@article{ART003153914},
author={Chang Jiyeun},
title={Analysis of Switching Intention to ChatGPT as a Learning Tool: Applying Push-Pull-Mooring Theory},
journal={Journal of Internet of Things and Convergence},
issn={2466-0078},
year={2024},
volume={10},
number={6},
pages={87-94}
TY - JOUR
AU - Chang Jiyeun
TI - Analysis of Switching Intention to ChatGPT as a Learning Tool: Applying Push-Pull-Mooring Theory
JO - Journal of Internet of Things and Convergence
PY - 2024
VL - 10
IS - 6
PB - The Korea Internet of Things Society
SP - 87
EP - 94
SN - 2466-0078
AB - This study aims to identify the factors influencing the intention to switch to ChatGPT, which has emerged as a powerful alternative to traditional learning tools and internet searches, using the Push-Pull-Mooring (PPM) framework to establish a research model. The push factors include the limitations of traditional lecture environments and the lack of immediate feedback, while the pull factors are ease of access and the provision of personalized learning experiences. Social influence was selected as a mooring factor and set as a moderating variable to examine its effect on the intention to switch. A survey was conducted among university students in Chungcheongnam-do, and the data were analyzed using SPSS 27 and SmartPLS 4.0. The results revealed that push factors (limitations of traditional lecture environments), pull factors (ease of access and personalized learning experiences), and mooring factors (social influence) significantly affect the intention to switch. Notably, the moderating effect of social influence was significant only for ease of access, reflecting the decision-making characteristics of Generation Z university students. This study is expected to provide important insights into the utilization and development of innovative learning tools and the formulation of educational strategies through the analysis of ChatGPT switching intentions.
KW - Push-Pull-Mooring(PPM) Theory;ChatGPT;Switching Intention;Generative AI;Learning Tools
DO -
UR -
ER -
Chang Jiyeun. (2024). Analysis of Switching Intention to ChatGPT as a Learning Tool: Applying Push-Pull-Mooring Theory. Journal of Internet of Things and Convergence, 10(6), 87-94.
Chang Jiyeun. 2024, "Analysis of Switching Intention to ChatGPT as a Learning Tool: Applying Push-Pull-Mooring Theory", Journal of Internet of Things and Convergence, vol.10, no.6 pp.87-94.
Chang Jiyeun "Analysis of Switching Intention to ChatGPT as a Learning Tool: Applying Push-Pull-Mooring Theory" Journal of Internet of Things and Convergence 10.6 pp.87-94 (2024) : 87.
Chang Jiyeun. Analysis of Switching Intention to ChatGPT as a Learning Tool: Applying Push-Pull-Mooring Theory. 2024; 10(6), 87-94.
Chang Jiyeun. "Analysis of Switching Intention to ChatGPT as a Learning Tool: Applying Push-Pull-Mooring Theory" Journal of Internet of Things and Convergence 10, no.6 (2024) : 87-94.
Chang Jiyeun. Analysis of Switching Intention to ChatGPT as a Learning Tool: Applying Push-Pull-Mooring Theory. Journal of Internet of Things and Convergence, 10(6), 87-94.
Chang Jiyeun. Analysis of Switching Intention to ChatGPT as a Learning Tool: Applying Push-Pull-Mooring Theory. Journal of Internet of Things and Convergence. 2024; 10(6) 87-94.
Chang Jiyeun. Analysis of Switching Intention to ChatGPT as a Learning Tool: Applying Push-Pull-Mooring Theory. 2024; 10(6), 87-94.
Chang Jiyeun. "Analysis of Switching Intention to ChatGPT as a Learning Tool: Applying Push-Pull-Mooring Theory" Journal of Internet of Things and Convergence 10, no.6 (2024) : 87-94.
