of learning data. Ultimately applied psychology may benefit from the methods so developed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Modeling deformation resistance for hot rolling based on generalized additive model

A model of deformation resistance during hot strip rolling was established based on generalized additive model.Firstly,a data modeling method based on generalized additive model was given.It included the selection of dependent variable and independent variables of the model,the link function of dependent variable and smoothing functional form of each independent variable,estimating process of the link function and smooth functions,and the last model modification.Then,the practical modeling test was carried out based on a large amount of hot rolling process data.An integrated variable was proposed to reflect the effects of different chemical compositions such as carbon,silicon,manganese,nickel,chromium,niobium,etc.The integrated chemical composition,strain,strain rate and rolling temperature were selected as independent variables and the cubic spline as the smooth function for them.The modeling process of deformation resistance was realized by SAS software,and the influence curves of the independent variables on deformation resistance were obtained by local scoring algorithm.Some interesting phenomena were found,for example,there is a critical value of strain rate,and the deformation resistance increases before this value and then decreases.The results confirm that the new model has higher prediction accuracy than traditional ones and is suitable for carbon steel,microalloyed steel,alloyed steel and other steel grades.