Cited by 2Educational Technology in LearningOnline and Blended LearningTechnology-Enhanced Education Studies

Contribution of Social Networks in Learning: A Study in Higher Education

Chamba-Rueda, Laura Magali, Armas, Reinaldo, Pardo-Cueva, Mariuxi·2023·Smart Innovation, Systems and Technologies

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Crossref · 10.1007/978-981-19-6585-2_50

Cites

17 of 17 references verified0 citation errors · 0 not checkable

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  • These findings are consistent with some studies conducted in recent years.

    “These findings are consistent with some studies conducted in recent years (Aba & Makinde, 2023;Awidi, Paynter & Vujosevic, 2019;Chamba-Rueda, Armas & Pardo-Cueva, 2023;Crilly & Kayyali, 2020;Manu et al., 2021).”

    From Opinions of Faculty Members on the Effects of Using Social Media in Higher Education (2023) · cites this paper as Chamba-Rueda, Armas & Pardo-Cueva, 2023

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Authors
Chamba-Rueda, L. M., Armas, R., & Pardo-Cueva, M.
Affiliations
Universidad Técnica Particular de Loja (EC)
Corresponding author
Chamba-Rueda, Laura Magali
Venue
Smart Innovation, Systems and Technologies
Published
2023
Pages
567-576
ISSN
  • 2190-3018 (ISSN-L)
  • 2190-3026
OpenAlex
W4313481527
Cited by
2
References
17
Citations by year
2024: 1 · 2023: 1
FWCI
1.33
Type
book chapter
Language
en
Open access
closed
Locations
Smart innovation, systems and technologies (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Information Systems › Educational Technology in Learning
  • Social Sciences › Education › Online and Blended Learning
  • Social Sciences › Education › Technology-Enhanced Education Studies
Keywords
social networks, higher education, group work, academic performance, cooperative learning, student motivation, information society, Universidad Técnica Particular de Loja

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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

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