Philosophy of Education in a Poor Historical Moment: A Personal Account

Under the post-metaphysical sky “old” humanistic-oriented education is possible solely at the cost of its transformation into its negative, into a power that is determined to diminish human potentials for self-exaltation. Nothing less than total metamorphosis is needed to rescue the core of humanistic genesis: the quest for edifying Life and resistance to the call for “home-returning” into the total harmony that is promised to us within nothingness.     

Psychometric network models from time-series and panel data

Researchers in the field of network psychometrics often focus on the estimation of Gaussian graphical models (GGMs)—an undirected network model of partial correlations—between observed variables of cross-sectional data or single-subject time-series data. This assumes that all variables are measured without measurement error, which may be implausible. In addition, cross-sectional data cannot distinguish between within-subject and between-subject effects. This paper provides a general framework that extends GGM modeling with latent variables, including relationships over time. These relationships can be estimated from time-series data or panel data featuring at least three waves of measurement. The model takes the form of a graphical vector-autoregression model between latent variables and is termed the ts-lvgvar when estimated from time-series data and the panel-lvgvar when estimated from panel data. These methods have been implemented in the software package psychonetrics, which is exemplified in two empirical examples, one using time-series data and one using panel data, and evaluated in two large-scale simulation studies. The paper concludes with a discussion on ergodicity and generalizability. Although within-subject effects may in principle be separated from between-subject effects, the interpretation of these results rests on the intensity and the time interval of measurement and on the plausibility of the assumption of stationarity.

     

Action-based and vision-based selection of input: Two sources of control

In the first part of this paper we review evidence suggesting that there exists a mechanism that selects input on the basis of its similarity to the required action. This response-based input selection differs from the more established space- and object-based input selection in that it is not constrained by the structure of the input. Our evidence suggests that the two-choice Stroop effect is caused by this response-based selection mechanism. By contrast, it is known that the flanker effect is determined by the space- and object- based selection mechanisms. We explore whether the conflict resolution of the Stroop and flanker tasks is different as well by embedding these two tasks in a PRP (Psychological Refractory Period) paradigm. We show that the Stroop and the PRP effects are additive whereas the flanker and the PRP effects are underadditive, suggesting that the processes in charge of the conflict resolution in the Stroop and the flanker tasks are indeed different. We discuss possible reasons for this difference, and discuss possible ways in which the response-based mechanism can be implemented in information processing models.     

Win-shift and win-stay learning in the short-beaked echidna (<Emphasis Type="Italic">Tachyglossus aculeatus</Emphasis>)

Numerous previous investigators have explained species differences in spatial memory performance in terms of differences in foraging ecology. In three experiments we attempted to extend these findings by examining the extent to which the spatial memory performance of echidnas (or "spiny anteaters") can be understood in terms of the spatio-temporal distribution of their prey (ants and termites). This is a species and a foraging situation that have not been examined in this way before. Echidnas were better able to learn to avoid a previously rewarding location (to "win-shift") than to learn to return to a previously rewarding location (to "win-stay"), at short retention intervals, but were unable to learn either of these strategies at retention intervals of 90 min. The short retention interval results support the ecological hypothesis, but the long retention interval results do not. Electronic Publication     

The Factor Structure of the Beavers Interactional Scales

Confirmatory factor analysis and regression analyses of the Beavers Interactional Scales did not appear to support the model offered by its developers, namely, several specified family attributes contributing respectively to two global factors of Family Competence and Family Style. Moreover, regression analysis indicated that only three of 12 items predicted raters' assessments of Global Family Health, and one of seven items predicted Global Family Style. Individuals interested in the family dynamic centripetal/centrifugal might best think of that as a unitary entity and rate it accordingly.