Commentary on social class differences in sociodramatic play in historical context: A reply to McLoyd

Historical origins of the research on the cultural correlates of imaginative behavior by the Israeli psychologists Feitelson, Smilansky, and Eifermann are presented. It is argued that despite McLoyd's searching analysis of the deficiencies in studies which attempt to relate level of imaginative play to social class, those earlier cross-cultural studies, together with some 50 years of prior research on social class and play in general, provide a context which gives support to those studies despite their particular methodological deficiencies.     

Help-seeking: An understudied problem-solving skill in children

Traditional approaches to the study of young children's behavior in helping relationships are examined and criticized as inadequate because they have failed to represent the child's perspective from the role of “active helpee” (i.e., help-seeker in such relationships). By failing to look at helping from the perspective of the one who seeks help, researchers have neglected to pursue an important lead in understanding why some children are able to learn and progress independently when confronted with the same obstacles that serve to defeat other children. This article focuses on instrumental help-seeking defined as an active, complex social-cognitive activity that is essential to learning and achievement. In the first sections of this article, it is argued that instrumental help-seeking can be formally distinguished from passive dependency as well as from the actual giving and receiving of help. In following sections, a heuristic model of the help-seeking process is offered, prior research relevant to the model is reviewed, and ideas for research on help-seeking in children are suggested within the framework of this model.     

Behavior modification in education: Contributions and limitations

Behavior modification has been applied widely in educational settings encompassing a wide range of student populations, ages, and areas of focus. Major contributions of behavior modification include development and evaluation of a large number of techniques with extensive classroom research. As a direct consequence of technique development, behavior modification has provided teachers with a selection of classroom practices and information regarding their use. Despite the widespread application of behavioral principles in education, several limitations can be identified including the responses that are altered, the emphasis on response consequences, the focus on child performance rather than behaviors of teachers and others, and the lack of maintenance of improvements evident in many programs. Although limitations can be identified within the field, remarkable advances have been made in identifying educational practices that can improve student and teacher behavior. A major limitation in applying behavior modification to education pertains to dissemination and extension of existing techniques to a large number of settings likely to profit their use. The present paper considers various contributions and limitations of contemporary behavior modification and suggests areas for expansion to augment the progress that has been made.     

Dichhaptic laterality and field dependence

Relationships among laterality, field dependence, and sex were investigated using right handed subjects. Dichhaptic measures of laterality showed a significant left-hand advantage for the discrimination of irregular shapes. No significant relationships were found between laterality and sex or sex role perceptions nor between laterality and field dependence. A modality of response effect on the laterality task was interpreted in terms of the functional cerebral space principle.     

A learning algorithm for boltzmann machines

The computational power of massively parallel networks of simple processing elements resides in the communication bandwidth provided by the hardware connections between elements. These connections can allow a significant fraction of the knowledge of the system to be applied to an instance of a problem in a very short time. One kind of computation for which massively parallel networks appear to be well suited is large constraint satisfaction searches, but to use the connections efficiently two conditions must be met: First, a search technique that is suitable for parallel networks must be found. Second, there must be some way of choosing internal representations which allow the preexisting hardware connections to be used efficiently for encoding the constraints in the domain being searched. We describe a general parallel search method, based on statistical mechanics, and we show how it leads to a general learning rule for modifying the connection strengths so as to incorporate knowledge about a task domain in an efficient way. We describe some simple examples in which the learning algorithm creates internal representations that are demonstrably the most efficient way of using the preexisting connectivity structure.