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This paper presents a case study of 3- to 9-year-old children's concepts of size, weight, density, matter, and material kind. Our goal was to examine two claims: (1) that individual concepts undergo differentiation during development; and (2) that young children's concepts are embedded in theory-like structures. To make progress on the first issue, we needed to specify in representational terms what an undifferentiated concept is like and in what sense this undifferentiated concept is a parent of the more differentiated concepts. Our strategy was to use a model of conceptual differentiation suggested by the history of science to guide our search for evidence. In this model, undifferentiated concepts, like differentiated concepts, can be analyzed in terms of their component properties, features, or dimensions. The key difference is that an undifferentiated concept unites certain components which will subsequently be analyzed as components of distinct concepts, and that the undifferentiated concept is embedded in a different theoretical structure from the differentiated concepts. In our study, the same group of 78 children (18 3-year-olds, 18 4-year-olds, 18 5-year-olds, 12 6-7-year-olds, and 12 8-9-year-olds) were given a range of tasks probing their understanding of size, weight, and density; a

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Research on judgment and choice has been dominated by functionalist assumptions that depict people as either intuitive scientists animated by epistemic goals or intuitive economists animated by utilitarian ones. This article identifies 3 alternative social functionalist starting points for inquiry: people as pragmatic politicians trying to cope with accountability demands from key constituencies in their lives, principled theologians trying to protect sacred values from secular encroachments, and prudent prosecutors trying to enforce social norms. Each functionalist framework stimulates middle-range theories that specify (a) cognitive–affective–behavioral strategies of coping with adaptive challenges and (b) the implications of these coping strategies for identifying empirical and normative boundary conditions on judgmental tendencies classified as errors or biases within the dominant research programs. Once an esoteric specialty of a small cadre of cognitive psychologists, experimental research on judgment and choice has—to judge just by citation counts—become psychology’s leading intellectual export to the social sciences as well as to a host of applied fields. The influence of this research program has spread (critics might say “metastasized”) into such diverse domains as

In social science, everything is somewhat correlated with everything (“crud factor”), so whether H0 is refuted depends solely on statistical power. In psychology, the directional counternull of interest, H*, is not equivalent to the substantive theory T, there being many plausible alternative explanations of a mere directional trend (weak use of significance tests). Testing against a predicted point value (the strong use of significant tests) can discorroborate T by refuting H*. If used thus to abandon T forthwith, it is too strong, not allowing for theoretical verisimilitude as distinguished from truth. Defense and amendment of an apparently falsified T are appropriate strategies only when T has accumulated a good track record (“money in the bank”) by making successful or near-miss predictions of low prior probability (Salmon’s “damn strange coincidences”). Two rough indexes are proposed for numerifying the track record, by considering jointly how intolerant (risky) and how close (accurate) are its predictions. For almost three quarters of a century, the received doctrine about appraising psychological theories has been to perform a statistical significance test. In the “soft ” areas (clinical, counseling, developmental, personality, and social psychology),

This article examines the theoretical status of latent variables as used in modern test theory models. First, it is argued that a consistent interpretation of such models requires a realist ontology for latent variables. Second, the relation between latent variables and their indicators is discussed. It is maintained that this relation can be interpreted as a causal one but that in measurement models for interindividual differences the relation does not apply to the level of the individual person. To substantiate intraindividual causal conclusions, one must explicitly represent individual level processes in the measurement model. Several research strategies that may be useful in this respect are discussed, and a typology of constructs is proposed on the basis of this analysis. The need to link individual processes to latent variable models for interindividual differences is emphasized. Consider the following sentence: “Einstein would not have been able to come up with his e � mc 2 had he not possessed such an extraordinary intelligence. ” What does this sentence express? It relates observable behavior (Einstein’s writing e � mc 2)toan unobservable attribute (his extraordinary intelligence), and it does so by assigning to the unobservable attribute a causal role in

This article advances a simple conception of test validity: A test is valid for measuring an attribute if (a) the attribute exists and (b) variations in the attribute causally produce variation in the measurement outcomes. This conception is shown to diverge from current validity theory in several respects. In particular, the emphasis in the proposed conception is on ontology, reference, and causality, whereas current validity theory focuses on epistemology, meaning, and correlation. It is argued that the proposed conception is not only simpler but also theoretically superior to the position taken in the existing literature. Further, it has clear theoretical and practical implications for validation research. Most important, validation research must not be directed at the relation between the measured attribute and other attributes but at the processes that convey the effect of the measured attribute on the test scores. We start this article with a request to the reader. Please take a slip of paper and write down your definition of the term construct validity. Now, take the classic article of Cronbach and Meehl (1955), who invented the concept, and a more recent authoritative article on validity, for instance that of Messick (1989), and check whether you recognize your definition in these works. You are

been embedded in the notion of technological impacts on society. References to the impacts of technology on society are pervasive in the literature of technology education. The notion of technological impacts is simple to comprehend and has permitted the field to interpret technology in the context of society and culture, but it has also contributed to a simplistic and inflexible view of the relationship between technology and society. The expression “technological impacts ” is a metaphor that implies that technology is a discrete force with a discernible direction and influence. Metaphors are figures of speech widely used in all disciplines and essentially involve the transfer of descriptive terms from primary usage to different, but

During the last three years we have been building an instantiation of a system's development paradigm, called ARTS. The paradigm consists of a view of what a system development environment is, in general terms, and a methodology for instantiating the paradigm for particular and specific domains of application. The motivation for and the explanation of the paradigm are derived from extant epistemological models of the method of Natural Science. We assert that these models are directly applicable to the domain of software and systems construction, and that, from them, we can derive principles and explanations for what a software development environment should be. We present a brief description of the Statement View of scientific theories, a conceptual architecture for software development environments whose rationale is given in terms of the Statement View and some examples of how the present instantiation of ARTS realises this conceptual architecture. 1# INTRODUCTION An envir...

“…the trademark of modern culture is science; if you can fake this, you’ve got it made ”- Mario Bunge The need for a special issue of Emergence on the question “What is complexity science? ” is disturbing on several levels. At one level, one could be forgiven for thinking that the voluminous literature generated in recent years on chaos and complexity theory must contain a clear exposition on the definition, mission, and scope of complexity science. That this exposition has not been forthcoming, or is the subject of controversy, is disconcerting. On another level, the inability to clearly differentiate science from pseudoscience in complexity studies is also problematic. Allowing pseudo-science to penetrate a field of study lowers the credibility of that field with mainstream scientists and hinders the flow of resources for future development. It is my contention that much of the work in complexity theory has indeed been pseudo-science, that is, many writers in this field have used the symbols and methods of complexity science (either erroneously or deliberately) to give the illusion of science even though they lack supporting evidence and plausibility (Shermer, 1997). This proliferation of pseudo-science has, in turn, obscured the meaning and agenda of the science of complexity. The purpose of this article is twofold: 1) to provide a working definition of complexity science and 2) to use this definition to differentiate complexity science from complexity