Information-Hierarchical Organization of Natural Systems I: The Information-Physical Principle

The mathematical notion of information characterizing system organization as such has been developed. The information-physical principle, which characterizes an information exchange in natural hierarchical systems and has been confirmed by its numerous applications, is laid down. It is shown to be based on the ancient “matter–measure–information” concept of physical world structure and talked about in the Hermes Trismegistus's will.     

Hierarchical structure of the Eysenck Personality Inventory in a large population sample: Goldberg’s trait-tier mapping procedure

The structure of the Eysenck Personality Inventory (EPI) is poorly understood, and applications have mostly been confined to the broad Neuroticism, Extraversion and Lie scales. Using a hierarchical factoring procedure, we mapped the sequential differentiation of EPI scales from broad, molar factors to more specific, molecular factors, in a UK population sample of over 6500 persons. Replicable facets at the lowest tier of Neuroticism included oversensitivity, mood lability, nervous tension and rumination. The lowest order set of replicable Extraversion facets consisted of social dynamism, sociotropy, haste, jocularity, communalism and impulsivity. The Lie scale consisted of an interpersonal virtue and a behavioral diligence facet. Users of the EPI may be well served in some circumstances by considering its broad Neuroticism, Extraversion and Lie scales as multifactorial, a feature that was explicitly incorporated into subsequent Eysenck inventories and is consistent with other hierarchical trait structures.     

Youth belonging and cognitive engagement in organized activities: A large-scale field study

Numerous studies of organized activities have found that participation is associated with a range of positive outcomes; however, findings from recent randomized trials have been more mixed. Understanding youth's psychological experiences of program involvement – their cognitive and emotional reaction to and participation in activities – may be key to understanding the influence of organized activities. Hierarchical linear modeling was used to investigate correlates of youth belonging and cognitive engagement in a sample of 1160 youth in 123 program offerings in 66 sites. Results revealed that intensity (frequency) of exposure positively predicted belonging and cognitive engagement; however, duration was negatively associated with cognitive engagement. The staff practice of providing a welcoming atmosphere predicted belonging; whereas provision of active skill-building predicted cognitive engagement. These relations were found to vary across content type.     

A tutorial on Bayes factor estimation with the product space method

The Bayes factor is an intuitive and principled model selection tool from Bayesian statistics. The Bayes factor quantifies the relative likelihood of the observed data under two competing models, and as such, it measures the evidence that the data provides for one model versus the other. Unfortunately, computation of the Bayes factor often requires sampling-based procedures that are not trivial to implement. In this tutorial, we explain and illustrate the use of one such procedure, known as the product space method (Carlin & Chib, 1995). This is a transdimensional Markov chain Monte Carlo method requiring the construction of a “supermodel” encompassing the models under consideration. A model index measures the proportion of times that either model is visited to account for the observed data. This proportion can then be transformed to yield a Bayes factor. We discuss the theory behind the product space method and illustrate, by means of applied examples from psychological research, how the method can be implemented in practice.     

Constructing informative model priors using hierarchical methods

Despite their negative reputation, informative priors are very useful in inference. Priors that express psychologically meaningful intuitions damp out random fluctuations in the data due to sampling variability, without sacrificing flexibility. This article focuses on how an intuitively satisfying informative prior distribution can be constructed. In particular, it demonstrates how the hierarchical introduction of a parameterized generative account of the set of models under consideration naturally imposes a non-uniform prior distribution over the models, encoding existing intuitions about the models. The hierarchical approach for constructing informative model priors is made concrete using a worked example, the Varying Abstraction Model (VAM), a family of categorization models including and expanding the exemplar and prototype models. It is shown how psychological intuitions about the relative plausibilities of the models in the VAM can be formally captured in an informative prior distribution over these models, by specifying a theoretically informed process for generating the models in the VAM. The smoothing effect of the informative prior in estimation is demonstrated by considering ten previously published data sets from the category learning literature.     

Hierarchical single- and dual-process models of recognition memory

Recognition memory is commonly modeled as either a single, continuous process within the theory of signal detection, or with two-process models such as Yonelinas’ dual-process model. Previous attempts to determine which model provides a better account of the data have relied on fitting the models to data that are averaged over items. Because such averaging distorts conclusions, we develop and compare hierarchical versions of competing single and dual-process models that account for item variability. The dual-process model provides a superior account of a typical data set when models are compared with the deviance information criterion. Parameters of the dual-process model are highly correlated, however, suggesting that a single-process model may exist that can provide a better account of the data.     

指导语形式、材料性质对解决四卡问题的影响

该文通过实验的方法,研究了指导语形式、材料性质对大学生解决四卡问题的影响。结果发现:(1)指导语形式影响大学生对四卡问题的解决,肯定式指导语有助于提高被试的成绩。(2)材料性质影响大学生对四卡问题的解决,具体材料相比抽象材料有促进效应。本实验表明,指导语形式和材料性质都能对大学生解决四卡问题产生影响,两者之间不存在交互作用。     

Mainstreams and Perspectives in Research on Learning (Mathematics) From Instruction

Le domaine de l’enseignement et de l’apprentissage des mathématiques est un exemple des plus représentatives de l’orientation des recherches sur l’apprentissage et l’instruction dans les différentes matières. Au cours du dernier quart de siècle écoulé, ce champ de questionnement a produit nombre d’investigations qui résultent d’une conception de l’apprentissage des mathématiques comme construction sociale de la signification et de la comprehension basée sur la modélisation de la réalité. Dans cet article, quelques tendances majeures et perspectives de recherche s.0s principalement aux Etats‐Unis et en Europe. Il y sera montré que d’une part, les investigations empiriques ont déjà produit des blocs de construction pour l’élaboration d’une théorie de l’apprentissage des mathématiques à partir d’instructions mais que, d’autre part, des questions et des problèmes majeurs requièrent d’être démêlés par la poursuite d’investigations. Ceci y sera documenté de façon exemplaire en utilisant comme cadre de référence quatre composants principaux d’une théorie de l’apprentissage des mathématiques à partir d’instructions: une théorie de l’expertise visant à analyser des compétences dans un domaine; une théorie de l’acquisition tendant à comprendre et expliquer les processus d’apprentissage qui conduisent à la réalisation de compétences; une théorie de l’intervention, focalisée sur la conception d’environnements enseignement‐apprentissage puissants pour provoquer ces processus d’acquisition; et une théorie de l’évaluation s’adressant au développement de méthodes et techniques pour la construction et l’application d’outils et instruments d’évaluation. The domain of mathematics learning and teaching is one of the most representative examples of the subject‐matter orientation in research on learning and instruction. During the last quarter of the past century this field of inquiry has produced a vast body of investigations, resulting in an enriched conception of mathematics learning as involving the (social) construction of meaning and understanding based on modeling of reality. In this article some of the main trends and perspectives in the field of research on mathematics learning and instruction are discussed, and illustrated with examples of empirical research, mainly carried out in Europe and the United States. It will be shown that, on the one hand, the available empirical investigations have already yielded substantial building blocks for the elaboration of a theory of mathematics learning from instruction, but that, on the other hand, major issues and problems need to be unravelled by continued inquiry. This will be documented in an exemplary way, using as a frame of reference four main components of a theory of learning mathematics from instruction: a theory of expertise, aiming at analysing competence in a domain; a theory of acquisition, attempting to understand and explain the processes of learning that are conducive to the attainment of competence; a theory of intervention, focusing on the design of powerful teaching–learning environments for eliciting those acquisition processes; and a theory of assessment, addressing the development of methods and techniques for the construction and application of assessment tools and instruments.     

Developing the Horizons of the Mind: Reich's Response to the Commentators

Some aspects of my writing the monograph Developing the Horizons of the Mind (2002) are highlighted, the central characteristics of relational and contextual reasoning (RCR) are explained, and the contributions to this symposium by John Albright, Varadaraja V. Raman, and John Teske are discussed.     

Revival and significance of political philosophy at present time

Taking a panoramic view on the history of modern philosophy, we can learn that political philosophy, a new arena for modern philosophy, has become an important field in philosophical studies since the later half of the 20th century. As far as the problem domain of political philosophy is concerned, political philosophy is only a special form of philosophy. The revival of political philosophy, however, indicates that philosophical inspection of political matters has regained legitimacy, and also means the restaging of philosophy as a knowledge type at modern times. In one sense, we can view the newly-revived political philosophy as typical modern philosophy, because its problem domain, its unique angle of looking into the life world and its ideal concern about the actual world make it one of the best ways in which we can reflect the existence of mankind in modern times. __________ Translated from Zhexue Yanjiu 哲学研究 (Philosophical Studies), 2005 (6) by Teng Jianhui