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Cited by 283

The DOI matches its Crossref record; 111 of the 111 references it cites were found in a registry or an index.

Technology-enhanced learning in higher education: A bibliometric analysis with latent semantic approach

Shen, Chien-wen, Ho, Jung-tsung·2020·Computers in Human Behavior
DOI 10.1016/j.chb.2019.106177
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Abstract

Abstract Technology-enhanced learning (TEL) describes information and communication technology applications as enhancing the outcomes of teaching and learning. Its adoption in higher education is an innovation as well as a disruption to conventional learning mechanisms. To further understand its development from the perspective of academic communities, a hybrid bibliometric approach that combines both direct citation network analysis and text analytics was proposed to examine the related research articles retrieved from the Web of Science database. In addition to visual analytics on the TEL research, a direct citation network approach with cluster analysis was used to delineate the historiographic development of the TEL research domain in higher education. Among the top internally cited articles, five main streams of TEL development were identified, namely adoption, critique, social media, podcasting, and blended learning. Then, the accumulated state of knowledge was summarized by highlighting the essential subgroup topics in each stream with latent semantic analysis. The extraction of the key features of the research domain by the proposed hybrid approach, including the principal streams of development, associated subgroup topics, and a critical article list, contributes a comprehensive method to enable the rapid understanding of the overall research development of the TEL in higher education.

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Research works printed but not linked: 4

  1. Kiteley, 2009, Towards a team-based, collaborative approach to embedding e-learning within undergraduate nursing programmes, Nurse Education Today, 29, 623, 10.1016/j.nedt.2009.01.010 · doi:10.1016/j.nedt.2009.01.010
  2. Lin, 2013, Towards an education behavioral intention model for e-learning systems: An extension of UTAUT, Journal of Theoretical and Applied Information Technology, 47
  3. Liu, 2016, The impact of peer review on creative self-efficacy and learning performance in Web 2.0 learning activities, Educational Technology & Society, 19, 286
  4. Shen, 2015, Learning in massive open online courses: Evidence from social media mining, Computers in Human Behavior, 51, 568, 10.1016/j.chb.2015.02.066 · doi:10.1016/j.chb.2015.02.066

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Metadata

Authors
Shen, C.-W., & Ho, J.-T.
Venue
Computers in Human Behavior
Publisher
Elsevier BV
Published
2020-03
Volume
104
Pages
106177
ISSN
0747-5632 (ISSN-L)
DOI
10.1016/j.chb.2019.106177
OpenAlex
W2981769453
Cited by
283
References
111
FWCI
36.86
Type
journal article
Language
en
Open access
closed
Licence
  • www.elsevier.com/tdm/userlicense/1.0/ (tdm)
  • www.elsevier.com/legal/tdmrep-license (tdm)

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CoChat. (2026). Citation check: Technology-enhanced learning in higher education: A bibliometric analysis with latent semantic approach. https://app.cochat.ai/papers/10.1016/j.chb.2019.106177
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Shen, C.-W., & Ho, J.-T. (2020). Technology-enhanced learning in higher education: A bibliometric analysis with latent semantic approach. Computers in Human Behavior. https://doi.org/10.1016/j.chb.2019.106177

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.