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

Chien wen Shen, Jung tsung Ho

Research output: Contribution to journalArticlepeer-review

75 Scopus citations

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.

Original languageEnglish
Article number106177
JournalComputers in Human Behavior
Volume104
DOIs
StatePublished - Mar 2020

Keywords

  • Bibliometrics analysis
  • Direct citation network
  • Latent semantic analysis
  • Technology-enhanced learning
  • Topic analysis

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