The present paper analyzes the self‐generated explanations (from talk‐aloud protocols) that “Good” and “Poor” students produce while studying worked‐out examples of mechanics problems, and their subsequent reliance on examples during problem solving. We find that “Good” students learn with understanding: They generate many explanations which refine and expand the conditions for the action parts of the example solutions, and relate these actions to principles in the text. These self‐explanations are guided by accurate monitoring of their own understanding and misunderstanding. Such (...) learning results in example‐independent knowledge and in a better understanding of the principles presented in the text. “Poor” students do not generate sufficient self‐explanations, monitor their learning inaccurately, and subsequently rely heavily on examples. We then discuss the role of self‐explanations in facilitating problem solving, as well as the adequacy of current AI models of explanation‐based learning to account for these psychological findings. (shrink)

REPORTS 6 STUDIES USING LABORATORY REPLICAS OF THE SITUATION IN WHICH A BEGINNING CLINICIAN OBSERVES THE DIAGNOSTIC TEST PROTOCOLS OF PATIENTS WITH VARIOUS SYMPTOMS IN ORDER TO DISCOVER THE CHARACTERISTICS OF TEST PERFORMANCE THAT DISTINGUISH PATIENTS WITH EACH SYMPTOM. NAIVE UNDERGRADUATES VIEWED A SERIES OF 45 DRAW-A-PERSON TEST DRAWINGS RANDOMLY PAIRED WITH CONTRIVED SYMPTOM STATEMENTS ABOUT THE PATIENTS WHO DREW THEM. SS "REDISCOVERED" THE SAME RELATIONSHIPS BETWEEN DRAWING CHARACTERISTICS AND SYMPTOMS AS CLINICIANS REPORT OBSERVING IN CLINICAL PRACTICE, ALTHOUGH THESE RELATIONSHIPS (...) WERE ABSENT IN THE EXPERIMENTAL MATERIALS. THE REPORTED RELATIONSHIPS CORRESPONDED TO RATED ASSOCIATIVE STRENGTH BETWEEN SYMPTOM AND DRAWING CHARACTERISTIC. (shrink)

A central theme throughout the impressive series of philosophical books and articles Stephen Toulmin has published since 1948 is the way in which assertions and opinions concerning all sorts of topics, brought up in everyday life or in academic research, can be rationally justified. Is there one universal system of norms, by which all sorts of arguments in all sorts of fields must be judged, or must each sort of argument be judged according to its own norms? In The Uses (...) of Argument Toulmin sets out his views on these questions for the first time. In spite of initial criticisms from logicians and fellow philosophers, The Uses of Argument has been an enduring source of inspiration and discussion to students of argumentation from all kinds of disciplinary background for more than forty years. (shrink)

A scientific community cannot practice its trade without some set of received beliefs. These beliefs form the foundation of the "educational initiation that prepares and licenses the student for professional practice". The nature of the "rigorous and rigid" preparation helps ensure that the received beliefs are firmly fixed in the student's mind. Scientists take great pains to defend the assumption that scientists know what the world is like...To this end, "normal science" will often suppress novelties which undermine its foundations. Research (...) is therefore not about discovering the unknown, but rather "a strenuous and devoted attempt to force nature into the conceptual boxes supplied by professional education". (shrink)

This target article presents a new computational theory of explanatory coherence that applies to the acceptance and rejection of scientific hypotheses as well as to reasoning in everyday life, The theory consists of seven principles that establish relations of local coherence between a hypothesis and other propositions. A hypothesis coheres with propositions that it explains, or that explain it, or that participate with it in explaining other propositions, or that offer analogous explanations. Propositions are incoherent with each other if they (...) are contradictory, Propositions that describe the results of observation have a degree of acceptability on their own. An explanatory hypothesis is acccpted if it coheres better overall than its competitors. The power of the seven principles is shown by their implementation in a connectionist program called ECHO, which treats hypothesis evaluation as a constraint satisfaction problem. Inputs about the explanatory relations are used to create a network of units representing propositions, while coherende and incoherence relations are encoded by excitatory and inbihitory links. ECHO provides an algorithm for smoothly integrating theory evaluation based on considerations of explanatory breadth, simplicity, and analogy. It has been applied to such important scientific cases as Lovoisier's argument for oxygen against the phlogiston theory and Darwin's argument for evolution against creationism, and also to cases of legal reasoning. The theory of explanatory coherence has implications for artificial intelligence, psychology, and philosophy. (shrink)

In this book Bruno Latour brings together these different approaches to provide a lively and challenging analysis of science, demonstrating how social context..