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Cited by 314

The DOI matches its OpenAlex record; 5 of the 5 references it cites were found in a registry or an index.

Collaborative Discovery in a Scientific Domain

Open access
Takeshi Okada, Herbert A. Simon·1997·Cognitive Science

Abstract

This study compares Pairs of subjects with Single subjects in a task of discovering scientific laws with the aid of experiments. Subjects solved a molecular genetics task in a computer micro‐world (Dunbar, 1993). Pairs were more successful in discovery than Singles and participated more actively in explanatory activities (i.e., entertaining hypotheses and considering alternative ideas and justifications). Explanatory activities were effective for discovery only when the subjects also conducted crucial experiments. Explanatory activities were facilitated when paired subjects made requests of each other for explanation and focused on them. The study extends from individual to collaborative discovery activities the importance to the discovery process of setting goals to find hypotheses and evidence (Dunbar, 1993) and to construct explanations of phenomena and processes encountered in examples (Chi, Bassok, Lewis, & Glaser, 1989).

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OpenAlex · 10.1016/s0364-0213(99)80020-2

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Metadata

Authors
Okada, T., & Simon, H. A.
Venue
Cognitive Science
Publisher
Wiley
Published
1997-04-01
Volume
21
Issue
2
Pages
109-146
ISSN
0364-0213 (ISSN-L)
OpenAlex
W2061622313
Cited by
314
References
5
FWCI
60.80
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Collaborative Discovery in a Scientific Domain. https://app.cochat.ai/papers/10.1016/s0364-0213(99)80020-2
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Okada, T., & Simon, H. A. (1997). Collaborative Discovery in a Scientific Domain. Cognitive Science. https://doi.org/10.1016/s0364-0213(99)80020-2

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.