TY - JOUR
T1 - Technology-enhanced learning in higher education
T2 - A bibliometric analysis with latent semantic approach
AU - Shen, Chien wen
AU - Ho, Jung tsung
N1 - Publisher Copyright:
© 2019 Elsevier Ltd
PY - 2020/3
Y1 - 2020/3
N2 - 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.
AB - 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.
KW - Bibliometrics analysis
KW - Direct citation network
KW - Latent semantic analysis
KW - Technology-enhanced learning
KW - Topic analysis
UR - http://www.scopus.com/inward/record.url?scp=85074012929&partnerID=8YFLogxK
U2 - 10.1016/j.chb.2019.106177
DO - 10.1016/j.chb.2019.106177
M3 - 期刊論文
AN - SCOPUS:85074012929
SN - 0747-5632
VL - 104
JO - Computers in Human Behavior
JF - Computers in Human Behavior
M1 - 106177
ER -