Live training versus e‐learning to teach implementation of listener response programs

Discrete‐trial teaching is an effective teaching procedure that must be implemented with high integrity to produce optimal learning. Behavioral Skills Training (BST) has proven effective for staff training; however, BST is time and labor intensive. Computer‐based instruction (CBI) programs may provide a more efficient and cost‐effective alternative to live training if the CBI program is as effective as BST in producing accurate implementation. The current study compared CBI to BST to train novice undergraduate students to conduct discrete‐trial teaching. Participants were randomly assigned to one of the two conditions and assessed prior to and after the completion of training. Results indicated that although both BST and CBI were effective at training participants to implement discrete‐trial teaching, BST was slightly but significantly more effective whereas CBI quickly created a return on the investment of product development.     

Stimulus presentation order in receptive identification tasks: A systematic replication

Conflicting recommendations exist in the literature regarding the optimal order of stimulus presentation when teaching auditory–visual conditional discriminations. The present study examined the generality of a previously demonstrated advantage of presenting the auditory sample before visual comparisons (sample‐first condition) over the reverse sequence (comparison‐first condition). Participants were four typically developing 5‐ and 6‐year‐old boys. The procedures of Petursdottir and Aguilar (2016) were systematically replicated with the addition of a prompted error correction trial following each incorrect response. Overall, there were more instances of quicker mastery in the sample‐first condition (four of seven evaluations) than in the comparison‐first condition (two of seven evaluations). A comparison‐first advantage was associated with slower acquisition in both conditions than in the remaining evaluations, and an analysis of stimulus and position bias yielded tentative evidence for unwanted sources of stimulus control.     

第二类有中介的调节模型

心理学研究常用有中介的调节模型揭示调节作用通过中介变量间接实现的现象。介绍了第二类有中介的调节模型(meMO-II)的概念及优势; 将meMO-II与其它中介调节混合模型进行了辨析; 给出了meMO-II的建模方法和分析流程, 并用一个实例演示; 介绍了基于潜变量的meMO-II的分析方法、meMO-II建模方法的新进展以及meMO-II的变式。研究有助于推动调节机制研究的发展。     

Repeated post- or presession cocaine administration: roles of dose and fixed-ratio schedule

Effects of repeated administration of cocaine to animals behaving under operant contingencies have depended on when the drug is given. Moderate doses given presession have generally led to a decrease in the drug's effect, an outcome usually referred to as tolerance. When these same doses have been given after sessions, the usual result has been no change or an increase in the drug's effects, with the latter usually referred to as sensitization. In the present study, repeated postsession administration of a relatively small dose of cocaine (3.0 or 5.6 mg/kg) to pigeons responding under a multiple fixed-ratio 5, fixed-ratio 100 schedule of food presentation generally resulted in tolerance to the rate-decreasing effects of the drug. When the same dose was given before sessions, little additional tolerance was observed, although some subjects showed further tolerance in the small-ratio component. A regimen of repeated postsession injection of larger (10.0-23.0 mg/kg) doses suppressed key pecking during the session; responding resumed following discontinuation of postsession administrations. Effects of postsession administration of cocaine, therefore, depended on the dose, with smaller doses leading to tolerance and larger ones to suppression of behavior during the session. Effects of postsession drug administration of either small or large doses were not related to whether effects of postsession drug were experienced mainly in the operant test chamber or in the pigeon's home cage. The results with large postsession doses are compatible with a view that the drug acted as a Pavlovian unconditional stimulus, with the session-related stimuli acting as a long-duration Pavlovian conditional stimulus. Tolerance following postsession administration of the smaller doses challenges the view that it depended on experiencing the drug's effects while the arranged reinforcement contingencies were in effect.     

四卡问题的视角效应发生机制：领域一般性还是领域特殊性？

视角效应（Perspective Effects)是指四卡问题解决中,当被试从不同的角度对条件规则进行检验时,其选择偏向会在卡片p,q和-p,q之间发生稳定变化的现象。视角效应对四卡问题的解决有重要影响,但其存在条件及发生机制仍存在争议。本研究通过3个实验,探讨四卡问题中的视角效应。实验1和实验2采用混合实验设计,结果表明,转换社会契约、因果规则的四卡问题中,发现视角效应,抽象规则中,提供反例比提供充分必要条件更有利于产生视角效应。实验3在不同视角下研究四卡问题与条件推理的关系。结果表明,四卡问题与条件推理之间不具有逻辑一致性,产生分离现象。总之,视角效应在抽象规则和特定规则中均存在,而提供反例更有利于视角效应的产生。领域一般性或领域特殊性均不能有效解释视角效应的产生,两种机制的综合调节为解释视角效应提供新的角度。     

Enhancing Interpretability in Factor Analysis by Means of Mathematical Optimization

Abstract

Exploratory Factor Analysis (EFA) is a widely used statistical technique to discover the structure of latent unobserved variables, called factors, from a set of observed variables. EFA exploits the property of rotation invariance of the factor model to enhance factors’ interpretability by building a sparse loading matrix. In this paper, we propose an optimization-based procedure to give meaning to the factors arising in EFA by means of an additional set of variables, called explanatory variables, which may include in particular the set of observed variables. A goodness-of-fit criterion is introduced which quantifies the quality of the interpretation given this way. Our methodology also exploits the rotational invariance of EFA to obtain the best orthogonal rotation of the factors, in terms of the goodness-of-fit, but making them match to some of the explanatory variables, thus going beyond traditional rotation methods. Therefore, our approach allows the analyst to interpret the factors not only in terms of the observed variables, but in terms of a broader set of variables. Our experimental results demonstrate how our approach enhances interpretability in EFA, first in an empirical dataset, concerning volumes of reservoirs in California, and second in a synthetic data example.     

Modelling monotonic effects of ordinal predictors in Bayesian regression models

Ordinal predictors are commonly used in regression models. They are often incorrectly treated as either nominal or metric, thus under- or overestimating the information contained. Such practices may lead to worse inference and predictions compared to methods which are specifically designed for this purpose. We propose a new method for modelling ordinal predictors that applies in situations in which it is reasonable to assume their effects to be monotonic. The parameterization of such monotonic effects is realized in terms of a scale parameter b representing the direction and size of the effect and a simplex parameter modelling the normalized differences between categories. This ensures that predictions increase or decrease monotonically, while changes between adjacent categories may vary across categories. This formulation generalizes to interaction terms as well as multilevel structures. Monotonic effects may be applied not only to ordinal predictors, but also to other discrete variables for which a monotonic relationship is plausible. In simulation studies we show that the model is well calibrated and, if there is monotonicity present, exhibits predictive performance similar to or even better than other approaches designed to handle ordinal predictors. Using Stan, we developed a Bayesian estimation method for monotonic effects which allows us to incorporate prior information and to check the assumption of monotonicity. We have implemented this method in the R package brms, so that fitting monotonic effects in a fully Bayesian framework is now straightforward.