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Cited by 488

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Investigating instructional strategies for using social media in formal and informal learning

Open access
Chen, Baiyun, Bryer, Thomas·2012·The International Review of Research in Open and Distributed Learning

Abstract

Despite the high popularity of personal use of online social media, a low percentage of students and instructors use them for educational purposes. This qualitative study explores the use of social media among faculty in the discipline of public administration in the United States. Eight instructors participated in telephone interviews about their experiences and perceptions of using social media for teaching and learning. Instructors perceive that informal learning using social media could be facilitated by instructors and integrated into formal learning environments for enriched discussions, increased engagement, and broad connections. This study provides qualitative empirical support for social learning theories while offering strategies for and examples of how social media can be used to connect formal and informal learning.

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Metadata

Authors
Chen, B., & Bryer, T.
Venue
The International Review of Research in Open and Distributed Learning
Published
2012-01-31
Volume
13
Issue
1
Pages
87
ISSN
1492-3831 (ISSN-L)
OpenAlex
W2145283076
Cited by
488
References
3
FWCI
100.47
Type
journal article
Language
en
Open access
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CoChat. (2026). Citation check: Investigating instructional strategies for using social media in formal and informal learning. https://app.cochat.ai/papers/10.19173/irrodl.v13i1.1027
The paper
Chen, B., & Bryer, T. (2012). Investigating instructional strategies for using social media in formal and informal learning. The International Review of Research in Open and Distributed Learning. https://doi.org/10.19173/irrodl.v13i1.1027

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.