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Cited by 364

The DOI matches its Crossref record; 83 of the 83 references it cites were found in a registry or an index.

“Isms” in information science: constructivism, collectivism and constructionism

Talja, Sanna, Tuominen, Kimmo, Savolainen, Reijo·2005·Journal of Documentation

Abstract

Purpose: Describes the basic premises of three metatheories that represent important or emerging perspectives on information seeking, retrieval and knowledge formation in information science: constructivism, collectivism, and constructionism. Design/methodology/approach: Presents a literature‐based conceptual analysis. Pinpoints the differences between the positions in their conceptions of language and the nature and origin of knowledge. Findings: Each of the three metatheories addresses and solves specific types of research questions and design problems. The metatheories thus complement one another. Each of the three metatheories encourages and constitutes a distinctive type of research and learning. Originality/value: Outlines each metatheory's specific fields of application.

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Crossref · 10.1108/00220410510578023

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Metadata

Authors
Talja, S., Tuominen, K., & Savolainen, R.
Venue
Journal of Documentation
Publisher
Emerald
Published
2005-02-01
Volume
61
Issue
1
Pages
79-101
ISSN
0022-0418 (ISSN-L)
OpenAlex
W1992156462
Cited by
364
References
83
FWCI
44.49
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: “Isms” in information science: constructivism, collectivism and constructionism. https://app.cochat.ai/papers/10.1108/00220410510578023
The paper
Talja, S., Tuominen, K., & Savolainen, R. (2005). “Isms” in information science: constructivism, collectivism and constructionism. Journal of Documentation. https://doi.org/10.1108/00220410510578023

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.