Verifying the link of innovativeness to the confirmation-expectation model of ChatGPT of students in learning

Purpose The purpose of this study is to explore how innovativeness influences learners’ intentions to continue using ChatGPT. Design/methodology/approach Data from 260 valid respondents are gathered online and analyzed with structure equation modeling. Findings The findings of this study show that user satisfaction significantly enhances learners’ intention to continue using ChatGPT in their studies. Moreover, learners exhibit distinct continuance patterns based on their innovativeness toward ChatGPT. Research limitations/implications These results help address the limitations of traditional expectation-confirmation theory in explaining the information systems expectation formation process. Originality/value The results also reflect the coming of flipping classrooms by generative artificial intelligence as a bottom-up innovation.

Authors

Publication Details

Journal
Journal of Information Communication and Ethics in Society
Published
2025-05-30
DOI
https://doi.org/10.1108/jices-07-2024-0086
Citations
7
Primary Topic
Engineering Education and Technology
Type
article
Field-Weighted Citation Impact
22.72
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article

Verifying the link of innovativeness to the confirmation-expectation model of ChatGPT of students in learning

Hsiu-Ju Chen
7 citations
Journal of Information Communication and Ethics in Society
Engineering Education and Technology
22.72
article

Verifying the link of innovativeness to the confirmation-expectation model of ChatGPT of students in learning

Hsiu-Ju Chen
article en
7 citations

Abstract

Purpose The purpose of this study is to explore how innovativeness influences learners’ intentions to continue using ChatGPT. Design/methodology/approach Data from 260 valid respondents are gathered online and analyzed with structure equation modeling. Findings The findings of this study show that user satisfaction significantly enhances learners’ intention to continue using ChatGPT in their studies. Moreover, learners exhibit distinct continuance patterns based on their innovativeness toward ChatGPT. Research limitations/implications These results help address the limitations of traditional expectation-confirmation theory in explaining the information systems expectation formation process. Originality/value The results also reflect the coming of flipping classrooms by generative artificial intelligence as a bottom-up innovation.

Journal of Information Communication and Ethics in SocietyVol. 23(3)
Openalex Percentile: Top 1%
Engineering Education and Technology
22.72
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