A social-cognitive,attributional model of personal goals: An empirical evaluation

A model of cognitive and affective antecedents and consequences of personal goals, which integrates constructs from social-cognitive and attribution theories, was examined. Data were gathered before and after course examinations in a large university class. Hierarchical and moderated regression analyses supported the model indicating that (1) relationships between self-efficacy, goals, and performance were positive during repeated trials over 4 1/2 months in a naturally occurring setting; (2) the stability dimension of causal attributions moderated the relationship between goal-performance discrepancies and self-efficacy; and (3) the locus of causality dimension of causal attributions moderated the relationship between goal-performance discrepancies and affective responses.We thank Susan Ashford, Jim Austin, Donald Fedor, Ruth Kanfer, Edwin Locke, Paul Nystrom, Donna Randall, Christina Shalley, Masoud Yasai-Ardekani and two anonymous reviewers for their helpful comments on earlier versions of this article. We also thank Eric Dietenberger for his help with graphics.     

Parallel distributed processing and neuropsychology: A neural network model of Wisconsin card sorting and verbal fluency

Neural networks can be used as a tool in the explanation of neuropsychological data. Using the Hebbian Learning Rule and other such principles as competition and modifiable interlevel feedback, researchers have successfully modeled a widely used neuropsychological test, the Wisconsin Card Sorting Test. One of these models is reviewed here and extended to a qualitative analysis of how verbal fluency might be modeled, which demonstrates the importance of accounting for the attentional components of both tests. Difficulties remain in programming sequential cognitive processes within a parallel distributed processing (PDP) framework and integrating exceedingly complex neuropsychological tests such as Proverbs. PDP neural network methodology offers neuropsychologists co-validation procedures within narrowly defined areas of reliability and validity.     

Data generation and analysis using spreadsheets

Modern spreadsheets are powerful and useful tools that can often replace special-purpose programs for generating data and for student analysis of simple statistical problems. The inherent flexibility of spreadsheets makes them especially convenient and extensible. Several templates for generating and analyzing data fort tests and analysis of variance are discussed. Users can specify then, \(\bar X\) , andSD of two or more groups and then execute macros that generate appropriate data. Overwriting the generated data with “real” values turns the spreadsheet into a data analysis program. Spreadsheets hold promise as valuable instructional supplements for simple designs, but they are less suitable for more complex designs, where special-purpose programs may be more appropriate.     

A quasi-nonmetric method for multidimensional scaling VIA an extended euclidean model

An Extended Two-Way Euclidean Multidimensional Scaling (MDS) model which assumes both common and specific dimensions is described and contrasted with the standard (Two-Way) MDS model. In this Extended Two-Way Euclidean model then stimuli (or other objects) are assumed to be characterized by coordinates onR common dimensions. In addition each stimulus is assumed to have a dimension (or dimensions) specific to it alone. The overall distance between objecti and objectj then is defined as the square root of the ordinary squared Euclidean distance plus terms denoting the specificity of each object. The specificity,s _j , can be thought of as the sum of squares of coordinates on those dimensions specific to objecti, all of which have nonzero coordinatesonly for objecti. (In practice, we may think of there being just one such specific dimension for each object, as this situation is mathematically indistinguishable from the case in which there are more than one.)We further assume that _ij =F(d _ij ) +e _ij where _ij is the proximity value (e.g., similarity or dissimilarity) of objectsi andj,d _ij is the extended Euclidean distance defined above, whilee _ij is an error term assumed i.i.d.N(0, ²).F is assumed either a linear function (in the metric case) or a monotone spline of specified form (in the quasi-nonmetric case). A numerical procedure alternating a modified Newton-Raphson algorithm with an algorithm for fitting an optimal monotone spline (or linear function) is used to secure maximum likelihood estimates of the paramstatistics) can be used to test hypotheses about the number of common dimensions, and/or the existence of specific (in addition toR common) dimensions.This approach is illustrated with applications to both artificial data and real data on judged similarity of nations.     

History,philosophy, and science teaching: A brief review

School science education is currently the subject of much debate. Historians and philosophers of science should play a role in this debate. Since the late nineteenth century there has been a persistent, if minor, tradition arguing for the incorporation of historical and philosophical dimensions in the teaching of school science. With the current crisis in science teaching, there are encouraging signs that more attention is being paid to this tradition. What is required is much greater collaboration between philosophers, historians, and science educators, particularly in the training of teachers.This article is a shortened version of my 1988, A Role for History and Philosophy in Science Teaching, inEducational Philosophy and Theory 20 (2). All references are to the following History, Philosophy, and Science Teaching: A Bibliography.This special number ofSynthese is part of a large international project on the place of history and philosophy in science teaching. Special issues ofEducational Philosophy and Theory, Interchange, andStudies in Philosophy and Education are being produced. An international conference on the subject will be held at Florida State University in November 1989. Details of the journals and the conference can be obtained from the author.The project commenced while the author was on leave at Florida State University in 1987. It began with a gracious invitation from Jaakko Hintikka to guest edit this number, and was furthered with the support and encouragement of David Gruender. I thank them both, and also the Philosophy Department for its hospitality. Special appreciation is due to the nearly 30 authors who have contributed papers to the project. I hope that their efforts will re-open the needed dialogue between historians, philosophers, and science educators.     

Assessing the relationship of Type A beliefs to cardiovascular disease risk and psychosocial distress

Investigators have begun to take a multimodal approach to the assessment and treatment of psychosocial risk factors for cardiovascular disease (CVD). For instance, cognitive responses have become the focus of contemporary research along with continued examination of overt Type A behaviors. Price (1982) has outlined a set of beliefs purportedly associated with Type A behavior and subsequent CVD risk. The current study examines the validity of this belief set as represented by a newly developed measure, the Type A Cognitive Questionnaire (TACQ). Subjects were 221 employed adults participating in a worksite CVD risk reduction program. They completed the TACQ as part of a pretreatment CVD risk screening protocol. As hypothesized, TACQ scores were significantly associated with Type A behavior, hostility, physiological mediators of CVD, and psychosocial distress. Discussion addresses continued refinement of the Type A belief construct.