What does it mean to ‘live’ and ‘die’? A cross‐linguistic analysis of parent–child conversations in English and Indonesian

Previous work on children's intuitive knowledge about the natural world has documented their difficulty in acquiring an overarching concept of biological life that includes plants as well as humans and non‐human animals. It has also suggested that the acquisition of fundamental biological concepts like alive and die may be influenced by the language used to describe them, as evidenced by differences between English‐ and Indonesian‐speaking children's performance in tasks involving these concepts. Here, we examine one particularly important source of linguistic information available to children during this acquisition process: everyday conversations with their parents. We take a cross‐linguistic approach in analysing the evidence available to English‐ and Indonesian‐speaking children as they acquire meanings for words corresponding to the concepts alive and die . Our analysis illustrates that young children acquiring English and Indonesian are faced with distinct problems, but that parental input in both languages does little to support the acquisition of broad, inclusive biological concepts.     

Socializing Attribution: Generalization to “Real” Social Environments1

Social status variables have been shown to influence attributional judgments, but their effects have been demonstrated almost entirely in experimental settings. The influence of such statuses in experimental settings may differ from their influence in natural settings. We examined the influence on attributional judgments of the status characteristics of both subjects and actors in conjunction with variations in the degree of “real world” characteristics of both subjects and social context. These comparisons were drawn through a partial replication of earlier research investigating the effects of a social status variable, victim sex, and a situational variable—type of assault—on attributions about an assault victim. The social status characteristic, victim sex, had less influence on attributions in an adult juror sample than in a student sample and testimony-related characteristics were more influential in the adult juror sample than in the student sample. Thus, the categories of variables that influence attributions appear to depend on the context of judgment and on the breadth of subjects' life experience. These findings are discussed and we conclude with the caution that careful identification of the differences produced by context and subject characteristics is necessary to support generalization of laboratory-based research.     

Burden of proof

This paper presents an analysis of the concept of burden of proof in argument. Relationship of burden of proof to three traditional informal fallacies is considered: (i) argumentum ad hominem, (ii) petitio principii, and (iii) argumentum ad ignorantiam. Other topics discussed include persuasive dialoque, pragmatic reasoning, legal burden of proof, plausible reasoning in regulated disputes, rules of dialogue, and the value of reasoned dialogue.     

An automated test development of parallel tests from a seed test

Binary programming models are presented to generate parallel tests from an itembank. The parallel tests are created to match item for item an existing seed test and match user supplied taxonomic specifications. The taxonomic specifications may be either obtained from the seed test or from some other user requirement. An algorithm is presented along with computational results to indicate the overall efficiency of the process. Empirical findings based on an itembank for the Arithmetic Reasoning section of the Armed Services Vocational Aptitude Battery are given.The Office of Naval Research, Program in Cognitive Science, N00014-87-C-0696 partially supported the work of Douglas H. Jones. The Rutgers Research Resource Committee of the Graduate School of Management partially supported the work of Douglas H. Jones and Ing-Long Wu. A Thomas and Betts research fellowship partially supported the work of Ing-Long Wu. The Human Resources Laboratory, United States Air Force, partially supported the work of Ronald Armstrong. The authors benefited from conversations with Dr. Wayne Shore, Operational Technologies, San Antonio, Texas. The order of authors' names is alphabetical and denotes equal authorship.     

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.     

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.