Mining Teacher Informal Online Learning Networks: Insights from Massive Educational Chat Tweets

Autor/inn/en	Du, Hanxiang; Xing, Wanli; Zhu, Gaoxia
Titel	Mining Teacher Informal Online Learning Networks: Insights from Massive Educational Chat Tweets
Quelle	In: Journal of Educational Computing Research, 61 (2023) 1, S.127-150 (24 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Du, Hanxiang) ORCID (Xing, Wanli)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0735-6331
DOI	10.1177/07356331221103764
Schlagwörter	Faculty Development; Informal Education; Teacher Education; Social Networks; Network Analysis; Communities of Practice; Social Media; Affordances; Interpersonal Communication; Discourse Analysis + Suchen Sie Ihr Suchwort? Informelle Bildung; Nichtformale Bildung; Lehrerausbildung; Lehrerbildung; Social network; Soziales Netzwerk; Netzplantechnik; Community; Soziale Medien; Interpersonale Kommunikation; Diskursanalyse
Abstract	Social-media-based teacher learning networks have the affordance to grant flexibility of time and space for teachers' professional learning, support the development and sustainability of social networking, and meet their just-in-time needs for exchanging knowledge, negotiating meaning and accessing resources. However, most existing research on teacher online learning networks relies on qualitative methods and self-report data. There is a lack of study using quantitative methods to study large networks, especially using authentic data from social media. This work adds to the literature through mining teacher informal online learning networks using authentic data retrieved from Twitter. Specifically, we collected around half a million tweets and developed a network with the data. Then, various social network analysis techniques were utilized to explore the network structure and characteristics, participants' behavioral patterns and how individuals connected with each other. We found that members of massive teacher informal online learning networks tended to communicate more with others of similar characteristics forming homogeneous communities, while hub participants connected many small communities which are significantly from one another, and hence, are the key to degree heterogeneity in a large network. (As Provided).
Anmerkungen	SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01