ArticleJournal of Intelligence2026
Exploring College Students' AI Dependence in Human-AI Collaborative Creation: Development and Validation of the CC-PACE Model.
Article in Journal of Intelligence, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
The development of Artificial Intelligence (AI) poses significant challenges to creativity research and practice. Managing the degree of AI dependence during the creative process is therefore critical to fostering the healthy development of human creativity. To address this concern, this study proposes the CC-PACE model by integrating the 5A's framework with the I-PACE model, and examines factors associated with AI dependence during the creative process. A cross-sectional survey was conducted with 813 college students in China, and the data were analyzed using partial least squares structural equation modeling (PLS-SEM). The results showed that (1) both creative personal identity and creative self-efficacy were positively associated with closeness with the audience and the perception of AI as a creative agent. (2) Both closeness with the audience and the perception of AI as a creative agent were positively associated with time spent using AI, usage preference, and perceived difficulty in avoiding AI use. (3) Time spent and usage preference were positively associated with students' creative self-assessment, whereas perceived difficulty in avoiding AI use was not significantly associated with creative self-assessment. This study provides a viable analytical framework for understanding AI dependence in creative contexts. The findings further suggest that teachers should help students develop an appropriate understanding of AI's role, strengthen students' creative agency, and emphasize process-oriented assessment in creative activities.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.