The use of analogues in comparability analysis

Klein, Gary; Weitzenfeld, Julian

doi:10.1016/0003-6870(82)90186-7

Cited by 16 publications

(6 citation statements)

References 3 publications

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“…That is, if analogical reasoning processes are critical for the generation of new implications from existing data and observations, then we might be able to apply what is known about scientific discovery to an understanding of more ordinary predictions. However, Klein and Weitzenfeld (1982) observed that engineers were not following the procedures Hesse had suggested. This was because they were not interested in identifying new hypotheses.…”

Section: Hypothesis Generationmentioning

confidence: 92%

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Applications of Analogical Reasoning

Klein¹

1987

Metaphor and Symbolic Activity

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Section: Hypothesis Generationmentioning

confidence: 92%

“…Julian Weitzenfeld and I have attempted to determine the logical basis for using analogical reasoning for technological prediction (Klein & Weitzenfeld, 1982;Weitzenfeld, 1984). We have examined four different types of explanations.…”

Section: Theoretical Models Of Analogical Reasoningmentioning

confidence: 99%

Applications of Analogical Reasoning

Klein¹

1987

Metaphor and Symbolic Activity

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“…In Klein and Weitzenfeld's (1982;Klein, 1987) study of avionics engineers, the problemsolving protocols revealed the sorts of stages described in Winston's model, with the same emphasis on the mapping of cause-effect relationships. Holland, Holyoak, Nisbett, and Thagard (1986, chap.…”

Section: Factor Functionmentioning

confidence: 96%

A Naturalistic Exploration of Forms and Functions of Analogizing

Hoffman

Eskridge

Shelley

2009

Metaphor and Symbol

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The purpose of this article is to invigorate debate concerning the nature of analogy, and to broaden the scope of current conceptions of analogy. We argue that analogizing is not a single or even a fundamental cognitive process. The argument relies on an analysis of the history of the concept of analogy, case studies on the use of analogy in scientific problem solving, cognitive research on analogy comprehension and problem solving, and a survey of computational mechanisms of analogy comprehension. Analogizing is regarded as a macrocognitive phenomenon having a number of supporting processes. These include the apperception of resemblances and distinctions, metaphor, and the balancing of semantic flexibility and inference constraint. Psychological theories and computational models have generally relied on (a) a sparse set of ontological concepts (a property called "similarity" and a structuralist categorization of types of semantic relations), (b) a single form category (i.e., the classic four-term analogy), and (c) a single set of morphological distinctions (e.g., verbal vs. pictorial analogies). This article presents a classification based on a "naturalistic" exploration of the variety of uses of analogical reasoning in pragmatically distinct contexts. The resultant taxonomy distinguishes pre-hoc, ad-hoc, post-hoc, pro-hoc, contra-hoc, and trans-hoc analogy. Each will require its own macrocognitive modeling, and each presents an opportunity for research on phenomena of reasoning that have been neglected.

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“…Numerous models of analogical reasoning have been proposed by researchers, including the proportion model (a:b:c:d) examined by Sternberg (197), the similarity matching model of Tversky (1973), and the philosophy of science model presented by Hesse (1966). However, when studying these models (Klein & Weitzenfeld 1982), found that none seemed to reflect the most important aspect of Comparability Analysis choosing an appropriate analogous situation, in order to assess the difference between the current situation, and the predicted analogue, thereby deriving an inference by making appropriate adjustments in data obtained from the comparison case. The proportion model presents subjects with the analogy, but does not reflect how people identify good comparison cases, nor does it address how they make adjustments if the analogy does not fit perfectly.…”

Section: Comparison-based Prediction (Cbp) Approachmentioning

confidence: 99%

Comparison-Based Predictions and Recommendations for Army Maintenance Training Devices

Klein¹,

Gordon²,

Palmisano³

et al. 1985

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Sr% of this rep has been madeb RI Pleas ddress rresp ence'a erng ehava and Social Sc ences, ATTN: PERI-POT. 5001 Eisenhower lexandr a,Virgin 3 0 FINAL DISPOSITION: This report may be destroyed when it is no longer needed. Please do not return it to the U.S. Army Research Institute for the Behavioral and Social Sciences. NOTE: The findings in this report are not to be construed as an official Department of the Army position, unless so designated by other authorized documents. %.

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The use of analogues in comparability analysis

Cited by 16 publications

References 3 publications

Applications of Analogical Reasoning

Applications of Analogical Reasoning

A Naturalistic Exploration of Forms and Functions of Analogizing

Comparison-Based Predictions and Recommendations for Army Maintenance Training Devices

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