Pragmatic GAI continuance through human-AI collaboration amid trendiness and creepiness

As generative artificial intelligence (GAI) becomes embedded in university learning, understanding why students continue using it is increasingly important. This study integrates the Expectation-Confirmation Model (ECM) and Task-Technology Fit (TTF) with Collaborative Effectiveness, Trendiness, and Creepiness to explain students’ GAI continuance. Survey data from 271 university students were analyzed using PLS-SEM.

The model explained 63.6% of the variance in continuance intention. Notably, TTF did not directly increase Perceived Usefulness; instead, its effect emerged through Confirmation, indicating that task fit becomes valuable when students’ actual experiences confirm their expectations. Collaborative Effectiveness, by contrast, directly enhanced Perceived Usefulness while also operating through Confirmation.

These post-use evaluations subsequently strengthened Satisfaction and Continuance Intention, revealing distinct but complementary pathways from functional fit and human–AI collaboration to continued use. Trendiness also promoted continuance, whereas Creepiness showed no significant direct effect. The findings extend post-adoption research by demonstrating how TTF is translated into sustained GAI use through experiential confirmation and subsequent post-use evaluations.

Practically, universities should move beyond simply providing AI access and design task-aligned learning activities that enable effective human–AI collaboration, verify AI outputs, and turn initial adoption into sustainable academic use. During the preparation of this work, the authors used Copilot in order to improve language and readability. After using this tool/service, the authors reviewed and edited the content as needed and took full responsibility for the content of the publication.

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. College of Education and Science, Yancheng Teachers University, Yancheng, 224002, China Graduate School of Business, Sogang University, Seoul, 04107, Republic of Korea The dataset used in this study was collected online, and anonymized data was utilized that did not contain personally identifiable information. Ethical approval for the broader research project, which covered data collection from university students in both Korea and China, was obtained from the Ethics Committee of Yancheng Teachers University, China (Approval No.

IRB-2026-02-003; approval date: February 16, 2026). The present study reports analyses based on the Korean sample collected under this approved research protocol. In addition, the survey clearly explained the purpose and scope of the study, voluntary participation, and the right to withdraw participation.