Discriminated interresponse times: role of autoshaped responses.

When discriminated interresponse-time (IRT) procedures have been used to assess preference relations among temporally extended operants, deviations from matching have been obtained. Using a yoked-control procedure, the present study found that key pecking in a discriminated IRT procedure has two sources of strength--that arising from the response-reinforcer contingency that is explicitly arranged, and that arising from a stimulus-reinforcer contingency that is a by-product of the explicitly arranged contingency. The key pecking of all lead birds, and that of 3 of the 4 birds exposed to a yoked autoshaping procedure, was controlled by the keylight that signaled the lead birds' criterion IRTs. Because stimulus control of key pecking by the keylight, whether autoshaped or discriminative, fosters deviations from matching, the discriminated IRT procedure does not provide an appropriate basis for conclusions about preference relations among IRTs.     

Estimation for structural equation models with missing data

A direct method in handling incomplete data in general covariance structural models is investigated. Asymptotic statistical properties of the generalized least squares method are developed. It is shown that this approach has very close relationships with the maximum likelihood approach. Iterative procedures for obtaining the generalized least squares estimates, the maximum likelihood estimates, as well as their standard error estimates are derived. Computer programs for the confirmatory factor analysis model are implemented. A longitudinal type data set is used as an example to illustrate the results.This research was supported in part by Research Grant DAD1070 from the U.S. Public Health Service. The author is indebted to anonymous reviewers for some very valuable suggestions. Computer funding is provided by the Computer Services Centre, The Chinese University of Hong Kong.     

Phenotypic plasticity and archetype: a response to common objections to the biological theory of archetype and instinct

Since Jung’s death in 1961, scholars have attempted to integrate growing biological science data into Jungian concepts such as the collective unconscious, instincts and the archetypes. This enterprise has been challenging due to persistent false dichotomies of gene and environment occasionally arising. Recent works by Roesler (2022a, 2022b) for example, have raised objections to the biological theory of archetypes, but the objections are plagued by such dichotomies. The concept of phenotypic plasticity, however, helps to both avoid this problem as well as bridge the gap between competing theories into a more integrated model with solid biological foundations.     

编码后奖赏影响基于议程的学习：奖赏预期和结果的作用

基于ABR模型考察奖赏预期和奖赏结果对不同难度词对记忆与元记忆的影响。结果发现：(1)限时学习条件下,奖赏结果促进不同难度词对记忆成绩和学习判断,奖赏预期仅提高简单词对的记忆成绩。(2)自定步调学习条件下,定时学习判断时奖赏结果仅影响学习判断;奖赏预期促进高难度词对的学习时间分配,从而提高记忆成绩和学习判断。(3)在自定步调学习时,奖赏预期超越难度成为影响学习时间分配的因素。以上结果表明,个体会综合奖赏预期、奖赏结果和难度构建学习议程,足够大的奖赏预期会超越难度成为议程构建的主导因素。但奖赏预期和奖赏结果对记忆成绩、学习时间分配和学习判断的影响受学习条件调节。     

Does code-switching influence novel word learning?

Code-switching occurs regularly in the input to bilingual children. Yet, the effect of code-switched input on language development is unclear. To test whether word learning would be affected by code-switching, Spanish–English bilingual children (N = 45, 19 boys, Mean_Age = 5.05 years; ethnicity: 37 Hispanic/Latino, six Non-Hispanic/Latino, two unreported) were taught English-like novel words in two conditions. In the English-only condition, definitions for novel words were provided entirely in English. In the code-switch condition, definitions for novel words were provided in English and Spanish, incorporating code-switches. Children required fewer exposures to retain novel words in the code-switch than the English-only condition and this effect was not moderated by children's language ability or exposure to code-switching, suggesting that code-switched input does not pose word-learning risks to bilingual children, including children with lower levels of language ability.     

An ecological pedagogy of embeddedness: Theological education for human flourishing

This paper sets forth a proposal for an ecological pedagogy of embeddedness informed by place-based, challenge-based, and competency-based methodologies. While some theological institutions have begun implementing principles from competency-based models, theological educators have not adequately explored the resources within place-based and challenge-based systems. This paper will contribute to the literature on theological education in three distinct ways: first, this proposal will perform the oft-overlooked task of bringing these three pedagogical models into conversation with one another; second, this proposal will aim the outcomes and effects of the three pedagogical models toward the flourishing of the communities in which institutions are embedded; and third, this proposal will break new ground in its application of these three pedagogical systems to the context of a theological seminary.     

Extending exploratory diagnostic classification models: Inferring the effect of covariates

Diagnostic models provide a statistical framework for designing formative assessments by classifying student knowledge profiles according to a collection of fine-grained attributes. The context and ecosystem in which students learn may play an important role in skill mastery, and it is therefore important to develop methods for incorporating student covariates into diagnostic models. Including covariates may provide researchers and practitioners with the ability to evaluate novel interventions or understand the role of background knowledge in attribute mastery. Existing research is designed to include covariates in confirmatory diagnostic models, which are also known as restricted latent class models. We propose new methods for including covariates in exploratory RLCMs that jointly infer the latent structure and evaluate the role of covariates on performance and skill mastery. We present a novel Bayesian formulation and report a Markov chain Monte Carlo algorithm using a Metropolis-within-Gibbs algorithm for approximating the model parameter posterior distribution. We report Monte Carlo simulation evidence regarding the accuracy of our new methods and present results from an application that examines the role of student background knowledge on the mastery of a probability data set.