TY - GEN
T1 - Quality Function Deployment Approach to Optimize E-learning Adoption among Lecturers in Universitas Indonesia
AU - Winarno, Dilla Aulia
AU - Muslim, Erlinda
AU - Rafi, Muhammad
AU - Rosetta, Alga
N1 - Funding Information:
This paper is supported by Universitas Indonesia through the Publikasi Terindeks Internasional Prosiding (PUTI) NKB-1156/UN2.RST/HKP.05.00/2020.
Publisher Copyright:
© 2020 ACM.
Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2020/11/6
Y1 - 2020/11/6
N2 - Along with the development of information system technology in the 21st century, the world has faced Industrial Revolution 4.0, this enhance transformation impacted all industries, including Education to create a new ecosystem named Education 4.0. This utilizes Electronic learning (E-learning) and many high institutions applied the E-learning system in their education scheme, but the level usage of e-learning is relatively low because of the lack of intention from lecturers as the user. This paper analyzed the factors that influence continuous intention in using e-learning with combined models; TAM (Technology Acceptance Model), TPB (Theory of Planned Behavior), ECM (Expectation Confirmation Model), and Flow Theory, and the results are continuance intention was associated with attitude, perceived enjoyment, perceived usefulness, satisfaction, confirmation, and perceived ease of use. Based on these factors, the researchers created and prioritized the strategies using Quality Function Deployment and concluded the improvements to increase the intention are training e-learning systems to users, add new interactive features, and enhancement in the e-learning interface.
AB - Along with the development of information system technology in the 21st century, the world has faced Industrial Revolution 4.0, this enhance transformation impacted all industries, including Education to create a new ecosystem named Education 4.0. This utilizes Electronic learning (E-learning) and many high institutions applied the E-learning system in their education scheme, but the level usage of e-learning is relatively low because of the lack of intention from lecturers as the user. This paper analyzed the factors that influence continuous intention in using e-learning with combined models; TAM (Technology Acceptance Model), TPB (Theory of Planned Behavior), ECM (Expectation Confirmation Model), and Flow Theory, and the results are continuance intention was associated with attitude, perceived enjoyment, perceived usefulness, satisfaction, confirmation, and perceived ease of use. Based on these factors, the researchers created and prioritized the strategies using Quality Function Deployment and concluded the improvements to increase the intention are training e-learning systems to users, add new interactive features, and enhancement in the e-learning interface.
KW - E-learning
KW - Education 4.0
KW - Information System
KW - Quality Function Deployment
KW - Structural Modelling Equation
UR - http://www.scopus.com/inward/record.url?scp=85101918651&partnerID=8YFLogxK
U2 - 10.1145/3439147.3439157
DO - 10.1145/3439147.3439157
M3 - Conference contribution
AN - SCOPUS:85101918651
T3 - ACM International Conference Proceeding Series
SP - 161
EP - 166
BT - ICEEL 2020 - 2020 4th International Conference on Education and E-Learning
PB - Association for Computing Machinery
T2 - 4th International Conference on Education and E-Learning, ICEEL 2020
Y2 - 6 November 2020 through 8 November 2020
ER -